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Fatty acids in berry lipids of six sea buckthorn (Hippophae rhamnoides L., subspecies carpatica) cultivars grown in Romania

BackgroundA systematic mapping of the phytochemical composition of different sea buckthorn (Hippophae rhamnoides L.) fruit subspecies is still lacking. No data relating to the fatty acid composition of main lipid fractions from the berries of ssp. carpatica (Romania) have been previously reported.ResultsThe fatty acid composition of the total lipids (oils) and the major lipid fractions (PL, polar lipids; FFA, free fatty acids; TAG, triacylglycerols and SE, sterol esters) of the oils extracted from different parts of six sea buckthorn berry subspecies (ssp. carpatica) cultivated in Romania were investigated using the gas chromatography-mass spectrometry (GC-MS). The dominating fatty acids in pulp/peel and whole berry oils were palmitic (23-40%), oleic (20-53%) and palmitoleic (11-27%). In contrast to the pulp oils, seed oils had higher amount of polyunsaturated fatty acids (PUFAs) (65-72%). The fatty acid compositions of TAGs were very close to the compositions of corresponding seed and pulp oils. The major fatty acids in PLs of berry pulp/peel oils were oleic (20-40%), palmitic (17-27%), palmitoleic (10-22%) and linoleic (10%-20%) acids, whereas in seeds PLs, PUFAs prevailed. Comparing with the other lipid fractions the SEs had the highest contents of saturated fatty acids (SFAs). The fatty acid profiles of the FFA fractions were relatively similar to those of TAGs.ConclusionsAll parts of the analyzed sea buckthorn berry cultivars (ssp. carpatica) exhibited higher oil content then the other European or Asiatic sea buckthorn subspecies. Moreover, the pulp/peel oils of ssp. carpatica were found to contain high levels of oleic acid and slightly lower amounts of linoleic and α-linolenic acids. The studied cultivars of sea buckthorn from Romania have proven to be potential sources of valuable oils.

fatty_acids_in_berry_lipids_of_six_sea_buckthorn_(hippophae_rhamnoides_l.,_subspecies_carpatica)_cul

Background<!>Oil content of the SB materials<!><!>Fatty acid composition in oil of pulp/peel, seeds and whole berries<!><!>Fatty acid composition in oil of pulp/peel, seeds and whole berries<!><!>Fatty acid composition in individual lipid fractions of oils from pulp/peel and seeds<!><!>Fatty acid composition of TAGs<!><!>Fatty acid composition of PLs<!>Fatty acid composition of SEs<!>Fatty acid composition of FFA<!>Conclusions<!>Samples and chemicals<!>Lipid extraction<!>Fatty acid composition<!>Analysis of FAMEs by GC<!>Statistical analyses<!>Abbreviations<!>Competing interests<!>Authors’ contributions<!>Acknowledgements

<p>Sea buckthorn (SB) (Hippophae rhamnoides L. Elaeagnaceae) is a bush or a small tree, of the Elaeagnaceae family, naturally distributed in Eurasia. The classification of genus Hippophae is still unclear. The most common species (sp.), H. rhamnoides, was classified in several subspecies (ssp.), including ssp. carpatica, which is native in Romania [1]. Over the last decades the SB was domesticated in many countries from Asia, North and South America and Europe, not only for its soil and water conservation ability but also for its yellow-orange berries with an acidic and astringent taste and a high nutritional value. SB berries are rich in a variety of phytochemicals with physiological properties such as vitamins (B, C, E and K), flavonoids, carotenoids, tocopherols and many volatile compounds (i.e., aliphatic esters, alcohols and hydrocarbons [2-4]. Significant amounts of inositols and methylinositols were found in SB berries, which are supposed to contribute to health benefits of SB fruits and derivatives [5]. SB fruit membranes are rich in carotenolipoprotein complexes with 61% phospholipids and 39% galactolipids, as structural components [6]. In vitro and clinical studies show that the SB fruits have positive effect in the treatment of type 1 diabetic patients improving the glucose and lipid metabolism [7], possess high anti-oxidant, hemostatic and anti-inflammatory effects [8,9] and help prevent cardiovascular disease and cancer [10,11].</p><p>In last years SB pulp and seed oils have become popular food supplements playing important role in cancer therapy [9]. Several studies have indicated that these berry oils possess important immunostimulant, anti-ulcer and cholesterol-lowering effects, and may also be used in treatment of various skin diseases [12-15].</p><p>Both the seeds and soft parts (pulp/peel) of berries show high amounts of oil. The contents of bioactive lipophilic compounds, (i.e., phytosterols (up to 23 g/kg in seed oil and up to 29 g/kg in pulp/peel oil), tocopherols and tocotrienols (up to 2.9 g/kg in seed oil and up to 1.8 g/kg in pulp oil) and carotenoids (up to 3.5 g/kg in pulp oil) are generally high in the extracted seed and pulp/peel oils [2,16,17]. The existing studies reported different chemical compositions for SB seed and pulp/peel oils which vary widely depending on the subspecies, harvesting time of the fruits and the many other climatic and geographical conditions. Whereas the seed oil contains high amounts of unsaturated fatty acids, with linoleic (C18:2n-6) (30-40%) and α-linolenic (C18:3n-3) (20-35%) acid as the dominating fatty acids, the pulp/peel oil is rich in palmitoleic (C16:1n-7) (16-54%) and palmitic acids (C16:0) (17-47%) being more saturated [16,18,19]. The TAGs and PLs are the major lipid fractions in both of SB seed and pulp/peel oils [17].</p><p>A systematic mapping of the phytochemical composition of different SB fruits subspecies is still lacking. Ssp. carpatica is the most cultivated sea buckthorn ssp. in Romania. No data relating to the fatty acid composition of main lipid fractions from this berry ssp. have been previously reported. The purpose of the present study was to characterize the fatty acid composition of the total lipids (oils) and the major lipid fractions (PLs, FFAs, TAGs and SEs) of the oils extracted from different fruit parts of six SB subspecies (ssp. carpatica) cultivated in Romania.</p><!><p>The oil content of seeds, soft parts and whole berries (based on fresh weight, f.w.) of different SB cultivars (ssp. carpatica) are presented in Figure 1-A. The oil amounts of the analyzed berry parts varied widely: 45–84 g kg -1- in whole berries, 45- 88 g kg -1- in pulp/peel and 106–135 g kg -1- in seeds. The average oil content in seeds of the studied SB ssp. (123 g kg -1) was significantly higher (p < 0.05) than in soft parts (60 g kg -1) and whole berries (62 g kg -1), respectively (Figure 1-B). These results are similar with the oil contents of ssp. mongolica, and higher than those reported for ssp. sinensis (97 g kg -1 seeds, f.w. and 41 g kg -1 berry, f.w.) [16]. Yang et al. [17] determined the following amounts of oils for ssp. rhamnoides: 11% (f.w.) in seeds, 3% (f.w.) in soft parts and 3.5% (f.w.) in whole berries, respectively. Gutierrez et al. [18] concluded that the drying methods of SB berry parts could affect the oil extraction yield. These authors reported significant differences between the total oil content of air-dried berry pulp (cultivar Indian-summer) and freeze-dried pulp (36% vs. 16% (weight/weight, w/w)), whereas the total lipid recovery from air-dried seeds and freeze-dried seeds were similar (11% and 12% (w/w)).</p><!><p>Oil content (g kg-1fresh weight) of sea buckthorn berries (ssp. carpatica): A- oil content of different parts of six cultivars; B- the average oil content in analyzed parts of berries (mean of six cultivars).</p><!><p>The fatty acid compositions of pulp/peel, seeds and whole berries oils of six SB berry cultivars (ssp. carpatica) are listed in Tables 1 and 2. Due to the dominance of the pulp and peels in SB fruit, the composition of the oil from the whole berry resembled that of the pulp/peel oil.</p><!><p>Fatty acid composition (weight % of total fatty acids) of oils from whole berries, pulp/peel and seeds of different cultivars of H. rhamnoides L. (ssp. carpatica) fruits</p><p>Values are mean ± SD of three samples of each fruit part, analyzed individually in triplicate; C1- C6, sea buckthorn (ssp. carpatica) cultivars.</p><p>C14:0, myristic; C15:0, pentadecanoic; C16:0, palmitic; C16:1n-9, cis-7 hexadecenoic; C16:1n-7, palmitoleic; C17:0, margaric; C18:0, stearic; C18:1n-9, oleic; C18:1n-7, vaccenic; C18:2n-6, linoleic; C18:3n-3, α-linolenic; C20:0, arachidic; C20:1n-9, eicosenoic acids.</p><p>Fatty acid composition (weight % of total fatty acids) of oils from different parts of sea buckthorn fruits (ssp. carpatica)</p><p>C1- C6, sea buckthorn (ssp. carpatica) cultivars.</p><p>Values are mean ± SD of three samples of each fruit part, analyzed individually in triplicate. Means in the same row followed by different superscript letters indicate significant differences (p < 0.05) among cultivars (C1-C5); means in the same column followed by different subscript letters indicate significant differences (p < 0.05) between fatty acid classes of each cultivar; SFAs, saturated fatty acids; MUFAs, monounsaturated fatty acids; PUFAs, polyunsaturated fatty acids.</p><!><p>The fatty acid levels of the seed and berry pulp/peel oil varied widely.</p><p>The dominating fatty acids in berry pulp/peel oils were palmitic (16:0) (23-40%), oleic (18:1n-9) (20-53%) and palmitoleic (16:1n-7) (11-27%). Small or trace amounts of vaccenic (18:1n-7), linoleic(18:2n-6), α-linolenic (18:3n-3), stearic (18:0), myristic (14:0), pentadecanoic (15:0), cis-7 hexadecenoic (16:1n-9), margaric (17:0) and two long chain fatty acids, arachidic (20:0) and eicosenoic (20:1n-9) acids were observed in all analyzed soft part oils. In two cultivars, C1 and C2, the proportions of oleic acid (32.76% for C1 and 53.08% for C2) exceeded that of the palmitoleic acid (19.53% for C1 and 11.05% for C2). From these results can be concluded that MUFAs were the dominant fatty acid classes (53-70%), followed by SFAs (26-41%) and PUFAs (3-7%) (Table 2). The PUFA/SFA ratios were close to zero, with a significantly high value (0.17) (p < 0.05) in pulp/peel oil of C6. Statistically significant differences (p < 0.05) were observed between n-6/n-3 ratios of analyzed berry pulp/peel oils, with the highest value in cultivar C4 (7.67) and the lowest in C6 (1.09), respectively (Table 2).</p><p>Similar amounts of palmitic (in cv. Indian-summer and H. rhamnoides (India)), vaccenic (in cv. Indian-summer and ssp. sinensis) and α-linolenic (in cv. Indian-summer, H. rhamnoides (India) and H. salcifolia) acids were recently reported by different authors for berry pulp oil. Higher proportions of palmitoleic acid and much lower levels of oleic acid were characteristic of the Finnish, Chinese and Canadian soft part SB oils, excepting species H. tibetana which presented similar percentages of (18:1n-9) with those of results from the present study [2,17,18].</p><p>Seed oils consisted mainly of linoleic, α-linolenic, oleic, palmitic and stearic acids, with minor or trace amounts of vaccenic, palmitoleic, arachidic, eicosenoic, myristic, pentadecanoic and margaric acids (Table 1). A notable feature of the berry seed oils was the extremely low level of palmitoleic acid (0.1-0.5%). The relatively high deviations were observed in the proportions of oleic (13-21%) and linoleic (33-43%) acids. In contrast to the pulp oils, seed oils had higher amounts of PUFAs (65-72%) and lower proportions of MUFAs (16–21.5%) and SFAs (11-16%), respectively (Table 2). These oils, characterized by high ratios of PUFAs/SFAs, with an extremely significant high value (p < 0.05) for cultivar C2 (6.25), are susceptible to oxidative damage due to their high α-linolenic acid content (28-33%). Statistically significant variations (p < 0.05) were observed between n-6/n-3 ratios of analysed six seed oils, with all the values close to 1 (Table 2). This phenomenon could be explained by the ratio of linoleic to α-linolenic acid (close to 1:1), which is different from the main vegetable oils [20,21]. Generally the proportions of unsaturated fatty acids from seed oils obtained in this study were in accordance with those reported by Yang and Kallio [17] and Yang et al. [22] for ssp. sinensis and rhamnoides. The concentration of α-linolenic was found slightly higher in air- and freeze- dried SB seed oils (~ 37% and ~ 39%, respectively) of cv. Indian-summer than in the corresponding oils from the present work [18].</p><p>The high amount of palmitoleic acid, unusual for a vegetable oil, distinguishes the berry pulp/peel oils from the seed oils of SB. This valuable fatty acid, which is an important component of skin fat, has attracted an increasing interest due to its hypocholesterolemic and hypoglyceridemic activities [2].</p><p>Comparing the average proportions (average of six cultivars) of the fatty acid classes from the oils of different parts of berries, the seed oil contained significantly lower proportions of SFAs and MUFAs (p < 0.05), and significantly higher amount of PUFAs (p < 0.05), than the whole berry and pulp/peel oils (Figure 2).</p><!><p>Comparison of the fatty acid classes compositions (as % of total fatty acids) from the oils of different parts of sea buckthorn fruits (ssp. carpatica).</p><!><p>The fatty acid compositions of the main lipid classes (PLs, FFAs, TAGs and SEs) from pulp/peel and seed oils are presented in Tables 3, 4, 5 and 6.</p><!><p>Fatty acid composition (weight % of total fatty acids) of individual lipid classes from pulp/peel oils of different cultivars (C1-C6) of sea buckthorn fruits (ssp. carpatica)</p><p>PL- polar lipids, FFA- free fatty acids, TAG- triacylglycerols, SE- sterol esters.</p><p>Fatty acid composition (weight % of total fatty acids) of individual lipid classes from seed oils of different cultivars (C1-C6) of sea buckthorn fruits (ssp. carpatica)</p><p>PL- polar lipids, FFA- free fatty acids, TAG- triacylglycerols, SE- sterol esters.</p><p>Fatty acid composition (weight % of total fatty acids) of individual lipid classes from pulp/peel oils of different cultivars of sea buckthorn fruits (ssp.carpatica)</p><p>Values are mean ± SD of three samples, analyzed individually in triplicate</p><p>Means in the same row followed by different superscript letters indicate significant differences (p < 0.05) among fatty acid classes; means in the same column followed by different subscript letters indicate significant differences (p < 0.05) among lipid classes of each cultivar.</p><p>PL, polar lipids; FFA, free fatty acids; TAG, triacylglycerols; SE, steryl esters; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids.</p><p>Fatty acid composition (weight % of total fatty acids) of individual lipid classes from seed oils of different cultivars of sea buckthorn fruits (ssp.carpatica)</p><p>Values are mean ± SD of three samples, analyzed individually in triplicate</p><p>Means in the same row followed by different superscript letters indicate significant differences (p < 0.05) among fatty acid classes; means in the same column followed by different subscript letters indicate significant differences (p < 0.05) among lipid classes of each cultivar.</p><p>PL, polar lipids; FFA, free fatty acids; TAG, triacylglycerols; SE, steryl esters; SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids.</p><!><p>The fatty acid compositions of TAGs (Figure 3) were very close to the compositions of corresponding seed and pulp oils, with the same dominating fatty acid classes (Table 1; Figure 4 (a), (b) and (c)).</p><!><p>GC-MS chromatogram of FAMEs from the TAGs of pulp/peel (a) and seeds (b) of sea buckthorn berries (ssp. carpatica).</p><p>The average proportions of fatty acid classes (3a- % of MUFAs, 3b- % of SFAs, 3c- % of PUFAs) in lipid fractions from pulp/peel and seeds of sea buckthorn berries (ssp. carpatica).</p><!><p>The dominating fatty acids in descending order in berry pulp/peel oils were oleic (20-40%), palmitic (17-27%), palmitoleic (10-22%), linoleic (10%-20%) and α-linolenic (4-9%) acids (Table 3). In all PL fractions extremely significant differences (p < 0.05), were observed between the proportions of fatty acid classes, with the MUFAs as the major fatty acids (Table 5). All the values of PUFA/SFA ratios were close to 1, varying between 0.67 (for C4) and 1.36 (for C2), respectively. Comparing the pulp/peel lipid fractions from the studied cultivars, PLs presented the highest values (p < 0.05) for PUFA/SFA ratios. The n-6/n-3 ratios varied between 1.4 (in C1) and 4.1 (in C3) (Table 5). Recent studies have shown that a balanced intake of dietary PUFA and SFA (ranged between 1.0 and 1.5) can contribute to reduce cardiovascular diseases [23,24]. The glycerophospholipids from pulp/peel oils of subspecies sinensis, rhamnoides and mongolica presented greater amounts of the 18:2n-6 (25.7%, 24.2% and 32.1%, respectively) and 18:3n-3 (15.4%, 12.9% and 10%, respectively) fatty acids than those of corresponding PLs from the present study [16,17]. The phospholipid fractions from SB pulp oils of cv. Indian- summer exhibited much higher amounts of palmitoleic (22.7-25%) and lower amounts of oleic (1.4-2.4%) acids than coresponding samples of this work [18].</p><p>In seeds PLs, PUFAs were present in a significantly greater proportion (p < 0.05), than SFAs and MUFAs (Tables 4 and 6). The oleic and linoleic acid contents (Table 4) were comparable with the values reported for the seeds of Asian and European SB berries [16-18]. Small variations of n-6/n-3 ratios were observed for the seed oils PLs, the values (Table 6) being close to the recommended essential fatty acid balance, reported in literature [25]. As shown in Figure 4 (a) and (c) the average value of MUFAs was significantly higher, in the berry pulp/peel oil PL than in the seed oil PL (53.5% vs 17.9%, p < 0.001) and vice versa for PUFAs (21.3% vs 54.9%, p < 0.001).</p><!><p>The major fatty acids in ascending order in all berry soft part oils were linoleic (5-9%), oleic (16-26%), palmitic (24-30%), and stearic (33-41%). The relatively high values of n-6/n-3 ratios of the berry pulp/peel oils SEs closely resembled those of the berry pulp/peel oil TAGs, excepting cultivars C2 and C4 (see Table 5). Comparing with the other lipid fractions from these oils, the SEs had the highest content of SFAs (p < 0.05). This class of fatty acids were also predominant in seed oil SEs due to their high content of palmitic and stearic acids (Tables 4 and 6).</p><p>It is interesting to note that the arachidic acid levels were around of 2% in pulp/peel oils SEs and between 3% and 6% in seed oils SEs.</p><p>The long chain saturated fatty acids, with more than 20 carbons, are major structural components of plant cuticular lipids [26].</p><p>Average proportions of MUFAs and SFAs were significantly higher in pulp/peel oils SEs than in seed oils SEs (p < 0.01) and vice versa for PUFAs (p < 0.001) (see Figure 4 (a), (b) and (c)).</p><p>The levels of SFAs from studied SB oils SEs were comparable to those reported for other berry SE fractions [27,28].</p><!><p>The fatty acid profiles of the FFA fractions of pulp/peel and seed oils were relatively similar to those of TAGs excepting the proportions for stearic acid (in berry pulp/peel oils) and for palmitic, stearic and α-linolenic acids (in seed oils), respectively (Tables 3 and 4). Generally, the SFAs were the most representative in all analysed cultivars, followed by MUFAs in pulp/peel and PUFAs in seed oils FFAs, respectively (Tables 5 and 6). Low levels of free fatty acids (2-4%) have been reported for oils from air- and freeze- dried SB (cultivar Indian- Summer) seeds and pulps by Gutierrez et al. [18], with the similar fatty acid profiles to those of neutral lipids. The quality of the vegetable oils depends on their lipid profile. A high proportion of the free fatty acids offers an unacceptable flavour to the oils [29]. Differences between the fatty acid profiles of the studied lipid fractions could be due to the different phases of biosynthesis and accumulation of TAGs, SEs, PLs and fatty acids. In the first stage PLs and SEs are synthesized with the SFAs as dominating fatty acid classes in their composition. The TAGs proportion, with high unsaturated fatty acid content, increases in the second phase of biosynthesis [28,30,31].</p><!><p>This study provides valuable information about the fatty acid composition of the major lipid fractions (PLs, FFAs, TAGs and SEs) in the oils extracted from different berry parts of six SB subspecies (ssp. carpatica).</p><p>Comparing with the other European or Asiatic SB subspecies, all berry parts of the analyzed cultivars exhibited higher oil content. Moreover, the pulp/peel oils of ssp. carpatica were found to contain high levels of oleic acid and slightly lower amounts of linoleic and α-linolenic acids.</p><p>The PLs presented the highest PUFA/SFA ratios between the analysed pulp/peel lipid fractions (from 0.67 to 1.36), values which were close to the recommended PUFA/SFA intake of nutrition scientists (1–1.5).</p><p>The seed oils could be considered excellent sources of PUFAs due to their high contents of linoleic and α-linolenic acids which in human body are precursors of other long-chain n-3 and n-6 fatty acids.</p><p>The data obtained in the present work are useful to identify suitable SB cultivars when organizing the berry breeding programs and also provides important information for food and pharmaceutical industry.</p><!><p>Berries of SB (Hippophae rhamnoides L., ssp. carpatica, cvs. Auras (C1), Serpenta (C2), Tiberiu (C3), Victoria (C4), Ovidiu (C5) and Silvia (C6)) were collected from the experimental field of the Fruit Research Station- Bacau, Romania. The fruits were collected during June to November of 2011 at the stage of commercial maturity and were stored in polyethylene bags at -20°C until analysis.</p><p>Seeds were isolated manually from the fruits just before analysis at the laboratory.</p><p>Standards of fatty acid methyl esters (37component FAME Mix, SUPELCO, catalog No: 47885-U) were purchased from Supelco (Bellefonte, PA, USA). All reagents, chemicals of analytical or HPLC purity and polar lipid standards were purchased from Sigma–Aldrich (St. Louis, MO, USA). The thin layer chromatography (TLC) plates (silica gel 60 F254, 20 × 20 cm) were purchased from Merck (Darmstadt, Germany).</p><!><p>The oils of the whole berries, pulp/peel and seeds were extracted from 5 g of samples using a methanol/chloroform extraction procedure [17,32]. The sample was homogenized in methanol (50 mL) for 1 min with a high-power homogeniser (MICCRA D-9, Germany), chloroform (100 mL) was added, and homogenization was continued for a further 2 min. The mixture was filtered and the solid residue resuspended in chloroform: methanol (2:1, v/v, 150 mL) and homogenized for another 3 min. The mixture was filtered again and washed with 150 mL chloroform: methanol (2:1, v/v). The filtrates were combined and cleaned with 0.88% potassium chloride water solution and methanol: water (1:1, v/v) solution. The bottom layer containing the purified lipids was filtered before the solvent was removed on a rotary evaporator. The lipid samples were transferred to vials with 4 mL chloroform (stock solution), and stored at −18°C until they were analyzed.</p><!><p>Fatty acid methyl esters (FAMEs) were obtained from lipids using acid-catalysed transesterification procedure described by Christie [33].</p><p>For total FAME analysis, 0.2 mL of each oil extract (stock solution) was dissolved in 1 ml toluene and then methylated with 1% sulfuric acid in methanol (2 ml), using a 15 mL screw-cap Pyrex culture tube at 80°Cfor 2 h. After cooling to room temperature, 5 ml of water (with 5%NaCl) and 2 mL hexane were added. The hexane layer was collected and concentrated before the FAMEs were applied to TLC plates. The loaded TLC plates were developed in a mixture of petroleum ether: diethyl ether: acetic acid (85:15:1, v/v/v), sprayed with 2', 7'-dichlorofluoroscein/methanol (0.1% w/v) and viewed under UV light (254 nm) [34]. The corresponding FAME band was scraped and eluted with chloroform. The eluent was removed with a gentle nitrogen stream. The FAMEs were dissolved in 1 mL hexane and placed into a gas chromatography (GC) vial. The vial was capped and placed at −18°C until GC analysis.</p><p>The lipid classes (PLs, FFAs, TAGs and SEs) were separated also by TLC. For fractionation, 0.2 ml of each oil (stock solution) was applied on the TLC plates, developed and viewed under UV light as above. The polar lipids remained at the origin of the plates (the first band). The other major lipid class bands from TLC plates, were identified using commercial standards (which were run in parallel with the samples) and then scraped from the plates. The bands for PLs and FFAs were eluted with methanol: chloroform (1:1, v/v), and the upper two major bands corresponding to TAGs and SE respectively, were eluted with chloroform. After the chloroform was evaporated under a nitrogen stream, the lipid classes were methylated (20 min at reflux for PLs and 2 h at reflux for the other lipid fractions). The extraction of the corresponding FAMEs in hexane was done as described above.</p><!><p>The FAMEs were determined by gas chromatography–mass spectrometry (GC-MS), using a PerkinElmer Clarus 600 T GC-MS (PerkinElmer, Inc., Shelton, U.S.A.) equipped with a SUPELCOWAX 10 column (60 m × 0.25 mm i.d., 0.25 μm film thickness; Supelco Inc., Bellefonte, PA). The initial oven temperature was 140°C, increased to 220°C with a rate of 7°C/min and then held at this temperature for 23 min. Flow rate of the carrier gas He and the split ratio were 0.8 ml/min and 1:24, respectively. The injector temperature was 210°C. The positive ion electron impact (EI) mass spectra was recorded at an ionization energy of 70 eV and a trap current of 100 μA with a source temperature of 150°C. The mass scans were performed within the range of m/z: 22–395 at a rate of 0.14 scan/s with an intermediate time of 0.02 s between the scans. The injection volume was 0.5 μl. Identification of FAMEs was done comparing their retention times with those of known standards (37component FAME Mix, SUPELCO # 47885-U) and the resulting mass spectra to the ones from our database (NIST MS Search 2.0).</p><!><p>All the extractions and GC-MS analysis were made in triplicate. Dates were expressed as mean ± S.D. Statistical differences among samples were estimated using Student's t-test and ANOVA (Tukey's Multiple Comparison Test; GraphPad Prism Version 4.0, Graph Pad Software Inc., San Diego CA). P < 0.05 was accepted to be statistical significant.</p><!><p>Ssp: Subspecies; sp: Species; PLs: Polar lipids; FFAs: Free fatty acids; TAGs: Triacylglycerols; SEs: Sterol esters; PUFAs: Polyunsaturated fatty acids; SFAs: Saturated fatty acids; MUFAs: Monounsaturated fatty acids; SB: Sea buckthorn; f.w.: Fresh weight; w/w: Weight/weight; cv: Cultivars; FAMEs: Fatty acid methyl esters; TLC: Thin layer chromatography; GC-MS: Gas chromatography–mass spectrometry.</p><!><p>The author declares that he has no competing interests.</p><!><p>FVD carried out all experiments and prepared the final manuscript.</p><!><p>This work was financially supported by the Research Grant of University of Agricultural Sciences and Veterinary Medicine nr.1215/4, 2012, Cluj-Napoca, Romania. The author thanks dr. I.V. Rati and prof. dr Carmen Socaciu for providing the sea buckthorn berries.</p>

PubMed Open Access

Ensemble completeness in conformer sampling: the case of small macrocycles

In this study we compare the three algorithms for the generation of conformer ensembles Biovia BEST, Schrödinger Prime macrocycle sampling (PMM) and Conformator (CONF) form the University of Hamburg, with ensembles derived for exhaustive molecular dynamics simulations applied to a dataset of 7 small macrocycles in two charge states and three solvents. Ensemble completeness is a prerequisite to allow for the selection of relevant diverse conformers for many applications in computational chemistry. We apply conformation maps using principal component analysis based on ring torsions. Our major finding critical for all applications of conformer ensembles in any computational study is that maps derived from MD with explicit solvent are significantly distinct between macrocycles, charge states and solvents, whereas the maps for post-optimized conformers using implicit solvent models from all generator algorithms are very similar independent of the solvent. We apply three metrics for the quantification of the relative covered ensemble space, namely cluster overlap, variance statistics, and a novel metric, Mahalanobis distance, showing that post-optimized MD ensembles cover a significantly larger conformational space than the generator ensembles, with the ranking PMM > BEST >> CONF. Furthermore, we find that the distributions of 3D polar surface areas are very similar for all macrocycles independent of charge state and solvent, except for the smaller and more strained compound 7, and that there is also no obvious correlation between 3D PSA and intramolecular hydrogen bond count distributions.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13321-021-00524-0.

ensemble_completeness_in_conformer_sampling:_the_case_of_small_macrocycles

Introduction<!><!>Conformer generation<!>Molecular dynamics simulations<!><!>Processing of dihedral angles<!>Torsion space maps<!>Properties for color-coding of PCA plots<!>Results and discussion<!><!>Results and discussion<!><!>Dependence on charge state<!><!>Dependence on charge state<!>Dependence on solvent<!><!>Dependence on solvent<!>Ensemble completeness of conformer generators<!><!>Torsion map overlaps<!>Quantification of the map overlaps<!><!>Quantification of the map overlaps<!><!>Quantification of the map overlaps<!>Intramolecular hydrogen bonds<!><!>Intramolecular hydrogen bonds<!>Polar surface areas<!><!>Polar surface areas<!><!>Polar surface areas<!>Conclusions<!>

<p>Molecules at ambient conditions are flexible fluctuating three-dimensional objects composed of atoms held together by electrons. Since there exists no appropriate and applicable description for this state, computational chemists apply different types of approximations. For tasks like QSAR/machine learning predictions, structure alignments, pharmacophores, docking, or molecular energy calculations (e.g. binding energies, relative configurational energies, conformer or reaction energies) molecular descriptors, structural fingerprints, line notations, classical molecular mechanics or quantum mechanics are applied. Most of these tasks to be performed need at least one set of 3D coordinates, and many approaches like pharmacophore searching or docking rely either on a coordinate set of the binding or minimum energy conformation or an ensemble of low-energy conformations, respectively. Only if one can create all relevant conformations or otherwise relevant representatives from the complete accessible phase space one can be sure not to introduce random errors into model setup. It is important to emphasize that the ensemble space is not only about energy minima: deep minima can correspond to small populations while shallow minima can be more populated. Conformations in binding pockets are influenced by the pocket and may not correspond to minima in solvent. The ability of a compound to pre-adapt in medium A to a conformer state relevant in medium B (A and B being solvents, membranes, binding pockets, for instance) has recently be shown again [1] but is a long-known fact [2]. Adequate conformational sampling should therefore be based on free energy (including entropic effects) rather than on the potential energy only. We are interested in relevant statistical information (most populated states).</p><p>Structure-based machine learning is typically based on descriptors from atomic connectivity or 2D structures. Nevertheless, with comparative field analysis (CoMFA) already in 1988 the first 3D-based method appeared [3]. The concept was further refined (without finding broad application) with the 4-dimensional xMap [4] approach that avoids the two main issues of CoMFa, namely reliance on only one conformer and the necessity to align the ligands onto each other, and the 5D-QSAR method [5] by Vedani and Dobler that in addition also considers different protonation states. The relevance of 3D conformation-based machine learning recently sees a revival triggered by so-called beyond rule of five compounds [6] and the observation that many ADMET properties of compounds rely on conformational flexibility determined inter alia by intramolecular hydrogen bonding [7]. One such descriptor derived for modeling solvation free energies is the MDFP by Riniker [8] which allows to transfer information from a molecular dynamics simulation in one solvent to another solvent and to derive distribution coefficients. Clever descriptions of three-dimensional features of molecules will certainly constitute one approach towards the improvement of in silico ADMET and other ML models.</p><p>Unfortunately, there is no experimental technique that consistently provides information on the accessible ensemble, especially since the surrounding medium strongly influences conformational preference. There is data for any aggregate phase and medium but experiments in different phases or media will give different results, for well-understood reasons. Gas-phase conformer coordinates describe the structure in a more or less undisturbed state but are limited to small structures able to sublimate into gas-phase without decomposition. In solvent (liquid phase for most organic molecules is not accessible) the conformer ensembles can only indirectly be determined by shifts and couplings from spectroscopic methods like NMR [9] or IR- or FTIR- spectroscopy [10, 11], often in combination with mass spectroscopy to fragment larger molecules and with quantum-chemical calculations [12]. Solid state coordinates are obtained by crystallography either for the ligand itself or for a ligand co-crystallized with a target protein. Small molecule crystals provide high-resolution coordinates which however often do not represent the global minimum conformation, as they are defined by intra—and more importantly—intermolecular interactions like hydrogen bonds, pi-stacking, dispersion, charge-charge interactions etc., which strongly influence the torsional angles in particular. Coordinates derived from protein–ligand complexes are also heavily biased by intermolecular interactions and additionally are significantly less accurate, providing only heavy-atom positions which often have non-equilibrium distances, angles and torsions [13], and even high-resolution structures often have no electron density for parts of the ligand [14]. A study by Perola [2] reported that from the 150 protein–ligand complexes evaluated, about 60% were no local minima, about 60% had strain energies of up to 5 kcal/mol and at least 10% had strain energies higher than 9 kcal/mol. Other studies, using higher levels of theory, report much lower (< 2 kcal/mol) or much higher (> 10 kcal/mol) strain energies, as summarized by Hawkins [15].</p><p>A computational process for the generation of conformers must fulfill two requirements, namely create a complete ensemble of energetically accessible conformers to allow for a selection of a representative subset and provide accurate conformer energies as a prerequisite to select the subset. In a previous publication we have benchmarked [16] two force-fields, three semi-emprical and a performance-optimized density functional method with regard to accurate relative energies. In this publication we look at the completeness of conformer ensembles from three different algorithms for conformer generation in comparison with ensembles derived from extensive molecular dynamics simulations applying multiple starting conformers in three solvents and two different charge states. The intention of our study is to identify the generator algorithm best suited to the task, since in industry we are willing to accept fast and approximate methods as long as they are reliable or at least allow to identify the breakdown of the approximation. To our knowledge there is one study by Agrafiotis et al. addressing explicitly the topic of ensemble completeness [17] and one study by Schrödinger that followed the same concept but with some limitations regarding the completeness of the MD derived ensemble [18]. Additionally to cluster-based and covariance metrics approaches to identify the conformer overlaps between MD and generators, we propose a novel measure for the quantification of overlap of ensembles of different origin but also discuss the "uncertainty principle" for measuring ensemble completeness.</p><p>In this article we focus on seven small macrocycles from a series of about 50 compounds we had synthesized in order to investigate parameters that determine cell permeation [19], influenced by the work of the groups of Jacobsen and Lokey [20–23]. In a future study we plan to extend this work to typical drug-like small molecules.</p><!><p>Structures of the macrocycles</p><p>Property space of the dataset, listing amino acid sequence, calculated physicochemical properties pKa, logD, molecular weight in g/mol and topological polar surface area TPSA in Å2, and numbers of conformers generated by conformer generators</p><!><p>Starting 3D coordinates in SD file format were generated by CORINA [28] version 4.2.0 0026 using the driver option "write hydrogens". For all calculations using the Schrödinger Suite we applied version 2018–4 [29].</p><p>Three sets of conformers were tested. The first set was created using the BEST algorithm [30, 31] implemented in BIOVIA Pipeline Pilot [32] generating up to 200 diverse conformers with an energy window of 50 kcal mol−1. In contrast to our previous work [1], here, we were concerned with thorough sampling instead of speed. The second set (abbreviated PMM) was created with Schrödinger PRIME MACROCYCLE SAMPLING with 200 requested conformers and "sample peptide bonds" and "preserve major ring shape" deselected.</p><p>The third set (abbreviated CONF) was obtained with the software CONFORMATOR [33] with 200 conformers requested, "quality" set to "best" and keeping "macrocycle_size" at 10 atoms. No other flags were used.</p><p>Each conformer set was then post-optimized by macromodel using the OPLS3e [34] forcefield with extended cut-off and FF charges, using default settings, i.e. conjugate gradient PRCG optimizer with maximum 2500 iterations, gradient convergence threshold of 0.05 kJ mol−1 Å−1 and no constraints applied.</p><p>In an alternate setting we assessed the space of non-optimized conformations obtainable from generators for the example of compound 1 in its neutral state in comparison with the non-optimized MD snapshots. For this we had to stretch the settings of the algorithms considerably, still never reaching the numbers obtained from MD. The settings applied that differ from the ones before were "-n 30,000" for conformator, "discard existing conformations = false", "required = 30,000", "energy threshold = 10,000 kJ mol−1″, separate conformer = false", "minimization = false" for BEST, and 100,000 conformations requested in case of PMM, respectively.</p><!><p>MD simulations were carried out with DESMOND [35, 36] as implemented in the Schrödinger suite in three different solvents, namely SPC water, DMSO and CHCl3. Since there is no pre-built CHCl3 solvent box, we had to create it following the procedure outlined in the Schrödinger knowledge base [37]. For this we did a 100 ns simulation at 300 K using an NPT ensemble and checked for pressure and temperature fluctuations using the simulation event analysis [38]. Additionally, we also checked for the correct macroscopic density of the solvent.</p><p>The System Builder was used to setup systems for the three solvents SPC water, DMSO and custom-created CHCl3 using an orthorhombic box shape, the buffer box size set to 10 Å in each direction. We used the OPLS3e forcefield without calculation of custom parameters. For charged ligands the systems were neutralized by adding a chlorine ion.</p><p>All standard simulations ran for 100 ns under NPT conditions at 300 K and 1.01325 bar and generating 10,000 snapshots, starting from five diverse input conformers, and in case of molecule 5 (neutral, solvent water) for 3 additional diverse low-energy conformers selected from the PMM ensemble. The relaxation protocol provided in the Schrödinger suite was used, with all advanced options set to defaults. Some simulations were performed at temperatures of 400 K, 500 K, and 800 K as well as one long-running job with 1000 ns. Diverse starting conformers were selected from the BEST conformer ensemble with the Schrödinger tool "Conformer Cluster" based on ring heavy atom root mean square error (RMSE) with "average linkage" and "retain mirror-image conformers" checked, yielding the centroid structure per cluster, and requesting 200 clusters.</p><p>Additionally, we did simulated annealing (SA) runs applying a custom 82 step protocol consisting of 10 heating cycles from 300 to 500 K, each cycle having a 10 ns sampling phase at 300 K and 8 ns heating phase. Simulation time was accordingly set to 172 ns resulting in 17,200 snapshots. Again, an NPT ensemble with 1.01325 bar and the upfront relaxation protocol was used. Due to differences in the DESMOND implementations for CPUs and GPGPUs, the thermostat had to be changed to Nose–Hoover [39] for calculations on GPGPUs. For one case study, we performed 5 simulated annealing runs with 5 diverse starting structures.</p><!><p>Numbering of torsions; torsions T7, T8, T9, T10 are missing for structure 7</p><!><p>For the MD and SA snapshots the values were extracted by the Schrödinger script analyze_simulation.py [40]. The configuration files (file type "st2") with the dihedral definitions were created with the "Simulation Event Analysis panel" for each charge state of each macrocycle (MC).</p><p>The BEST, PMM and CONF conformers dihedral angles were calculated with the script "measure_by_numbers.py" provided by Schrödinger support and exported to csv format. All further processing was performed in R [41].</p><!><p>Principal components analysis (PCA) as implemented in R base was used to create a 2-dimensional representation of the multi-dimensional space defined by the ring torsions of macrocycles 1 to 6. Due to four missing torsions for 7 we projected the torsional space of this ligand onto the map spanned by the 16 torsions from all snapshots from the MD and SA runs performed for the other ligands. It is not possible to use the torsions themselves due to a discontinuity in their definition, i.e., dihedrals of −178° and 178° result in almost perfect superposition of two conformers (minimal atom RMSDs), but in a large distance in latent space. Therefore, we transformed the dihedral angles θ into a pair of values, namely sin(θ) and cos(θ). By this, for instance, − 178° and 178° transform into (0.035; − 0.999) and (− 0.035; − 0.999) populating the same region of latent space.</p><p>The PCA mappings were plotted using ggplot and RColorBrewer_1.1.2 [42]. A graphical user plot generation interface allowing for fast and easy comparison of the maps was implemented in Shiny [43], a web application framework for R.</p><!><p>For each snapshot, we counted the number of intramolecular hydrogen bonds (IMHB). We used values between 110° and 220° as angle and between 1.5 and 2.6 Å as distance thresholds, slightly softening the standard parameters often used, to account for the MD snapshots not being local minimum coordinates. A detailed analysis of prevalence of the different optional IMHB for compounds 1, 2, 3 was provided in a previous publication [3] and is out of scope of this work.</p><p>Relative energies were derived for each macrocycle with the OPLS3e force field after stripping off the explicit solvent molecules. Since the MD snapshots are not local energy minima but carry a certain but unknown portion of the overall system energy, the values cannot be compared even for the same ligand between the post-optimized conformers and the snapshots. We always set the values for the lowest energy snapshot for each run to zero, knowing that still the maps are only qualitatively comparable.</p><p>For comparison to the BEST, PMM and CONF conformers, we post-optimized the snapshots with the OPLS3e forcefield using implicit solvation, resulting in relative energies on the same scale as the ones from the generated and post-optimized conformers.</p><p>For the quantification of the overlapping and unique conformations from MD simulations and generator methods we clustered each combined set of minimized structures from MD and the respective generator based on the first eight principal components which have a cumulative explained variance of 67.5%.</p><p>The clustering was conducted using the function "kmeans" from the internal R-package 'stats' [44]. K-means identifies a pre-specified number of clusters that minimizes the within-cluster sum of squares. This is done by randomly picking cluster centers and assigning each point to the closest cluster (evaluated by Euclidean distance), re-calculating the new center of the cluster and assigning again each data point to its closest cluster. This is iterated till no cluster changes anymore [45]. The returned result is locally optimal. For all cases we requested 500 clusters, with maximally 1000 iterations (no issues of non convergence), and 25 random sets to start with. The underlying method is the algorithm of Hartigan and Wong [46]. Each structure was labelled by its origin being either from MD or a generator. The RMSD for each cluster was calculated based on the cluster members' respective radTorsion data for each cluster member against each cluster member, max and median RMSD were saved. The overall max RMSD is defined as the max of all clusters' max RMSD. The overall median RMSD is defined as the median of all median RMSD.</p><p>Statistical analysis on the significance of the differences of the post-optimized MD conformer and generator maps was performed to obtain p-values with the function betadisper [47, 48] from the R package vegan on the Euclidean distances of the respective latent variables' coordinates. A multivariate permutation test was performed for the homogeneity of group variances using the function permutest from the same package with 10,000 permutations, pairwise comparison was set to 'TRUE'. Note that using this permutation method with a set number of permutations computed p-values cannot be lower than 1 * 10–5. Utilizing the TukeyHSD function from the same package, confidence intervals for the difference between the group's respective mean distance-to-centroid are calculated. The difference is always defined as \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\mathrm{\Delta }\mathrm{D}={D}_{miniMD}-{D}_{generator}$$\end{document}ΔD=DminiMD-Dgenerator, whereas \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$D$$\end{document}D is the mean distance-to-centroid.</p><p>The 3D polar surface areas [49] as derived in Pipeline Pilot [12] are color-coded with thresholds of 95 ± 17.7 Å2 and 145 ± 21.4 Å2 based on the correlation (slope: 1.01; intercept 5.32) between 2D TPSA and 3D PSA values for 10,000 randomly selected compounds from the Aldrich Market Select catalogue (Additional file 1: Figure S1), by using the TPSA thresholds regarding oral absorption and bioavailability considerations as published [50–52].</p><p>Further color-coding options applied include starting conformer, solvent, simulation temperature, simulation run number.</p><!><p>In this work, the diversity of conformational ensembles was analyzed via a map derived from principal component analysis of the torsional space of the macrocyclic ring atoms. We did so to avoid any ambiguities from root-mean-square error (RMSE) calculations for the macrocycle atoms due to structural alignment algorithm used. Apart from this, our approach allows to create one consistent map from all six 16-membered ring macrocycle structures based on all MD and SA snapshots. We excluded side chain dihedrals since we expect any algorithm to be able to comprehensively sample this torsional subspace. The map was created from the 32-dimensional space spanned after transformation of dihedral angles into sinus and cosinus values, avoiding discontinuities in mapping.</p><p>Torsions of all conformers of compound 7 as well as of all conformers from the conformer generators for compounds 1 to 7 were projected onto the global map defined by compounds 1 to 6. The global map was derived from all snapshots for neutral and positive charge state in the three solvents at 300 K and from the simulated annealing runs to allow direct comparison between molecules, solvents and charge states. The combined PCA map from 1 to 6 provides accumulated variance of 15.1, 27.7, 37.6 and 45.2% for PC1 to PC4, respectively. We loose information with respect to the maps created from the conformers of any individual compound (between about 37 and 48% accumulated explained variance for PC1 and PC2, cf. Additional file 1: Table S1), but at the same time we yield comparability.</p><!><p>PCA loading plots for a the latent variables PC1 and PC2 and b latent variables PC3 and PC4 for the 32-dimensional space spanned by sinus and cosinus values of the 16 torsional angles as defined in Scheme 2</p><!><p>In the following paragraphs we will first compare the individual macrocycle maps for both charge states in solvent water. Next, on the example of macrocycle 1, we will demonstrate the influence of starting coordinates, i.e. multiple starting conformers versus simulated-annealing run, on the conformer landscape. Third, we will look into population differences depending on the solvent.</p><p>We will then map the conformer generator ensembles onto the MD-derived maps and discuss ensemble completeness based on mapping overlap, conformer energy overlap, intramolecular hydrogen bonding and polar surface areas.</p><!><p>Maps for compound 1 resulting from five 100 ns MD runs at 300 K in solvent SPC water; a neutral, and b positively charged. Color-coding reflects starting coordinates</p><p>Conformer density maps for six macrocycles in solvent water, color-coded by binned raw conformer relative energies with thresholds < 6.0 (blue), ≤ 10.0 kcal mol−1 (pink) and > 10.0 kcal mol−1 (orange). Conformers with relative energies higher than 100 kcal mol−1 were filtered out. Plots a, c, e, g, i, k in the left column show maps for neutral and plots b, d, h, j, l in the right column for positively charged ligands (charged ligand 3 is missing due to N-methylation)</p><!><p>One must be aware that these energies are not comparable to the energies obtained for post-optimized structures, since they always contain an unknown portion of the thermal energy from the MD simulation of the ligand-solvent system. In the final section of this work, we will compare the conformer energy distributions of the post-optimized and RMSD-clustered snapshots with the distributions derived from the ones from conformer generators.</p><p>The maps clearly show that each macrocycle has its distinct conformational profile and that the profile is also dependent on charge state. This indicates that a change in charge state which is a prerequisite to cross a lipophilic cell membrane, will be more probable for structures with highly populated overlapping low energy conformer ensembles between charged and neutral states. For most structures, the map for the charged ligand is more constrained, with the unexpected exception of compound 2, which differs to 1 only by the change in stereochemistry from l-Leu to d-Leu. Drastic changes in the minimum conformations upon change in one stereogenic center were previously also reported by the group of Lokey [20], which allow us to expect the observed differences in the ensemble maps. Also, the distribution between low, medium and high-energy conformations differs between compounds, and more pronounced between charge states. Compound 5 exhibits mostly high-energy conformers (for both neutral and charged state) and only small restricted low energy islands, indicating incomplete sampling, as discussed in the next section. Methylation of Leu in position 1 restricts the overall flexibility much more than the other N-methylations.</p><p>Analysis of the respective maps for the other solvents (Additional file 1: Figures S3, S4) reveals a certain tendency for more constrained maps for charged compared to neutral ligands in DMSO but not in CHCl3. We explicitly mention here that protonation of macrocycles will probably not play a role in DMSO and CHCl3 experimentally. Nevertheless, the computer experiment allows to get insights as far as the force field parametrization is meaningful in this respect.</p><p>Overall, we can conclude that the population of conformational space significantly differs for any ligand between the different solvents.</p><!><p>Conformer map for additional MD runs with three low energy starting conformers of compound 6 in solvent water. a color-coded by starting conformer; b color-coded by binned raw relative energies with thresholds < 6.0 kcal mol−1 (blue), <  = 10.0 kcal mol−1 (pink) and > 10.0 kcal mol−1 (orange). Conformers with relative energies higher than 100 kcal mol−1 were filtered out; the insert in b shows the distribution of snapshot energies over 8 MD runs (energy range 40 kcal mol−1)</p><!><p>Though the maps for all compounds except 5 appear to be complete regarding sampling, exhibiting similar shapes and balanced distributions of snapshot energies, we nevertheless performed some more experiments.</p><p>To test for the effect of sampling time, we additionally ran 10 simulations of 1000 ns each for compound 2 in CHCl3. Longer sampling did not yield new conformational states, suggesting that our standard settings are appropriate, whereas additional diverse starting points are needed in some cases, as shown for 5. Alternatively, we test for the risk of partial coverage of torsional space not caused by sampling time, but by too high barriers to be overcome at 300 K. Simulations for 100 ns at 400 K and 500 K yielded increasingly more overlap between the regions covered by the different starting conformers, providing evidence for high barrier hypothesis (at 800 K the simulations stopped after some time due to evaporating solvent), but also proof that even elevated temperatures do not allow to sample with only one starting conformer as shown in Additional file 1: Figure S6.</p><p>To further confirm the hypothesis, we did simulated annealing molecular dynamics runs with 10 heating and cooling phases up to 500 K for the lowest energy conformer of each molecule, and exemplary also with multiple starting conformers for positively charged 2 in water (see Additional file 1: Figure S7). We found that (i) there were no new basins explored anymore after four to five heating and cooling phases and (ii) the conformational space explored is significantly smaller with missed areas on the map, compared to diverse starting conformer MD runs. Our setup thus allows for exchange between neighbor basins but probably many more cycles and higher temperatures would be needed, making the diverse starting conformer setup the method of choice.</p><p>Based on our findings for compound 5, we emphasize here that we cannot provide final evidence that we were able to identify complete ensembles by our approach. The similar proportions of low, medium and high energy conformation snapshots when applying higher temperature, longer simulation time and simulated annealing suggest complete or near-to-complete sampling, but there is no rigorous approach to quantify completeness.</p><!><p>We performed the simulations in three solvents, namely SPC water, DMSO, and CHCl3, with dielectric constants [53] ε of 78.35, 46.83, and 4.71, respectively. Based on the ε values, and that water is a polar protic and DMSO a polar aprotic solvent, we speculated the conformational space in DMSO to be somewhere in the middle, but with more overlap to water.</p><!><p>Density maps for distributions of accumulated conformers derived from five MD simulations at 300 K with five different starting coordinates for 1 in solvent water (yellow), DMSO (green), and CHCl3 (purple), a for neutral and b for positively charged species</p><!><p>The denser the lines, the more populated. For solvent water there are densely populated areas and distinct islands, and overall only one area of dense overlap between conformers from all solvents, in the upper right corner (latent coordinates of center: 1.3; 2.4). There is more overlap between water and DMSO conformational space. The situation is similar for the neutral and charged species, but with more pronounced water islands for the charged case. We here stress again that experimentally the charged species will not be existent in the organic solvent and play only a minor role in DMSO, whereas in silico we can look into the solvent dependence of such states. The observations can be generalized to the other compounds (cf. Additional file 1: Figure S8).</p><p>The clear separation of conformational spaces in water and chloroform indicates that there will barely be any metastable states pre-formed in water that would allow for rapid entrance and permeation through cell membranes, if we follow the conclusions from the work of the Riniker group [1, 54, 55]. Nevertheless, to test this hypothesis, we would need to apply Markov-state modelling based on much larger numbers of diverse starting conformers.</p><p>Our motivation to perform MD simulations also in DMSO was that this solvent plays a major role as solvent in pharmaceutical research, especially in NMR experiments as the ones performed in our earlier work [13]. Since DMSO based results are always somewhere between water and chloroform results and since there is no implicit solvent model for DMSO for OPLS3e, we decided to not further include DMSO results here.</p><!><p>In the previous section we described the general shapes and properties of the conformational space accessible to the compounds at room temperature as simulated by molecular dynamics. The said space of conformations spanned from 50,000 MD snapshots is significantly larger than the space of minimized conformers generated by conformer search algorithms. To make the spaces comparable, the MD snapshots were all minimized in implicit solvent, always resulting in a collapse of various MD snapshots onto one local minimum conformer. Nevertheless, the plots are still dominated by MD snapshots. No attempt on a meaningful clustering by different algorithms was successful due to the many smaller clusters we would have lost. We therefore decided to stay with the original set sizes.</p><!><p>Maps of latent torsional space accessed by post-minimized MD snapshots (5 starting conformers, 300 K, 100 ns each) for neutral compounds 1, 2 and 7 in SPC water in purple, overlaid with conformers created by BEST (left), PMM (middle) and CONF (right) in yellow. Asterisks indicate level of significance (*** = p-value < 0.0001, ** = p-value < 0.001, * = p-value < 0.01, ns = non-significant)</p><!><p>For compounds 1 to 6, the general observation is that the space covered by MD is larger than for the other methods, at least in the 2-dimensional space of the first principal components. In the following we will discuss in how far our conclusions are true if considering the other 30 dimensions. We observe that the coverage of the maps is highest for PMM, followed by BEST, and most restricted for CONF. The deviations between the torsional spaces covered are highly significant for almost all maps (p-value < 0.0001), with significantly higher mean distance-to-centroid for all MD maps (see also Additional file 1: Table S4). The exception is 2 with significant uncharted territory explored by BEST and PMM compared to MD, but at the same time BEST missing a large part of the MD space. The same is true for the charged species in water and the neutral one in chloroform. This was totally unexpected, since 1 and 2 are enantiomers. Non-overlapping PCA map areas are seen also for compounds 5 in chloroform and positively charged 7 in water (cf. Additional file 1: Figures S10, S11).</p><p>Another major finding that is even more critical for the application in drug design, is that the post-optimized conformer maps from BEST, PMM and CONF are highly similar independently of solvent and charge state, whereas the MD-derived maps show the expected variability. Whereas explicit solvent molecules interact with each other and the solute and by this influence preference of conformational states, implicit solvent models do only modulate the energy function during optimization. Therefore, one can probably not expect to identify solvent-specific low-energy conformers for a particular charge state with a conformer generator if the raw conformer is not preferable based on the "scoring function", may it be some gas-phase like energetics or RMSD or whatever is used.</p><p>Since one could argue that the plots in Fig. 6 could be biased by the imbalance of the number of conformations between MD and the generator methods, we attempted to create the same number of 50,000 raw unoptimized conformations for each method. Even though we stretched settings up to extreme, beyond meaningful values like e.g. an energy threshold of 100,000 kJ mol−1 in case of BEST, we were still not able to arrive at the desired numbers. The computation times increased significantly to multiple hours per run. We obtained only 6,337 conformations for BEST, 12,142 for PMM (38,897 redundant ones that were automatically reduced to the final number), and 24,775 in case of CONF. The respective plots are shown in Additional file 1: Figure S12. The plots clearly indicate that the latent space covered by all generator methods is smaller than that of the MD snapshots, with ranges of about − 1.5 to 2.3 for PC1 and − 2.7 to 2.1 for PC2 of the BEST and PMM maps, compared to about − 2.6 to 2.8 for PC1 and − 2.7 to 2.5 for PC2 of the MD snapshot plot. The map for CONF is drastically different in that it shows only about 20 distinct ring shapes, which means about 1000 side chain conformations obtained per distinct ring conformation.</p><!><p>In the last paragraph, we provided the qualitative picture based on the 2-dimensional overlap maps. The question is now in how far a quantification of the map overlap is possible. In the following we provide three measures to quantify the overlap, namely statistics on mixed and unique clusters, variance statistics, and a novel metric, the Mahalanobis distance for the coverage of torsion space.</p><p>As a first metric, we tried k-means clustering for each combined set of post-optimized conformers from MD and generators for neutral and charged state in water and CHCl3 (for more details and results see Additional file 1: Table S3). With exception of the charged state of the smaller and more rigid macrocycle 7, we find significantly less mixed clusters for CONF than for BEST and PMM. Overall, we have to state here that a reliable quantification of map overlap, and not even a qualitative description, is at all possible by clustering, especially given the strong dependence on arbitrary parameters like required cluster size or RMSD.</p><p>An alternative to clustering that is not dependent on the method and its settings is the quantification of the variance explained by the PCA projection used for the maps. There are two metrics commonly used, namely the total variance and generalized variance, i.e. the trace and the determinant of the eigenvalues of the covariance matrix of the latent variables, the latter generally being interpreted as the volume of the point cloud [56].</p><p>Though it is sometimes claimed that only the metrics considering all principal components are able to describe the ensemble variance, one has to keep in mind that especially higher order principal components might be misleading. Since any geometry optimization is determined by the energy threshold applied, the numerical precision of the dihedral angles obtained will introduce some numerical noise. Such expected smaller variance is also captured, most likely within the higher order principal components. And that is exactly what we see in the total and generalized variance plots.</p><!><p>Plots of the variance explained from the PCA analyses. a Reported is the generalized variance vs. the numbers of the latent variables used for the three methods BEST, PMM and CONF in comparison to the total variance of the MD simulations; b total variance vs. the numbers of the latent variables</p><!><p>Figure 7b on total variance, i.e. the trace of the covariance matrix, analogously shows an earlier and steeper increase for the MD curve than for the generator curves but a crossing of the curves at 14 (BEST), 18 (PMM) or 17 (CONF) latent variables used for the total variance calculation. Perfectly in line with plots of Fig. 6, for the earlier PCs that carry most of the information (67% for PCs 1 to 8) on conformer diversity the total variance is higher for the MD conformational space than for the others. The crossing of the curves was nevertheless unexpected. To identify the root cause of the crossing, we created plots of each pair of latent variables for the example of neutral compound 1 in water (Additional file 1: Figure S13). We find that after 10 latent dimensions, the spaces of the generator and the MD conformers start to separate more and more. As those PCs contain 3% and less of the information content of the conformer space we suspect that such observed variances display more likely uncertainties than meaningful variation.</p><p>To further investigate if that crossing we observe really reflects the noise from the spurious contributions of the higher latent variables, we added artificial normal distributed noise (mean = 0, sd = 2 * pi/180) to the dihedrals. Respective plots are shown in Additional file 1: Figure S14. The trace for the minimized MD conformers describes a logarithmic behavior just like the accumulated variance of the entire space. This is expected as the underlying PCA space is based on the raw MD conformers which are obviously closely related to the minimized samples. Also, as observed already in Fig. 7 the BEST trace describes a more linear curve. This is most likely due to the fact, that the principal components are constructed to maximize the variance of the raw MD conformers. Adding noise results for both sets in reduced traces and in a linearization of the minimized MD trace, affecting the minimized MD trace stronger due to the much higher number of samples with added noise and is therefore difficult to interpret. However, the differentiation between curves with and without noise for the generator starts after the first eight latent variables, that we consider to carry relevant information.</p><p>Both, total and generalized variance provide some indication that the diversity of MD conformer space is indeed higher than for the generators. The variance is concentrated on the early PCs. The starting values of the generalized variance plots indicate the order PMM > BEST >> CONF in accordance to maps in Fig. 6 and the cluster analysis, whereas the curves for the total variance are more or less identical. Since both total and generalized variance do not provide the desired quantification, we looked into a third alternate metric.</p><p>We here apply a concept from machine learning, namely the Mahalanobis distance [57] which is a measure for outliers and thus for the applicability domain of models for a specific data point. The idea here is that we define the conformer space from the generators as the "training set" and the conformer space of the post-optimized conformers from MD as the "prediction set". The more extended the MD space is compared to the generator space, the more "outliers" and the higher the median and maximal Mahalanobis distances.</p><p>The Mahalanobis distance is defined as\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$D{M}_{M}\left(x ight)=\sqrt{{\left(x-\mu ight)}^{T}{S}^{-1}(x-\mu )}$$\end{document}DMMx=x-μTS-1(x-μ)</p><p>With x = ( x1, x2…xN) and µ = (µ1, µ2, … µN) being the latent variables (principal component coordinates, i.e. cartesian coordinates) derived from the original 16-dimensional torsional space (as transformed to 32 sin and cos values) of either a specific conformer or the mean vector of the "training set" and the covariance matrix S. We stress here that for each dimension, i.e. number of latent variables considered, the Mahalanobis distance is scaled independently and the absolute numbers are not strictly comparable. Nevertheless, since the principal components decrease when adding more and more components, and each PC is greater equal zero, the curves will increase monotonically. Both the MD maps and the generator maps are projections on the PCAs from all raw conformers (we define the more restricted map as "training set").</p><!><p>Plots of maximum (top row) and median (bottom row) Mahalanobis distances (y-axis) for generator conformers (red) and MD conformers (blue) for increasing numbers of PCA latent variables (x-axis; between 2 and 32) for neutral compounds in water. Plots a and d show Mahalanobis distances for BEST conformers, b and e for PMM conformers and c and f for CONF conformers</p><!><p>For any number of latent dimensions and any dataset (with the one exception of dimensionalities of 30 and 31 for PMM), the Mahalanobis distances for the MD conformers are always higher than the distances of the conformers for the "training sets" derived from the generators, and the median values are always about half or less of the maximum values. The median Mahalanobis distance values for the conformers for all three generator methods are roundabout 30 for the 32-dimensional space, i.e. the core regions of all spaces are similar in size. The maximum Mahalanobis distances on the other hand differ considerably, with 58 in case of BEST, 116 for PMM and 96 for CONF. Though not quantitatively comparable, this is a hint that the BEST space is overall more compact and that PMM and CONF at least have islands of distinct conformations.</p><p>If we now compare the Mahalanobis distances for the MD conformers with the ones for the generator conformers we find that the MD conformer covered multi-dimensional shapes are always larger. In the cases of BEST and PMM the distances are more or less shifted in parallel, whereas in the case of CONF there is a tremendous distance increase for spaces higher than 7-dimensional. We only observe this change in profile but have no explanation.</p><p>One could argue that Mahalanhobis distance did not indicate the amount of spread were larger for MD, but only that the MD set were different from the conformer generators in some way. We again refer to Additional file 1: Figure S13 that provides the individual maps for compound 1 that shows that the projections indeed overlap in space for all latent dimensions that carry significant information.</p><p>In summary, the plots confirm that BEST and PMM show a better overlap with MD conformers than the very compact conformer ensemble from CONF. Nevertheless, none of them is a complete ensemble. Again, we explicitly state, that there is no guarantee that the MD ensembles, though more diverse, are complete.</p><p>Finally, we should mention that in this work we provide strong evidence that it is important to consider typically more than 2 latent dimensions to represent the data correctly. In the past there were many publications on mapping of chemical spaces like ChemGPS [58], protein–protein interaction ligands [59], or modeling of solubility [60] that did not address this issue.</p><!><p>It is common understanding that compounds capable of forming intramolecular hydrogen bonds (IMHB) will do so more likely in apolar solvents to expose their lipophilic surface, whereas in polar and especially protic solvents they will expose their donor and acceptor functions. The phenomenon is frequently referred to as chameleonic behavior [61, 62]. We therefore calculated the numbers of IMHB for each ensemble of snapshots, based on slightly relaxed angle and distance constraints to account for the non-minimum nature of the snapshot coordinates.</p><!><p>Histograms of percentages of intramolecular hydrogen bonds (0 to 3 IMHB, top x-axis labels) for the conformers of molecules 1 to 7 (bottom x-axis labels) as derived from five MD simulations at 300 K with five different starting coordinates in different media; blue bars for neutral compounds in SPC water, red bars for positively charged compounds in SPC water, green bars for neutral compounds in CHCl3; a MD snapshots; b post-optimized MD snapshots; c BEST conformers; d PMM conformers; e CONF conformers</p><!><p>The IMHB population profiles for all molecules based on MD snapshots in Fig. 9a proof the assumption that in CHCl3 there is a higher proportion of snapshots with two and even with three IMHB. Unexpectedly, the charged structures in water have a higher proportion of snapshots with zero IMHB, whereas the neutral species have more snapshots with one or two IMHB than the charged species though formally possessing one less hydrogen donor. Visual inspection of the 3D structures reveals that the additional proton disturbs the ring geometry in a way that reduces the interactions of the NH donor at the linker and carbonyl acceptors.</p><p>Post-optimizing the snapshots with OPLS3e and implicit solvent increases the proportions of snapshots with higher numbers of IMHBs in most cases (Fig. 9b).</p><p>The conformers derived from BEST and CONF shown in Fig. 9c, e, which were also post-optimized with OPLS3e and implicit solvent provide a different picture. For all structures, the IMHB population statistics is zero > one > two >> three. On the other hand, the PMM profiles in Fig. 9d are somehow in between the profiles from not-optimized MD and the other generators.</p><p>We conclude that the differences in profiles for PMM (which is using the same force field than the MD) are mostly governed by the influence of the implicit solvent used for post-optimization, whereas the differences for BEST and CONF mostly originate from conformer generation and are additionally influenced by post-optimization. Nevertheless, all generator conformer populations differ from the MD population.</p><!><p>The chameleonic behaviour seen with regards to IMHB—at least from the MD snapshots—should also be reflected in the distributions of polar surface areas calculated from the 3-dimensional structure.</p><!><p>Median, minimum and maximum 3D-PSA values in Å2 for MD snapshots in different media and charge states</p><p>aWater, neutral</p><p>bWater, positively charged</p><p>cChloroform, neutral</p><!><p>The other driver is as expected N-methylation as in compounds 3, 4, 5, 6 which reduces polar surface area by median 8.9 Å2 (+−5.6) compared to the highest value in each column.</p><!><p>Histograms for the frequencies of 3D polar surface areas in Å2 of the conformers derived from five MD simulations at 300 K with five different starting coordinates for compounds 1 (top row) and 7 (bottom row); a solvent water, neutral, b water, positively charged, c CHCl3, neutral</p><!><p>The changes in 3D-PSA are in fact to a high degree governed by side chain and backbone movements hiding polar functional groups and not so much by stability and changes of the intramolecular hydrogen bond networks.</p><!><p>The completeness of the conformational ensemble one obtains by a computational method will significantly influence the outcome of any computational study based on the ensemble. In this work we provide a thorough investigation on the multiple parameters that determine the resulting conformer ensembles from molecular dynamics simulations and from three algorithms for the generation of conformers for seven small macrocycles resulting from a collaboration with the University of Sherbrooke.</p><p>We show that multiple molecular dynamics simulations on diverse starting conformations per molecule are needed to generate ensembles covering the accessible conformational space, but even such procedure does not guarantee complete sampling, i.e. the intended ensemble completeness, in the case of such highly rigid macrocycles. This is in line with other publications on molecular dynamics and Markov-state modelling.</p><p>The conformer map projections from principal components analysis on the ring torsions differ between molecules, for different charge states and for different solvents. Especially the maps for compounds 1 and 2 which are enantiomers (l-Leu vs. d-Leu) differ much more than anticipated, which can be rationalized by the loadings plots from the PCA showing that only a small number of torsions determine the conformer distributions.</p><p>The conformer maps in the three solvents considered, namely water, DMSO and CHCl3 differ strongly for each molecule and there is low overlap of the densely populated spaces, what, according to current work in the group of Riniker, would be a prerequisite for pre-orientation and smooth transfer through cell-membranes.</p><p>Ensembles from molecular dynamics at room temperature cover a conformational space significantly larger than the space of local minima. The maps of post minimized MD derived snapshots span a larger space than maps derived from algorithms for conformer generation. In addition to performing a cluster-based analysis and the evaluation of variance metrics we here propose a novel metric for the quantification of the space spanned by such algorithms compared to MD derived space by applying the Mahalanobis distance used in machine learning as an applicability domain measure and for outlier detection. We show that the space covered by PMM is more complete than the BEST space and that the CONF space is the most restricted one.</p><p>Furthermore, we find that whereas the MD ensembles from different explicit solvent simulations look distinct, the implicit solvents used during the post optimization of the raw conformers only slightly influence the final coordinates. Therefore, conformational states in implicit solvents will not reflect the true interactions between solute and solvent and the ensemble obtained from explicit solvent calculations. Any results from such ensembles might be doubted.</p><p>Finally, since our investigation aimed at an understanding of parameters influencing membrane permeation as an important parameter in the design of drug candidates, we looked into the two parameters often related to permeation, namely polar surface area and intramolecular hydrogen bonding. For molecules 1 to 6 we see no significant differences in the 3D-PSA profiles over the MD snapshots between the molecules but also for different charge states or solvents for one molecule. Compound 7 with the smaller ring system shows the shift in 3D-PSA, but again there is no differentiation on charge state or solvent. Overall, the molecules are too rigid to react on the exterior. There is no correlation between 3D-PSA and distributions of intramolecular hydrogen bond patterns but at least as expected more IMHB in nonpolar solvents. In contrast, we find that the 3D-PSA of 1 with the smaller ringsize is 20 Å2 higher than that of the larger ring 5 but at the same time 1 has a higher mean population of intramolecular hydrogen bonds. Though unintuitive, this can be rationalized by looking at the conformer coordinates. Whereas the small ring is so constrained that it has to expose polar groups to the exterior, the less constrained larger ring can partially mask the polar functionalities by side chains like the aromatic ring of phenylalanine or the leucine chain.</p><p>The work performed here is concerned with small rigid macrocycles. Though we expect the findings to be transferable, we will perform a follow-up study on open-chain small drug-like molecules.</p><!><p>Additional file 1: Table S1. Data on explained variance by the latent variables PC1 to PC4 from the principal component analyses for the macrocycle ensemble (1 to 6: all) and for individual macrocycles for the different charge states. Solvents considered are mixed all solvents, water, DMSO and chloroform. Table S2. Percentages of conformers with between 0 and 3 IMHB in different media and charge state. Table S3. Cluster populations for compounds 1 to 7 for neutral (n) and charged (c) species in water (W) and chloroform (C). Table S4. Results of Homoscedasticity Test with post Hoc Tukey HSD Test. Figure S1. Correlation between 2D TPSA and 3D PSA values for 10,000 randomly selected compounds from the Aldrich Market Select catalogue. Figure S2. Torsion angle distribution profiles expressed as sinus and cosinus distributions of the original 32-dimensional space after transformation. Figure S3. Conformer maps for macrocycles 1 to 6 in solvent DMSO, color-coded by binned raw conformer relative energies with thresholds of 6 and 10 kcal mol-1 (conformers with relative energies higher than 100 kcal mol-1 were filtered out). Figure S4. Conformer maps for macrocycles 1 to 6 in solvent CHCl3, color-coded by binned raw conformer relative energies with thresholds of 6 and 10 kcal mol-1 (conformers with relative energies higher than 100 kcal mol-1 were filtered out). Figure S5. Histograms of the energy distributions of the MD snapshots for macrocycles 1 to 7 in solvent water. Figure S6. Conformer ensembles for charged compound 1 in solvent CHCL3. Figure S7. Ensembles for compound 2 in water generated by a simulated annealing protocol; a) and c) show the neutral, b) and d) the charged state. Figure S8. Density maps for distributions of accumulated conformers derived from five MD simulations at 300 K with five different starting coordinates in solvent water (orange), DMSO (blue), and CHCl3 (pink), for neutral compounds 1 to 6. Figure S9. Maps of latent torsional space accessed by post-minimized MD snapshots (5 starting conformers, 300 K 100 ns each) for neutral compounds in SPC water in purple, overlaid with conformers created by BEST (left column), PMM (middle) and CONF (right) in orange for macrocycles 1 to 7 (see row labels). Figure S10. Maps of latent torsional space accessed by post-minimized MD snapshots (5 starting conformers, 300 K 100 ns each) for charged compounds 1 to 7 in SPC water in purple, overlaid with conformers created by BEST (left column), PMM (middle) and CONF (right) in orange. Note that compound 3 is missing since it is N-methylated. Figure S11. Maps of latent torsional space accessed by post-minimized MD snapshots (5 starting conformers, 300 K 100 ns each) for neutral compounds 1 to 7 in CHCl3 in purple, overlaid with conformers created by BEST (left column), PMM (middle) and CONF (right) in orange. Figure S12. Maps of latent torsional space accessed by a) raw MD snapshots (5 starting conformers, 300 K 100 ns each, solvent water) for neutral compound 1, b) raw (non-minimized) conformations by BEST, c) raw conformations by PMM, d) raw conformations by CON. Figure S13. 16 plots providing the complete conformer space mapping in 32 latent dimensions for 1, neutral state in water. Figure S14. Dependence of total variance (trace) on the number of principal components considered; a) traces for minimized MD (blue) and BEST (green), both projected on the map created from all raw conformers, and the accumulated variance (cum. Proportion, red), showing that the curves cross at the point of about 90% of explained variance; b) traces for minimized MD (pink) and BEST (blue), with dashed lines for normal distributed noise (mean=0, sd=2*pi/180) generated for each sample for each dihedral angle. Figure S15. Histograms of 3D-PSA distributions for the MD snapshots (5 starting conformers, 300 K 100 ns each) of compounds 1 to 7; left column shows neutral compounds in water, center column charged compounds in water, right column neutral compounds in CHCl3. For N-methylated compound three there is no charged species.</p><p>Additional file 2. Text file with 3D coordinates of starting conformers in SDF file format.</p><p>Publisher's Note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>

PubMed Open Access

Cascade radical reaction of substrates with a carbon–carbon triple bond as a radical acceptor

The limitation of hydroxamate ester as a chiral Lewis acid coordination moiety was first shown in an intermolecular reaction involving a radical addition and sequential allylation processes. Next, the effect of hydroxamate ester was studied in the cascade addition-cyclization-trapping reaction of substrates with a carbon-carbon triple bond as a radical acceptor. When substrates with a methacryloyl moiety and a carbon-carbon triple bond as two polarity-different radical acceptors were employed, the cascade reaction proceeded effectively. A high level of enantioselectivity was also obtained by a proper combination of chiral Lewis acid and these substrates.

cascade_radical_reaction_of_substrates_with_a_carbon–carbon_triple_bond_as_a_radical_acceptor

Introduction<!>Results and Discussion<!>Conclusion<!>Supporting Information

<p>Strategies involving a cascade process offer the advantage of multiple carbon-carbon and/or carbon-heteroatom bond formations in a single operation. Radical chemistry has been developed as one of the most powerful tools for carbon-carbon bond formation in organic synthesis [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Particularly, the advantages for utilizing the radical methodologies are the high functional group tolerance and the mild reaction conditions, because radical intermediates are not charged species. Therefore, a number of extensive investigations into sequential radical reactions have been reported over the past fifteen years and significant progress has been made in recent years [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]. We have also directed our efforts toward the development of new and efficient cascade approaches for the construction of carbon-carbon/heteroatom bonds based on radical chemistry. These approaches can be classified into two categories according to their reaction mechanism (Figure 1) [37][38][39][40][41][42][43].</p><p>Enantioselective radical reactions have been intensively studied over the past fifteen years. Compared with stereocontrol studies on intermolecular radical reactions, the enantioselective stereocontrol in radical cyclizations still remains a major challenge . We have also investigated a new type of chiral Lewis acid mediated cyclization approach for cascade bond-forming reactions via sequential radical-radical processes (Figure 2) [39][40][41][42][43]. In these studies, the control of the enantioselectivities was achieved by the introduction of a hydroxamate ester as a two-point-binding coordination tether into the middle of substrates A, together with the control of the rotamer population of substrates [39,42]. In this paper, we describe in detail the cascade addition-cyclization-trapping reaction of substrates with a carbon-carbon triple bond as a radical acceptor as well as the effect of hydroxamate ester as a Lewis acid coordination moiety. Some results have been reported in our preliminary communication [39].</p><!><p>Renaud's group showed in 2002 that hydroxamic acid derivatives are useful achiral templates in enantioselective Diels-Alder reactions [69,70]. To study the effect of hydroxamate ester as an achiral template in the intermolecular radical reaction, our experiments began with the investigation of cascade radical addition-allylation of hydroxamate esters 3A-C having an acryloyl moiety (Scheme 1). The reactions were eval-Scheme 1: Effect of hydroxamate ester on intermolecular C-C bondforming reactions. uated in CH 2 Cl 2 at −78 °C by employing isopropyl iodide, allyltin reagent, and Et 3 B as a radical initiator. The enantiomeric purities of products were checked by chiral HPLC analysis. The effect of the substituents R 1 and R 2 of hydroxamate esters 3A-C on yield and selectivity was evaluated in the presence of a chiral Lewis acid prepared from box ligand L1 and Zn(OTf) 2 . The results are shown in Scheme 1. Although good enantioselectivities were not observed, the size of the substituents had an impact on enantioselectivity with the larger group leading to lower ee. These observations indicate that the formation of the rigid ternary complex of hydroxamate ester, Zn(OTf) 2 and the ligand L1 is required for enantioselective transformation. A similar trend was observed in our studies on the addition-cyclization-trapping reaction of hydroxamate esters [39,42]. The chiral Lewis acid promoted the reaction of substrate 3A having a bulky 2-naphthylmethyl group as substituent R 2 to form the product 4A in 40% yield with 7% ee. Moderate enantioselectivity was observed by employing the substrate 3B having a benzyl group as R 1 and a methyl group as R 2 . Particularly, the steric factor of the fluxional substituent R 1 affected not only enantioselectivity but also the chemical efficiency. The use of 3C having a 2-naphthylmethyl group as R 1 led to a decrease in the chemical yield, probably because of the steric repulsion by a bulky substituent R 1 leading to the dissociation of the chiral Lewis acid. In these studies, the absolute configuration at newly generated stereocenters has been not determined.</p><p>We recently reported in detail the cascade addition-cyclization-trapping reaction of substrates with carbon-carbon double bonds as two kinds of polarity-different radical acceptors [42]. On the basis of these results, the possibility of the carbon-carbon triple bond as a radical acceptor and the hydroxamate ester functionality as a two-point-binding coordination tether was next studied in detail. To understand the scope and limitation of the cascade transformation of hydroxamate esters with carbon-carbon triple bonds, the substrates of choice were 5, 6A-C, 7 and 8 having hydroxamate ester functionality (Figure 3). At first, we studied the cascade reaction of 5 with an acryloyl moiety and 6A-C with a methacryloyl moiety as an electrondeficient acceptor in the absence of a chiral ligand (Scheme 2). To control the rotamer population of substrates, Zn(OTf) 2 was used as a Lewis acid to coordinate the hydroxamate ester functionality. The reactions were evaluated in CH 2 Cl 2 at 20 °C under the tin-free iodine atom transfer conditions by using isopropyl iodide and Et 3 B. The reaction of hydroxamate ester 5 did not give the desired product probably due to polymerization of 5 through the labile acrylamide moiety. In contrast, the reaction of 6A-C proceeded effectively to give the cyclic products 9Aa-9Ca in good yields. Among them, hydroxamate esters 6A and 6B, which have a small methyl or benzyl group as R 1 , have shown a high reactivity, although a 76% yield of product 9Ca was obtained even when hydroxamate ester 6C having a 2-naphthylmethyl group was used. Furthermore, the regiochemical course of the initial radical addition to 6A-C was well controlled. The nucleophilic isopropyl radical reacted selectively with the electron-deficient methacryloyl moiety to give the single isomers 9Aa-9Ca.</p><p>It is also important to note that Z-isomers 9Aa-9Ca were selectively obtained without the formation of corresponding E-isomers. The E,Z-selectivities are determined by capturing the intermediate vinyl radicals with an atom-transfer reagent such as isopropyl iodide (Figure 4). These selectivities are controlled by the steric factor around vinyl radicals. The vinyl radicals are σ-radicals in a very fast equilibrium between E-isomer B and Z-isomer C. The steric hindrance between the substituents on the α-carbon atom of radical C and isopropyl iodide is assumed to lead to selective iodine atom-transfer in radical B giving 9Aa-9Ca as single Z-isomers. On the basis of the above results, we next studied the reaction of 6A-C at −78 °C in the presence of Zn(OTf) 2 and chiral box ligands L1-L3 (Scheme 3 and Table 1). A stoichiometric amount of chiral Lewis acid prepared from Zn(OTf) 2 and ligand L1 accelerated the reaction of hydroxamate ester 6A having a methyl group as substituent R 1 (Table 1, entry 1), although the reaction of 6A did not proceed effectively at −78 °C in the absence of box ligand L1. The desired product 9Aa was isolated as a single isomer in 51% yield with 60% ee after being stirred for 10 h. The use of hydroxamate ester 6B having a benzyl group led to not only an enhancement in chemical yield but also to an improvement in enantioselectivity to give the pro- 1, entry 3 and 4). Further reduction of the chiral Lewis acid load to 10 mol % resulted in a decrease of both the chemical yield and enantioselectivity (Table 1, entry 5). In the case of 10 mol % of the chiral Lewis acid, the ternary complex of the ligand, the Lewis acid and the substrate were not effectively formed, and the background reaction giving the racemic product proceeded. Additionally, the high Z-selectivity of product 9Ba indicates that the stereoselective iodine-atom transfer from isopropyl iodide to an intermediate radical proceeded effectively under these catalytic reaction conditions. The reaction using box ligand L2 instead of L1 attenuated the enantioselectivity ( The absolute configuration at the newly generated stereocenters of 9Aa-Bd was assumed by similarity between the present reaction and the previously reported reaction of substrates having the carbon-carbon double bond [39,42]. In these reactions, a ternary complex of ligand, Lewis acid and substrate would control the three-dimensional arrangement of two radical acceptors. A tetrahedral or cis-octahedral geometry around the zinc center was proposed [71,72]. In Figure 5, a tentative model of an octahedral complex is shown, in which two oxygen atoms of the hydroxamate ester functionality occupy two equatorial positions.</p><p>To study the effect of an electron-deficient acceptor on the cascade process, the reactions of propiolic acid derivatives 7 and 8 were tested (Scheme 4). At first, the reaction of 7 was evaluated under asymmetric reaction conditions. However, the cascade addition-cyclization-trapping reaction did not proceed, and the simple adduct 10 was formed in 57% yield by the addition-trapping process. Next, the reaction of propiolic acid derivative 8 was tested, because we expected the [1,5]-hydrogen shift from 1,3-dioxolane ring into the reactive vinyl radical as shown as D. However, the simple adduct 11 was only obtained Scheme 6: Cascade reaction of 14.</p><p>in 78% yield. The results from these studies show that a carbon-carbon double bond, e.g., a methacryloyl group, of the electron-deficient acceptor is essential for the successful cascade transformation.</p><p>To gain further insight into the stereocontrol in the cyclization step, we next studied the opposite regiochemical cyclization by using the substrate 12 via the intermediate radical F (Scheme 5). The reaction was carried out in the presence of Bu 3 SnH under asymmetric reaction conditions. Although the reaction proceeded even at −78 °C, the nearly racemic product 13 was isolated in 60% yield. This observation indicates that the regiochemical course of the cyclization step is an important factor to achieve the highly asymmetric induction.</p><p>Scheme 5: Opposite regiochemical cyclization using substrate 12.</p><p>We next investigated the reactivity of internal alkynes as electron-rich acceptors (Scheme 6). The internal alkyne 14 has shown a good reactivity comparable to that of the terminal alkynes 6A-C. In the absence of a chiral ligand, the zinc Lewis acid accelerated the reaction of alkyne 14 with an isopropyl radical at 20 °C to give the desired cyclic product 15a in 73% yield. Under analogous reaction conditions, both cyclohexyl iodide and cyclopentyl iodide worked well to give 15b and 15c in 65% and 68% yields, respectively. However, the reaction with a bulky tert-butyl radical did not proceed effectively, probably due to side reactions such as polymerization.</p><p>We finally investigated the enantioselective reaction of internal alkynes 14 and 16 (Scheme 7). The reaction of 14 proceeded with good enantioselectivities (Table 2). When a stoichiometric amount of chiral Lewis acid was employed, the reaction with an isopropyl radical gave the desired product 15a in 86% yield with 83% ee (Table 2, entry 1). The reaction proceeded equally well with 30 mol % of chiral Lewis acid as with a stoichiometric amount (Table 2, entry 2). The secondary radicals, generated from cyclohexyl iodide or cyclopentyl iodide, reacted well to afford 15b and 15c with 85% ee and 83% ee, respectively (Table 2, entry 3 and 4). In marked contrast to the reaction in the absence of a chiral ligand (Scheme 6), the use of bulky tertbutyl iodide led to not only an enhancement in chemical yield but also to an improvement in enantioselectivity ( 2, entry 9). It is also important to note that the high Z/E-selectivity of products was observed even when internal alkynes 14 and 16 were employed. These results indicate that the iodine atom-transfer from R 2 I to the substituted vinyl radicals proceeded stereoselectively. Particularly, the substrate 16 having a phenyl group gave the intermediate linear π-radical. Thus, the capture of linear vinyl radical with atom-transfer reagent would be influenced by the steric hindrance around the quaternary carbon atom [43].</p><!><p>We have shown the cascade radical addition-cyclization-trapping reaction of substrates with a carbon-carbon triple bond as a radical acceptor as well as the scope and limitation of hydroxamate ester as a coordination site with a chiral Lewis acid. Synthetic strategies involving enantioselective radical cyclizations would be desirable tools for preparing functionalized cyclic compounds with multiple stereocenters. These studies offer opportunities for further exploration of fascinating possibilities in the realm of cascade radical reactions.</p><!><p>Supporting Information File 1</p><p>General experimental procedures, characterization data of obtained compounds, and preparation of substrates.</p><p>[http://www.beilstein-journals.org/bjoc/content/ supplementary/1860-5397-9-128-S1.pdf]</p>

Beilstein

A fingerprint pair analysis of hERG inhibition data

BackgroundDrugs that bind to the human Ether-a-go-go Related Gene (hERG) potassium channel and block its ion conduction can lead to Torsade de Pointes (TdP), a fatal ventricular arrhythmia. Thus, compounds are screened for hERG inhibition in the drug development process; those found to be active face a difficult road to approval. Knowing which structural transformations reduce hERG binding would be helpful in the lead optimization phase of drug discovery.ResultsTo identify such transformations, we carried out a comprehensive analysis of all approximately 33,000 compound pairs in the Novartis internal database which have IC50 values in the dofetilide displacement assay. Most molecular transformations have only a single example in the data set; however, a few dozen transformations have sufficient numbers for statistical analysis.ConclusionsWe observe that transformations which increased polarity (for example adding an oxygen, or an sp2 nitrogen), decreased lipophilicity (removing carbons), or decreased positive charge consistently reduced hERG inhibition between 3- and 10-fold. The largest observed reduction in hERG was from a transformation from imidazole to methyl tetrazole. We also observe that some changes in aromatic ring substituents (for example hydrogen to methoxy) can also reduce hERG binding in vitro.

a_fingerprint_pair_analysis_of_herg_inhibition_data

Background<!><!>Results and discussion<!>Aggregate size distribution vs. mean effect of hERG inhibition<!><!>Aggregate size distribution vs. mean effect of hERG inhibition<!>Size distribution of aggregates follows a power law distribution<!><!>Sets of transformations<!><!>Adding aliphatic oxygen frequently reduces hERG inhibition<!>Aromatic substitutions reduce hERG inhibition<!><!>Changing the environment of the amine nitrogen can reduce hERG inhibition<!><!>Miscellaneous transformations that reduce lipophilicity<!><!>A comment on transformations not observed<!>ΔSlogP versus Δlog (hERG) for the transformations<!><!>Conclusions<!>Methods<!>Abbreviations<!>Competing interests<!>Authors’ contributions<!>Authors’ information<!>Additional file 1: Figure S1<!>

<p>Inhibition of the human Ether-a-go-go Related Gene (hERG) channel can be a limiting toxicity for drug candidates. The hERG channel regulates transmembrane movement of potassium ions and is a major contributor to the repolarization phase of the cardiomyocyte action potential in the heart [1]. Inhibition of the hERG channel causes lengthening of the cardic QT interval, which can lead to Torsade de Pointes (TdP) [2]. It was this toxicity that in 1997 led to the withdrawal of terfenadine (Seldane) [3]. Although the Redfern criteria is that the IC50 (half maximal inhibitory concentration in vitro) be more than 30 fold greater than the Cmax (the maximum plasma concentration in vivo), typically during lead optimization the Cmax (or dose) is not known [2]. However, project teams can estimate toxicity from in vitro IC50s. For drugs with submicromolar Cmax, an in vitro hERG inhibition IC50 of greater than 30 micromolar (μM) in the radio-ligand binding assay [4] is generally considered desirable; having an IC50 of less 10 μM is cause for concern and must be improved. The frequency and severity of hERG inhibition drives drug discovery teams to make considerable efforts in measuring, analyzing, and mitigating hERG inhibition [4].</p><p>QSAR (Quantitative structure–activity relationship) models using machine learning algorithms [5,6] are established tools for analyzing biological activity data, either with linear (linear discriminate analysis (LDA), partial least squares (PLS) [7]) or non-linear (multi-layer perceptrons [8] support vector machines (SVM), random forest, multivariate adaptive regression splines (MARS) methods. These models find several important descriptors of hERG inhibition, including AlogP or ClogP (measures of lipophilicity), the presence of two lipophilic atoms separated by 10 bonds, fluorine atom count, carbon-carbon double bonds, the presence of a hydroxyl, and partial negative surface area [7,8]. Regardless of the method chosen, the resulting mathematical model is smoother than the sharpest changes in the data [9]. This contrasts with the needs of lead optimization, in which one wants to find the smallest chemical change that makes the best similar compound. To find the sharpest changes in the data, it is molecular pair analysis rather than global QSAR models that is most applicable approach [10,11].</p><p>Matched molecular pairs analysis defines a transformation as a change at an attachment point (this may be generalized to multiple attachment points). Literature reports of analysis of pairs started in the mid-2000s [9,12,13]. Leach et al. aggregated their aqueous solubility, plasma protein binding and oral exposure data with pre-specified transformations [14]. In a very comprehensive analysis of GlaxoSmithKlines's internal data, Papadatos et al. analyzed the effects that many matched pairs transformations had on hERG inhibition [15]. The authors analyzed those pairs for context and found several that were statistically different from the overall matched pair average and for hERG they gave details for 3 such examples.</p><p>The SALI (Structure-Activity Landscape Index) approach to pairs analysis uses similarity distance (typically fingerprint based) to identify pairs [10]. While SALI may be useful for inspection of individual (also called cliff) pairs, these singleton examples lack statistical significance. To identify transformations that have a Wilcoxon consistent effect on hERG inhibition, we introduce fingerprint pairs, which are an extension of the SALI approach. Aggregating the pairs allows us to make observations about which transformations have an effect on hERG binding (see Figure 1 and Methods section). In contrast with matched pairs approaches, which aggregate the pairs by breaking at a single bond, in our approach the fingerprint pairs implicitly aggregate based on contextual information.</p><!><p>A schematic of a transformation and its ECFP representation. At the top of the schematic, we show the initial and final molecules, and their EFCP fingerprint representation. The last line shows the EFCP representation of the transformation is characterized by which EFCP fingerprints disappear from the initial molecule and which appear in the final molecule.</p><!><p>With a list of individual fingerprint pairs, we then collect the individual pairs into aggregates. We then make observations about the whole collection of transformations. We move onto the discussion of particular transformations where we have enough supporting examples. We conclude with some observed trends across these pairs.</p><!><p>After computing all the transformations in the data, we group the pairs such that those making the same chemical transformation are aggregated together. Each aggregate is summarized by its mean hERG inhibition and the number of pairs in the aggregate (Figure 2). The x-axis shows the number of examples it has and the y-axis its average change in log (hERG) inhibition. The graph's top and bottom halves are symmetrical about the y-axis because each transformation also appears in reverse. In the reverse transformation, the initial molecule, final molecule, the sign of the difference vector, and the sign of the log (fold change) are all reversed.</p><!><p>Aggregate size vs. its mean change in log potency. Each point is an aggregate of the same kind of transformation. The x-axis shows the numbers of examples the aggregate has and the y-axis shows the geometric average of fold change in each aggregate. See text for discussion.</p><!><p>To determine which aggregates have sufficient statistical power, we use the Wilcoxon distribution, since we do not assume the data are normally distributed. Most transformations probably have at least a small effect on hERG inhibition; however, for aggregates with 4 or fewer examples (that is almost all aggregates), the Wilcoxon confidence interval includes zero or no change. We discard these aggregates and proceed only with those aggregates containing five or more examples (see Methods for details).</p><p>In our data set of ~33 K aggregates, there are 112 aggregates with five or more examples; that is, 56 transformations and their reverse transformations. Each is considered individually. While the observed changes in these transformations may be explainable by various models based on SlogP, predicted ionization, and/or aromatic atom counts, such quantitative analysis is beyond the scope of this paper. However, we do note the ΔSlogP in each aggregate.</p><!><p>Figure 3 shows the size of aggregates versus the frequency of their occurrence in the data set. These are the examples from the top half of Figure 2 (that is, one direction of the transformation). The distribution of sizes of collected aggregates roughly follows a power law: a few transformations occur commonly, very many occur infrequently, and most transformations are only seen once. The power law distribution is also observed when 3the transformations are aggregated as matched molecular pairs. In this data set, 32,802 of the transformations are singletons (that is, they are size 1); just two aggregates have 28 examples.</p><!><p>A histogram of aggregate size. The x-axis is aggregate size and the y-axis is the numbers of aggregates at that size in log scale at that size. Aggregate sizes follows a power law distribution. See text for discussion.</p><!><p>As discussed above, only 56 aggregates had sufficient examples to allow for conclusions to be drawn about the chemical transformation. Of these 56, only 17 made a significant reduction in hERG inhibition. Figure 4 through 7 enumerate these transformations. In many of the transformations hERG inhibition follows the expected qualitative trends: decreasing lipophilicity, decreasing basicity, and increasing acidity all decrease the potency of hERG blockers. While our observations reflect consistent behavior seen in the database, we cannot claim that they are completely general because of the narrowness of the molecular context. Due to their proprietary nature, we cannot disclose the full structures, but the molecules in the transformations are similar to each other. Given the range of changes in hERG inhibition IC50s observed in our data set, improvements by 2- and 3-fold are notable.</p><!><p>Transformations that add oxygen and reduce hERG inhibition. For each transformation we show the fold reduction in hERG inhibition, the number of examples that increase the IC50, the number that decrease the IC50, and change that this transformation makes in the SlogP model of logP.</p><!><p>We observe that transformations that introduce a hydroxyl near an amine and changing a 7 member ring into a 6 membered ring and a methyl group reduce hERG inhibition by 2 to 6 fold (Figure 4, Rows 3 and 5). There are no transformations in which introducing a hydroxyl near an amine increases hERG binding (see Figure 4). Changing a molecule with two amines into a system with one amine and a hydroxyl group reduces hERG inhibition by 4 to 6 fold (Figure 4, Rows 1, 2 and 4), and increases SlogP/estimated lipophilicity.</p><!><p>Basic nitrogen atoms are the key to potent hERG blockers; however, introducing sp2 nitrogens reduces inhibition in many transformations. Our largest observed reduction in hERG inhibition lowers hERG inhibition by 15 fold by adding sp2 nitrogens to the slightly basic imidazole to obtain the somewhat less lipophilic methyl tetrazole (Figure 5, row 1). Changing a pyridyl nitrile to a -CF3 group reduces inhibition by 4.7 fold (Figure 5, row 2). We speculate that these reductions in hERG inhibition come from reducing lipophilicity and/or altering the energetics of pi-stacking of the inhibitor's aromatic groups with aromatic groups in the hERG channel. However, exploring this question is beyond the scope of this paper [16].</p><!><p>Transformations that alter an aromatic system. For both transformations we show the fold reduction in hERG inhibition, the number of examples that increase the IC50, the number that decrease the IC50, and change that this transformation makes in the SlogP model of logP.</p><!><p>Transformations in Figure 6 show that removing carbons and/or changing the electronic environment around the basic nitrogen can result in a modest reduction in hERG binding. The transformation in Figure 6, Row 1 shows us that removing carbon atoms and adding a hydroxyl has a consistent and substantial effect on hERG inhibition. Row 2 shows us that adding a cyclopropyl adjacent to nitrogen reduces the hERG inhibition. It is the reduction in basicity [17] that is likely responsible for this change. Three transformations show that removing carbon atoms reduces hERG inhibition (Figure 6, rows 3, 4 and 5). The last row (Figure 6, row 6) shows that the effect is not simply reducing lipophilicity, but is also from changing the chemical environment around the nitrogen, in particular the removal of the beta carbon.</p><!><p>Transformations which remove carbons or change the N environment. For these transformations we show the fold reduction in hERG inhibition, the number of examples that increase the IC50, the number that decrease the IC50, and change that this transformation makes in the SlogP model of logP.</p><!><p>In this Figure the transformations that reduce hERG inhibition generally reduce lipophilicity. The transformation in Figure 7, row 1 which removes 2 carbons and changes the primary nitrogen into a secondary nitrogen improves hERG by 3 fold. Going from pyridyl, gem dimethyl hydroxyl to pyridyl nitrile (Figure 7, row 2) improves hERG by 2.5 fold and reduces inhibition in 7 out of 8 examples. Going from ethyl piperazine to methyl piperazine (Figure 7, row 3) results a 2.2 fold reduction in hERG inhibition. This change may result from lipophilicity and/or pKa effects on the nitrogen. A transformation from methyl to methoxy (Figure 7, row 4) has a small effect (~1.7 fold), reducing hERG binding in 17 out of 21 examples.</p><!><p>Miscellaneous lipophilicity reducing transformations. For these transformations we show the fold reduction in hERG inhibition, the number of examples that increase the IC50, the number that decrease the IC50, and change that this transformation makes in the SlogP model of logP.</p><!><p>The direct addition of a carboxylic acid or the removal of an amine group does not occur in any aggregate with 5 or more examples. While we would expect these transformations to make a difference in hERG inhibition, our approach also looks at context, and none of these transformations appear with enough examples to pass our statistical threshold. Other techniques are needed to observe this effect (and others) in the data.</p><!><p>Although we expect SlogP to make a difference in hERG inhibition, Figure 8 shows that its effect is not determinative. It is likely confounded by ionization and as well as other factors. We observe a number of transformations that reduce hERG inhibition even while increasing the SlogP. The points in Figure 8 are labeled with the Figure and Row in which they appear.</p><!><p>This plot shows the ΔSlogP versus Fold Change (log scale) for the transformations. Each point is labeled by the Figure and Row in which it appears. See text for discussion.</p><!><p>An attractive aspect of our approach, which does not use a preselected list of transformations, is that the resulting pair list is comprehensive in the data set used; that is, every transformation in the dataset is considered in the analysis. However because of the stringent statistical approach we applied most transformations are not used. One approach to extracting additional information from this dataset is to build a QSAR model on the vector fingerprint change of the transformations. Another attractive aspect of pair analysis for informing lead optimization is that the analysis is directly in the form of a change in chemical structure. Specific structural changes are revealed to reduce hERG binding, rather than indirect through descriptors like SlogP [18], PSA [19], Chi-Square [20] or BCUT [21]. In broad terms, the transformations' effects are straightforward; for example, the removal of the basic nitrogen or the manipulation of the pKa of the basic nitrogen environment by addition or removal of nearby alkyl groups. This approach found some subtle transformations that reduce hERG binding, including adding hydroxyls, adding sp2 nitrogens, or putting amide substitutions on aromatic rings. We expect that just as cheminformatics tools are currently applied to molecular representations to cluster, search and model molecules, these approaches can be applied to cluster, search and model transformations.</p><p>We observe that most transformations have no more than a modest change in hERG inhibition. This reinforces our impression from medicinal chemistry that hERG inhibition has a rather flat structure activity relationship: we rarely observe subtle changes in structure that result in dramatic changes in activity. Contrast this with biochemical potency, where subtle structural changes can often result in abolishing activity. Biochemical potency depends on receptors that have been designed by evolution to be sensitive to subtle changes in chemical structure (for example estrogen vs. testosterone, or epinephrine vs. norepinephrine) whereas the hERG channel has been designed to transport potassium and has had little or no evolutionary pressure to be selective against micromolar concentrations of aromatic amines.</p><!><p>Dofetilide displacement measurement data [22] were extracted from the Novartis corporate database. We computed the pairwise difference in the log of measured IC50 for each compound pair. Pairs were excluded if both measurements were off scale in the same direction. Otherwise, off-scale measurements were treated numerically as being at the extreme end of the scale; i.e., every value >30 μM was treated as 30 μM. We characterized the chemical structure with Pipeline Pilot's extended connectivity fingerprints (ECFP) [23]. We use the ECFP family of fingerprints because of their utility in cheminformatics applications [12,24]. The transformation between molecules was represented by the "difference fingerprint". In the difference fingerprint we record those ECFPs that disappear from the initial molecule and that appear in the final molecule (see Figure 1). The fingerprint approach is both much faster than maximum common substructure (MCS) methods and implicitly includes some molecular context. However, advances in MCS methods have reduced the computational effort needed to calculate MCS based matched pairs [25].</p><p>We define the aggregates by the change in fingerprint: pairs are put together in the same transformation if and only if they have the same change in fingerprint. In ECFP-N fingerprints, the molecules are characterized by substructures around each atom, and the 'N' denotes the maximum diameter of the substructures used. Thus, in ECFP0 fingerprints these substructures are just a count of the different atoms and the fingerprint has equivalent information to the molecular formula. We did not choose N = 0 because all transformations with the same change in molecular formula would have been aggregated together, and an aggregate would contain molecular pairs that are making different chemical transformations. Using ECFP2 has similar drawbacks. We initially tried N = 4, but not all the pairs it grouped together were similar enough. After tightening our criteria one step further to N = 6, the aggregates represent the same chemical transformation. However this came at the cost of spreading the available data over more aggregates, which reduced the number of aggregates with enough examples to make statistically definitive statements.</p><p>To assess the statistical power of a particular transformation, we consider the probability that a particular distribution of either increases or decreases IC50 would be observed by chance alone. Our null hypothesis is that the transformation on average has no systematic effect. From the Wilcoxon, we estimate the likelihood of observing a particular distribution IC50s occurring by chance. In the null hypothesis, a sample size of 5 pairs which all either increase or decrease occurs 6.25% of the time. This gives us our threshold of 5 examples. For a sample size of 8 pairs, samples that have 7 increases and 1 decrease or 1 decrease and 7 increases occur (that is, has a p-value of) 5.46% of the time (see Additional file 1: Figure S1 on the paired Wilcoxon distribution).</p><p>Many biochemical assays have substantial correlation between measured IC50 and logP (a measure of lipophilicity). Because we lack logP measurements for many of our molecules we use a Crippen's model of logP. In particular, we use MOE's [26] (Chemical Computing Group, Montreal QC, Canada) implementation of that model which it calls SlogP [18]. SlogP is based on atom types, so each molecular pair in a particular aggregated transformation has the same change in SlogP.</p><!><p>Cmax: Maximum in vivo plasma concentration; SALI: Structure-activity landscape index; logP: Measurement of a compound's equilibrium partitioning between octanol and water; SlogP: LogP calculator found in MOE21; hERG: Human ether-a-go-go related gene; IC50: Half maximal inhibitory concentration; MOE: Molecular operating environment, a software product of the Chemical Computing Group; MCS: Maximum common substructure; ECFP: Extended connectivity fingerprint; μM: Micromolar; nM: Nanomolar.</p><!><p>We have no competing interest financial or otherwise in these techniques.</p><!><p>CS devised the research plan, supervised the work, and drafted the manuscript. KS carried out the day-to-day computational work. Both authors read and approved the final manuscript.</p><!><p>CS works as CADD scientist at Novartis. KS was a summer intern in his lab.</p><!><p>Shows the Wilcoxon statistical significance for the different aggregiates observed in our data set. Each symbol in the graph represents an aggregate. The x-axis shows the number of examples that increase the hERG inhibition. The y-axis shows the number of examples that decrease hERG inhibition. The aggregate is colored by its Wilicoxon p-value (all the aggregates with the same number of increasing and deceasing examples have the sample Wilcoxon p-value). The total number of paired values is given by the sum of these two thus there is no 0,0 point. For example an aggregate with 0 increases, 5 decreases (that is 5 total) has significance value of <0.05 (~0.03). For an aggregate of 8 pairs, 1 increase and 7 decreases has statistical significance.</p><!><p>Click here for file</p>

PubMed Open Access

Structures of apo and product-bound human L-asparaginase: Insights into the mechanism of autoproteolysis and substrate hydrolysis

Asparaginases catalyze the hydrolysis of the amino acid asparagine to aspartate and ammonia. Bacterial asparaginases are used in cancer chemotherapy to deplete asparagine from the blood, since several hematological malignancies depend on extracellular asparagine for growth. To avoid the immune response against the bacterial enzymes it would be beneficial to replace them with human asparaginases. However, unlike the bacterial asparaginases, the human enzymes have a millimolar Km value for asparagine, making them inefficient in depleting the amino acid from blood. To facilitate the development of human variants suitable for therapeutic use, we solved the structure of human L-asparaginase (hASNase3). This asparaginase is an N-terminal nucleophile (Ntn) family member that requires autocleavage between Gly167 and Thr168 to become catalytically competent. For most Ntn-hydrolases this autoproteolytic activation occurs efficiently. In contrast, hASNas3 is relatively stable in its uncleaved state, and this allowed us to observe the structure of the enzyme prior to cleavage. To determine the structure of the cleaved state we exploited our discovery that the free amino acid glycine promotes complete cleavage of hASNase3. Both enzyme states were elucidated in the absence and presence of the product aspartate. Together, these structures provide insight into the conformational changes required for cleavage, and on the precise enzyme-substrate interactions. The new understanding of hASNase3 will serve to guide the design of variants that possess a decreased Km value for asparagine, making the human enzyme a suitable replacement for the bacterial asparaginases in cancer therapy.

structures_of_apo_and_product-bound_human_l-asparaginase:_insights_into_the_mechanism_of_autoproteol

<!>Cloning of human ASNase3<!>Expression and purification of hASNase3<!>Crystallization of hASNase3<!>Data collection and structure solution of hASNase3<!>Cleaved versus uncleaved states of hASNase3<!>Comparison to E. coli Type III asparaginase and hAGA<!>Cleaved and uncleaved ASP-complex structures<!>Product binding to fully cleaved hASNase3<!>Implication for the auto-cleavage mechanism<!>Rationalizing the substrate specificity of hASNase3<!>Conclusions

<p>Asparaginases are enzymes that catalyze the hydrolysis of the free amino acid asparagine (ASN) into aspartate (ASP) and ammonia. The human genome codes for at least three enzymes that can catalyze this reaction, though the true physiological substrate of these enzymes may not be the free amino acid. One is actually called 60-kDa-lysophospholipase, due to the fact that in addition to asparagine it can hydrolyze lysophospholipids (1). This little-studied enzyme contains an N-terminal domain that is homologous to the E. coli Type I and II asparaginases, followed by several ankyrin repeats of unknown function (1, 2). A second human enzyme that can hydrolyze ASN is aspartylglucosaminidase (hAGA). The main function of this lysosomal enzyme is to remove carbohydrate groups linked to asparagine, as a final step in the degradation of cell surface glycoproteins. Defects in hAGA are the cause of aspartylglucosaminuria (AGU), which is an inborn lysosomal storage disease (3). The third enzyme with asparaginase activity, and the focus of this report, is indeed called L-asparaginase (also known as hASRGL1/ALP(4)/CRASH(5)), despite the fact that it can also hydrolyze isoaspartyl peptide linkages (6), which are a common source of protein damage (7). This enzyme is homologues to the E. coli Type III asparaginase, and therefore, we refer to it as human asparaginase 3 (hASNase3).</p><p>Type III asparaginases belong to the N-terminal nucleophile (Ntn) family of hydrolases (8). Interestingly, the aspartylglucosaminidase hAGA also belongs to this family. Ntn-enzymes are produced as a single polypeptide that must undergo intramolecular cleavage to attain catalytic activity. The cleavage reaction is an auto-catalytic process, in which the side chain of a threonine/serine/cysteine (depending on the specific Ntn enzyme (9)) residue attacks the carbonyl group of the preceding amino acid to form a covalent intermediate. The intermediate subsequently undergoes hydrolysis to yield the peptide-cleaved enzyme. This type of activation by autoproteolysis is different to that which occurs in proenzymes such as trypsin. In proenzymes, peptide bond cleavage typically functions to displace a short N-terminal inhibitory segment. In contrast, in Ntn-enzymes, cleavage occurs around midway of the peptide sequence, and the resulting two chains, termed α- and β̃ chains, remain intact to form a single functional unit. The purpose of the cleavage reaction is to release the amino group of the Thr/Ser/Cys residue from being involved in peptide bond formation to being N-terminally exposed in the β-chain, which can then attack its substrate. Thus, the Thr/Ser/Cys residue plays dual roles, first in initiating the maturation reaction of the enzyme into its active state, and then in catalyzing hydrolysis of free asparagine or asparagine derivatives. Human ASNase3 differs from most studied Ntn-enzymes by undergoing a very slow self-cleavage reaction. For example, whereas the E. coli Type III asparaginase purifies as the fully cleaved form (10), SDS-PAGE of purified recombinant hASNase3 expressed in E. coli shows a predominate single band corresponding in size to the uncleaved enzyme, with only weak bands for the lower molecular weight α- and β-chains of the cleaved state. Incubation of hASNase3 in a buffer containing NaCl and Tris/HCl, pH 7.5 increases the proportion of the cleaved state at a very slow rate, as observed by us (manuscript submitted) and others (6). The uncleaved enzyme crystallizes in several salt-containing conditions, such as malonate, citrate, and ammonium sulfate. Diffraction data collected from these crystals show that the extent of protein cleavage (i.e. the peptide bond break between Gly167 and Thr168) is dependent on the age of the crystals, with fresh crystals being uncleaved and older crystals (>90 days) predominantly cleaved. In our earlier work we made the unexpected discovery that the amino acid glycine very selectively accelerates the cleavage reaction (manuscript submitted).</p><p>In addition to hydrolyzing ASN and diverse ASN-linked substrates, asparaginases play a prominent role in cancer chemotherapy (11). Bacterial asparaginases, specifically the E. coli Type II enzyme (trade name Elspar), its conjugate with polyethylene glycol (PEG), Oncospar, and that from Erwinia chrysanthemi (Erwinase) are key agents in inducing remission of acute lymphoblastic leukemia and lymphoblastic lymphoma. Note that these clinically-used asparaginases are not Ntn-enzymes and have a completely different structure to hASNas3 (12); for a discussion of different types of asparaginases, see the recent review by Michalska et al (13). The clinical success of asparaginase therapy is attributed to the rapid and complete depletion of the amino acid ASN in plasma (14). Serum contains a steady-state level of ~50 μM ASN (15). Although ASN is not an essential amino acid, several tissues (thymus, T-cells, etc) depend on extracellular sources of ASN for their metabolic needs. ASN is a crucial amino acid for protein, DNA, and RNA synthesis (16) and its requirement is cell cycle specific for the G1 phase of cell division (17). While a de novo pathway for ASN synthesis exists (via ASN synthetase), many cancer cells such as leukemic cells are dependent on the availability of extracellular ASN. Hence, ASN depletion achieved upon administration of the bacterial asparaginases interferes with the metabolic status of the cancer cell and ultimately results in apoptosis (18).</p><p>However, clinical use of these drugs is complicated by an immune response against the bacterial enzymes. Use of the Oncospar version attempts to limit this immunogenicity, based on the observation that foreign proteins covalently linked to PEG may mask immunogenic epitopes. However, eventually enzyme-specific or even PEG-specific antibodies are elicited (19), which cause a variety of adverse effects including hypersensitivity and anaphylactic shock. Moreover, these bacterial asparaginase-specific antibodies inactivate the enzyme and promote its clearance, negating its therapeutic potential. To eliminate the immunogenicity of the enzymes, we propose use of human asparaginases in lieu of bacterial enzymes. However, intrinsically none of the three human asparaginases has the required kinetic property (low μM Km) adequate for replacing bacterial asparaginases. Hence, we commenced the study of hASNase3 with the ultimate goal of engineering a low Km ASN variant suitable for use in humans. As a first step towards this goal, we solved the crystal structures of hASNase3 in various states. Here we present the uncleaved and cleaved enzyme states, either without substrate or in complex with the product L-aspartate. Together these structures reveal details of the substrate-enzyme interactions, inform us on the specific roles of active site residues, and provide insight on the mechanism of autocleavage and ASN hydrolysis.</p><!><p>The open reading frame (ORF) of hASNase3 (UniProt Q7L266, also called human asparaginase-like protein 1, hASRGL1, ALP, CRASH) consisting of 927 base pairs, was PCR-amplified using as template cDNA from a human skin and meninges cDNA library (Source Bioscience, UK). NdeI and BamHI sites were incorporated in the oligonucleotides targeting the 5′ and 3′ ORF ends, respectively. The PCR product was gel-purified, digested with NdeI and BamHI-HF (New England Biolabs) and ultimately ligated overnight at 16 °C into pET14b-SUMO vector using T4 DNA ligase. The ligation mixture was used to transform DH5α E. coli cells. Positive clones were determined following restriction digestion with NdeI and BamHI-HF, and finally the gene insert was sequenced. The final construct includes an N-terminal 6-histidine tag, followed by SUMO (Small Ubiquitin Modifier; yeast protein Smt3p of 101 residues) tag, which has been proven to improve heterologous protein solubility and stability. For bacterial expression, the E. coli BL21(DE3) C41 strain was transformed with the hASNase3 plasmid.</p><!><p>Two liters of 2YT media was inoculated with a starter culture of E. coli BL21(DE3) C41 carrying the hASNase3 plasmid. When the cultures reached an optical density at 600 nm in the range of 0.6–0.8, the temperature was reduced from 37 to 18 °C, 0.5 mM IPTG was added to induce expression, and cells were left to grow overnight. Cells were spun down and then lysed by sonication (Lysis buffer: 50 mM Tris/HCl, pH 7.5, 500 mM NaCl, 10% glycerol, 1% Triton 100, 1 mM PMSF), and the lysate cleared by ultracentrifugation (1 h at 33k rpm). The supernatant was loaded onto a 5 ml His-Trap HP Ni Sepharose column (GE Healthcare), washed with 150 ml of a buffer containing 25 mM Tris/HCl, pH 7.5, 500 mM NaCl and 10 mM imidazole. Further washing was done with a similar buffer that contains 25 mM imidazole. Elution of the protein was accomplished with a buffer containing 250 mM imidazole, with a yield of 290 mg total protein (Bradford assay). At this stage, SUMO protease was added (1:200 weight ratio) to cleave the His-SUMO tag from hASNase3, and the protein left to dialyze overnight in order to remove the imidazole. The cleaved protein was put back onto the His-Trap column, with hASNase3 coming out in the flow through. After protein concentration to a volume of 5 ml (22 mg/ml), the sample was injected onto a S-200 gel filtration column (GE Healthcare) pre-equilibrated with 25 mM Tris/HCl, pH 7.5, 200 mM NaCl, 2 mM DTT. The protein eluted as two peaks; a minor peak that would correspond to the dimer, and a major peak that would correspond to the monomer. The monomer peak was pooled, concentrated to 38 mg/ml, aliquoted, and stored at −80 °C.</p><!><p>Purified hASNase3 was subject to crystallization condition screening, and crystals of hASNase3 (without added amino acid) were obtained in several conditions with salts as precipitants (e.g. citrate, malonate, ammonium sulfate). Optimization of JCSG+Suite (Qiagen) condition 69 (2.4 M Sodium malonate, pH 7) to 2.2 M malonate resulted in large crystals that diffracted beyond 1.6 Å. For setups, 1 μL of hASNase3 at 38 mg/ml (in 25 mM Tris pH 7.5, 200 mM NaCl, 2 mM DTT) was mixed with 1 μL of the reservoir on a glass cover slip, and left to undergo vapor diffusion using the hanging drop method at 20 °C. Crystals appeared after ~5 days. We also obtained crystals in the JCSG+Suite condition 23 (1.6 M Sodium Citrate) and the Ammonium sulfate Suite (Qiagen) condition 9 (0.2 M Ammonium iodide, 2.2 M Ammonium sulfate).</p><p>Crystals used in this study were grown in the malonate condition, except for one substrate-free structure obtained from crystals grown in ammonium sulfate. Electron densities resulting from crystals grown in these three different conditions revealed precipitant molecules occupying the substrate binding site (see below). To solve this precipitant-competition problem for the purpose of obtaining the structure of hASNase3 in complex with L-aspartate (ASP), crystals grown in malonate were transferred to a 2 M aspartate pH 7.5, 20% glycerol solution for 5 min. In order to obtain the fully cleaved structure in complex with ASP, we first transferred crystals to a 2 M glycine solution pH 7.5 for 1 min, and then to the 2 M ASP pH 7.5, 20% glycerol solution for 5 min.</p><!><p>Diffraction data were collected using the in-house x-ray source (Rigaku RU-200 rotating anode) with a R-Axis IV++ image plate detector. Data were processed using XDS (20). The structure was solved by molecular replacement (Molrep (21) CCP4) using the bacterial asparaginase EcAIII as starting model (PDB entry 2ZAK), and refined with Refmac5 (22). Structure figures were made with PyMol. All crystals were perfectly twinned, with the true space group being P65 (apparent space group, P6522), and contained two copies of hASNase3 in the asymmetric unit. Data collected on freshly grown crystals showed the uncleaved state of the enzyme, whereas older crystals the cleaved state. In all the crystallization conditions mentioned above, the salt used as precipitant was observed at the enzyme active site. Attempts to soak in the product ASP, even at a concentration of 100 mM, failed to result in density for this amino acid. We interpret this as being due to competition by the precipitant salt. Hence, to obtain the ASP complex, we transferred crystals into a high concentration ASP solution that acted to stabilize the crystals and to provide the source of the amino acid binding at the active site.</p><!><p>We solved two amino acid-free hASNase3 structures, one from crystals grown with ammonium sulfate as the precipitant (at 2.13 Å resolution) and another from crystals grown in malonate (1.85 Å). Data collection and refinement statistics are presented in Table 1. Regardless of the precipitant used, the crystals adopted the same space group and unit cell dimensions, contained two molecules in the asymmetric unit, and were invariably twinned. Additionally, in every case we observed a precipitant molecule bound at the active site (see below). This is not surprising due to the similar structural properties of the precipitants and the substrate ASN.</p><p>Human ASNase3 is a homodimer, and its structure obtained from crystals grown in ammonium sulfate revealed the uncleaved state of the enzyme in both protomers. We could model several sulfate molecules, with one sulfate at the active site (hence the designation sulfate-complex). Likewise, the structure from the malonate condition contained the predominantly uncleaved state in protomer A (protA; modeled as 75% uncleaved/25% cleaved). In contrast, protomer B (protB) of the malonate-grown crystal was observed to be 100% cleaved. We could model a malonate molecule bound at the active site of protA (hence the designation malonate-complex) but not in protB. Apart from localized structural differences due to cleavage of protB, these substrate-free structures from the different precipitants are basically identical (rmsd 0.27 Å over 529 Cα-atoms). A comparison of all uncleaved protomers discussed here is presented in Fig. S1. Based on the fact that the amino acid-free structure of the malonate complex was of higher resolution, and since it allows us to compare the uncleaved-versus-cleaved state from the same crystal (Fig. 1a), our analysis of the amino acid-free structure is focused on this data set.</p><p>The amino acid-free hASNase3 structure is presented as a ribbon diagram of the dimeric asymmetric unit (Fig. 1b). However, it is unclear if this dimer (interface area ~1,800 Å2; PISA server (23)) is indeed the physiological oligomeric state for hASNase3 since the gel filtration elution profile shows a major peak corresponding to the monomer, and only a minor peak corresponding to the dimer. This is similar to the observation made with the homologous glycosylasparaginase from Flavobacterium meningosepticum, where only a monomer was observed using gel filtration (24). On the other hand, all known structures of Ntn-enzymes, including the latter one, reveal a similar dimeric arrangement, suggesting that the dimer is physiologically relevant. Since active site residues originate from a single protomer, and since kinetic studies have not observed cooperativity, dimer formation may serve only a stabilizing role. The uncleaved protA of hASNase3 (shown in green, Fig. 1) has a malonate molecule (depicted in magenta, Fig. 1b) at the active site, whereas the active site of the uncleaved protB (shown in dark and light blue representing the α- and β-chains, respectively) is occupied by solvent molecules. The reason for this difference is not clear, and does not seem to be a result of the cleavage status. The determination of cleaved versus uncleaved enzyme state was made based on two criteria: one, the presence or absence of electron density extending in the N-terminal direction from Thr168. In this amino acid-free structure, for protA we could model the preceding Gly167 and the main chain atoms of Leu166 (at 75% occupancy), but not beyond (Fig. 1c and 1d, zoom). In contrast, for protB the electron density did not extend beyond Thr168, and hence it was designated as cleaved. The second criterion was the conformation of Gly9, which we observe for the first time for Ntn-enzymes, to flip depending on the cleavage state of the enzyme (Fig. S2). Interestingly, a glycine at this position is common for Ntn-enzymes (Fig. S3), suggesting that this glycine-enabled peptide flip is important for stabilizing the cleaved state. We discuss the possible function of this region in the section detailing the cleavage mechanism.</p><p>Despite the fact that protA was uncleaved, residues spanning His153 and Leu166 lacked clear electron density (Fig. 1c). This observation is consistent with that made with other Ntn-enzymes (25, 26) that even in the uncleaved state (in those cases, requiring mutants devoid of cleavage ability) several residues at the tip of the α-chain cannot be modeled, suggesting that this region is intrinsically disordered. In the cleaved protB we also could only trace the α-chain as far as His153, demonstrating that after cleavage, the most C-terminal residues of the α-chain (residues 154–167) do not adopt a defined conformation. Whereas the two protomers differ in their cleavage state and in the presence of precipitant molecule bound at the active site, their overall structure is nearly identical, with an rmsd of 0.31 Å over 267 atoms (Fig. 1d). Hence, cleavage does not induce a significant conformational change, with the most pronounced differences between the cleaved and uncleaved enzyme being the positioning of Thr168 (Fig. 1d, zoom), which differs by 0.6 Å (Cα-atom), and the aforementioned conformation of Gly9. In the cleaved state, a water molecule occupies the position previously taken by Gly167. Of course, the most significant aspect of the cleavage is the liberation of the amino group of Thr168, which then becomes the N-terminal residue of the β-chain, and can now participate in catalyzing ASN hydrolysis. To our knowledge this is the first structure of an uncleaved Ntn-enzyme obtained without resorting to mutations that abolish or slow self-cleavage, an accomplishment made possible by the intrinsically slow cleavage rate of hASNase3.</p><!><p>Both human ASNase3 and AGA are homologs of the E. coli Type III asparaginase (Fig. 2a and S3). In terms of overall structure, hASNase3 is highly similar to the E. coli Type III asparaginase (25) (rmsd 0.52 Å over 228 atoms; Fig. S4a), yet has significant structural differences with its human homologue AGA (27) (rmsd 1.0 Å over 175 atoms; Fig. S4b), as clearly seen in the overlay of the three enzymes (Fig. 2b). This mirrors the greater sequence homology between hASNase3 and the E. coli enzyme (37.5% identity, 64.5% similarity, over 301 residue overlap) compared to that between hASNase3 and hAGA (29.2/60.6% identity/similarity, over 277 residue overlap). The hallmark of these three asparaginases is the presence of three threonine residues at the active site; based on hASNase3 numbering, these are Thr168, Thr186, and Thr219 (Fig. 2a). Also conserved are Arg196 and Asp199 that bind the substrate (see below). Not surprising due to high structural and sequence homology between hASNase3 and E. coli Type III asparaginase, these residues occupy identical relative positions in the active site (Fig. 2b, zoom). More remarkable is that these residues also line up exceptionally well with those from the less similar hAGA, demonstrating conserved active site architecture.</p><!><p>For insight on how hASNase3 binds its substrate we sought the structure of the enzyme with the product ASP. Hence, preformed crystals were transferred to a solution containing the crystallization mix plus the amino acid (up to 100 mM). However, diffraction data collected on such crystals failed to show electron density for the ASP, instead showing density consistent with the precipitant used in the crystallization. We attribute this to the fact that the precipitant (e.g. malonate, citrate, or ammonium sulfate at over 1.5 M) also binds to the active site, and thus out-competes the soaked-in ASP. To overcome this problem we transferred preformed crystals into a 2 M ASP solution, pH 7.5, with the rationale that such a high amino acid concentration would substitute the precipitant salt in stabilizing the crystal and at the same time provide the ASP that binds at the active site. Indeed, a data set collected on a crystal soaked into ASP (1.75 Å resolution, Table 1) did show a clear electron density for the amino acid, which was present in both protomers.</p><p>Recapitulating the observation made with the malonate-complex structure, in this ASP-complex we observed that protA was only partially cleaved (modeled as 50% uncleaved/50% cleaved) and protB was fully cleaved, and that the cleaved and partially cleaved protomers have a nearly identical structure (rmsd 0.34 Å on 288 atoms) with differences limited to the cleavage site (Fig. 3a). This structure, designated as the partially cleaved ASP complex, demonstrates that the product ASP, and by analogy the substrate ASN, can bind to the enzyme irrespective of its cleavage status. For the partially cleaved protA, we could model three residues that precede Thr168, but the residues linking His153 and Asn165 had no interpretable electron density (Fig. 3a, zoom). In the cleaved protomer (protB), we could not build a model beyond His153 of the α-chain. This shows that the presence of product (and presumably of substrate as well) does not induce order to the C-terminal residues of the α-chain (residues 154–167), either in the uncleaved or cleaved state.</p><p>This crystal structure allows a direct comparison of ASP binding to the uncleaved and cleaved states of hASNase3 (Fig. 3, zoom) for understanding the essentiality of cleavage for asparaginase activity. The hydrolysis of ASN is thought to commence with the attack of the Thr168 hydroxyl group on the amino acid's side chain carbonyl group. Figure 4 presents a schematic of the hASNase3 asparaginase reaction mechanism, adapted from that previously suggested for hAGA (28). The amino group of Thr168 (free in the cleaved state) acts to activate its hydroxyl group to attack the ASN side chain (panel I), with the negatively charged tetrahedral intermediate being stabilized by the oxyanion hole composed of Thr219 and Gly220 (panel II). Breakdown of the intermediate releases ammonia (panel III) with the amino acid remaining covalently bound to Thr168. The water molecule observed sandwiched between the amino group of Thr168 and the side chain amino group of ASN could act as a proton donor to the leaving NH2 group. Hydrolysis (panel IV) would likely build a very similar tetrahedral intermediate (panel V) to yield the free enzyme and the product ASP (panel VI). In our structures, in both the uncleaved and cleaved states, the Thr168 hydroxyl group is within 2.8–3.1 Å to the ASP side chain carbonyl group. Hence, improper substrate positioning can be ruled out as the reason for the lack of asparaginase activity of the uncleaved enzyme, and supports the catalytic role of the Thr168 amino group as detailed in the reaction schematic.</p><!><p>In order to determine the structure of fully cleaved hASNase3 in complex with ASP we took advantage of our discovery that the amino acid glycine promotes the cleavage reaction (manuscript submitted). Hence, a preformed crystal was first transferred into a 2 M glycine solution, pH 7.5, and incubated for ~4 minutes to promote cleavage. Subsequently, the crystal was transferred to a 2 M ASP, pH 7.5 solution, and after a short soak, frozen in liquid nitrogen. Indeed, diffraction data (1.84 Å, Table 1) from this crystal revealed full cleavage of both protomers and the presence of an ASP molecule (Fig. 5a) in each active site of the dimeric enzyme (hence the designation fully cleaved ASP complex). The amino acid is bound at the active site through several polar interactions (Fig. 5b & c): (i) The α-carboxylic moiety forms a bidentate salt bridge with the side chain of Arg196, as well as interacting with the main chain NH-group of Gly222. (ii) The amino moiety of ASP is stabilized by the side chain of Asp199 and by the carbonyl of Gly220. (iii) The carboxylic side chain of ASP is at interacting distance to the side chain of Thr219 and the NH-group of Gly220. Since both of these moieties can function as hydrogen-bond donors, they would interact with the oxygen atom of ASN's side chain, not its amino group. This would orient the side chain such that the leaving group of the reaction, the amino group, is not encumbered by interactions with the enzyme. (iv) Most notable in terms of the reaction mechanism, the ASP carboxylic side chain is at 2.2 Å distance to the hydroxyl of Thr168. In fact, this hydroxyl group is only 2.6 Å from the ASP carboxylate carbon atom (red dashed line, Fig. 5c). The asparaginase reaction is dependent on the free amino group of Thr168, which is thought to be required, directly or via a water molecule (29), to activate the Thr168 hydroxyl group (see proposed mechanism, Fig. 4) (28). Of the water molecules observed closest to the Thr168 amino group (numbered 1, 2, and 3, Fig. 5c), none acts to bridge the amino group and the Thr168 hydroxyl group. Further inspection of this region reveals that nearby water molecules are stabilized by the side chain of Asn62, which is in turn positioned by interactions with Gly187 and Gly188 (Fig. 5d). Hence, in the case of hASNase3, it seems that the amino group of Thr168 directly activates its hydroxyl group (distance 2.9 Å), and that nearby water molecules, held in position by Asn62, can help to shuttle the proton.</p><p>Asn62 is a part of the sodium-binding loop (residues 55 to 65), a feature previously observed previously for this asparaginase family (30), that would anchor its main chain position. Inspection of Ntn-type enzyme sequences shows that Asn62 and the tandem glycine residues following Thr186 (Gly187 and Gly188) are highly conserved (Fig. S3). This supports the model where these conserved residues act to position water molecules near the amino group of Thr168, whose function is to stabilize the protonated amine group once it has abstracted the proton from the Thr168 hydroxyl group (Fig. 4, panels I & II). Interestingly, the homologous asparagine residue in the E. coli Type III asparaginase (Asn67) has been implicated in the cleavage reaction (31), suggesting a dual cleavage and asparaginase role for this side chain.</p><!><p>In the three crystal structures of hASNase3 analyzed here (for simplicity we omit the sulfate-complex), we observe a total of two protomers in the uncleaved state (protAs of the malonate and partially cleaved ASP-complex) and four protomers in the cleaved state (protBs of the above, plus both protomers of the fully cleaved ASP-complex). What can these structures tell us about the auto-cleavage mechanism? Just as the side chain of the N-terminal threonine of the β-chain is required for ASN hydrolysis, this side chain is also required to initiate the cleavage process. It does this by attacking the carbonyl group of the preceding amino acid, in the case of hASNase3, Gly167. However, in our uncleaved structures the distance between the Thr168 hydroxyl group and the carbonyl carbon atom of Gly167 is too large − 4.0 Å in the case of the uncleaved ASP-complex protomer (Fig. 6a). This suggests that a conformational change is needed prior to this first step of the cleavage reaction. To gain insight as to what this conformational change may be, we analyzed the structures of other asparaginases solved in the uncleaved state. In the case of the glycosylasparaginase from F. meningosepticum, this required the use of the W11F mutant (32). In that structure, the distance between the threonine at the scissile position (Thr152) and the carbon atom of the carbonyl group of the preceding residue is only 3.1 Å (Fig. 6b; PDB code 9GAF). Likewise, in the case of the E. coli Type III asparaginase, obtaining the structure of the uncleaved state required the mutation of the critical threonine (Thr179) that was replaced by alanine (31). In that structure (Fig. 6c; PDB code 3c17), after first modeling a threonine side chain in place of the alanine (shown in red, Fig. 6c), we measured an analogous distance of 3.2 Å. The central difference between our uncleaved hASNase3 conformation, where the critical distance is too large (Fig. 6a), to that in the uncleaved F. meningosepticum and E. coli structures, where that distance is more appropriate for a direct attack by the threonine hydroxyl group on the preceding residue's carbonyl group (Fig. 6b and c), is the conformation of the peptide bond that precedes the threonine. Therefore, we suggest that for hASNase3 cleavage to occur, a conformational change in Gly167 is required, such that the distance between the carbonyl group and the Thr168 hydroxyl is shortened. This would necessitate flexibility in this part of the enzyme. Indeed, the conformation of this section differs in the two structures of the uncleaved protomers (Fig. 6d), implying an intrinsic flexibility of the region that would allow for the required conformational change.</p><p>One of the few structural consequences of hASNase3 cleavage, from a single polypeptide to the α- and β-chains, is the flip in the conformation of Gly9, a residue in spatial proximity to the cleavage site (double-headed arrow, Fig. 6e). The conformation adopted by Gly9 in the post-cleavage state would be incompatible with the conformation of Gly167 in the pre-cleavage state (Fig. 6e). In fact, the flip-in Gly9 conformation may act to promote the change in conformation of Gly167 to one that brings its carbonyl group closer to Thr168, and in so doing, promotes the cleavage reaction. In conclusion, our structures suggest that the inherent flexibility of the cleavage region is required for the buildup of a cleavage-competent hASNase3 conformation.</p><!><p>Enzymes such as human ASNase3 and AGA, in addition to being able to hydrolyze the free amino acid ASN, show hydrolytic activity with ASN-derivatives. For example, hAGA's main function is to hydrolyze ASN-linked oligosaccharides in the lysosome, and hence its designation as aspartylglucosaminidase. In contrast, hASNase3 does not hydrolyze ASN-linked sugars, but is able to hydrolyze isoaspartyl linkages (6). The shape of the active site cavities would dictate this difference in substrate specificity, prompting us to analyze the geometries of the active site entrance regions.</p><p>Common to both enzymes is the orientation of the minimal substrate, the amino acid ASN: the amino acid binds with its α-amino and carboxyl groups oriented towards the center of the protein, and with the side chain pointing out (Fig. 7a–d). Divergence occurs as to the space possible for derivatives to extend from the ASN side chain. In the case of hASNase3, any molecule connected to the ASN side chain would most likely take one path (dotted black line, Fig. 7b), whereas in hAGA, it would take an alternate path (dotted white line, Fig. 7d). These paths are mutually exclusive since structural elements in one occupy the path most likely to be taken by the ASN-derivative in the other. More specifically, residues only present in true asparaginases (such as E. coli Type III asparaginase and hASNase3), and missing from aspartylglucosaminidases (such as hAGA), block the path that would be required for the sugar derivative (Figs. S3 and S5). For example, hASNase3 differs from hAGA by having a long linker between β-strand A and α-helix 1 (for secondary structure labeling see Fig. 1b). Modeling of such a long linker (extra 16 residues) in hAGA demonstrates that this linker would block the space most likely to be required by the sugar moiety of an ASN-sugar derivative (Fig. S5). This analysis illuminates the structural reasons behind the different substrate specificities of human ASNase3 and AGA.</p><!><p>Here, we present the crystal structures of amino acid-free and ASP-complexed human asparaginase 3, in both the uncleaved (inactive) and cleaved (active) states. The ASP-complex structures, in addition to supplying a detailed view of the interactions made between the enzyme and the product of the reaction, ASP, suggest that in the cleaved state, a direct interaction between the Thr168 amino and hydroxyl groups takes place. It is this interaction that would activate the Thr168 hydroxyl group for attack on the side chain of the substrate ASN. The slow intrinsic auto-cleavage rate of hASNase3 allowed us to observe the uncleaved state without resorting to cleavage-inactivating mutations. The structures also suggest a role for the conserved N-terminal segment (His8-Gly9) in promoting the cleavage-competent conformation, a feature not noted previously for other members of this enzyme family. Any modifications to hASNase3 done for the purpose of lowering its ASN Km value, to allow it to act as a replacement of bacterial asparaginases in blood cancer therapy, would need to take these aspects into consideration, so as to still permit the essential intramolecular cleavage reaction.</p>

PubMed Author Manuscript

A CycloRGDf(Me-V) Analog as Chemical Probe to Study Integrins Function in Living Cells

Studying the role of integrins in cellular processes requires the ability to monitor their localization in dynamic events. We report a chemical probe that can be used to image integrins in living cells. The fluorescent probe was derived from cyclo-RGDf(Me-V), a compound selective for integrins that possess an RGD-binding domain. We describe its synthesis and we demonstrate its use to detect integrin αVβ5 in cells. The probe's dissociation constant for the integrin αVβ5 protein is 0.18 µM. The probe's activity was validated in murine BV-2 microglial cells using cell engulfment assays, flow cytometry, and confocal fluorescence imaging. This probe will provide access to spatiotemporally resolved studies of RGD-binding integrin function in living cells without the need for genetic modification. 8 0.1% DMSO 10 nM Cilengitide (1) 0.1% DMSO 10 nM Probe 2 10 nMProbe2

a_cyclorgdf(me-v)_analog_as_chemical_probe_to_study_integrins_function_in_living_cells

■ INTRODUCTION<!>■ RESULTS AND DISCUSSION<!>Labeling Integrins in Cells<!>Imaging Probes Cilengitide-PB405 (2) and Cilengitide-A568 (3) Label Endogenous Integrin αVβ5<!>■ CONCLUSION<!>■ SIGNIFICANCE<!>■ AUTHORS CONTRIBUTIONS

<p>Integrins are heterodimeric transmembrane proteins found at the surface of cells, where they connect the intracellular cytoskeleton to the extracellular matrix. Besides being essential structural elements of cells, they also play important signaling roles in development and in pathology. [1] The function of integrin proteins is dictated by the differential pairing of 18 alpha and 8 beta subunits. [2,3] A family of integrins-αVβ3, αVβ5, α5β1 and αIIβ3-binds extracellular matrix proteins that contain the "RGD" peptide sequence such as fibronectin, fibrinogen, vitronectin, and osteopontin. [4,5] These integrins, αVβ3 in particular, have been studied extensively in cancer: their upregulation in tumour angiogenesis [6] and metastasis [7] has made them attractive drug targets. [8,9] The complex role that integrins play in cellular signaling events is dynamic: it must be studied in living systems to reveal meaningful information about signaling cascades and how integrins respond to biochemical stimuli. This is especially true in the brain, where the physiological role of integrins αVβ3 and αVβ5 remains understudied.</p><p>The αVβ3 and αVβ5 subtypes may play a crucial role in synaptic plasticity [10] and participate in microglial activation/inflammation. [11] However, obtaining time-resolved information at the molecular level in brain tissue is still a major challenge due to a lack of appropriate technology. The most common fluorescence microscopy methods used to visualize proteins are not ideal to study dynamic events in cells: they rely on immunocytochemistry (fast method, but not dynamic as cells must be fixed), or on genetic fusion of the protein of interest with a reporter tag, e.g., GFP fusion (very specific, but time-consuming genetic manipulations). [12] Part of our research program on the role of integrin in neuron-glia interactions motivated us to address this challenge.</p><p>Accordingly, we aimed to create a fluorescence imaging probe to monitor endogenous integrin receptors in living cells. An exogenous chemical compound that targets a conserved motif of an integrin protein in its native state would ensure that: (1) the expression levels are unperturbed, (2) the method is independent of species or cell line, and (3) the wavelength of the fluorescence reporter can be modified to allow for multiplexing (e.g., pulse-chase experiments). For our design, we selected a class of ligands discovered by Kessler that is wellestablished to be selective for RGD-binding integrins: cyclo-RGDf(Me)V, more commonly known by its commercial name cilengitide (1, Figure 1). [5,13,14] This pseudopeptide shows nanomolar inhibitory activity for αVβ3, αVβ5 and α5β1, and micromolar activity for the platelet receptor αIIβ3. This compound has also been exploited in cancer diagnosis where the overexpression of αVβ3 in tumour tissues can be detected with cilengitide analogs conjugated with radionuclides, MRI contrast agents, fluorophores, and nanoparticles; [15] however, several of these techniques lack high spatiotemporal resolution. [16] Figure 1. Permissible structural variations of Kessler's cRGDf(Me-V) (1). Affinity decreases when the N-methylvaline is replaced by lysine, but it can be compensated by creating oligomers.</p><p>Cyclic pentapeptide 1 is a rigid mimic of the RGD motif found on the extracellular matrix protein vitronectin that associates tightly with integrins αVβ3 and αVβ5. A crystal structure of αVβ3 bound to cyclo-RGDf(Me)V was reported in 2002; it shows that the valine and D-phenylalanine residues of 1 are pointing away from the binding site, toward the extracellular milieu (Fig. 2). [17] Most reported compounds used for conjugation are analogs of 1 where the valine residue is replaced by lysine, with a reporter tag covalently attached to the amine of the lysine residue (typically, a PET radionuclide). [15] Although it is synthetically simpler to replace the N-methylvaline by a lysine to attach linker chains, this substitution leads to at least a 30-fold loss of activity on integrin αVβ5. [15] Lower binding affinity due to structural changes can be partially compensated by creating cRGDfK dimers, trimers, or tetramers. [18] Figure 2. Crystal structure of the extracellular portion of integrin αVβ3 with bound ligand cRGDf(Me)V. The RGD binding domain is located at the apical junction of the dimer. The cyclo-RGDf(Me)V ligand (orange) is nested at the interface of the alpha (grey) and beta (blue) subunits. The ligand's phenyl sidechain points away from the protein; modifying this aromatic ring to attach a linker chain should maintain a high affinity. (PDB 1L5G). [17] In contrast, the distal aromatic positions of the D-Phe residue have never been exploited for conjugation, despite the analog being shown to be equally active to 1. [19] Only a tyrosine-substituted and a meta-iodinated analog have been reported, and both showed the same activity as 1 (Fig. 1). [20] Herein, we report the design and application of molecular imaging probes cilengitide-PB405 (2) and cilengitide-A568 (3) (Figure 1). We demonstrate the use of the probes for fluorescence imaging of integrins in living cells, and for functional study of endocytosis in a bead engulfment assay.</p><!><p>The molecular imaging probes cilengitide-PB405 (2) and cilengitide-A568 (3) differ from other conjugates in that the reporter cargo is appended to the aromatic ring of the ent-Phe residue of cyclo-RGDf(Me)V (Fig. 1). A fluorescent imaging molecule has been reported, cRGDyK-A568 (22), but three structural deviations from cilengitide made it less potent: the valine was replaced by lysine, the N-methyl group was removed, and the phenylalanine was replaced by a tyrosine. [17] Hypothesizing that the meta position of D-Phe in 1 should be amenable to substitution with a fluorescent label without loss of activity for integrin αVβ3 and αVβ5, we synthesized two analogs: blue-fluorescent probe cilengitide-PB405 (2) and red-fluorescent probe cilengitide-A568 (3).</p><p>Synthesis of modified Cyclo-RGDf(Me)V Pseudopeptides. Imaging probe cilengitide-PB405 (2) was synthesized in a total of 27 steps, with 19 steps for the longest linear sequence (Fig. 3). The preparation of a novel meta-substituted aminomethyl-D-phenylalanine derivative 9 is outlined in Figure 3A. m-Toluic acid (4) was converted to benzylic bromide 5 in five steps. The stereocenter of the amino acid precursor was installed via enantioselective alkylation of glycinyl imine 6 with 0.1 mol% of Maruoka's chiral catalyst (7) under biphasic conditions. [21] The chiral product showed a 94% ee. Three additional steps were required to obtain the modified D-phenylalanine 9 bearing protecting groups appropriate for solid-phase synthesis. The protected N-methylvaline 12 was prepared in 88% over two steps according to a reported procedure. [22] The linear form of the pentapeptide was assembled on trityl chloride resin 10, starting with Fmoc-protected glycine. HBTU was used as the principal coupling agent, with the exception of coupling of phenylalanine 9 to N-methylamine of 12, where the more reactive HATU was used. The pentapeptide 13 was cleaved from the resin with hexafluoroisopropanol and purified by chromatography to give diastereomers 14 in a 97:3 ratio (reflecting the 94% ee of 9). Pentapeptide 14 was cyclized under high dilution conditions with diphenyl phosphoroazidate as the coupling reagent. Global deprotection in 95% trifluoroacetic acid led to cyclic pentapeptide 15 in very good yield.</p><p>Blue fluorescent imaging probe cilengitide-PB405 (2) was assembled by coupling 15 to a fluorophore via a six atoms linker chain (Figure 3B). The dye Pacific Blue (16) was activated as a succinimidyl ester, coupled with 3-oxa-ω-aminovaleric acid, and converted to succinimidyl ester 17b. [23] Coupling of 15 with activated ester 17b yielded the desired fluorescent probe 2 in 29%. The low yield is due to a challenging purification by reversephase HPLC. While the small size of the fluorescent moiety on 2 is an advantage, its excitation/emission wavelengths in the violet/blue spectrum (405/455 nm) can limit the range of possible experiments (e.g., strong autofluorescence background). A complementary red variant was therefore synthesized.</p><p>Red fluorescent imaging probe cilengitide-A568 (3) was prepared from fully protected pentapeptide 18 (Fig. 3C). In this case, the N-Boc protecting group on the modified D-Phe allowed a selective deprotection, followed by coupling to the NHS-activated ester of ω-azidobutyric acid. Global deprotection afforded peptidic azide 19. Sulforhodamine Alexa568 dye (20) was reacted with HATU to obtain propargyl glycinamide 21. Both azide 19 and alkyne 21 fragments were then connected using a copper-catalyzed click reaction to yield redfluorescent cilengitide-A568 (3). [24] To evaluate the efficiency of 2 and 3, we synthesized known probe cRGDyK-A568 (22) by preparing the cyclo(RGDyK) peptide according to the literature. [19] Then, fluorophore 20 was directly attached to lysine sidechain to provide the closest analog with respect to fluorescent and chemical properties (See Supplementary Information).</p><p>Binding Activity of Cilengitide-A568 (3) with Isolated Integrin αVβ5. The binding was investigated with isolated human integrin αVβ5 protein (in line with our interest in studying its role in glia). The change in fluorescence anisotropy was measured with probe 3 to obtain a dissociation constant (Kd) of 0.18 ± 0.13 µM (95% CI). The value was calculated by fitting the data to a non-linear regression representing a single-site binding model (see Fig. 4 and Methods). The difference between the anisotropy of the free and bound states was small, likely due to the free rotation around the long linker of 3 (propeller effect). [25] Nevertheless, the assay demonstrates that fluorescently-labeled compound 3 retains affinity for integrin αVβ5 receptor in the midnanomolar range. The binding assay was conducted only with cilengitide-A568 probe 3 due to instrumental constraints. Yet, given that the fluorescent sidechain in 3 is much larger than that of Pacific Blue-labeled probe 2, the activity of 2 is expected to be very similar (supported by qualitative observations in other experiments, data not shown).</p><!><p>With the imaging probes in hand, we turned to confirm their use in cellular contexts to study integrins that bind the RGD-motif, integrin αVβ5 more specifically. The probes' spectrophysical properties were measured using fluorescence spectroscopy and confocal microscopy in live-and fixed-cell systems. We investigated whether our modifications of cRGDf(Me)V maintained the binding affinity, selectivity, and inhibitory effect of the probes 2 and 3 towards integrin αVβ5 and its associated signaling functions</p><!><p>in BV-2 Microglia. The labeling of endogenous integrin αVβ5 was investigated with probe 3 using live BV-2 microglia (for experiments with probe cilengitide-PB405, see Supp. Info.). BV-2 cells are a robust model for primary murine microglia, [26] and αVβ5 represents close to 60% of the RGD-binding integrin proteins they express. [27][28][29] BV-2 cells were labelled with cilengitide-A568 probe 3 within 10 min at a concentration of 1 µM.</p><p>While lower concentrations can be used, they require impractical incubation times (e.g., one hour or longer, data not shown). We opted for a short incubation time of 10 minutes as the probe's intended use is for the imaging of dynamic events in living cells.</p><p>Fluorescent imaging probe cilengitide-A568 3 labelled native integrin proteins in living BV-2 cells at a level significantly higher than the background, the free dye 20, or the lysine-modified analog cRGDyK-A568 (Fig. 5). Importantly, competition experiments with 10 equivalents of cilengitide (1) reduced the fluorescence to background level (Fig. 5G). In terms of selectivity, cilengitide-A568 (3) performed ca. 50% better than cRGDyK-A568 (22); the difference in fluorescence signal between the probes only and the pre-blocked cells was greater with 3 than 22. It suggests that it is indeed less perturbing to the ITG-cilengitide interaction to append the linker-dye moiety to the phenyl substituent of cilengitide in 2 and 3, instead of a lysine residue substituting for Me-Val in cRGDyK-A568.</p><p>A common limitation of fluorescent imaging probes based on small molecules is false positives arising from their embedment within the cell lipid bilayer via their linker-dye component. [30] Cilengitide-A568 and its dye component 20 are very hydrophilic and are not expected to permeate the cell membrane via passive diffusion.</p><p>With the free dye 20, the background cytosolic signal observed is ascribed to normal pinocytosis of the nutrient medium. Co-incubation of the free dye with cilengitide did not cause an increase of the cellular fluorescence, supporting that only the bound probe is internalized. Large vesicles can be clearly observed in the labelled cells (Figure 5A and 5D). In contrast, both cRGDyK-A568 and cilengitide-A568 are concentrated in smaller vesicles in the cytoplasm and nearby focal adhesion points (Figure 5B, C, E and 5F). [31] Presumably, the RGD-peptide is internalized with the integrin once 6 the ligand displaces attachment to extracellular matrix. Localization and intensity of the fluorescent signal in all the competition experiments resembled that of the free dye (see Supp. Info., Fig. S9).</p><p>Probes cilengitide-PB405 (2) and cilengitide-A568 (3) Inhibit Integrin αVβ5-Mediated Engulfment Cascades in BV-2 Microglia. In the brain, synaptic pruning has been proposed to involve neuron phagocytosis mediated by microglia via upregulated αVβ5 cascades, however, it has never been observed directly. [10,[32][33][34] As a proof of concept toward studying this important phenomenon, we developed a functional assay to assess whether our probes can be used to monitor αVβ5 in living cells. A reliable method to quantify microglial phagocytosis is the detection of internalized latex beads using confocal microscopy and flow cytometry. [35] When beads are coated with extracellular matrix (ECM) proteins, such as collagen and fibronectin, they trigger signaling pathways that can initiate phagocytic cascades (vitronectin is the native ECM protein ligand for integrin αVβ5). These cascades are responsive to inhibitors, and bead engulfment serves as a measure of phagocytic activity. [36][37][38] Accordingly, we conducted an assay to determine whether probes cilengitide-PB405</p><p>(2) and cilengitide-A568 (3) inhibit phagocytosis of vitronectin-coated latex beads in model glia.</p><p>This assay confirmed that probes cilengitide-PB405 and cilengitide-A568 maintain integrin αVβ5-binding activity despite being covalently modified with a fluorophore. Figure 6 indicates that both cilengitide-PB405</p><p>and cilengitide-A568 block microglial engulfment of vitronectin-coated beads with similar efficiency (or better) than the parent cilengitide inhibitor. Their half-maximal inhibitory concentrations (IC50) were calculated to be: cilengitide (1) = 623 ± 235 nM, probe 2 = 903 ± 348 nM, and probe 3 = 71 ± 23 nM. It may be noted that these IC50 values for cilengitide are one to two orders of magnitude higher than previously reported: integrin αVβ3 = 0.65 nM; integrin αVβ5 = 11.7 nM. [39] However, the assay we used measures the phenotype (blocking microglial phagocytic response), while prior reports used displacement assays with purified αVβ3 and αVβ5 proteins. Here, cilengitide and the probes showed similar efficacy in blocking phagocytosis initiated by integrin.</p><p>While the data presented in Figure 6 show a slight deviation of probe 3 relative to 1 and 2, this experiment confirms that modifying cilengitide with fluorophores attached to the aromatic D-Phe residue does not adversely affect its binding affinity or selectivity. Importantly, none of the compounds reduced the viability of BV-2 cells, supporting that the reduced phagocytic response results from integrin inhibition and not cell death (Fig. 6F). Practical considerations make cilengitide-based probes 2 and 3 attractive tools to label endogenous integrin αVβ5 in cell systems. First, they can be used across multiple species as the RGD binding site is highly conserved.</p><p>Second, the procedure is faster than other labeling techniques, such as immunocytochemistry or recombinant gene expression/editing. Indeed, from seeding cells to collecting confocal microscopy images, the entire workflow described herein can be completed under 3 h. Third, they also circumvent limitations of other complementary techniques: immunocytochemistry requires sample fixation prior to analysis, and the expression of recombinant genes can alter the subcellular localization of the modified proteins. [40] Current limitations for these first generation probes include: the localization of the probe was found to differ between live cells vs fixed cells; and integrins that are labelled are also inhibited by design, thereby preventing the study of active integrin function in cells.</p><!><p>We reported two new molecules that label endogenous integrin αVβ5 proteins in living cells. In this proof of concept study, we described the synthesis of fluorescent imaging probes based on the selective integrin inhibitor cyclo(RDGf(Me)V): Pacific Blue-linked probe 2 (cilengitide-PB405) and Alexa568-linked probe 3</p><p>(cilengitide-A568), both modified at the D-phenylalanine residue. We demonstrated that the probes maintain their activity toward integrin αVβ5 using a protein binding assay, as well as a whole-cell functional assay. The larger of the two probes, 3, was found to have a KD of 0.18 ± 0.13 µM with isolated integrin αVβ5, which confirms that modifying cilengitide (1) with fluorophores on its aromatic residue alters its potency only minimally. Importantly, we confirmed that the inhibitory function of the probes was equal to or stronger than cilengitide itself in a new phagocytotic functional assay. Finally, given that cilengitide binds both integrin αVβ5 and αVβ3 isoforms, it is highly likely that probes 2 and 3 can also be used to study integrin αVβ3 in living cells. Both integrins serve similar functions and are often co-expressed.</p><!><p>Little is known about integrin αVβ5's regulation, localization, or associated proteins in glia-mostly due to a lack of methods to track these proteins in their native environment. To elucidate integrin αVβ5's contributions to physiology, it is imperative to characterize integrin dynamics at the molecular level. Through rational design, we synthesized integrin-selective blue and red fluorescence imaging probes that are: easy to use, rapidly applicable, and organism-independent. [40] These probes offer a well-needed alternative to recombinant genetic fusion-highly specific, but a lengthy technique to implement, currently the only method that can label endogenous proteins for longitudinal analyses through time. Access to practical means of monitoring integrin αVβ5 in live-cell systems will help define their role in molecular pathways contributing to glia-mediated synaptic elimination and neuron phagocytosis associated with cognitive deficits in neurodegenerative diseases. [32,41,42] ■ SUPPLEMENTAL INFORMATION Supplementary information includes experimental synthetic procedures, characterization, and spectroscopic data; it can be found with this article online.</p><!><p>V.K. and W.S. are co-first authors and contributed equally to this paper. V.K., W.S., and F.M. conceived the study and wrote the manuscript. V.K. synthesized all compounds. W.S. and V.K. conducted experiments and interpreted the data.</p>

ChemRxiv

Quantum dynamics study of energy requirement on reactivity for the HBr + OH reaction with a negative-energy barrier

A time-dependent, quantum reaction dynamics approach in full dimensional, six degrees of freedom was carried out to study the energy requirement on reactivity for the HBr + OH reaction with an early, negative energy barrier. The calculation shows both the HBr and OH vibrational excitations enhance the reactivity. However, even this reaction has a negative energy barrier, the calculation shows not all forms of energy are equally effective in promoting the reactivity. On the basis of equal amount of total energy, the vibrational energies of both the HBr and OH are more effective in enhancing the reactivity than the translational energy, whereas the rotational excitations of both the HBr and OH hinder the reactivity. The rate constants were also calculated for the temperature range between 5 to 500 K. The quantal rate constants have a better slope agreement with the experimental data than quasi-classical trajectory results.The title reaction HBr + OH → Br + H 2 O has attracted great interest with many experimental and theoretical studies during the past several decades. From the practical aspect, this reaction plays an important role in atmospheric chemistry because it produces bromine atoms, and the bromine atoms can very effectively destroy the ozone by a catalytic cycles in the stratosphere:In addition, the reaction also plays a key role in combustion chemistry as some brominated compounds act as fire retardants.From experimental studies, there is a number of measurements of rate constants mainly at room temperature (298 K) [1][2][3][4][5][6] . Moreover, the rate constants were also measured at the temperature ranges 249-416 7 , 23-295 8 , 76-242 9 , 230-360 10 , 120-224 11 , 20-350 12 , 53-135 K 13 , and at a high temperature of 1925 K 14 . Among them, four studies 4,10,11,13 have also measured the rate constants for the isotopomers system and found the primary kinetic isotope effect (KIE) is independent of temperature between 53 and 135 K 13 . The results of these investigations reveal that the HBr + OH reaction's rate constants are extremely negative temperature-dependent below 150 K and nearly independent temperature between ~400 K and room temperature. Furthermore, Butkovskaya and Setser 15 studied the vibrational distributions for H 2 O, HOD and D 2 O produced in reactions of OH and OD with HBr and DBr. Che et al. 16 observed the negative collision energy dependence of reaction cross section for the HBr + OH/OD reaction in a crossed molecular beam experiment. Tsai et al. 17,18 reported the orientation dependence of the Br formation and found that O-end attack is more favored for this reaction.From theoretical studies, Clary et al. 19 provided the upper limit of rate constant for HBr + OH at low temperatures and predicted a maximum rate constant with the value of 3.5 × 10 −10 cm 3 molecule −1 s −1 at 20 K, using the statistical adiabatic capture theory with a long-range barrierless electrostatic interaction potential. After that, Clary et al. 20 reported a three-dimensional quantum scattering calculation with the rotating bond approximation on a simple potential energy surface (PES) based on a LEPS function and an accurate H 2 O potential. The reaction cross sections are found to be dependent on (2j + 1) −1 , where j is the initial rotational quantum number of OH. And the calculated rate constant has a − T 1/2 dependence at low temperatures. Furthermore, Nizamov et al. 21 readjusted the LEPS PES 20 to fit the experimentally measured H 2 O vibrational energy and the thermal rate constant, they performed a quasi-classical trajectory (QCT) study on the mechanism for excitation of the bending mode and isotopic effects on the energy disposal. In 2001, Liu et al. 22 investigated the dynamic properties of the

quantum_dynamics_study_of_energy_requirement_on_reactivity_for_the_hbr_+_oh_reaction_with_a_negative

<!>Results and Discussion<!>Rotational excitations ICSs.<!>Discussion<!>Theoretical Methods<!>

<p>hydrogen abstraction reaction HBr + OH over a wide range of temperatures 23-2000 K, by employing the improved canonical variational transition-state theory (VTST) 23 with a small-curvature tunneling correction.</p><p>Recently, Bowman's group 24 has developed a high-quality, full dimensional PES for the HBr + OH system based on 26,000 high-level ab initio energies. There is a van der Waals (vdW) well in the entrance channel, as well as in the product channel respectively, and a negative energy saddle-point barrier on the PES. They carried out a QCT calculation to obtain the reaction's rate constants over the temperature range from 5 to 500 K, and found an inverse temperature dependence of rates below 160 K and a nearly constant temperature dependence above 160 K. In addition, they also studied the reaction cross section, energy disposal and rate constant for the isotopomers reaction DBr + OH 25 . In 2015, Ree et al. 26 reported the temperature dependence of the title reaction using analytic forms of two-, three-, four-body and long-range interaction potentials in a QCT calculation over the temperature range of 20-2000 K. In 2016, Coutinho et al. 27 investigated the stereodirectional dynamics of the title reaction as the prominent reason for the peculiar kinetics on a multidimensional PES mechanically generated on-the-fly 28 .</p><p>Till now, there have been no full-dimensional, quantum dynamics studies on the HBr + OH reaction. Thus, in this paper, we carry out the first, full-dimensional, quantum dynamics time-dependent, wave-packet study on the PES developed by Bowman's group. Our purpose of the present work is to (1) calculate the thermal rate constants over the temperature range of 5-500 K and compare our six degrees of freedom (6DOF) results with experiments [2][3][4][5][6][7][8][9][10][11][12][13] and the QCT results 24 , see the relationship of the rate constants with the temperature; (2) investigate the energy efficiency of the translational, vibrational, and rotational energy on a negative-energy barrier.</p><p>In recent years, studies on energy efficacy rules for more than three atoms systems show there does not exist a unified rule on the energy efficacy to reactivity regarding the location of the transition states. For example, the O + CH 4 /CD 4 /CHD 3 reaction with a slightly late barrier, studies [29][30][31] on the reactions indicate that the translational energy is more effective than all the vibrational motions in surmounting the slightly late barrier. Similar to the O + CH 4 reaction, the reaction H + CH 4 also has a slightly late barrier. However, the quantum dynamics calculations 32,33 show that the vibrational energy is more efficient in promoting the reaction than the translational energy.</p><p>The title reaction HBr + OH has a large exoergicity with an early barrier, however, the early barrier is − 0.52 kcal mol −1 lower than the reactant on the PES. There has been no quantum reaction dynamics studies before on the energy efficacy for the negative early barrier. Since the ground-state energy of the reactant is already higher than the barrier height, there is no barrier for the reactant to surmount, one wonders whether any form of the reactant energy (translational, vibrational or rotational energy) is equal to enhance the reactivity; if not, it would be interesting to find the energy efficacy in surmounting this negative early barrier and to see what energy efficacy rule governs this reaction system.</p><!><p>Vibrational excitation of HBr. Figure 1(a) and (b) give the integral cross sections' (ICSs) comparison for the first four vibrational excitation states of HBr (v 1 , j 1 = 0) with OH (v 2 = 0, j 2 = 0) at ground state as a function of translational energy and total energy, respectively. To converge the ICSs for the initial states: (v 1 = 0, j 1 = 0), (v 1 = 1, j 1 = 0), (v 1 = 2, j 1 = 0) and (v 1 = 3, j 1 = 0), 200, 230, 260 and 260 partial waves are calculated, respectively. For the partial waves of J ≤ 100, the reaction probability for every partial wave was calculated explicitly, and the reaction probabilities for different partial waves of J > 100 were computed using the J-shifting method 34 with a J interval of 5. The standard centrifugal sudden (CS) approximation 35,36 was employed in calculation for J > 0. This figure shows the cross sections decrease as the translational energy increases. Especially for the excited state ICSs, v 1 = 1, 2, 3, the cross sections decrease significantly about 75% as the translational energy goes from 0.05 to 0.3 eV. On the other hand, the ground state cross section drops slower only about 45% for the same energy. Among these four cross sections, the ground state ICS is the smallest. For the translational energy lower than 0.1 eV, the amplitudes of the HBr v 1 = 1, 2, 3 ICSs are about 3~4 times bigger than that of ground state; even for the collision energy is larger than 0.1 eV, the three excited-state ICSs are also about 2 times bigger than the ground state's. As this reaction has a negative barrier height, even the ground state energy is higher than the barrier, it is surprising to see that the higher of the excited state the more reactive of this reaction.</p><p>In order to see the energy efficacy of the vibrational energy of HBr on the reactivity. We plot the ICS ratios of the HBr, σ(v 1 = 1)/σ(v 1 = 0), σ(v 1 = 2)/σ(v 1 = 1) and σ(v 1 = 3)/σ(v 1 = 2), on the basis at an equivalent amount of total energy in Fig. 2. The ICS ratio of σ(v 1 = 1)/σ(v 1 = 0) has a maximum ~10.8 at the initial translational energy 0.037 eV, then rapidly drops to 3.5 at the 0.145 eV until it reaches to 2.2 at 0.283 eV. In the whole energy range, the ratio is always bigger than 1.0, which means that vibrational energy is more effective to promote the reaction than translational energy. Furthermore, the ratio of σ(v 1 = 1)/σ(v 1 = 0) is much bigger than those of σ(v 1 = 2)/σ(v 1 = 1) and σ(v 1 = 3)/σ(v 1 = 2), and the ratio of σ(v 1 = 3)/σ(v 1 = 2) is just slightly larger than σ(v 1 = 2)/σ(v 1 = 1). Bases on the above results, we can conclude that the vibrational excitation from the ground state to the first excited state is the most effective one to promote the reactivity; however, there is no much reactivity change as the vibrational quantum numbers increase from v 1 = 1 to v 1 = 2 and from v 1 = 2 to v 1 = 3. Nevertheless, the comparison of the ICS ratios on the equal amount total energy indicates that the vibrational energy of HBr is more effective than translational energy on promoting the reactivity for this negative-barrier reaction.</p><p>Vibrational excitations of OH. In Fig. 3(a) and (b), we also compares the ICSs for those vibrational excitation states of OH with HBr (v 1 = 0, j 1 = 0) at ground state as a function of translation energy and total energy, respectively. There are 215, 210 and 210 partial waves needed to converge the vibrational excitation state of OH (v 2 = 1, j 2 = 0), (v 2 = 2, j 2 = 0), (v 2 = 3, j 2 = 0), respectively. The results show that ICSs almost stick together in regard to the translation energy, and the ICSs decrease as the translational energy increases. The reaction path of the PES 24 we used here has a vdW minimum at the entrance channel with a structure of the O-end of OH linked to HBr, HOHBr. This means the favorite route of this reaction is the two reactants enter the entrance vdW minimum to form HOHBr, then scale the transition state to make the reaction occur. This has been confirmed by the crossed beam scattering experiment 17,18 by Tsai et al. They found the orientation dependence for the title reaction that the reaction is favored by OH re-orientating its O-end to face the HBr. Since the barrier height respect to the vdW minimum is 0.12 eV on the PES 24 , thus as seen in Fig. 3(a), the reaction ICSs are almost the same at the translational energy larger than ~0.15 eV because the reactants would overpass the vdW minimum without reorientation in this large energy range; however, for the translational energy less than ~0.15 eV, the reactants will enter the vdW minimum to re-orientate themselves then surmount the barrier, therefore the ICSs are bigger for translational energy smaller than 0.15 eV. In order to investigate the vibrational energy efficacy of the OH, we need to check the ICS ratio of the excited state over the ground state in terms of equal amount of the total energy.</p><p>Figure 4 gives the ICS ratio, σ(v 2 = 1)/σ(v 2 = 0), in terms of translational energy at the equal amount of total energy. This figure shows that the ratio is larger than 1 in the whole energy range and the ICS ratio curve of σ(v 2 = 1)/σ(v 2 = 0) is very similar to the HBr's. The ratio is also inversely proportional to the energy and has a rapid decline at lower energy. This shows that the vibrational energy of OH is also much more efficient than the translational energy in promoting the reaction. Compared with the F + CH 4 37 and F + H 2 O reaction 38 , the title reaction HBr + OH has some similarities with them in regard to the PES. The three reactions all have an early saddle point located in the reactant channel, a vdW well in the entrance channel, and a relatively deep vdW minimum in the product valley. And the difference is that the HBr + OH reaction has a negative energy barrier (− 0.52 kcal mol −1 ) on the PES, while F + CH 4 barrier height is 0.5 kcal/mol and F + H 2 O's is 3.8 kcal/mol. For the early barrier reaction HBr + OH, our calculation shows both the vibrational energies of HBr and OH are more effective than translational energy in enhancing the reactivity. While for the two early barrier of F + H 2 O 39 and F + CHD 3 40,41 reactions, the study of F + H 2 O shows that the vibrational energy of H 2 O has higher efficacy in enhancing the reactivity than the translational energy; however, the vibrational excitation of C-H stretching motion of CHD 3 hinders the overall reaction rate. Thus, these investigations further prove that, Polanyi rules 42 in which the translational energy is more effective to raise the reactivity for the early-barrier tri-atomic reaction systems cannot be extended to the ploy-atomic reaction systems. Nonetheless, this study shows that, for this negative, early barrier reaction, the vibrational energy is more efficient than the translational energy in promoting the reactivity.</p><!><p>In addition, we also studied the rotational excitations on the reactivity for this reaction. For all the excited rotational ICSs' calculations, 200 partial waves were needed to converge the excited rotational ICSs, and the CS approximation 35,36 was also used to calculate the partial wave reaction probabilities for J > 0. Similar to the vibrational ICSs' calculations, for the reaction probabilities of partial waves for J ≤ 100, every J partial wave was calculated; and for J > 100, the reaction probabilities were computed using the J-shifting method 34 with a J interval of 5. Figure 5 presents the first five rotational excited ICSs of the HBr (v 1 = 0, j 1 ) with OH (v 1 = 0, j 1 = 0) at the ground state as a function of translational energy. As the figure shows that the ground state has the largest ICS among the 5 ICSs, and as the rotational quantum numbers j 1 increases, these excited rotational states' ICSs significantly decrease. So the rotational-excited modes of the HBr greatly hinder the reactivity.</p><p>In Fig. 6, the first four ICSs of rotational excitations and the ground state of the OH were compared. It is shown that overall the OH rotational excitations greatly inhibit the reactivity, and the faster of the rotation, the smaller of the ICS. This can be explained due to the fact that the OH plays a receiver role, the faster rotation of OH will further add difficulty for H atom in HBr to attack the O atom in OH. And our 6DOF quantum dynamics results here are in agreement with the three-dimensional quantum scattering calculations by Clary et al. 20 who found the reaction cross sections are proportional to (2j + 1) −1 , where j is the initial rotational quantum number of OH.</p><p>Overall, the rotational excitations, both HBr and OH, hinders the reactivity. This indirectly proves Tsai et al. molecular beam study 17,18 that Br formation of this reaction has orientation dependence which favors the O-end attack. On one hand, the faster rotation of HBr will make H in HBr cannot attack O-end easily; on the other hand, the faster rotation of OH will make O-end having difficulty to receive the H in HBr. Therefore, both the rotational excitations of HBr and OH hinder the reactivity. Thermal rate constants. By summing over all the ro-vibrational states of HBr and OH, we can obtain the 6DOF cumulative reaction probability (CRP). In order to converge the rate constants up to 500 K to compare with the experimental results [2][3][4][5][6][7][8][9][10][11][12][13] , the reaction probabilities of the ground vibrational state including 6 HBr rotational excitation states (j 1max = 5) and 3 OH rotational excitation states (j 2max = 3) were calculated.</p><p>The thermal rate constants are obtained using the J-K shifting rate expression from equation ( 8) in the Method Section. Note, in the QCT calculation by Bowman's group 24 , they compared their calculated rates, with the OH spin-orbit coupling (RR/SO rates), without the spin-orbit coupling(RR/nSO rates), and with a fully coupled partition function (Coupled rates), with the experimental measured ones. They found that, with the spin-orbit coupling neglected, the RR/nSO rates have the best overall agreement with the experimental results. Therefore, in the current study, we neglected the spin-orbit coupling to calculate our 6DOF quantal rate constants. In Fig. 7, our 6DOF results are compared with experimental [2][3][4][5][6][7][8][9][10][11][12][13] and QCT results (RR/SO, RR/nSO, Coupled) 24 . And the QCT calculations of RR/SO, RR/nSO and Coupled are obtained from three different approaches to treat the reactant OH rotational and associated electronic partition function. As the comparison shows, our 6DOF rate constants have a good agreement with the experimental data and demonstrate a negative temperature dependence, which is in agreement with the experimental ones and the QCT results. However, at the very low temperature range upto about 50 K, our 6DOF results are bigger than the experimental and QCT results. Nonetheless, in general, our 6DOF results have a better agreement with the slope of the experimental data than the QCT results. In addition, our 6DOF results give a maximum at about 15 K just as RR/SO and RR/nSO results do. This agrees with Clary et al.'s 19 prediction that a maximum rate constant should appear at 20 K. On the whole, Fig. 7 shows that our 6DOF rate constant has a better slope agreement with the experiments than the QCT results except at the extreme low temperature.</p><!><p>In this work, we carried out a 6DOF quantum reaction dynamics, time-dependent wave packet propagation approach to study the HBr + OH → Br + H 2 O reaction system on the PES developed by Bowman's group. This is the first, full-dimensional, quantum dynamical study on the title reaction. For the HBr + OH reaction system with a negative-early barrier, this study shows that not all forms of energy are equal in enhancing the reactivity. Even the ground state energy of the reactant is higher than the barrier, the calculation still shows that vibrational excitations of both the HBr and OH vibrational enhance the reactivity. Furthermore, the HBr and OH vibrational excitations are more effective in enhancing the reactivity than the translational energy. We also studied the rotational excitations of HBr and OH. The results show that both the rotational excitations hinder the reactivity. This is due to the fact that the faster rotation of HBr makes H having difficult to attack O in OH; and the faster rotation of OH makes O having difficult to receive H from HBr. Comparing with other two early barrier reaction systems, F + H 2 O and F + CHD 3 , we can see there are no general rules so far on the energy efficacy for the ploy-atomic reaction systems as the Polanyi rules do to the tri-atomic systems. We think this is due to the complexity of the PESs of the poly-atomic systems with vdW wells usually in both the reactant and product channels. These wells, especially the entrance channel well before the transition state, might also play a role that cannot be neglected on energy efficacy on surmounting the energy barrier.</p><p>Furthermore, the comparison of the thermal rate constants between our 6DOF quantum results and the experimental display that our data agree well with experimental measurement except at extreme low temperatures.</p><!><p>6DOF approach. We performed a full dimensional, 6DOF, time-dependent quantum dynamics study for the HBr + OH → Br + H 2 O reaction. The 6DOF Hamiltonian in the reactant Jacobi coordinates, as shown in Fig. 8, can be written as, where, μ R is the reduced mass of the whole reaction system; R is the center-of-mass distance between HBr and OH, r 1 is the distance of H-Br and r 2 is the distance of O-H; θ 1 and θ 2 are the two Jacobi angles between r 1 and R and r 2 and R, Φ is the torsion angle; J is the total angular momentum operator of the reaction system, j 1 and j 2 are the rotational angular momentum operators for HBr and OH, respectively, j 12 is the coupled angular momentum operator of j 1 and j 2 ; and V 6D is the interaction potential. The vibrational reference Hamiltonians h 1 (r 1 ) and h 2 (r 2 ) are defined as</p><!><p>Here V(r 1 ) and V(r 2 ) are the one-dimensional reference potentials for HBr and OH, and μ 1 and μ 2 are the corresponding masses. These potentials correspond to the reactant at the asymptotic region with other coordinates fixed at the equilibrium geometry. The split-operator method 43 is employed here to propagate the wave packet on the full-dimensional ab initio PES for the quantum scattering calculation. And we expand the time-dependent wave-function in terms of the body-fixed (BF) rovibrational eigenfunctions defined in terms of the above reactant Jacobi coordinates. After the time-dependent wave function is propagated into the product region, we perform the standard reactive flux [44][45][46][47] method to extract the initial-state-selected reaction probability. To obtain the initial-state-selected ICS, we first 1/2 is the wave number and E is the translational energy, v 0 and j 0 denotes, respectively, the initial vibrational and rotational quantum numbers, K 0 is the projection of J onto BF z axis of the reaction system.</p><p>Cumulative reaction probability and thermal rate constant. The CRP N J=0 (E) is defined as the sum of all the initial sate selected ro-vibrational reaction probabilities = P E ( )</p><p>Next, the J-shifting method 34 is employed here to calculate the CRP for the nonzero total angular momentum J. The total CRP, N(E) is defined as the sum of CRPs for all the open J and K channels</p><p>where ‡ E JK is the rigid rotor rotational energy of the reaction system at the transition state. This energy is approximated by the expression for a symmetric top molecule,</p><p>JK 2</p><p>A ‡ and B ‡ are the rotational constants of OHHBr at the transition state.</p><p>Thus the thermal rate constant can be computed as where Q r (T) is the reactant partition function, which is written as a product of vibrational, rotational, and translational partition functions. The equation ( 7) simplifies under the J-K shifting approximation in terms of Equation ( 5),</p><p>where ‡ Q rot is the rotational partition function of the reaction system at the transition state.</p><p>Numerical aspects. To converge the above 6DOF, wave-packet, quantum dynamics calculation, we used the following numerical parameters to expand the wavefunction: for the translational coordinate R from 2.5 to 12.5 bohr, 240 sine basis functions are used, and among these, 150 are used for the interaction region; 30 potential-optimized vibrational discrete variable representation (DVR) points 48 for the r 1 coordinates in the range from 1.6 to 5.5 bohr; 40 spherical harmonic rotational functions are used for θ 1 and 15 for θ 2 , which gives 4896 coupled parity adapted total angular momentum basis. The time-dependent wave packet is propagated for a total time of about 16,000 atomic unit time with a time step of 15 a.u. For the thermal rate constant calculation in equation ( 6), the rotational constants A ‡ and B ‡ of OHHBr at the transition state are 15.46 cm −1 and 0.14 cm −1 . For the reactant HBr and OH's vibrational partition function, the used harmonic vibrational frequencies of HBr and OH are 2525 cm −1 and 3611 cm −1 . For reactant rotational partition function, the HBr's rotational constant is 8.46 cm −1 and the OH's 18.86 cm −1 .</p>

Scientific Reports - Nature

Theoretical, Solid-State and Solution Quantification of the Hydrogen Bond Enhanced Halogen Bond

Proximal noncovalent forces are commonplace in natural systems and understanding the consequences of their juxtaposition is critical. This paper experimentally quantifies for the first time a Hydrogen Bond enhanced Halogen Bond (HBeXB) without the complexities of protein structure or preorganization. An HBeXB is a halogen bond that has been strengthened when the halogen donor simultaneously accepts a hydrogen bond. Our theoretical studies suggest that electron-rich halogen bond donors are strengthened most by an adjacent hydrogen bond. Furthermore, stronger hydrogen bond donors enhance the halogen bond the most. X-ray crystal structures of halide complexes (X\xe2\x88\x92 = Br\xe2\x88\x92, I\xe2\x88\x92) reveal that HBeXBs produce shorter halogen bonds than non-hydrogen bond analogues. 19F NMR titrations with chloride highlight that the HBeXB analogue exhibits stronger binding. Together, these results form the foundation for future studies concerning hydrogen bonds and halogen bonds in close proximity.

theoretical,_solid-state_and_solution_quantification_of_the_hydrogen_bond_enhanced_halogen_bond

Introduction<!>Design considerations<!>Computational evaluations<!>Molecular electrostatic potential analysis<!>Interaction energy analysis<!>Comparison to substituent effects<!>Other Functionals & Complexation Energy<!>Structural evaluations of HBeXB and XB systems<!>Solution evaluation of the HBeXB<!>Conclusion

<p>Electronegative substituents in polar covalent bonds are usually adept hydrogen bond acceptors. However, terminal organohalogens are paradoxical, as they are considered weak hydrogen bond acceptors.[1] Despite decades of hydrogen bond research, the rationale for this observation remains largely enigmatic.[2] Efforts to understand organohalogens as hydrogen bond acceptors (Figure 1A) have largely focused on fluorine.[3–8] In contrast, the consideration of heavier halogens (that halogen bond: X = Cl, Br, I) has lagged. The few studies of heavy organohalogens as hydrogen bond acceptors have largely been theoretical,[9–11] with only a handful of experimental[12–18] and database[19,20] studies reported. The importance of addressing this deficiency is underscored by the recent proliferation of halogen bonding materials, the ubiquity of the hydrogen bond, and a recent appreciation that hydrogen bonding can significantly influence halogen bonding (vide infra). Herein, we examine the intersecting fields of hydrogen and halogen bonding by experimentally quantifying, for the first time, the influence of a hydrogen bond to the electronegative region of a halogen bond donor.</p><p>The halogen bond is an attractive noncovalent interaction between an electrophilic halogen and a Lewis base (Figure 1B).[21] The linear interaction has found applications in fundamental and functional chemical disciplines.[22–31] The directionality is often attributed to an anisotropic distribution of electron density that develops on an electron-deficient halogen—an electropositive region at the tip of the halogen projected away from the covalent bond (frequently referred to as the 'σ-hole') and an electronegative belt orthogonal to the covalent bond. The electropositive region is often invoked to explain the attractive interaction with Lewis bases, while the electronegative region has helped explain the linearity of the halogen bond, as well as various "side-on" interactions with electrophilic species.[32,33]</p><p>The amphoteric nature of halogen bond donors (X= Cl, Br, I) has led researchers to consider their significance as hydrogen bond acceptors (H•••X—C; Figure 1A) or as halogen bond donors (C—X•••LB; Figure 1B) within ligand-protein complexes. Select examples highlight the remarkable influence of halogens when operating in either role. In one case, a hydrogen bond from an arginine side chain of a hepatitis C virus to a bromine atom (H•••Br—C) of an inhibitor contributed to a 250-fold improvement in efficacy (IC50).[34] A separate study showed that a halogen bond (C—Br•••O) from an inhibitor to a hydroxyl oxygen of a threonine contributed to a > 1000- fold selectivity (IC50) of aldose reductase over the closely related aldehyde reductase.[35] These contrasting examples echo conflicting findings of recent Protein Data Bank and theoretical studies. Here, one group has suggested that the halogen bond (C—X•••O) is more important to ligand-protein binding,[36,37] while another has suggested that the hydrogen bond to the halogen (H•••X—C) is more significant.[38] Differences aside, the implications are that both interactions (halogen bonds and hydrogen bonds to halogens) are understudied, yet can remarkably influence binding, selectivity, and molecular structure.</p><p>While both groups above noted the potential for organohalogens to simultaneously operate as a hydrogen bond acceptor and halogen bond donor, they did not consider how these interactions influence each other nor the potential consequences on molecular structure. In this light, we have recently investigated the Hydrogen Bond enhanced Halogen Bond (HBeXB; Figure 1C).[39] Under these conditions, a hydrogen bond to the electronegative belt of a halogen bond donor further polarizes and strengthens the halogen bond donor. An HBeXB can significantly influence both macromolecule stability and small molecule binding. In one case, the Ho group engineered a meta-chlorotyrosine (HBeXB donor) into T4 lysozyme which increased the thermal stability and activity of the enzyme at elevated temperatures compared to the parent enzyme.[40] Concurrently, our lab demonstrated that a hydrogen bond to a halogen bond donor can preorganize molecular structure and augment halogen bond strength in bidentate anion receptors—leading to a near 9-fold increase in halide binding.[41] These seminal studies provided proof-of-concept, yet the complexities of protein structure and anion receptor preorganization effects obscured quantification of just the HBeXB. Thus, we designed a model system with isolated HBeXBs that allowed us to quantify the HBeXB in solution, the solid-state and in silico.</p><!><p>Model compounds designed to study the HBeXB included a halogen bond donor adjacent to a sterically shielded hydrogen bond donor (Figure 1C). The iodine halogen bond donor was attached to an electron-deficient pyridinium ring to strengthen the halogen bond donor and ensured the presence of an anion in solid-state evaluations. The amide hydrogen bond donor was incorporated proximal to the iodine to form a 5-membered intramolecular hydrogen bond ring (Figure 1C). A trityl group flanking the amide proton provided sufficient steric hindrance to prevent intermolecular hydrogen bonding. The effectiveness of this functional group arrangement has been described in several reports by Li and coworkers, who noted that five-membered N–H•••X (X = Cl, Br, I) hydrogen bonding rings were more stable than six-membered rings in aromatic amides.[42–44] A charge-assisted C–H hydrogen bond donor ortho to the amide substituent was designed to reduce conformational flexibility by intramolecular hydrogen bonding to the amide carbonyl oxygen. Furthermore, functionalizing the positions ortho to the pyridinium nitrogen enabled evaluation of substituent effects on the HBeXB and limited intermolecular C – H hydrogen bonding. Neutral compounds with trifluorophenyl as the electron-withdrawing group were also assessed. Lastly, ester derivatives lacking a hydrogen bond donor were employed for comparison. Combined, these compounds represent four systematically altered pairs of HBeXB (amides) and non-hydrogen bonding (esters) molecules—three pairs of pyridinium compounds (1 & 2, 3 & 4, 5 & 6; Figure 2) and one neutral pair (7 & 8; Figure 3).</p><!><p>Pyridinium halogen bonding compounds 1–6 (Figure 2) were evaluated using gas-phase density functional theory. Using Gaussian 09,[45] calculations were performed using the B3LYP, M06-2X, and ωB97-XD functionals with the def2-TZVPP basis set for all atoms and the small-core energy-consistent relativistic effective core potential (def2-ECP) applied to iodine. A smaller basis set was also evaluated for comparison using the B3LYP functional with the 6-31+G (d,p) basis set for all atoms except iodine. In this case, the LANL2DZdp and large-core effective core potential were used to model iodine (for additional computational details see SI). The amide and ester conformations are most similar in the B3LYP/def2-TZVPP calculations and thus initial discussions focus on these calculations. The results from the other functionals and the smaller basis set with B3LYP are discussed at the end of the computational sections.</p><!><p>Molecular electrostatic potential maps of 1–6 were calculated to provide an estimate of halogen bond strength by assessing the σ-hole (Vs,max) of the iodine donors (Figure 2). As expected, derivatives with electron withdrawing fluorine substituents (5 & 6) had the most positive Vs,max, followed by the hydrogen (3 & 4) and methyl (1 & 2) derivatives (Figure 2), respectively. The Vs,max values span 11.55 kcal/mol (difference between 5 and 2, B3LYP/def2-TZVPP) reiterating that substituents can be used to modulate the halogen bond (Vs,max) in charge assisted pyridinium donors.</p><p>To probe how an adjacent hydrogen bond influences the halogen bond, amide derivatives (1, 3 & 5) were compared to isostructural ester derivatives (2, 4 & 6). Specifically, the Vs,max of the σ-holes for HBeXB derivatives (1, 3, & 5)—with an adjacent hydrogen bond—are more positive by 3.58–3.89 kcal/mol compared to the isostructural non-hydrogen bonding ester controls (2, 4, & 6; Table 1, B3LYP/def2-TZVPP). The largest difference between the amide/ester pairs occurred between the most electron-rich analogues (1 & 2). Considering this, a relatively electron-rich pair of charge-neutral trifluorophenyl halogen bonding derivatives (7 & 8) were also evaluated. Here, an even greater difference in Vs,max was observed (4.52 kcal/mol) between the HBeXB and the non-hydrogen bond derivative (7 and 8, Figure 3). Thus, the adjacent hydrogen bond has a larger influence on the more electron-rich halogen bond donors.</p><!><p>Interaction energies for the HBeXB model compounds (1, 3, 5, 7) and the non-hydrogen bonding controls (2, 4, 6, 8) with chloride were computed to further assess the impact of an intramolecular hydrogen bond on halogen bond strength (see SI for details).[46] Chloride was chosen as the anion for this analysis for computational simplicity. The interaction energies correlated with the σ-hole analysis (Table S1 and S2 in SI on page S36 & S37). For example, the strongest charge-assisted halogen bond occurred with the fluoro HBeXB derivative 5, the species with the most positive σ-hole. Likewise, the weakest halogen bond of the pyridinium derivatives occurred with the non-hydrogen bonding methyl derivative 2 which also had the smallest Vs,max. The largest difference in interaction energies (a measure of HBeXB amplification) between pyridinium HBeXB donors and the non-hydrogen bonding derivatives occurred with the most electron-rich pair (1 & 2). Here, there was a 1.01 kcal/mol HBeXB enhancement, whereas the proto (3 & 4) and fluoro (5 & 6) derivatives exhibited smaller differences in interaction energies by 0.47 and 0.17 kcal/mol, respectively. This trend further highlights that electron-rich halogen bond donors are influenced more by an adjacent hydrogen bond. Analysis of the neutral trifluoro derivatives provides more evidence, where the amide derivative 7 (HBeXB) has a stronger interaction energy with chloride than 8 (no intramolecular hydrogen bond) by 1.44 kcal/mol.</p><p>Next, we considered what factors may be limiting HBeXB enhancement in this model system. The local environment surrounding the hydrogen bond donor is congested and the amide protons of 1, 3, 5, & 7 can be described as bifurcated donors (Figure 4), having contacts with the π-electron system of a phenyl ring and the iodine halogen bond donor. As such, we considered the implications of hydrogen bond bifurcation on the HBeXB, to evaluate if approximately 1.4 kcal/mol is the upper limit to HBeXB amplification. To test this, interaction energies were calculated for derivatives of 1–4, where the trityl group was replaced with a methyl group (Figure 4, for additional details see SI). Interestingly, the methyl derivatives, with monodentate hydrogen bonds, led to a greater enhancement of halogen bond strength. The Δ interaction energies were 2.70 kcal/mol for the 3-methyl & 4-methyl derivatives and 3.02 kcal/mol for the 1-methyl & 2-methyl derivatives (Table S2 in SI). The enhanced halogen bonding is attributed to the monodentate amide hydrogen bond donor of the methyl derivatives (Figure 4). This is the first evidence that stronger hydrogen bond donors will provide greater improvement of halogen bond strength in HBeXBs. The data presented here indicates that halogen bonds can be enhanced by up to 3 kcal/mol per iodine halogen bond donor in this system (gas-phase DFT analysis) when accepting a single amide hydrogen bond.[47] However, altering the angle of the hydrogen bond may also influence the halogen bond and will be considered in future studies.</p><!><p>Substituent effects are a standard method used to enhance halogen bond strength. Appending electron withdrawing groups typically strengthens the halogen bond while electron donating groups have the opposite effect. To contextualize the HBeXB, interaction energies were calculated for two iodobenzene derivatives (see SI) and compared to the HBeXB augmentation described vida infra at the same level of theory. The halogen bonding interaction energy of 4-fluoroiodobenzene with chloride was 2.60 kcal/mol greater than iodobenzene with chloride. For comparison, the HBeXB enhancement for the 1-methyl & 2-methyl derivatives noted above was 3.02 kcal/mol. Thus, the enhancement from an HBeXB can be greater than introducing a fluorine atom to the para position of iodobenzene.</p><!><p>While B3LYP has shown good agreement between calculated and experimental binding[48,49] we also carried out all the calculations using the M06-2X and ωb97xd functionals with the def2-TZVPP basis set for comparison. All the calculations highlight that the HBeXB augments the halogen bond. For the M06-2X and ωb97xd calculations the ΔVs,max ranges from 1.76-5.52 kcal/mol and the ΔIEs range from −0.56-(−1.81) kcal/mol (Table 1 and Table S1 and S2). The trends in the data for the interaction energy calculations with the M06-2X and ωb97xd functionals parallel the B3LYP results described above showing that the more electron rich HBeXB compounds (1-6) enhance the halogen bond the most.</p><p>Complexation energies were also calculated as another method of evaluating the HBeXB that accounts for ligand deformation upon binding. Regardless of computational method, the HBeXB derivatives led to more stable complexes than the non-hydrogen bonding derivatives. Differences in complexation energies were −2.10-(−3.39) kcal/mol within the pyridinium family (1-6, Table 1) and −1.60-(−2.42) kcal/mol for the neutral species (7-8, Table 1). This further highlights that an adjacent hydrogen bond enhances the halogen bond.</p><p>For the Vs,max and complexation energy calculations we note a slight difference in data trends when using the M06-2X and ωb97xd functionals as compared to the B3LYP calculations. This deviation is attributed to the notably different ester conformations (when not bound to chloride) when using M06-2X and ωb97xd (Figure S27). The M06-2X and ωb97xd functionals include dispersion effects and thus the esters in these calculations display π-stacking between the pyridinium and one of the trityl aromatic rings. Nevertheless, the HBeXB strengthens the halogen bond in every case.</p><!><p>Triflate salts of 1 & 2 were synthesized (see SI) and crystal structures with halides (chloride, bromide, and iodide) were obtained, affording the first assessment of isostructural monodentate HBeXB and non-hydrogen bonding pairs in the solid-state (Figure 5; for crystallization and crystallographic details see SI).[50]</p><p>Halide crystal structures of 1 reaffirm that the trityl group prevents intermolecular hydrogen bonding and facilitates intramolecular hydrogen bonding to the iodine donors (parameters shown in Table 2). Previous theoretical investigations have indicated that larger halogens have a wide range (~40-180°) of favorable hydrogen bond contact angles.[38] The H•••I—C angles 61.2(5)°, 61.8(6)°, and 60.8(6)° for the chloride, bromide, and iodide complexes of 1, respectively, are within this range. Systematically, halogen bond contacts for HBeXB (1) with halides are shorter (or in the case of chloride similar) than halide structures of the non-hydrogen bonding 2, despite being less linear (Table 2). Specifically, the bromide and iodide structures of 1•Br− and 1•I− are roughly 0.058 Å and 0.076 Å shorter than 2•Br−, and 2•I−, even though the contact angles are less linear by about 9.6° and 7°, respectively. The 1•Cl− and 2•Cl− halogen bond distances are within the standard uncertainty of the measurements and have a difference in halogen bond angle of ≈ 2°. The similar halogen bond distances in 1•Cl− and 2•Cl− is attributed to the fact that these halogen bond contacts are already quite close (reduction ratios for both are 0.77—for definition of reduction ratio see table 2 footer). This is in contrast with the bromide and iodide structures where the reduction ratios of the non-hydrogen bonding ester derivatives are 0.82 (2•Br−) and 0.83 (2•I−). The HBeXB reduces the reduction ratios to 0.80 (1•Br−) and 0.81 (1•I−). Thus, these halide crystal structures highlight that hydrogen bonding to halogen bond donors strengthens halogen bonds in the solid-state.</p><p>Differing C–H hydrogen bond patterns between the chloride and iodide structures of 1 and 2 led to subtle conformational differences that affected the environment around the anions. For example, the C–H group meta to the pyridinium nitrogen contacts the halide in all three structures of 2 (Figure S25). In contrast, in 1•Cl− and 1•I− the pyridinium C–H donor forms an intramolecular hydrogen bond with the carbonyl oxygen. Nevertheless, both the 1•Br− and 2•Br− structures have similar conformations that provides compelling evidence that the contraction of the halogen bond in the 1•anion complexes is due to the amide hydrogen bond to the iodine. The 1•Br− and 2•Br− structures both have C—H•••Br− contacts (2.7426(3)Å and 158.48(11)° for 1•Br−, and 2.7846(4)Å and 155.44(12)° for 2•Br−) yet, the halogen bond distance in 1•Br− is shorter than in 2•Br−. Thus, small differences in packing and receptor conformation do not explain the shorter halogen bonds in the HBeXB derivatives (1•I− &1•Br−), rather the HBeXB strengthens binding and produces shorter contacts in the solid-state. [51]</p><!><p>The theoretical analysis herein indicated that the most electron-rich HBeXB and non-hydrogen bonded pairs (1, 2 and 7, 8) should provide the greatest differences in binding and allow for an isolated monodentate HBeXB to be measured in solution for the first time. To test this, titration experiments with chloride were carried out under the hypothesis that HBeXB compounds would result in greater association constants. Regrettably, 1 and 2 were hampered by solubility issues and decomposition, preventing solution assessment. Fortunately, 7 and 8 were not affected by the same challenges. Association constants for 7 and 8 with chloride (tetra-n-butylammonium chloride, TBACl) were measured by 19F NMR titrations at 25° C. Acetone-d6 was used as the solvent based on reports by Taylor who showed that this medium produced the greatest binding between TBACl and neutral halogen bond donors.[52,53] Likewise, these studies also indicated that chloride produces the greatest halide binding constants with neutral halogen bond donors. Halogen bonding of 7 and 8 to chloride was confirmed by the upfield shift of the fluorine signals upon addition of TBACl.[54] Association constants were determined using BINDFIT,[54] and the data was modeled to a 1:1 binding stoichiometry (see SI for further details). The non-hydrogen bonding derivative (8) halogen bonds to chloride with an association constant of 35.7 M−1, which is consistent with other charge-neutral halogen bonding molecules in solution. In contrast, the isostructural HBeXB derivative, 7, showed a marked increase in halogen bonding strength with an association constant of 43.3 M−1. After replicating the experiment four times a rough estimate of the spread was obtained by multiplying the standard deviation by two to obtain an approximation of the 95% confidence interval.[55] Treatment of the data in this manner led to interval values of [47.0, 39.8] and [37.9, 33.4] for 7 and 8, respectively (Table 3). Thus, the derivative with the HBeXB (7) exhibits stronger binding in solution when compared to the non-hydrogen bonding control which is fully consistent with the theoretical and solid-state findings.</p><p>To rule out possible direct intermolecular amide hydrogen bonding of 7 to chloride, 1H NMR data were collected in the presence of increasing equivalents (≈ 21.3 equivalents) of TBACl in acetone-d6. A common indication of hydrogen bonding is the downfield shift of the proton resonance upon complexation. The amide proton signal of 7 shifted only 0.16 ppm downfield. For comparison, a derivative of 7 was synthesized that would allow for intermolecular hydrogen bonding to chloride (9, a hydrogen in place of the iodine, Figure 3, and Figure S26). Compound 9 exhibited a much larger 0.72 ppm shift downfield in the presence of slightly fewer equivalents of TBACl (≈ 20.7 equivalents of TBACl). Fitting this 1H NMR data to a binding constant highlights that 9 binds chloride quite weakly with an association constant of 12.8 M−1. This weak binding coupled with the fact that the shift of the amide hydrogen in 9 is 4.5 times greater than 7 suggests that the amide hydrogen in 7 does not directly hydrogen bond to chloride in solution (See SI).</p><p>This conclusion is further supported by the severe steric congestion of the amide in 7, as demonstrated in the theoretical and solid-state analyses. Collectively, the evidence indicates that the amide proton is not a considerable 'direct' contributor (i.e. hydrogen bonding to chloride) to the association constant, and likely does not account for the increased affinity observed between 7 and 8. Thus, the solution data reveal that the hydrogen bond augments halogen bonding in solution.</p><!><p>The first experimental quantification of a monodentate HBeXB has revealed several new fundamental features. Solid-state structures highlight that HBeXB analogues form shorter halogen bonds with bromide and iodide, despite a less linear interaction when compared to non-hydrogen bonding controls. 19F NMR titrations of neutral fluorinated derivatives showed that HBeXB derivative (7) bound chloride stronger than a similar derivative that does not have a hydrogen bond (8), at a (approximate) 95% confidence interval. Theoretical studies indicated that HBeXB amplification is likely greater in more electron-rich systems where the halogen (iodine) is less polarized. Comparison of the trityl species (with a bifurcated amide hydrogen bond) to methyl derivatives (with a monodentate amide hydrogen bond) suggested that the strength of a halogen bond can be fine-tuned by varying the strength of an adjacent hydrogen bond. Interaction energies with chloride showed that with monodentate iodine halogen bond donors can be strengthened by up to 3 kcal/mol when concurrently accepting a single intramolecular amide hydrogen bond—an enhancement comparable to introducing a para-fluorine substituent to iodobenzene. Collectively, the data presented here form the foundation for future studies of organohalogen hydrogen bond acceptors and HBeXBs.</p><p>The studies herein demonstrate the significance of a halogen operating simultaneously as a halogen bond donor (C—X•••LB) and a hydrogen bond (H•••X—C) acceptor, leading to several outlooks. Consider again the debated importance of hydrogen bonding (H•••X—C) and halogen bonding (C—X•••LB) in protein-ligand interactions. While the degree of significance likely depends on the circumstances, the HBeXB should be considered in future analyses as its effects will be amplified and occur more frequently in environments where solvent effects are limited, and conformational flexibility is muted (i.e. protein-ligand complexes). The implications of the HBeXB are further heightened when one considers that over half of all launched organohalogen drugs contain heavy halogens (X= Cl, Br, I) with the capacity for halogen bonding.[56] In synthetic supramolecular systems, HBeXB effects will be pronounced when multidentate hydrogen and halogen bond donors are employed—as demonstrated by the preorganization of anion receptors.[41] Our results also show that amplification from the HBeXB is comparable to substituent effects and that the enhancement in halogen bond strength is likely more evident in electron rich systems. This suggests that HBeXBs may permit one to utilize a more stable halogen bond donor while maintaining a stronger halogen bonding interaction.[57] Overall, continued studies of HBeXBs will enrich our grasp of the chemical relationship between hydrogens and halogens and refine our understanding of halogen bond properties and the puzzling behavior of late group 17 hydrogen bond acceptors.</p>

PubMed Author Manuscript

The Flögel-three-component reaction with dicarboxylic acids – an approach to bis(β-alkoxy-β-ketoenamides) for the synthesis of complex pyridine and pyrimidine derivatives

An extension of the substrate scope of the Flögel-three-component reaction of lithiated alkoxyallenes, nitriles and carboxylic acids is presented. The use of dicarboxylic acids allowed the preparation of symmetrical bis(β-ketoenamides) from simple starting materials in moderate yields. Cyclocondensations of these enamides to 4-hydroxypyridine derivatives or to functionalized pyrimidines efficiently provided symmetrically and unsymmetrically substituted fairly complex (hetero)aromatic compounds containing up to six conjugated aryl and hetaryl groups. In addition, subsequent functionalizations of the obtained heterocycles by palladium-catalyzed couplings or by oxidations are reported. We also describe the simple synthesis of a structurally interesting macrocyclic bispyrimidine derivative incorporating a 17-membered ring, whose configuration was elucidated by DFT calculations and by subsequent reactions.

the_flögel-three-component_reaction_with_dicarboxylic_acids_–_an_approach_to_bis(β-alkoxy-β-ketoenam

<!>Introduction<!><!>Introduction<!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Conclusion<!>General methods<!>Three-component-reaction of methoxyallene, nitriles and dicarboxylic acids (typical procedure 1)<!>Cyclization of β-ketoenamides to 4-hydroxypyridines (typical procedure 2)<!>Nonaflation of 4-hydroxypyridines (typical procedure 3)<!>Cyclization of β-ketoenamides to pyrimidines (typical procedure 4)<!>

<p>This article is part of the Thematic Series "Multicomponent reactions II".</p><!><p>Multicomponent reactions (MCRs) generally allow a diversity-oriented fast and efficient access to complex synthetic intermediates and are thus powerful tools for the assembly of small-molecule libraries [1–2]. MCRs leading to functionalized N-heterocycles [3–7] have long been known before the general concept of MCRs was introduced, e.g. the Hantzsch dihydropyridine synthesis [8] or the Biginelli reaction [9] leading to dihydropyrimidinones or the corresponding dihydropyrimidinethiones. Due to their general importance (e.g. as biologically active compounds) the development of efficient protocols for the preparation of functionalized pyridine [10–20] and pyrimidine derivatives [21–33], in particular by MCRs, is of permanent high interest. In the course of exploring the reactivity of alkoxyallenes and their utilization as C-3 building blocks [34–37] our group developed a highly flexible method to synthesize β-alkoxy-β-ketoenamides of type 1 that are remarkably versatile cyclization precursors for the synthesis of functionalized heterocycles such as 4-hydroxypyridines [38–44], furopyridines [45], 5-acetyloxazoles [46–47], pyrimidines [43,48–49] and their corresponding N-oxides [50] (Scheme 1). This approach – discovered and mechanistically elucidated by Oliver Flögel – features a three-component reaction that employs alkoxyallenes, nitriles and carboxylic acids: upon treatment with n-butyllithium the allene is lithiated in α-position to the alkoxy moiety; the addition of a nitrile as electrophile to this highly reactive nucleophile results in the formation of an iminoallene adduct [38] that is protonated and subsequently acylated by the addition of a carboxylic acid furnishing a β-alkoxy-β-ketoenamide 1. A detailed mechanistic proposal for this reaction has been disclosed in previous reports [38–39].</p><!><p>Flögel-three-component reaction of lithiated alkoxyallenes, nitriles and carboxylic acids providing β-alkoxy-β-ketoenamides 1 – versatile precursors for the synthesis of functionalized N-heteroaromatics 2–6.</p><!><p>Our earlier investigations revealed that this method tolerates a broad variety of differently substituted starting materials – inter alia (het-)aromatic and (branched) aliphatic nitriles and carboxylic acids. It is also noteworthy to mention that the configurational integrity of enantiopure α-chiral carboxylic acids and/or nitriles is retained during this reaction [40]. In the present report we describe our efforts to further broaden the substrate scope of this multicomponent reaction and the subsequent cyclizations by employing aromatic dicarboxylic acids. This extension should allow a rapid access to fairly complex heteroaromatic systems containing up to six conjugated aryl and hetaryl groups. Complementary examples employing aromatic dinitriles in this Flögel-three-component reaction have previously been presented [39].</p><!><p>As typical model substrates we chose to employ isophthalic acid (11) and diphenic acid (12) in combination with methoxyallene (7), pivalonitrile (9) and thiophene-2-carbonitrile (10) in the three-component reaction (Scheme 2). Gratifyingly we were able to isolate the expected bis(β-ketoenamides) 13–15 in reasonable yields of 15–28%. Taking the number of individual steps into account (six new bonds are formed for each product) and considering possible (unknown) side reactions these yields are quite satisfactory. In analogy to our previously published results [38,51–52] the double bond geometry of the enamide moiety is likely to be E-configured as shown in Scheme 2, allowing an intramolecular hydrogen bridge between the amide NH and the β-carbonyl group. However, we did not further investigate the nature of the double bond geometry, since it was irrelevant for the planed subsequent cyclization reactions where the (Lewis-)acidic conditions allow a facile isomerization of E- and Z-configured enamide moieties [51–52], finally leading to identical products.</p><!><p>Synthesis of bis(β-ketoenamides) 13–15 by three-component reactions of lithiated methoxyallene 8 with nitriles 9 or 10 and isophthalic acid (11) or diphenic acid (12).</p><!><p>After these successful multicomponent reactions we investigated the intramolecular condensations of the bis(β-ketoenamides) 13–15 to pyridine and pyrimidine derivatives. Enamides 13 and 14 were treated with trimethylsilyl trifluoromethanesulfonate (TMSOTf) and triethylamine to provide the bis(4-hydoxypyridines) 16 in 50% yield and 18a in 60% yield, respectively (Scheme 3). A mechanistic proposal for this aldol type condensation has been presented in a previous report [53]. For precursor 14 partial monocyclization was observed under the applied conditions, affording in 18% yield 4-hydroxypyridine 18b with a retained β-ketoenamide moiety. Treatment of compounds 16, 18a and 18b with sodium hydride followed by nonafluorobutanesulfonyl fluoride (NfF) provided the corresponding sulfonates 17, 19 and 20 in yields in the range of 60–72%. Pyrid-4-yl nonaflates are excellent precursors for transition metal-catalyzed cross-coupling reactions [42,54–58], which was demonstrated here by the successful Suzuki coupling of bisnonaflate 19 with (E)-styrylboronic acid and the Stille coupling of 19 with 2-(tributylstannyl)thiophene. Albeit the expected twofold coupling products 21 and 22 were obtained in only moderate yields, the presented approach nevertheless features a quite rapid access to these fairly complex heteroaromatic systems containing six conjugated aryl and hetaryl groups. Upon excitation with UV light (253 nm) compound 22 shows fluorescence with a maximum intensity at 378 nm (see Supporting Information File 1 for details). The photophysical properties of structurally related pyridine–thiophene conjugates were recently investigated in detail [55,57–58].</p><!><p>Cyclocondensations of β-ketoenamides 13 and 14 to 4-hydroxypyridines 16, 18a and 18b, their subsequent nonaflations and palladium-catalyzed coupling reactions of 19 leading to compounds 21 and 22. NfF = C4F9SO2F</p><!><p>Next, we investigated the cyclocondensation of bis(β-ketoenamides) 13–15 to pyrimidines (Scheme 4) using ammonium acetate as ammonia source. Initially we subjected enamide 13 to conditions that had been optimized for mono-β-ketoenamides [48–49], in this case resulting in incomplete conversion: after heating 13 with 8 equiv of ammonium acetate in a sealed tube we obtained a 1:1 mixture of bis(pyrimidine) derivative 23a and pyrimidine 23b still containing one β-ketoenamide unit with an overall yield of 68%. However, full conversion of 13 into 23a was achieved by increasing the amount of ammonium acetate to 16 equiv and using a higher reaction temperature, raising the yield of 23a from 34% to 55% yield. When enamide 14 was cyclized under these optimized conditions the conversion was nevertheless incomplete giving the desired bis(pyrimidine) derivative 24a in 56% yield and the corresponding mono-pyrimidine 24b in 23% yield. For enamide 15 however, the cyclization was complete under these conditions furnishing bis(pyrimidine) derivative 25 as a single product in 60% yield.</p><!><p>Cyclocondensations of β-ketoenamides 13–15 with ammonium acetate to bis(pyrimidine) derivatives 23a, 24a and 25 and mono-pyrimidines 23b and 24b.</p><!><p>Although initially not desired the incomplete conversions of the bis(β-ketoenamides) leading to mono-pyridine derivatives such as 18b or to mono-pyrimidine derivatives like 23b and 24b provided new synthetic options to construct unsymmetrically substituted mixed heteroaromatic systems. As an example we used mono-pyrimidine derivative 24b and cyclized its β-ketoenamide moiety by treatment with TMSOTf and triethylamine. Pyrimidine/pyridinol derivative 26 was isolated in 79% yield (Scheme 5) and subsequently converted into the corresponding nonaflate 27 in 70% yield.</p><!><p>Conversion of mono-pyrimidine derivative 24b into unsymmetrically substituted biphenylen-bridged pyrimidine/nonafloxypyridine conjugate 27. NfF = C4F9SO2F</p><!><p>As recently described, β-alkoxy-β-ketoenamides may also be directly cyclized to pyrimidine-N-oxides under mild conditions if hydroxylamine hydrochloride is used as reagent [50]. Accordingly, the reactions of β-ketoenamides 14 and 20 with hydroxylamine hydrochloride provided the symmetric bis(pyrimidine-N-oxide) 28 in 39% yield or the mono-pyrimidine-N-oxide 30 in 54% yield (Scheme 6). The acetoxylation of 2- and 4-alkyl substituted pyridine-N-oxides by treatment with acetic anhydride is known as the Boekelheide rearrangement [59–60]. For pyrimidine-N-oxides however, only few examples of this type of transformation have been reported [50,61–65]. Therefore we were pleased to find that upon treatment with acetic anhydride the obtained pyrimidine-N-oxides 28 and 30 smoothly underwent the expected rearrangement to give the acetoxymethyl-substituted pyrimidine derivatives 29 and 31 in 61% and 55% yield, respectively. This approach thus allows the simple functionalization of the 4-methyl group of the pyrimidine derivatives and is a very useful tool for the preparation of other compounds.</p><!><p>Condensation of β-ketoenamides 14 and 20 with hydroxylamine hydrochloride to pyridine-N-oxides 28 and 30 and their subsequent Boekelheide rearrangements furnishing functionalized bis(pyrimidine) derivative 29 and pyrimidine/pyridine conjugate 31.</p><!><p>An alternative option for the side chain functionalization of 4- or 6-methyl substituted pyrimidines involves an oxidation with selenium dioxide (Riley oxidation [66–68]). To explore the synthetic potential of the newly prepared compounds we exemplarily oxidized bis(pyrimidine) 23a by this method in order to finally prepare a macrocyclic compound such as 34 (Scheme 7). Treatment of 23a with an excess of selenium dioxide at 90 °C resulted in the formation of an inseparable mixture of two different aldehydes (probably the dialdehyde and the monoaldehyde). After reduction of the mixture with sodium borohydride the obtained products could be separated by column chromatography providing the dialcohol 32a in 51% yield over two steps and the monoalcohol 32b in 25% yield, respectively. The subsequent O-allylation of 32a furnished bisallyl ether 33 with 77% yield that was subjected to a ring closing metathesis (RCM) [69] with Grubbs-II-catalyst smoothly leading to the structurally interesting macrocyclic compound 34 in 73% yield. Compounds of this type – incorporating a 17-membered ring – have the potential to serve as structurally quite unique ligands for a variety of applications, e.g. in catalysis.</p><!><p>Riley oxidation of bis(pyrimidine) derivative 23a and conversion of diol 32a into macrocycle 34.</p><!><p>With ruthenium-based catalysts bearing N-heterocyclic carbene (NHC) ligands, RCM usually delivers macrocyclic olefins as mixtures of E- and Z-isomers, in most cases in favor of the E-isomer [70–73]. The E/Z-ratio is often under thermodynamic control, reflecting the energy difference between the two isomers. According to TLC and NMR spectroscopy, macrocycle 34 was isolated as a single compound. Due to the symmetry of 34 no couplings of the olefinic protons in its 1H NMR spectrum can be observed. Thus at this stage, we were unable to assign the configuration of the double bond. In lack of suitable crystals for an X-ray analysis, we calculated the energy for the two possible isomers of 34, suggesting that the E-isomer should be considerably more stable than the corresponding Z-isomer (Table 1). Using the semi-empirical AM1 method an energy difference of ΔEZ-E of 28.7 kJ/mol was determined. DFT calculations using the B3LYP method with the basis sets 6-31(d) or 6-31G(d,p) both gave a ΔEZ-E value of 16.4 kJ/mol. This energy difference may be attributed to the strain of the macrocycle and higher torsion angles between the central benzene unit and the pyrimidine rings for the Z-isomer of 34, resulting in less efficient conjugation of the aromatic π-systems. The optimized molecular geometries of E-34 and Z-34 as well as the calculated torsion angles are depicted in Figure 1.</p><!><p>Calculated relative energy differences of the Z- and E-configured isomers of macrocycle 34.</p><p>Optimized geometries of (a) E-configured and (b) Z-configured macrocycle 34 at B3LYP/6-31G(d,p) level. The numbers represent the calculated torsion angles between the aromatic rings.</p><!><p>In order to unambiguously identify the double bond configuration of 34, we oxidized this compound with potassium osmate/NMO to obtain the vicinal diol 35 in 76% yield (Scheme 8). In the case of a Z-configured olefin 34 this dihydroxylation should give a cis-configured diol (meso compound), whereas an E-configured olefin 34 would lead to a racemic mixture of the corresponding trans-configured diol. However, due to the symmetry of both vicinal diols a distinction between cis- and trans-35 (σv- or C2-symmetry respectively) by NMR is still not possible. The resulting diol 35 was therefore treated with an excess of (S)-Mosher's acid chloride to obtain the bis-(R)-Mosher ester 36 [74]. TLC analysis and NMR-spectroscopy revealed, that compound 36 was obtained as a pair of C2-symmetric diastereomers and that the obtained diol 35 was in fact a racemic mixture. This observation allowed the conclusion that the RCM reaction of 33 produced the expected thermodynamically more stable E-configured macrocyclic olefin 34. Hence this experimental result is in perfect agreement with the DFT calculations.</p><!><p>Dihydroxylation of the macrocyclic olefin 34 to diol 35 and subsequent esterification to the bis-(R)-Mosher ester 36; (S)-MTPA-Cl = (S)-3,3,3-trifluoro-2-methoxy-2-phenylpropanoyl chloride.</p><!><p>We were able to extend the substrate scope of the Flögel-three-component reaction of alkoxyallenes, nitriles and carboxylic acids by successfully utilizing aromatic dicarboxylic acids to prepare three new bis(β-methoxy-β-ketoenamides). With these products of a multicomponent reaction we performed cyclizations to rapidly construct symmetrically and unsymmetrically substituted pyridine and pyrimidine derivatives. Hence a very short approach to fairly complex functionalized oligoaromatic systems was established. In addition we exemplarily investigated subsequent transformations of these compounds either by palladium-catalyzed cross-couplings or by oxidations of the 4-methyl groups of the pyrimidine subunits. Although the yields for the crucial initial multicomponent reactions leading to the bis(β-methoxy-β-ketoenamides) are only moderate when dicarboxylic acids are used the simplicity of the processes and the diversity of the products accessible is impressive. The described methods allow the preparation of oligo(hetero)aromatic compounds not available by alternative procedures.</p><!><p>Reactions were performed under an atmosphere of argon in flame-dried flasks. Solvents and liquid reagents were added by syringe. Et2O, CH2Cl2 and THF were transferred from a MB SPS-800-dry solvent system into the reaction vessels. Dry DMF was purchased from Acros Organics and stored in the presence of molecular sieve under an atmosphere of argon. NEt3 was distilled from CaH2 and stored over KOH under argon. Methoxyallene was prepared from propargylic alcohol in two steps according to literature procedures [34,75]. All other solvents and reagents were purchased from commercial suppliers and were used without further purification. Thin-layer chromatography (TLC) analyses were performed on TLC plates purchased from Merck (silica gel 60, fluorescence indicator F254, 0.25 mm layer thickness). Products were purified by flash column chromatography on silica gel 60 (230–400 mesh, Macherey-Nagel). NMR spectra were recorded with Bruker (AC 500, AVIII 700) and JEOL (ECX 400, Eclipse 500) instruments. Chemical shifts are reported relative to solvent residual peaks or TMS. Integrals are in accordance with assignments, and coupling constants are given in Hz. All 13C NMR spectra are proton-decoupled. 13C NMR signals of Nf-groups [CF3(CF2)3] are not given since unambiguous assignment is not possible due to strong splitting by coupling with the 19F nuclei. IR spectra were measured with a Jasco FT/IR-4100 spectrometer. HRMS analyses were performed with a Varian Ionspec QFT-7 (ESI–FT ICRMS) or an Agilent 6210 (ESI–TOF) instrument. Melting points were measured with a Reichert apparatus (Thermovar) and are uncorrected.</p><!><p>To a solution of methoxyallene (7, 2.07 g, 29.6 mmol) in dry Et2O (25 mL) was added n-BuLi (10.8 mL, 27.0 mmol, 2.5 M in hexanes) at −50 °C. After 30 min stirring at −50 °C, the reaction mixture was cooled to −78 °C and pivalonitrile (9, 0.752 g, 9.06 mmol) in dry Et2O (10 mL) was added to the mixture. After stirring for 4 h a suspension of diphenic acid (12, 6.54 g, 27.0 mmol) in dry Et2O (50 mL) was added. The temperature was allowed to rise to rt and the mixture was stirred overnight. The reaction was quenched with sat. aq NaHCO3 solution (25 mL) and the layers were separated. The aqueous layer was extracted with Et2O (3 × 50 mL) and the combined organic layers were washed with brine (25 mL), dried with Na2SO4 and filtered. The solvent was removed under reduced pressure and the obtained crude product was purified by column chromatography (silica gel, hexanes/EtOAc = 1:2) to provide bis(β-ketoenamide) 14 (1.39 g, 28%) as a pale yellow solid.</p><p>N2,N2'-Bis(4-methoxy-2,2-dimethyl-5-oxohex-3-en-3-yl)biphenyl-2,2'-dicarboxamide (14): mp 140–143 °C; IR (ATR) ν: 3145 (NH), 3040–2835 (=C-H, C-H), 1695 (C=O), 1525–1390 (C=C) cm−1; 1H NMR (CDCl3, 500 MHz) δ 0.96 (s, 18H, t-Bu), 2.09 (s, 6H, Me), 3.42 (s, 6H, OMe), 7.07–7.09, 7.31–7.37, 7.49–7.51 (3 m, 2H, 4H, 2H, Ar), 8.13 (br s, 2H, NH) ppm; 13C NMR (CDCl3, 126 MHz) δ 27.6 (q, Me), 28.4, 36.5 (q, s, t-Bu), 58.8 (q, OMe), 127.0, 127.9, 129.6, 130.4 (4 d, Ar), 131.9, 136.4, 138.4, 151.0 (4 s, C=C, Ar), 169.5 (s, CONH), 200.1 (s, C=O) ppm; ESI–TOF (m/z): [M + Na]+ calcd for C32H40N2NaO6, 571.2779; found, 571.2783.</p><!><p>Bis(β-ketoenamide) 14 (0.310 g, 0.57 mmol) was placed in an ACE-sealed tube and dissolved in DCE (10 mL). NEt3 (0.40 mL, 2.89 mmol) and TMSOTf (0.50 mL, 2.76 mmol) were added and the resulting mixture was stirred at 90 °C for 3 d. After cooling to rt the reaction was quenched with sat. aq NH4Cl solution (10 mL) and the layers were separated. The aqueous layer was extracted with CH2Cl2 (3 × 25 mL) and the combined organic layers were dried with Na2SO4 and filtered. The solvent was removed under reduced pressure and the obtained crude product was purified by column chromatography (silica gel, EtOAc) to provide bis(4-hydroxypyridine) 18a (0.174 g, 60%) as a brown liquid and 18b (54 mg, 18%) as pale yellow oil. The products were directly converted into the corresponding nonaflates 19 and 20.</p><!><p>Bis(4-hydroxypyridine) 18a (0.805 g, 1.57 mmol) was dissolved in THF (25 mL) and NaH (0.313 g, 7.86 mmol, 60% in mineral oil) was added under argon atmosphere. Nonafluorobutanesulfonyl fluoride (2.35 g, 7.79 mmol) was added drop-wise and the mixture was stirred at rt for 12 h. After dilution with Et2O (25 mL), the reaction was slowly quenched with ice and water (25 mL). The layers were separated and the aqueous layer was extracted with Et2O (3 × 25 mL). The combined organic layers were dried with Na2SO4, filtered and concentrated to dryness under reduced pressure. The residue was purified by column chromatography (silica gel, hexanes/EtOAc = 9:1 to 4:1) to provide pyridyl nonaflate 19 (1.20 g, 71%) as a pale yellow oil.</p><p>6,6'-(Biphenyl-2,2'-diyl)bis(2-tert-butyl-3-methoxypyridine-6,4-diyl) bisnonaflate (19): IR (ATR) ν: 3065–2870 (=C-H, C-H), 1555–1410 (C=C) cm−1; 1H NMR (CDCl3, 500 MHz) δ 1.19 (s, 18H, t-Bu), 3.89 (s, 6H, OMe), 6.92 (s, 2H, Py), 7.10 (dd, J = 7.5, 1.2 Hz, 2H, Ar), 7.30 (td, J = 7.5, 1.4 Hz, 2H, Ar), 7.36 (dd, J = 7.5, 1.4 Hz, 2H, Ar), 7.59 (dd, J = 7.5, 1.2 Hz, 2H, Ar) ppm; 13C NMR (CDCl3, 126 MHz) δ 29.1, 38.7 (q, s, t-Bu), 61.7 (q, OMe), 115.2 (d, Py), 127.4, 128.6, 130.1, 131.6 (4 d, Ar), 138.2, 140.6 (2 s, Ar), 145.3, 149.3, 153.2, 163.7 (4 s, Py) ppm; 19F NMR (CDCl3, 470 MHz) δ −80.6 (t, J = 9.6 Hz, 6F, CF3), −109.5 (t, J = 13.7 Hz, 4F, CF2), −120.7, −125.8 (2 mc, 4F each, CF2) ppm; ESI–TOF (m/z): [M + Na]+ calcd for C40H34F18N2NaO8S2, 1099.1361; found, 1099.1394.</p><!><p>Bis(β-ketoenamide) 14 (0.162 g, 0.296 mmol) and NH4OAc (0.365 g, 4.73 mmol) were placed in an ACE-sealed tube. The mixture was dissolved in MeOH (5 mL) and stirred for 2 d at 90 °C. After addition of H2O (10 mL) and Et2O (20 mL) the layers were separated and the aqueous layer was extracted with Et2O (2 × 25 mL). The combined organic layers were dried with Na2SO4, filtered and the solvent was evaporated under reduced pressure. The residue was purified by column chromatography (silica gel, hexanes/EtOAc = 5:1) to provide pyrimidines 24a (88 mg, 56%) and 24b (35 mg, 23%), both as colorless oils.</p><p>2,2'-Bis(4-tert-butyl-5-methoxy-6-methylpyrimidin-2-yl)biphenyl (24a): IR (ATR) ν: 3070–2855 (=C-H, C-H), 1550–1440 (C=C) cm−1; 1H NMR (CDCl3, 500 MHz) δ 0.99 (s, 18H, t-Bu), 2.28 (s, 6H, Me), 3.70 (s, 6H, OMe), 7.30 (dt, J = 7.7, 1.9 Hz, 2H, Ar), 7.34–7.39 (m, 4H, Ar), 7.70 (dd, J = 7.7, 1.0 Hz, 2H, Ar) ppm; 13C NMR (CDCl3, 126 MHz) δ 19.7 (q, Me), 28.7, 37.6 (q, s, t-Bu), 60.9 (q, OMe), 126.4, 128.7, 130.2, 131.4 (4 d, Ar), 138.4, 142.6 (2 s, Ar), 149.8, 159.3, 159.4, 166.9 (4 s, Py) ppm; ESI–TOF (m/z): [M + H]+ calcd for C32H39N4O2, 511.3068; found, 511.3085.</p><p>2'-(4-tert-Butyl-5-methoxy-6-methylpyrimidin-2-yl)-N-(4-methoxy-2,2-dimethyl-5-oxohex-3-en-3-yl)biphenyl-2-carboxamide (24b): IR (ATR) ν: 3325 (N-H), 3065–2865 (=C-H, C-H), 1700, 1665 (C=O), 1550–1445 (C=C) cm−1; 1H NMR (CDCl3, 500 MHz) δ 0.71 (s, 9H, t-Bu), 1.26 (s, 9H, t-Bu), 2.31, 2.33 (2 s, 3H each, Me), 3.45, 3.70 (2 s, 3H each, OMe), 6.64 (dd, J = 7.5, 1.0 Hz, 1H, Ar), 7.07, 7.25 (2 dt, J = 7.5, 1.2 Hz, 1H each, Ar), 7.32 (dd, J = 7.5, 1.2 Hz, 1H, Ar), 7.39 (dt, J = 7.5, 1.8 Hz, 1H, Ar), 7.43 (dt, J = 7.5, 1.0 Hz, 1H, Ar), 7.50 (dd, J = 7.8, 1.2 Hz, 1H, Ar), 7.91 (dd, J = 7.8, 1.8 Hz, 1H, Ar), 8.40 (br s, 1H, NH) ppm; 13C NMR (CDCl3, 126 MHz) δ 19.2 (q, Me), 27.2 (q, Me), 28.1, 29.2, 35.9, 37.9 (2 q, 2 s, t-Bu), 58.9, 61.0 (2 q, OMe), 126.8, 127.9, 128.0, 128.5, 129.0, 129.4, 130.3, 130.7, 131.0 (8 d, s, Ar, =C), 137.5, 138.4, 138.9, 140.5, 150.1 (5 s, Ar, =C), 150.4, 159.6, 160.0, 168.4 (4 s, Py), 169.3 (s, CONH), 199.8 (s, C=O) ppm; ESI–TOF (m/z): [M + Na]+ calcd for C32H34N3NaO4, 552.2833; found, 552.2844.</p><!><p>Additional experimental procedures and analytical data, as well as copies of NMR spectra of representative examples.</p>

PubMed Open Access

The DNA polymerase activity of Pol ε holoenzyme is required for rapid and efficient chromosomal DNA replication in Xenopus egg extracts

BackgroundDNA polymerase ε (Pol ε) is involved in DNA replication, repair, and cell-cycle checkpoint control in eukaryotic cells. Although the roles of replicative Pol α and Pol δ in chromosomal DNA replication are relatively well understood and well documented, the precise role of Pol ε in chromosomal DNA replication is not well understood.ResultsThis study uses a Xenopus egg extract DNA replication system to further elucidate the replicative role(s) played by Pol ε. Previous studies show that the initiation timing and elongation of chromosomal DNA replication are markedly impaired in Pol ε-depleted Xenopus egg extracts, with reduced accumulation of replicative intermediates and products. This study shows that normal replication is restored by addition of Pol ε holoenzyme to Pol ε-depleted extracts, but not by addition of polymerase-deficient forms of Pol ε, including polymerase point or deletion mutants or incomplete enzyme complexes. Evidence is also provided that Pol ε holoenzyme interacts directly with GINS, Cdc45p and Cut5p, each of which plays an important role in initiation of chromosomal DNA replication in eukaryotic cells.ConclusionThese results indicate that the DNA polymerase activity of Pol ε holoenzyme plays an essential role in normal chromosomal DNA replication in Xenopus egg extracts. These are the first biochemical data to show the DNA polymerase activity of Pol ε holoenzyme is essential for chromosomal DNA replication in higher eukaryotes, unlike in yeasts.

the_dna_polymerase_activity_of_pol_ε_holoenzyme_is_required_for_rapid_and_efficient_chromosomal_dna_

Background<!>Isolation of cDNA encoding each subunit of Xenopus Pol ε holoenzyme<!>The C-terminal Zinc finger domain of p260 is required for binding p60 but not p12-p17<!><!>DNA polymerase activity of xPol ε holoenzyme is required for DNA synthesis in Xenopus egg extracts<!><!>DNA polymerase activity of xPol ε holoenzyme is required for DNA synthesis in Xenopus egg extracts<!><!>xPol ε holoenzyme interacts with xCdc45p, xCut5p, and xGINS<!><!>xGINS stimulates xPol ε-holoenzyme-catalyzing DNA synthesis<!><!>Discussion<!>Conclusion<!>cDNA cloning<!>Rapid amplification of cDNA ends (RACE)<!>Antibodies<!>Xenopus egg extracts and DNA replication assay<!>Expression, purification, and reconstitution of Xenopus Pol ε Complex<!>Preparation of Pol ε-depleted Xenopus egg extracts<!>Recombinant Xenopus GINS, Cut5p, and Cdc45p<!>Authors' contributions<!>Additional file 1<!><!>Additional file 2<!><!>Additional file 3<!><!>Additional file 4<!><!>Additional file 5<!><!>Acknowledgements

<p>Three structurally and functionally distinct DNA polymerases, known as DNA polymerases α, δ, and ε (Pol α,-δ, and -ε, respectively), are required for chromosomal DNA replication in yeasts [1-3]. The complex structure of each Pol α, -δ, and -ε is well conserved from yeast to human [4], thus their function inside the cell is also believed to be conserved [4].</p><p>DNA primase initiates DNA replication by synthesizing a short oligo-ribonucleotide primer which is immediately elongated by Pol α to form short RNA-DNA fragments on both leading and lagging strand of DNA. Pol δ elongates the short RNA-DNA fragment initiated by Pol α-primase to make a mature Okazaki fragment [2,5]. To carry out processive DNA synthesis in vitro, Pol δ requires PCNA and its loader, Replication Factor-C (RF-C) [5]. In cooperation with Fen1p (Rad27p), Dna2p and RPA, Pol δ also plays a crucial role in processing RNA-linked Okazaki-fragments in budding yeast [5].</p><p>Although the precise role of Pol ε in vivo is still unclear, it has been implicated in DNA replication, repair, recombination, and mitosis [1,2,4]. Pol ε has at least one essential function in both budding and fission yeasts [3,6], and several lines of evidence suggest that Pol ε plays an essential catalytic role during chromosomal DNA replication. Yeast cells harboring a temperature-sensitive pol2 allele are temperature sensitive for growth and express a thermolabile Pol ε DNA polymerase activity [7]. Furthermore, Pol2p is associated with replication forks during S phase [8] and pol2 mutants fail to complete chromosomal DNA replication [7,9]. Furthermore, 3'–5' exonuclease-deficient mutants of POL2 and POL3 (Pol δ) accumulate strand-specific lesions in chromosomal DNA [10-13]. These observations support models for chromosomal DNA replication in which Pol ε and Pol δ play leading strand- and lagging strand-specific roles during chromosomal DNA replication, respectively. Pol ε has been proposed as the leading strand DNA polymerase because Pol ε is a highly processive polymerase without PCNA [1,14] and pol3 mutants have defects in maturation of Okazaki fragments [5]. Nevertheless, it has been reported that the amino-terminal portion of budding yeast Pol ε (Pol2p), which includes motifs required for DNA polymerase and exonuclease activities, is dispensable for DNA replication, DNA repair, and viability [15]. However, this conclusion is controversial, because the polymerase active domain mutant (polymerase-dead-mutant) is lethal [16] and our studies showed that the deletion mutant confers temperature-sensitivity for growth, a defect in DNA elongation, premature senescence, and short telomeres. Furthermore, this pol2p deletion is lethal in combination with temperature-sensitive cdc2 and with exonuclease-deficient Pol δ (pol3-01). These results suggest that Pol ε plays a crucial role in maintaining genomic integrity [17,18].</p><p>In higher eukaryotes, the function of Pol ε is much less clear than in S. cerevisiae, although some reports showed that Pol ε is required for cellular chromosomal DNA replication [19-21]. In order to understand how Pol ε involves in higher eukaryotic chromosomal DNA replication, we have been characterizing DNA replication catalyzed by Xenopus egg extracts [22,23]. We have shown previously that both the initiation and elongation steps of chromosomal DNA replication are markedly impaired in Pol ε-depleted Xenopus egg extracts, resulting in significant reduction of the overall DNA synthesis as well as accumulation of small replication intermediates. Moreover, despite the decreased DNA synthesis, excess amounts of Pol α are loaded onto the chromatin template in Pol ε-depleted extracts, indicative of the failure of proper assembly of DNA synthesis machinery at the fork [22]. Although these experiments clearly demonstrate that Pol ε is required for a normal chromosomal DNA replication in Xenopus egg extracts, they did not give any answer whether DNA polymerase activity of Pol ε directly involves in chromosomal DNA replication process.</p><p>In the present report we show that the reconstituted and purified Xenopus Pol ε holoenzyme, which is proficient in DNA polymerase activity, fully complements DNA replication defect of Pol ε-depleted Xenopus egg extracts, but neither DNA polymerase domain deleted Pol ε holoenzyme, DNA polymerase-dead-Pol ε holoenzyme, the catalytic subunit of Pol ε, nor other subunits of Pol ε holoenzyme complements the defect at all. These results clearly prove that the DNA polymerase activity of Pol ε holoenzyme directly participates in chromosomal DNA replication in Xenopus egg extracts and that the products made by Pol ε-depleted Xenopus egg extracts are not fully replicated DNA.</p><!><p>A previous study reported cloning of a partial cDNA for the catalytic subunit (p260) of Xenopus Pol ε (xPol ε) [24], and in this report, the corresponding full-length cDNA was cloned by 5' Rapid amplification of cDNA ends (5' Race) (see Additional file 1). The fact that the full length cDNA encodes a 2285 amino acid residue protein whose predicted amino acid sequence is 81% identical to human p260 [25] and 62% identical to S. cerevisiae Pol2p [6] within the polymerase domain (see Additional file 2 and Additional file 3) confirms the identity of the cloned fulllength cDNA. Full length cDNA encoding p17 and p12 of xPol ε were also cloned using 3' RACE, Xenopus ovary mRNA and partial cDNA clones 4783571(5') (GenBank ACC# BI349483) and PBX0037B02(5') (GenBank ACC# AW635703), respectively. The predicted amino acid sequences of p12 and p17 showed very high similarity to p12 and p17 of human Pol ε, respectively [26](see Additional file 4), confirming the identity of the cloned cDNAs. cDNA encoding p60 of xPol ε holoenzyme was cloned previously [22]; thus, with this report, full length cDNA clones have been isolated for all four subunits of xPol ε holoenzyme.</p><!><p>Deletion mutants of xPol ε p260 were constructed and used to identify protein regions involved in the interfaces between p260 and the other subunits of Pol ε holoenzyme. For these experiments, p260 deletion mutants were fused to the FLAG epitope tag (Fig. 1A) and the following mutants were generated: (a) FLAG-p260full, (b) FLAG-p260ΔC2157, (c) FLAG-p260ΔC1054, (d) FLAG-p260D860N, and (e) FLAG-p260ΔCat (equivalent to yeast Pol2-16p [15,16,27]). The p260 mutants were co-expressed with xPol ε p60, p12 and p17 using a baculovirus insect cell expression system and immunoprecipitated with anti-Flag antibodies. Figure 1B shows that anti-Flag antibodies co-immunoprecipitated p260, p60, p12, and p17 from crude extracts of insect cells expressing wild type p260, p60, p12, and p17. In contrast, in cells expressing p260ΔC2157, p12 and p17 co-immunoprecipitated with the catalytic subunit but p60 did not, and in cells expressing p260ΔC1054, no other subunits of Pol ε holoenzyme co-immunoprecipitated with the p260 mutant protein. These results suggest that p60, but not p12 or p17, interacts with p260 residues 2157 to 2285, which includes Zinc-finger motifs (Fig. 1C), and that p12 and p17 interact with a motif or region between residues 1054 and 2157 of p260 (Fig. 1C). Both p260D860N (a DNA polymerase-dead-point mutant) and p260ΔCat did not interfere with formation of the xPol ε holoenzyme, because all four Pol ε subunits co-immunoprecipitated from cells expressing these p260 mutants. In cells expressing histidine-tagged p60 (H-p60), p12, and p17, Ni2+ -chelating beads only precipitated H-p60, indicating that H-p60 does not interact directly with p12 or p17, or both subunits (Fig. 3), although it was known that both subunits interact each other and form a 1:1 complex in insect cells (data not shown) as S. cerevisiae Dpb3p-Dpb4p complex [28].</p><!><p>p12, p17 and p60 of Xenopus Pol ε interact with the C-terminal region of p260. (A) Schematic representation of wild type (full)- and mutant (ΔC2157, ΔC1054, Δ860N, and ΔCat) forms of xPol ε p260. The conserved catalytic DNA polymerase domain and putative zinc finger domain of Pol ε are indicated. (B) FLAG-tagged p260 was co-expressed with p60, p17 and p12 in insect cells. Cell lysates were prepared and immunoprecipitated with anti-FLAG antibody and the precipitates were subjected to SDS-PAGE followed by immunoblotting with antibodies for each subunit. "Lysates" and "bound" indicate total protein and immunoprecipitated proteins, respectively. (C) Schematic representation of Xenopus Pol ε holoenzyme.</p><p>Interactions between histidine-tagged p260 (H-p260) or p60 (H-p60) and other subunits of Pol ε. Interactions between histidine-tagged p260 (H-p260) or p60 (H-p60) and other subunits of Pol ε were investigated using a pull down assay with Ni2+ -chelating beads and crude extracts prepared from insect cells expressing the indicated subunits of xPol ε. Cell lysates containing H-p260 or H-p60 (lane 1) and bound proteins (lane 2) were subjected to SDS-PAGE, followed by immunoblotting with the indicated antibodies. Beads without Ni2+ were also used as a control (lane 3).</p><!><p>Previous studies suggested that the amino-terminal portion of yeast Pol ε is dispensable for DNA replication, DNA repair, and viability. Because this portion of the enzyme includes all known DNA polymerase and exonuclease motifs, these results suggest that the DNA polymerase activity of Pol ε is dispensable for chromosomal DNA replication in yeast [15,16,27]. To investigate this possibility further, the xPol ε mutant complexes described in Figure 2 as well as partial holoenzyme complexes lacking specific subunits were purified from insect cells and used in an in vitro Xenopus chromosomal DNA replication system with Pol ε-depleted Xenopus egg extracts. The following xPol ε holoenzyme complexes were used: (a) wild type r-xPol ε holoenzyme, (b) Pol ε-DN containing p260D860N, (c) Pol ε ΔCat containing p260ΔCat, (d) p260p60 sub-complex of xPol ε, (e) p260-p12-p17 sub-complex of xPol ε, and (f) p260 (Fig. 2 and 3). The specific activity of each enzyme complex is summarized in Table 1. Although we did not measure the specific activity of p260-p60 and p260-p12-p17 sub-complexes, they were similarly purified as r-xPol ε holoenzyme and p260 and might be the same specific activity as that of p260 alone. Pol ε-DN and Pol ε ΔCat holoenzymes do not have any significant DNA polymerase activity as predicted, although a slight contaminating DNA polymerase activity could be detected (Table 1). This may be due to contamination of insect DNA polymerase activity. It should be noted here that recombinant xPol ε holoenzyme complexes (r-xPol ε) purified from insect cells had minor contaminants, and all enzyme preparations except Flag-tagged p260 included p60, p12, and p17 in amounts that were detected by immunoblotting.</p><!><p>The specific activity of the DNA polymerase</p><p>Purified xPol ε holoenzyme from insect cells. Wild type and mutant FLAG-tagged p260 was co-expressed with p60, p17 and p12 in insect cells and Pol ε complexes were purified by DEAE Sepharose and anti-FLAG antibody chromatography. Fractions were eluted from the antibody affinity column, pooled and subjected to SDS-PAGE followed by CBB staining (Left) and immunoblotting (Right). Native Xenopus Pol ε (native) holoenzyme was purified from Xenopus egg extracts as described previously [22]. Fractions shown are rPol ε, rDN Pol ε, rΔcat Pol ε, and rF260 (see text). rF260 is FLAG-tagged p260.</p><!><p>Figure 4 shows that the extent and rate of DNA synthesis were greatly reduced in Pol ε-depleted Xenopus extracts, and this defect was fully complemented by addition of purified native (n-xPol ε)(data not shown, and [22]) or wild type recombinant xPol ε (r-xPol ε). In contrast, addition of xPol ε ΔCat or xPol ε DN to Pol ε-depleted Xenopus extracts only partially (30–40%) complemented the replication defect and did not restore normal kinetics of the initiation of DNA replication (Fig. 4). Furthermore, neither p260, p260-p12-p17 nor p12-p17 complemented the defect in DNA synthesis in xPol ε-depleted Xenopus extracts. Of the partial holoenzyme complexes tested, only the p260-p60 sub-complex of xPol ε significantly complemented the defect (Fig. 4). These results clearly demonstrate that the DNA polymerase activity of xPol ε holoenzyme is required for normal, rapid and efficient chromosomal DNA replication in Xenopus egg extracts.</p><!><p>DNA replication activity in Pol ε-depleted Xenopus egg extracts. (A) The same number of wild type-, mutant or partial r-xPol ε complex molecule, which has been estimated based on the result of Fig. 2, was added to xPol ε-depleted egg extracts as indicated (see text for detailed description of mutants and partial complexes). DNA replication was initiated by the addition of sperm chromatin and the rate and extent of DNA synthesis was measured by neutral agarose gel electrophoresis followed by autoradiography [22]. The origin (well) is and DNA size markers are indicated on the right. (B) Radioactive material, which migrated slower than the 23-kb marker DNA (shown by an arrow in (A)), was considered to be fully replicated product and quantified by a scintillation counter.</p><!><p>Previous studies suggested that Cdc45p, Cut5p, and GINS are critical for loading Pol α and Pol ε onto DNA replication origins and for initiating chromosomal DNA replication in yeast and Xenopus egg extracts [2,22,24,29-31]. However, those studies did not show any direct interaction between these initiation proteins and Pol ε holoenzyme. Therefore, in this study, we tested this possibility by measuring physical interactions between r-xPol ε holoenzyme and xCdc45p, xCut5p, and xGINS. The experiments were performed by incubating r-xPol ε holoenzyme with these proteins and immunoprecipitating protein complexes with anti-FLAG antibody. Figure 5A shows that xGINS was co-immunoprecipitated with Pol ε holoenzyme from reactions containing r-xPol ε holoenzyme and recombinant xGINS [29]. Addition of xCdc45p, but not xCut5p [31], slightly disrupted the complex between r-xPol ε holoenzyme and xGINS (Fig 5C), and incubation of xCdc45, xCut5p, and xGINS in the absence of r-xPol ε holoenzyme resulted in formation of a heterotrimeric complex lacking xPol ε holoenzyme (Fig. 5B). xCdc45p also interacts directly with xPol ε holoenzyme in vitro (Fig. 5C), and the amount of this complex decreased slightly in the presence of xGINS, but not in the presence of xCut5p (Fig. 5C). These results suggest that the trimeric xCdc45/xCut5p/xGINS complex interacts with xPol ε holoenzyme, and this interaction may involve direct contacts with xCdc45p and xGINS but not with xCut5p (Fig. 5D).</p><!><p>Xenopus Pol ε holoenzyme interacts directly with xGINS, xCdc45p, and xCut5p in vitro. (A) Flag-tagged r-xPol ε holoenzyme was incubated with xGINS [29] for 1 h at 4°C and immunoprecipitated with anti-Flag antibody. The immunoprecipitates were analyzed by SDS-PAGE followed by Western blotting. IP; immunoprecipitates, SUP; supernatant. (B) Increasing concentrations of xCut5p were incubated with xGINS and Flag-tagged xCdc45 [30] or Flag-tagged BAP for 1 h at 4°C and immunoprecipitated as in (A). (C) r-xPol ε holoenzyme was pre-incubated with either Flag-tagged xGINS or Flag-tagged xCdc45p prior to addition of the indicated protein(s). Reactions were analyzed as in (A). (D) A model for the interaction between r-xPol ε and replication accessory proteins (xGINS, xCdc45, and xCut5).</p><!><p>Previous studies demonstrated a direct interaction between yeast GINS and yeast Pol ε holoenzyme and that this interaction stimulates the rate and processivity of DNA synthesis by Pol ε holoenzyme [32]. A similar result was obtained using r-xPol ε and r-xGINS [29]. As observed previously for yeast GINS, maximum stimulation by xGINS was obtained at a stoichimetry of 5–10 xGINS/xPol ε (Fig. 6). Under these conditions, however, xCdc45p or xCdc45p plus xCut5p did not stimulate the rate or extent of DNA synthesis by r-xPol ε holoenzyme (see Additional file 5).</p><!><p>xGINS stimulates DNA synthesis by xPol ε holoenzyme. (A) DNA synthesis reactions (10 μl) contained 200 fmol 32P-labeled 34-mer primer/65-mer template replication substrate [32], 15 fmol r-xPol ε holoenzyme and 45 fmol (×5), 150 fmol (×10), or 300 fmol (×20) xGINS as indicated. Reactions were incubated at 25°C for the indicated amount of time, terminated by addition of stop solution (5 μl), and analyzed by sequencing gel and autoradiography [32]. The 32P-labeled 65-mer is the reaction product and the 32P-labeled 34-mer is the primer.(B) The amount of the reaction products in (A) (65-mer) was quantified by Image analyzer (Fiji).</p><!><p>Previous genetic studies in yeast suggested that Pol ε plays an important role during chromosomal DNA replication [1,7-9]. However, because the amino-terminal portion of Pol ε, that is required for its DNA polymerase- and exonuclease activities, is dispensable for yeast DNA replication, repair, and viability [15,16,27], the role of Pol ε during DNA replication has remained obscure. This study explores this role using an in vitro Xenopus DNA replication system and wild type and mutant forms of r-xPol ε holoenzyme. Here we show that the DNA replication defect in xPol ε-depleted Xenopus egg extracts is readily corrected by native (n-xPol ε) (data not shown and [22]) or recombinant xPol ε (r-xPol ε) holoenzyme or the p260-p60 Pol ε sub-complex, but not by p260ΔCat holoenzyme, p260 DN, p260 or p260-p12-p17 (Fig. 4). Because the former enzymes are polymerase proficient, while p260ΔCat holoenzyme and p260 DN are polymerase-deficient, although these preparations contained a small amount of DNA polymerase activity, and the last two sub-complexes do not contain the second essential subunit of xPol ε holoenzyme (Table 1), these results clearly demonstrate that the DNA polymerase activity of Pol ε holoenzyme is required for chromosomal DNA replication in Xenopus egg extracts. Note that both p260ΔCat and p260 DN holoenzymes partially complements DNA replication defect of xPol ε-depleted egg extracts (Fig. 4). However, these DNA synthesis activities never reach to the levels of either mock-depleted-, n-xPol ε holoenzyme-, or r-xPol ε holoenzyme-supplemented egg extracts even after long time incubation (Fig. 4 and [22]), thus we conclude that those residual activity of DNA synthesis upon addition of catalytically dead polymerases is not significant to the key issue of this paper.</p><p>We do not know why n-xPol ε holoenzyme preparations always exhibit higher specific activity of DNA polymerase than that of r-xPol ε holoenzyme (Table 1), although both polymerase holoenzymes equally complement the defect of the Pol ε-depleted Xenopus egg extracts ([22] and Fig. 4). However, we noticed that the reconstituted r-xPol ε holoenzyme is much more volatile than n-xPol ε holoenzyme during purification (Shikata K and Sugino A, unpublished results). Thus, it is possible that r-xPol ε holoenzyme purified from insect cells would not be fully activated yet and it might be activated during incubation with xPol ε-depleted egg extracts by unknown mechanism(s) and function in the egg extracts as does n-xPol ε holoenzyme.</p><p>The previous studies showed that a yeast strain consisting of a deletion of the amino-terminal portion of Pol2p (pol2-16) is temperature-sensitive for its growth, has a defect in elongation of DNA replication, has a short cell senescence, has a shorting telomere length, and is synthetic lethal with temperature-sensitive cdc2 (pol δ) mutations and with the 3'-5' exonuclease minus Pol δ mutant pol3-01, suggesting that Pol ε is required primarily for maintenance of genome integrity and that the DNA polymerase activity of Pol ε might be substituted by the remaining polymerase(s), if the polymerase domains are completely missing [16-18]. However, the requirement of xPol ε holoenzyme for chromosomal DNA replication in Xenopus egg extracts is much more strict than that of yeasts and Pol εΔCat holoenzyme cannot restore DNA synthesis activity of Pol ε-depleted extracts to the levels of mock-depleted extracts (Fig. 4) and residual DNA synthesis observed in Pol ε-depleted extracts is not authentic chromosomal DNA replication, unlike yeast systems [15-18,27]. Therefore, we conclude that the DNA polymerase activity of Pol ε holoenzyme is strictly required for normal chromosomal DNA replication in higher eukaryotes, including Xenopus, but it may not be absolutely required for chromosomal DNA replication in S. cerevisiae and S. pombe, which have a relative small chromosomal DNA.</p><p>If the above analysis is correct, then it is important to determine whether Pol ε holoenzyme participates in leading or lagging strand DNA synthesis. Although the present study does not answer this question, previous studies are consistent with a role for Pol ε in leading strand DNA synthesis [23]. Furthermore, Cdc45p and GINS associate directly with Mcm2–7p, a DNA helicase that works at the replication fork, in yeast, Xenopus, and Drosophila [33-35], and xPol ε also associates directly with xGINS, xCdc45p, and xCut5p, as shown in this study. xGINS, like yeast GINS, also stimulates DNA synthesis catalyzed by xPol ε. Thus, it is very likely that the DNA polymerase activity of xPol ε holoenzyme, plus xCdc45p, xGINS and xMcm2–7p, perform a coordinated function at the replication fork in Xenopus egg extracts. We propose that this function is required for leading strand DNA synthesis [32], while lagging strand DNA synthesis in Xenopus may be carried out by Pol δ, PCNA, RF-C and Pol α-primase as well as Fen1p, Dna2p, RPA, DNA ligase and RNase H [4,5,36].</p><!><p>This work shows that the DNA polymerase activity proficient xPol ε holoenzyme complements DNA replication defect of the Pol ε-depleted Xenopus egg extracts. However, neither the DNA polymerase-domain-deleted xPol ε, DNA polymerase-dead-xPol ε, the catalytic subunit of Pol ε nor other subunits of Pol ε without the catalytic subunit complements the defect at all. Furthermore, we show that xPol ε holoenzyme directly interacts with xCdc45, xCut5, and xGINS, which are required for the initiation of chromosomal DNA replication in Xenopus egg extracts. These results are the first, direct and biochemical evidence that the DNA polymerase activity of xPol ε holoenzyme is absolutely required for chromosomal DNA replication in higher eukaryotes, unlike in yeasts.</p><!><p>The cDNA for the p260 subunit of Xenopus laevis Pol ε (GenBank accession no. AB259046) was isolated by 5'-RACE using Xenopus laevis ovary mRNA as templates and oligonucleotides primers synthesized based on the nucleotide sequence information of a partial cDNA for the p260 subunit of Xenopus Pol ε [24]. Both strands of its cDNA insert were sequenced with the use of an Applied Biosystems Prism dye terminator cycle sequencing kit and a DNA sequencer (ABI377). The initiation methionine was postulated on the basis of a comparison with the amino acid sequence of HeLa Pol ε p260 (gi:62198237). For cloning of the p17 subunit of XPol ε, the IMAGE cDNA clone 4783571(5') (GenBank ACC# BI349483) was obtained and sequenced. This clone did not contain a complete cDNA insert, so the 3' portion of p17 cDNA was cloned by 3' RACE using Xenopus mRNA prepared from Xenopus ovary (GenBank ACC# AB259047). For cloning of the p12 subunit of XPol ε, the cDNA clone PBX0037B02(5') (GenBank ACC# AW635703) was obtained and sequenced (GenBank ACC# AB259048).</p><!><p>Xenopus ovary mRNA was prepared as published [37], and was used for cloning of the 3'-untranslated region by using 3'-Full RACE Core Set (TAKARA, Japan). The PCR products were cloned into pBR322-based plasmid DNA and sequenced. The 5'-terminal sequence was obtained by 5'-Full RACE Core Set (TAKARA, Japan) using Xenopus ovary mRNA as templates.</p><!><p>Rabbit anti-Xenopus Pol ε p60 antibodies were affinity-purified as published [22] and used for making antigen-immobilized Affi-Gel 15 (Bio-Rad). The purified p60 antibodies or whole rabbit IgG (Pierce) as a control was crosslinked to Affi-Prep Protein A matrix (Bio-Rad) (1 mg of IgG per ml of matrix) and used for immunoprecipitation and immunodepletion experiments. Rabbit anti-Xenopus Pol ε p12 and p17 antibodies were raised by using p12 and p17, which were expressed in E. coli and purified, as antigens (K. Shikata, unpublished).</p><!><p>Xenopus laevis egg extracts (low-speed supernatant) were prepared as described previously [22]. Immunodepletion was performed by mixing egg extracts three times with the antibody-crosslinked matrix at 4°C. DNA replication with membrane-removed sperm nuclei (2,000 sperm heads per ml of extract) was carried out at 23°C in the presence of [α-32P]dATP as described [22]. The reaction products were purified by RNase A digestion, proteinase K digestion, and phenol-chloroform extraction followed by ethanol precipitation and then separated by 0.8% agarose gel electrophoresis under neutral (Tris/borate/EDTA buffer) condition as described previously [22]. After electrophoresis, the gel was fixed, dried, and subjected to autoradiography. The quantification of replication products was carried out with a Fuji image analyzer (BAS1500).</p><!><p>For expression of proteins, 150 × 106 log phase sf21 insect cells were grown in suspension tissue culture flasks. The cells were infected with viral supernatant at a multiplicity of infection of 10 for p260 (a catalytic subunit of xPol ε complex), 5 for p60 (the second subunit of xPol ε complex), 5 for p12 (the third subunit of XPol ε complex), and 5 for p17 (the fourth subunit of xPol ε complex). After a 2-day incubation at 27 °C, cells were harvested, washed once with cold 1 × Tris-buffered saline, flash frozen in liquid N2, and stored at -80 °C. The frozen cells were thawed once on ice and then resuspended in 5 ml of buffer A (50 mM Tris, 150 mM NaCl, 5 mM EDTA, 20% glycerol, pH 7.5) containing 20 μg/ml leupeptin. After lysis, cells were kept on ice for 15 min and centrifuged at 12,000 rpm in a microcentrifuge for 10 min, and supernatant was recovered. Pol ε complex was purified from insect cell extracts with DEAE sepharose column, followed by anti-FLAG antibody column. Native Xenopus Pol ε (n-xPol ε) was purified from Xenopus egg extract by 4 sequential column chromatographies as published [22]. Throughout the purification, column fractions were assayed for DNA polymerase activity with the use of [α-32P]dTTP and oligo(dT)10/poly(dA)400 (1:19; 0.04 mM nucleotides) as a primer/template and were analyzed by Western blotting. One unit of Pol ε supported the incorporation of 1 nmol of dTMP under the conditions described above.</p><!><p>Immunodepletion of xPol ε was performed by mixing Xenopus egg extracts three times with the xPol ε-p60-antibody-crosslinked matrix [22] at 4°C as published [22,23], resulting in successful removal of more than 99% of xPol ε holoenzyme including the catalytic subunit p260 as prviously [22]. Various amounts of the n-xPol ε obtained from Xenopus egg extracts or r-xPol ε holoenzyme purified from insect cells and the buffer were added back to Pol ε- or mock-depleted egg extracts as published before [22]. Then DNA replication reaction was initiated by the addition of membrane-removed sperm nuclei (2,000 sperm heads per μl of extract. After incubation at 25°C for various times, aliquots were withdrawn and analyzed by neutral agarose gel electrophoresis followed by autoradiography as published before [22,23].</p><!><p>6 × His-tagged Cut5p, 6 × Flag-tagged Cut5p, 6 × Flag-tagged Cdc45p, 6 × Flag-tagged Psf2p containing GINS were expressed and purified from insect cells as described previously [24,27,31].</p><!><p>KS carried out the molecular biological and genetic studies, participated in the sequence alignment and drafted the manuscript. TSM carried out the purification of Xenopus proteins from insect cells and immunoprecipitation assays. YO participated in preparation of Xenopus egg extracts. SW participated in the design of the study and discussion. AS conceived of the study, participated in its design and coordination, performed some experiments, and helped to draft the manuscript. All authors read and approved the final manuscript.</p><!><p>Cloning strategy of Xenopus Pol ε p260 subunit cDNA by 5' RACE. The 6,855 bp open reading frame of Xenopus Pol ε p260 is shown as a white arrow (top). Red bar shows the region, where Mimura et al. previously cloned and sequenced (4,884 bp)[24]. The yellow (1,011 bp) and green (960 bp) bars represent the regions obtained by the first and second RACE, respectively. The black arrows represent primers used in RACE. E and S represent EcoRI and SphI sites, respectively.</p><!><p>Click here for file</p><!><p>Deduced amino acid sequences of Xenopus and human Pol ε p260. Deduced amino acid sequences of Xenopus and human Pol ε p260 [38] were aligned using a ClustalW program. The identical amino acids between Xenopus and human Pol ε p260 are boxed. The amino acid sequence of Xenopus p260 is 81% identical to that of human p260. Shaded, and shaded- and blacked squired amino acids represent similar and identical amino acid, respectively. Red arrow indicates the portion of cDNA previously cloned [24].</p><!><p>Click here for file</p><!><p>Structural similarity between Xenopus and S. cerevisiae Pol ε catalytic subunit. In the figure, DNA polymerase catalytic domains (shown by red box), the 3'-5' exonuclease domains (shown by yellow box), zinc finger domain (shown by green box), and putative nuclear localization signals (shown by blue boxes), which are missing in S. cerevisiae Pol ε gene (POL2)[6], are shown. The numbers shown in the middle of two genes are the homology, suggesting that the catalytic domain is well conserved throughout evolution.</p><!><p>Click here for file</p><!><p>Cloning of Xenopus Pol ε p17 and p12 subunits. (A) Amino acid sequence comparison between human Pol ε p12 and its Xenopus homologue. Xenopus Pol ε p12 consists of 116 amino acids (predicted molecular weight is about 12 kDa) and the amino acid sequence exhibits 60% identity to that of human p12 [26]. (B) Amino acid sequence comparison between human Pol ε p17 and its Xenopus homologue. Xenopus Pol ε p17 consists of 147 amino acids (about 17 kDa protein) and its amino acid sequence has 84% identity to that of human p17 [26]. The full-length cDNA for Xenopus Pol ε p17 was obtained by 3' RACE using the sequence of the Xenopus EST clone that encodes the N-terminal region of p17. Shaded amino acid indicates identical amino acid residue.</p><!><p>Click here for file</p><!><p>xGINS stimulates DNA synthesis catalyzed by xPol ε holoenzyme. DNA synthesis reactions (10 μl) contained 200 fmol 32P-labeled 34-mer primer/65-mer template replication substrate [32], 15 fmol r-xPol ε holoenzyme and 150 fmol (x10) xGINS, xCut5, xCdc45, or xGINS/xCut5/xCdc45. Reactions were incubated at 25°C for the indicated amount of time, terminated by addition of stop solution (5 μl), and analyzed by sequencing gel and autoradiography [32]. The 32P-labeled 65-mer (the reaction product) was quantified by scintillation counter.</p><!><p>Click here for file</p><!><p>This work was supported partly by grants from the Ministry of Education, Science, Technology, Sports and Culture of Japan to AS.</p>

PubMed Open Access

Modified Ti-MWW Zeolite as a Highly Efficient Catalyst for the Cyclopentene Epoxidation Reaction

The liquid-phase epoxidation of cyclopentene (CPE) was performed in the Ti-zeolite/H2O2 catalytic system for the clean synthesis of cyclopentene oxide. Among all the Ti-zeolites (Ti-Beta, Ti-MOR, Ti-MCM-68, TS-1, TS-2, and Ti-MWW) investigated in the present study, Ti-MWW provided relatively lower CPE conversion of 13% due to the diffusion constrains but a higher CPO selectivity of 99.5%. The catalytic performance of Ti-MWW was significantly enhanced by piperidine (PI) treatment, with the CPE conversion and CPO selectivity increased to 97.8 and 99.9%, respectively. The structural rearrangement upon PI treatment converted the 3-dimensional (3D) MWW structure to a 2D lamellar one, which enlarged the interlayer space and greatly alleviated the diffusion constrains of cyclic cyclopentene. Furthermore, the newly constructed “open site” six-coordinated Ti active sites with PI as the ligand exhibited higher catalytic activity. The two factors contributed to more significant enhancement of the activity upon PI-assisted structural arrangement compared to the cases in linear alkenes.

modified_ti-mww_zeolite_as_a_highly_efficient_catalyst_for_the_cyclopentene_epoxidation_reaction

Introduction<!>Preparation of Ti-MWW<!>Structural Rearrangement of Ti-MWW<!>Synthesis of Different Titanosilicates<!>Characterization Methods<!>Catalytic Experiments<!>Effect of the Topologies of the Titanosilicates<!><!>Influence of the Nature of Solvents<!><!>Influence of the Nature of Solvents<!>A comparison of the Catalytic Performance Over a Series of Ti-MWW<!><!>A comparison of the Catalytic Performance Over a Series of Ti-MWW<!><!>A comparison of the Catalytic Performance Over a Series of Ti-MWW<!><!>A comparison of the Catalytic Performance Over a Series of Ti-MWW<!><!>A comparison of the Catalytic Performance Over a Series of Ti-MWW<!><!>Characterization of the Microenvironment of Ti Active Sites<!><!>Characterization of the Microenvironment of Ti Active Sites<!><!>Characterization of the Microenvironment of Ti Active Sites<!>Effect of the Catalyst Amount on Cyclopentene Epoxidation<!><!>Effect of the Reaction Time on Cyclopentene Epoxidation<!><!>Effect of the Reaction Temperature on Cyclopentene Epoxidation<!><!>Effect of the Reaction Temperature on Cyclopentene Epoxidation<!>Conclusions<!>Data Availability Statement<!>Author Contributions<!>Conflict of Interest

<p>Epoxy compounds, as important organic intermediates and chemical raw materials, can easily undergo ring-opening reactions with water, alcohols, amines, ammonia, or carboxylic acids to form a series of fine and bulk chemicals in the fields of petrochemical industry, polymer synthesis, and pharmaceuticals (Imamura et al., 1989; Yuan et al., 2011; Sharma et al., 2014; Jiang et al., 2019). The epoxidation of olefins is a typical way to produce epoxides. With the rapid development of the petrochemical industry, a large amount of cyclopentene (CPE) can be obtained from the C5 fraction of petroleum cracking, so the development of its downstream products has aroused increasing interests. In recent decades, many researchers focused on the catalytic oxidation reactions of cyclopentene, producing the corresponding alcohols, aldehydes, ketones, and acids (Xin et al., 2000; Jian et al., 2001; Dubkov et al., 2002; Guo et al., 2003; Yang et al., 2005; Yan and Xu, 2010). Moreover, several studies on cyclopentene epoxidation have also been reported (Hulea et al., 1998; Kluson et al., 2005). The main product of cyclopentene epoxidation is 1,2-epoxycyclopentane (CPO), which is widely used as the intermediate in medicine and organic synthesis (Milen et al., 2000; Huang et al., 2015; Seol et al., 2020).</p><p>Cyclopentene has been reported to be epoxidized by oxygen, hydrogen peroxide (H2O2), or organic peroxide, producing 1,2-epoxycyclopentane (Pramanik et al., 2007; Aleksandra, 2008; Maiti et al., 2008). However, the process using oxygen as the oxidant generally requires the addition of isobutyraldehyde and other co-oxidants to obtain a high yield (Qi et al., 2005; Mekrattanechai et al., 2018). In addition, the reaction system is too complex and difficult to control. The usage of organic peroxides could achieve high CPO selectivity, but the high price of organic peroxides would be a great issue. Hydrogen peroxide, with water as the sole by-product, serves as an environmentally friendly oxidant. However, H2O2 is a mild oxidant and thus needs appropriate catalysts for the CPE epoxidation reaction. Zhu et al. (2010) reported a three-phase transfer catalyst of phosphotungstic acid quaternary ammonium salt grafted by polystyrene-divinylbenzene to catalyze the CPE epoxidation with KCl as a co-catalyst, under solvent-free conditions, achieving a CPO yield of 96%. However, the cost of a phase transfer catalyst is relatively high. Yin et al. (2007) used nano-silver as the catalyst, giving an extremely low CPE conversion of 1.7–3.2%, which was not suitable for industrial production.</p><p>The titanosilicates are effective catalysts in liquid-phase epoxidation reactions, using H2O2 as the oxidant. Also, the Ti-zeolite/H2O2 catalytic system exhibited significant advantages, such as mild reaction conditions, high conversion, good selectivity, and environmental friendliness. The successful synthesis and application of TS-1 in the selective oxidation reactions are an important milestone in the field of zeolite catalysis after the industrial application of Y and ZSM-5 zeolite in the oil refining processes (Taramasso et al., 1983). As the first-generation Ti-zeolite, TS-1 has been extensively studied and widely used in various catalytic oxidation reactions, including olefin epoxidation, aromatic hydroxylation, aldehyde and ketone ammoxidation, and thiophene, alcohol, and amine oxidation, etc. (Spinace et al., 1995; Laha and Kumar, 2002; Kong et al., 2004). Afterward, numerous titanosilicates with different structural topologies have been reported such as microporous Ti-Beta (Wang et al., 2019), Ti-MWW (Wu et al., 2001), and mesoporous Ti-MCM-41 (Blasco et al., 1995). Very recently, extra-large pore Ti-zeolites with pores larger than the 12-member ring (MR), including Ti-ECNU-9 (Yang et al., 2018) and Ti-UTL (Liu et al., 2017; Shi et al., 2019), have been synthesized via post-modification strategy on layered zeolites and germanosilicates, respectively, which showed absolute advantages in processing bulky molecules.</p><p>The "five-membered ring" reaction mechanism is generally accepted in the Ti-zeolite/H2O2 catalytic system (Clerici and Ingallina, 1993). The tetrahedrally coordinated TiO4 species first interact with H2O2 to form the active intermediate species of Ti–Oα − Oβ − Hend, while the protic solvent (alcohol or water) in the reaction system coordinates with the titanium atom and forms a hydrogen bond with Oβ, thereby forming a five-membered ring intermediate. In addition, the hydrogen bonds can also be formed between Ti–Oα − Oβ − Hend species and the neighboring Si–OH to stabilize Ti–Oα − Oβ − Hend species (Ratnasamy and Srinivas, 2004). The Oα atom, directly connected to titanium atoms, has a stronger electrophilicity than Oβ. Thus, it can easily attack the double bond in the olefin molecules to transfer the active oxygen effectively and accomplish the epoxidation of olefins. Bearing the reaction mechanism in mind, the researchers have focused on modifying the microenvironment of Ti active sites with the purpose of improving the catalytic performance. The F atoms with strong electronegativity were introduced into the frameworks of Ti-MWW (Fang et al., 2017) and Ti-MOR zeolite (Yang et al., 2014), forming SiO3/2F groups, which imposed a strong electron pulling effect and improved the electropositivity of Ti active sites, thereby favoring the Oα transfer step and enhancing the catalytic performance. Also, numerous studies have shown that framework Ti species with a higher coordination number exhibited better catalytic performance in the epoxidation reactions. Xu et al. (2020) reported the one-step rapid synthesis of TS-1 with mononuclear TiO6 species affording a high turnover number value of 272 in the 1-hexene epoxidation reaction. Wu et al. (2016) illustrated that the mononuclear "TiO6" species showed the catalytic activity 2–3 times that of the "TiO4" species in TS-1 for the epoxidation of alkenes.</p><p>Among all the titanosilicates, Ti-MWW, with two sets of independent 10-MR pore channels, is fabricated from a layered precursor via interlayer condensation. One set is the sinusoidal 10-MR pore channel (0.4 × 0.51 nm) running within layers, and the other set is the 10-MR pore (0.40 × 0.55 nm) in the interlayer space (Wu et al., 2001). Although with relatively narrow pore opening, the unique lamellar structure of MWW-type titanosilicate provides the property of structural modification, such as delamination (Wu et al., 2004), interlayer expansion (Satoshi et al., 2011), and pillaring (Hao et al., 2016), to expose a larger surface area or enlarge the interlayer pore entrance. Moreover, the structural modifiable nature can also assist the modification of the microenvironment of Ti active sites by piperidine (PI) treatment. The transformation of a 3D structure to a 2D one occurred in the PI treatment and allowed the coordination of PI molecules to Ti atoms, forming the "open site" hexa-coordinated Ti active sites, which greatly improved the catalytic activity in the alkene epoxidation reactions (Xu et al., 2015).</p><p>Herein, with the purpose to find an appropriate catalyst for the CPE epoxidation reaction, we have investigated several Ti-zeolites, including Ti-Beta, Ti-MOR, Ti-MCM-68, TS-1, TS-2, and Ti-MWW, among which Ti-MWW showed relatively lower CPE conversion but higher CPO selectivity with acetonitrile (MeCN) as the solvent. Then, the microenvironment modification of Ti active sites, realized by PI-assisted structural rearrangement, dramatically enhanced the catalytic activity of Ti-MWW with H2O2 as the oxidant. Although comparable high catalytic activity has also been obtained by delaminated Ti-MWW (Wu et al., 2004), the condition for preparing the PI-modified Ti-MWW catalyst was milder and the introduction of PI molecules not only transformed the 3D structure to a more open 2D one but also constructed more active open-site Ti species. Additionally, the reaction parameters were also carefully investigated for the Ti-MWW catalyzed CPE epoxidation reaction, indicating it is a potential industrial catalyst for 1,2-epoxycyclopentane production.</p><!><p>Ti-MWW was hydrothermally synthesized with boric acid as the crystallization agent and piperidine (PI) as the organic structural directing agent (OSDA). The synthetic gel with a molar composition of 1.0 SiO2: 0.05 TiO2: 0.67 B2O3: 1.4 PI: 19 H2O was hydrothermally crystallized at 443 K for 7 days under a rotation rate of 10 rpm. The obtained sample was filtered, washed with deionized water, and dried at 373 K overnight. The obtained two-dimensional Ti-MWW lamellar precursor was denoted as Ti-MWW-AM. Then, Ti-MWW-AM was refluxed in 2 M HNO3 aqueous solution at 413 K for 4 h with the liquid/solid mass ratio of 30 to remove partial OSDA molecules, most of the framework B atoms, and extra-framework Ti species. The acid-treated product was filtered, washed with deionized water, and dried at 373 K overnight, denoted as Ti-MWW-AT. Subsequently, Ti-MWW-AT was calcined at 823 K for 6 h to produce the 3D Ti-MWW.</p><!><p>The structural rearrangement of Ti-MWW was carried out in the PI aqueous solution with a composition of 1.0 SiO2: 1.0 PI: 10 H2O at 443 K for 24 h dynamically. The obtained 2D Ti-MWW containing PI in the framework was filtered, washed, and dried at 373 K overnight, denoted as R-Ti-MWW-PI. As a reference, R-Ti-MWW-PI was further calcined at 823 K for 6 h to remove PI molecules, denoted as R-Ti-MWW-PI-cal.</p><!><p>For control experiment, other titanosilicate catalysts, including Ti-Beta (Wang et al., 2019), Ti-MOR (Yang et al., 2014), Ti-MCM-68 (Kubota et al., 2008), TS-1 (Taramasso et al., 1983), and TS-2 (Reddy and Kumar, 1991) were prepared strictly according to the methods reported in the literatures.</p><!><p>The X-ray diffraction (XRD) patterns were collected on a Rigaku Ultima IV diffractometer using Ni-filtered CuKα radiation (λ = 0.1541 nm). The voltage and current were 35 kV and 25 mA, respectively. The amount of Si and Ti was determined by inductively coupled plasma-atomic emission spectrometry (ICP-AES) on a Thermo IRIS Intrepid II XSP atomic emission spectrometer. The UV-Vis spectra were collected on a Shimadzu UV-2700 spectrophotometer by using BaSO4 as a reference. The FT-IR spectra were measured using the self-supported wafer by a Nicolet Nexus 670 FT-IR spectrometer with a resolution of 2 cm−1. The spectra in the framework vibration region (500–1,300 cm−1) were measured using KBr pellet technology. In order to eliminate the influence of absorbed water, all the samples were evacuated at 723 K for 3 h before measurement. Thermogravimetric (TG) analysis was carried out in a Netzsch Sta 4049 F3 apparatus in air with a heating rate of 10 K min−1 in the temperature range of 473–1,073 K. The solid-state 29Si MAS NMR spectra were recorded on a VARIAN VNMRS-400 MB NMR spectrometer using a 7.5-mm T3HX probe and single-pulse method at a frequency of 100.54 MHz and spinning rate of 3 KHz. [(CH3)3SiO]8SiO12 was used as the chemical shift reference. The surface and pore volume of the titanosilicates were determined by N2 physical sorption isotherms at 77 K using a BEL SORP instrument after degassing in vacuum at 473 K for 3 h. X-ray photoelectron spectroscopy (XPS) was measured using the Axis Ultra Imaging Photoelectron Spectrometer (Kratos Analytical Ltd.).</p><!><p>The liquid-phase cyclopentene epoxidation reaction was performed in a glass reaction tube equipped with a condenser tube. In a typical run, 50 mg of catalyst, 10 mmol of cyclopentene, 10 mL of solvent, 10 mmol of H2O2 (30 wt.%), or tert-butyl hydroperoxide (70 wt.%, TBHP) was placed in the reaction tube and stirred at 333 K for 2 h. After reaction, the mixture was centrifuged to separate the spent catalyst. The generated products were identified by a GC-MS (Agilent 6890 Series GC System, 5937 network mass selective detector). The amount of the remaining substrates and the products was analyzed by a gas chromatograph (Shimadzu 2014, FID detector) equipped with an Rtx-Wax capillary column. The residual amount of H2O2 was determined by the titration method with 0.05 M Ce (SO4)2 aqueous solution.</p><!><p>The XRD patterns of six titanosilicates with the topologies of MWW, *BEA, MOR, MSE, MFI, and MEL, respectively, were displayed in Supplementary Figure 1, showing high crystallinity without any impurity. As shown in SEM images (Supplementary Figure 2), Ti-MWW possessed unique thin platelet morphology with the thickness of ~50 nm, which was quite different from Ti-Beta (50 nm), Ti-MOR (200–500 nm), Ti-MCM-68 (50–150 nm), TS-1 (200 nm), and TS-2 (50–100 nm). Moreover, the coordination states of Ti species were investigated by UV-Vis in Figure 1, indicating that Ti species were mainly tetrahedrally coordinated in the framework for all the titanosilicates. In order to select a suitable catalyst for the cyclopentene epoxidation process, the catalytic performance of the above titanosilicates was firstly investigated under the same reaction conditions (Table 1). The six titanosilicates showed different CPE conversions, with the order of Ti-MCM-68 > TS-1 > TS-2 > Ti-MWW > Ti-Beta > Ti-MOR. Ti-MCM-68 displayed the highest CPE conversion of 29.7%, while the least active Ti-MOR only converted 0.4% of CPE. TS-1 showed a slightly lower conversion than that of Ti-MCM-68, but the CPO selectivity was only 94.3% with considerable amount of 1,2-cyclopentanediol (CPD) as the by-product, indicating the easy occurrence of ring-opening reactions. Besides, Ti-Beta with 3D 12-MR pores showed a CPE conversion of 10.1% only higher than Ti-MOR. Although Ti-MWW exhibited moderate CPE conversion, the CPO selectivity was even higher than that of Ti-MCM-68. Additionally, cyclopent-2-enol (CPEL) and cyclopent-2-enone (CPEE) could also be examined in all the six titanosilicates. Considering that these titanosilicates contained various Ti contents, the specific activity in terms of TON value was also compared. Ti-MCM-68 showed the highest TON value of 311, followed by TS-1 and TS-2. Ti-MWW and Ti-Beta were inferior to them, and Ti-MOR showed the lowest TON value of 3. In fact, Ti-MWW has been reported previously to exhibit comparable activity to Ti-MCM-68, higher than TS-1, in the epoxidation of linear alkenes (Xu et al., 2020a). However, in the case of cyclic CPE molecules, they suffered severe diffusion constrains over the Ti-MWW catalyst, with relative narrower 10-MR pores than TS-1 and Ti-MCM-68, thus showing lower catalytic activity.</p><!><p>UV-visible diffuse reflectance spectra of Ti-MWW (a), Ti-Beta (b), Ti-MOR (c), Ti-MCM-68 (d), TS-1 (e), and TS-2 (f).</p><p>A comparison of the catalytic performance of various titanosilicates in the cyclopentene epoxidation reaction with MeCN as the solventa.</p><p>Reaction conditions: catalyst, 50 mg; cyclopentene, 10 mmol; H2O2 (30 wt.%), 10 mmol; MeCN, 10 mL; temp., 333 K; time, 2 h. TON in mol (mol Ti−1).</p><p>Molar ratio determined by ICP analysis.</p><p>CPE, cyclopentene; CPO, cyclopentene oxide; CPD, 1, 2-cyclopentanediol; CPEL, cyclopent-2-enol; CPEE, cyclopent-2-enone.</p><!><p>It is well-known that the solvent plays a very important role in the catalytic performance of epoxidation (Jan et al., 1997). The solvent effect on the Ti-zeolite/H2O2 system is comprehensive because it is related to various factors such as the protonicity of the solvent, the hydrophilicity/hydrophobicity of the titanosilicates, and the solubility of the substrates. Ti-MCM-68, TS-1, TS-2, and Ti-MWW, with relatively higher CPE conversion, were further investigated in various solvents, including MeCN, H2O, methanol (MeOH), ethanol (EtOH), isopropanol (i-PrOH), tert-butanol (t-BuOH), and acetone (Figure 2). In all the solvents, Ti-MWW exhibited extremely high CPO selectivity of >98.6% except H2O, indicating that CPO was very stable and prone to hydrolyze to CPD via the ring-opening side reaction only in the solvent of H2O (Figure 2A). The transformation of the 2D lamellar MWW precursor to the 3D structure via calcination would inevitably induce structural defects due to the imperfect interlayer condensation. The protic solvent molecules would easily adsorb in the pore channels of the 3D MWW framework and hindered the diffusion of substrate molecules. Thus, the aprotic solvent of MeCN, acetone, and the protic alcohol solvent with longer alkyl line (i.e., t-BuOH) showed higher activity. Among all the solvents, MeCN gave the highest selectivity of 99.5% compared to other alcohols (MeOH, EtOH, i-PrOH, and t-BuOH), which would promote the solvolysis of CPO to produce corresponding cyclopentanol ethers (2-methoxycyclopentanol, 2-ethoxycyclopentanol, 2-isopropoxycyclopentanol, and 2-(tert-butoxy)cyclopentanol) (Supplementary Table 1).</p><!><p>The catalytic performance of Ti-MWW (A), TS-1 (B), TS-2 (C), and Ti-MCM-68 (D) in CPE epoxidation reaction with various solvents. Reaction conditions: catalyst, 50 mg; cyclopentene, 10 mmol, H2O2 (30 wt.%), 10 mmol; solvent, 10 mL; temp., 333 K; time, 2 h.</p><!><p>Unlike Ti-MWW, TS-1, and TS-2, with less defect sites, exhibited the highest CPE conversion of 43 and 23.2%, respectively, when using MeOH as the solvent. In the solvent of t-BuOH, TS-1 and TS-2 both exhibited high CPO selectivity of 95.6 and 98.6%, respectively. On the one hand, the relatively larger molecular size of t-BuOH in the pore channels may restrict the ring-opening side reactions because of a narrowed space. On the other hand, the much lower CPE conversion may also contribute to the higher selectivity. The undesired product of diols was also detected in aprotic solvents, which may be caused by the water formed in the epoxidation reaction (Supplementary Tables 2, 3).</p><p>In the case of Ti-MCM-68, the highest CPO selectivity of 98.9% was obtained in the solvent of MeCN due to the presence of defect sites in the structure. Although with similar solvent preference as Ti-MWW, the hydration of CPO to the by-product CPD in the solvent of H2O and MeOH over Ti-MCM-68 was more prominent than that over Ti-MWW, with the CPD selectivity of >90.9%, probably due to the residual Al-related active sites in the structure of Ti-MCM-68 catalyst (Supplementary Table 4).</p><!><p>Although Ti-MWW was not the most active one in the CPE epoxidation reaction among all the investigated Ti-zeolites, the selectivity was extremely high. Moreover, considering the possibility of modifying Ti-MWW with respect to both the structure and microenvironment of Ti active sites, Ti-MWW was further studied. The PI-assisted arrangement has been reported to be an effective way to enhance the catalytic performance of Ti-MWW zeolites in the epoxidation reactions of alkenes (Wu et al., 2016). Thus, in the present case of cyclopentene, PI-assisted structural modification was also performed. As shown in Table 2, with comparable Si/Ti ratio, the CPE conversion was remarkably enhanced from 13.0% for Ti-MWW to 97.8% for R-Ti-MWW-PI, with the CPO selectivity increased from 99.5 to 99.9% (Table 2, Nos. 1 and 2). In fact, the enhancement of the catalytic performance in CPE epoxidation was more significant compared to other alkene epoxidation reactions (Xu et al., 2015), probably because the cyclic CPE molecule encountered more severe diffusion constrains than other reported linear alkenes. The 3D Ti-MWW was transformed to 2D lamellar MWW structure upon the PI-assisted structural arrangement with the PI molecules intercalated into the interlayer space as well as the intralayer 10-MR pores, which enlarged the interlayer space compared to the original 10-MR pore channels and released the diffusion constrains, in spite the presence of PI molecules may also hinder the diffusion of substrates to some extent. Once the R-Ti-MWW-PI was calcined to remove the PI molecules and interlayer 10-MR pores were formed, the CPE conversion was decreased dramatically to 15.1%, which was slightly higher than that of the 3D Ti-MWW catalyst, while the CPO selectivity was decreased to 94.4% (Table 2, No. 3). As has been reported before in the case of linear alkenes (Xu et al., 2015), the calcined form of the PI-assisted MWW catalyst would show a much higher catalytic activity than the pristine 3D MWW structure because more "open-site" Ti species with H2O as the ligand formed in the structural reconstruction process and subsequent calcination. However, in the case of cyclic CPE molecules, the severe diffusion constraints weakened the benefit from the modified microenvironment of Ti active sites.</p><!><p>The catalytic performance of Ti-MWW related catalysts in the cyclopentene epoxidation reactiona.</p><p>Reaction conditions: catalyst, 50 mg; cyclopentene, 10 mmol; H2O2 (30 wt.%), 10 mmol; MeCN, 10 mL; temp., 333 K; time, 2 h. TON in mol (mol Ti−1).</p><p>Molar ratio determined by ICP analysis.</p><p>Determined by CHN analysis.</p><p>CPE, cyclopentene; CPO, cyclopentene oxide.</p><!><p>In the preparation of a highly active R-Ti-MWW-PI catalyst, the removal of PI molecules in the as-made Ti-MWW-AM structure via the successive acid treatment and calcination and then the reinsertion of PI molecules back into the MWW structure caused a waste of PI molecules and was uneconomic. Since the acid treatment in 2 M HNO3 aqueous solution could remove most of B atoms and the extra framework Ti species together with only part of the occluded OSDA molecules and the structure was still in 2D type (Wu et al., 2001), the acid-treated sample Ti-MWW-AT may show a similar catalytic behavior as that of R-Ti-MWW-PI. Before verifying this assumption, the structure, the amount of PI molecules, the porosity, and the state of Ti species in the framework were analyzed for all the Ti-MWW-related catalysts.</p><p>As shown in Figure 3, the XRD patterns showed that all of these Ti-MWW-related catalysts possessed the typical MWW topology. Ti-MWW-AM showed the characteristic layer-related 001 and 002 diffractions in the 2θ range of 3–7°, indicative of its 2D lamellar structure. After the acid treatment, the intensity of these two layer-related diffraction peaks decreased, because the partial OSDA removal disturbed the ordered layer-stacking in the pristine Ti-MWW-AM material. In spite of this, the Ti-MWW-AT still maintained the 2D structure. After further calcination, both of the 001 and 002 diffraction peaks disappeared, forming the 3D Ti-MWW structure. Upon the PI-assisted structural rearrangement, the layered-related 001 and 002 diffraction peaks were recovered for the R-Ti-MWW-PI material, due to structural transformation of the 3D to 2D MWW structure through the reinsertion of PI molecules into the framework. By removing the PI molecules via further calcination, the 2D structure was converted back into the 3D MWW structure, with the characteristic layer-related 001 and 002 peaks disappearing again.</p><!><p>XRD patterns of Ti-MWW-AM (a), Ti-MWW-AT (b), Ti-MWW (c), R-Ti-MWW-PI (d), and R-Ti-MWW-PI-cal (e).</p><!><p>The amounts of PI molecules occluded in the Ti-MWW-related structures were investigated by TG analysis, and the results are displayed in Figure 4. All the three PI-containing Ti-MWW catalysts, including Ti-MWW-AM, Ti-MWW-AT, and R-Ti-MWW-PI, showed three weight loss stages in the temperature range of 25–200°C, 200–350°C, and 350–800°C, attributed to the loss of physically absorbed water, the PI molecules occluded in the interlayer space, and the PI molecules located in the intralayer 10-MR pores, respectively. Meanwhile, a small part of weight loss at high temperatures could also include water from condensation of hydroxyl groups. The amount of the interlayer and intralayer PI molecules in Ti-MWW-AM material was 9.4 and 8.2%, respectively (Figure 4A). After the acid treatment, 65.9% of the interlayer PI molecules and 60.9% of the intralayer ones were extracted (Figure 4B). In the case of R-Ti-MWW-PI, the amounts of PI in the interlayer and intralayer space reached 8.5 and 4.1%, respectively (Figure 4C). According to Ti content and CHN elemental analysis, the molar ratios between the total PI and Ti amount of Ti-MWW-AM, Ti-MWW-AT, and R-Ti-MWW-PI were 3.17, 1.49, and 3.49 (Table 2), respectively.</p><!><p>TGA analysis of Ti-MWW-AM (A), Ti-MWW-AT (B), and R-Ti-MWW-PI (C).</p><!><p>The pore volume and surface area of all the Ti-MWW titanosilicates were determined by N2 sorption isotherms (Supplementary Figure 3), and the corresponding results are summarized in Table 3. The micropore volume and total surface area of Ti-MWW-AM was 0.01 cm3 g−1 and 65 m2 g−1, respectively. After the acid treatment, the micropore volume and total surface area increased to 0.05 cm3 g−1 and 184 m2 g−1 for Ti-MWW-AT. The occluded PI molecules were completely removed after further calcination, and the micropore volume and total surface area were significantly improved to 0.13 cm3 g−1 and 419 m2 g−1. After PI molecules were reinserted into the framework, the micropore volume and total surface area decreased to 0.04 cm3 g−1 and 140 m2 g−1 for R-Ti-MWW-PI. The removal of PI via calcination recovered the pore volume and surface area for 3D R-Ti-MWW-PI-cal. Since Ti-MWW-AT and R-Ti-MWW-PI possessed a comparable amount of intralayer PI molecules as revealed by the above TG analysis, the micropore volumes of the two 2D lamellar MWW structures, contributed by mainly intralayer 10-MR pores, were also very close. However, R-Ti-MWW-PI, containing more interlayer PI molecules, showed a lower total surface area than Ti-MWW-AT. Combining the results of TG and BET analysis, it is obvious that the PI-free 3D Ti-MWW samples possessed a higher pore-opening degree than those of PI-containing 2D structure Ti-MWW materials. For the three PI-containing materials, the pore-opening degree followed the order of Ti-MWW-AT > R-Ti-WWW-PI > Ti-MWW-AM.</p><!><p>The physicochemical properties of Ti-MWW related catalysts.</p><p>Given by N2 adsorption at 77 K.</p><p>Calculated by the BET method.</p><p>Calculated by the t-plot method.</p><!><p>As has been shown in Table 2, Ti-MWW-AT exhibited the CPE conversion of 25.1% and CPO selectivity of 99.8%, showing a TON value much higher than that of Ti-MWW-AM, because the partial removal of PI molecules provided space for the diffusion of substrates. Also, the acid treatment could remove most of the boron atoms, and the final boron content was low with the Si/B ratio >67 (Table 2). As has been investigated in our recent study (Xu et al., 2020b), a further increase in the Si/B ratio to >600 for Ti-MWW, synthesized from the B containing system with a similar method in the present study, hardly alters the catalytic activity. Thus, the role of B atoms could be excluded. After further removal of the PI molecules via calcination, the catalytic performance of 3D Ti-MWW was inferior to that of Ti-MWW-AT, due to the formation of interlayer narrow 10-MR pore channels. However, the catalytic activity of Ti-MWW-AT was much lower than that of R-Ti-MWW-PI, although the pore-opening degree of Ti-MWW-AT was higher and they both contained PI molecules with a 2D lamellar structure. The PI molecules occluded inside the framework of Ti-MWW-AT and R-Ti-MWW-PI may impose different effects on the Ti active sites and result in distinct TON values. The bulky TBHP was also used as the oxidant to investigate the catalytic activity of these Ti-MWW-related catalysts (Figure 5). All of the catalysts suffered a decrease in catalytic activity due to the severe diffusion constrains for the bulky TBHP molecules. Among them, Ti-MWW-AT exhibited the highest CPE conversion of 11.7%, even higher than that of R-Ti-MWW-PI (5.3%), which was contrary to the case using H2O2 as the solvent. The catalytic advantage of R-Ti-MWW-PI benefiting from the hexa-coordinated Ti active sites was dramatically weakened when using the bulky TBHP as the oxidant because pore-blocking effect of PI molecules was dominated in this case.</p><!><p>The catalytic performance of Ti-MWW-AM (a), Ti-MWW-AT(b), Ti-MWW (c), R-Ti-MWW-PI (d), and R-Ti-MWW-PI-cal (e) in the CPE epoxidation reaction with H2O2 or TBHP as an oxidant. Reaction conditions: catalyst, 50 mg; cyclopentene, 10 mmol, H2O2 (30 wt.%) or TBHP (70 wt.%), 10 mmol; MeCN, 10 mL; temp., 333 K; time, 2 h.</p><!><p>The microenvironment of Ti active sites was investigated via UV-Vis, FT-IR, and XPS spectra. As shown in Figure 6, Ti-MWW-AM displayed a main absorption band at 260 nm attributed to the extra-framework six-coordinated Ti species, together with a shoulder band at 220 nm, attributed to the framework TiO4 species. Both Ti-MWW-AT and Ti-MWW showed an absorption band at 220 nm attributed to TiO4 species, indicating that the extra-framework TiO6 species could be completely removed by the acid treatment. Besides the main band at 220 nm, R-Ti-MWW-PI also displayed a relatively weak shoulder band at 280 nm attributed to PI-coordinated Ti species, which was different from Ti-MWW-AT. After calcination, the weak absorption peak at 280 nm nearly disappeared for R-Ti-MWW-PI-cal. Moreover, the minor bands around 320–330 nm in the spectra of R-Ti-MWW-PI and R-Ti-MWW-PI-cal were attributed to TiO2 anatase formed through the aggregation of neighboring surface Ti species (Jarian et al., 2011). Therefore, the highest activity in the CPE epoxidation reaction when R-Ti-MWW-PI was used as the catalyst may be closely related to the coordination state of the Ti active sites.</p><!><p>UV-visible diffuse reflectance spectra of Ti-MWW-AM (a), Ti-MWW-AT (b), Ti-MWW (c), R-Ti-MWW-PI (d), and R-Ti-MWW-PI-cal (e).</p><!><p>The characteristic 960-cm−1 band in the IR spectra is generally accepted as the proof for the framework TO4 species, although the accurate attribution is still a debate. However, the presence of physically adsorbed H2O in the zeolite framework with silanol groups also contributes to the 960-cm−1 band. Thus, the samples were evacuated at elevated temperature before the FT-IR measurement to remove H2O, which would also remove the occluded PI molecules. Only the FT-IR spectra of Ti-MWW and R-Ti-MWW-PI-cal without PI molecules were measured (Supplementary Figure 4), and both of them showed the characteristic band at 960 cm−1, indicating the presence of framework TiO4 species.</p><p>In Ti 2p XPS spectra of Ti-MWW (Figure 7Ac), it exhibited the signals at 459.9 eV and 465.5 eV, which were attributed to Ti 2p3/2 and Ti 2p1/2, respectively. For Ti-MWW-AM (Figure 7Aa), the presence of extra-framework Ti species resulted in a lower binding energy of 458.2 and 463.9 eV. Moreover, the binding energy shifted to 459.5 and 465.3 eV for Ti-MWW-AT after the removal of extra-framework Ti species via acid treatment (Figure 7Ab). The PI treatment reduced the binding energy from 459.9 eV for Ti-MWW to 459.4 eV for R-Ti-MWW-PI (Figure 7Ad), indicating that the charge distribution of the Ti ions in R-Ti-MWW-PI became more negative. According to the previous report (Xu et al., 2015), the broad peak around 459.4 eV was associated with a new six-coordinated Ti species with the PI molecule as a ligand and another six-coordinated Ti species with two water ligands. Then, the removal of organic PI ligands leads to the increase in binding energy values to 459.8 eV, because the PI ligands were replaced by water molecules and some framework TiO4 species were also restored upon calcination (Figure 7Ae). Although both with PI molecules in the framework, Ti-MWW-AM and R-Ti-MWW-PI showed different Ti 2p XPS spectra, meaning different microenvironments of Ti active sites. The difference indicated that PI molecules in the Ti-MWW-AM structure did not coordinate with Ti active sites and only filled the pore channels. This was further improved by the N 1s XPS spectra. In the N 1s XPS spectra, Ti-MWW-AM, Ti-MWW-AT, and R-Ti-MWW-PI all showed a binding energy value of 401.7 eV. However, only R-Ti-MWW-PI showed a peak with binding energy of 399.2 eV with the area ratio of 19.1%, indicating that PI may coordinate with the Ti active sites by N atoms (Figure 7B). Therefore, the coordinated PI/Ti ratio was 0.66 according to the total PI and Ti amount calculated by CHN and ICP analysis.</p><!><p>Ti 2p XPS spectra (A) of Ti-MWW-AM (a), Ti-MWW-AT (b), Ti-MWW (c), R-Ti-MWW-PI (d), and R-Ti-MWW-PI-cal (e) and N 1s XPS spectra (B) of Ti-MWW-AM (a), Ti-MWW-AT (b), and R-Ti-MWW-PI (c).</p><!><p>The interaction between PI molecules and Ti active sites was distinct for Ti-MWW-AT and R-Ti-MWW-PI as revealed by the band at 280 nm in the UV-vis spectra and different binding energy values in the XPS spectra. The PI molecules in the synthetic gel hardly coordinated with Ti active sites and constructed mainly "close-site" Ti active sites. In contrast, the structural rearrangement with alkaline PI solution at elevated temperature could cleave the Si–O–Ti bonds and create numerous "open-site" Ti active sites and the PI molecules could also serve as a ligand for the Ti atoms by N atoms. In a recent study reported by our group (Yin et al., 2020), the high catalytic activity of PI-modified Ti-MWW was mainly because the PI-coordinated TiO6 species could accelerate the activation of H2O2 rather than favoring the transformation of active O atoms in Ti–O–O–H intermediate to the alkene molecules.</p><!><p>The effect of the catalyst amount on the cyclopentene epoxidation over Ti-MWW and R-Ti-MWW-PI was investigated, and the results are shown in Figure 8. With the Ti-MWW amount increasing from 50 to 150 mg, the CPE and H2O2 conversion also increased from 13.0 to 32.2% and from 13.3 to 41.4%, respectively (Figure 8A). Further increasing the Ti-MWW amount to 200 mg, both the CPE and H2O2 conversion increased slowly. However, with the increase in Ti-MWW amount, both the CPO selectivity and H2O2 efficiency gradually decreased. Although increasing the Ti-MWW amount favored the reactant conversion, the hydrolysis of CPO was also promoted due to the introduction of more Ti-related Lewis acid sites (Bittar et al., 1992). Comparatively, for R-Ti-MWW-PI, when the catalyst amount increased to 30 mg, both the CPE and H2O2 conversion reached nearly 90%, and they maintained at a very high level from 50 to 200 mg, almost close to 100% (Figure 8B). Under the same reaction conditions, the catalytic activity over R-Ti-MWW-PI was greatly enhanced compared to Ti-MWW. Thus, 50 mg of R-Ti-MWW-PI was enough to achieve high catalytic activity.</p><!><p>Dependence of CPE conversion, H2O2 conversion, H2O2 efficiency, and CPO selectivity on the amount of Ti-MWW (A), and R-Ti-MWW-PI (B). Reaction conditions: CPE, 10 mmol; H2O2 (30 wt.%), 10 mmol; MeCN, 10 mL; temp., 333 K; time, 2 h.</p><!><p>The effect of reaction time on the cyclopentene epoxidation was investigated at 333 K over Ti-MWW and R-TI-MWW-PI, respectively. As shown in Figure 9A, prolonging reaction time from 0.5 to 5 h, both the CPE and H2O2 conversion increased for Ti-MWW, whereas the CPO selectivity was maintained stable at about 99%. The H2O2 efficiency reached a maximum value of 99.3% at 2 h and gradually decreased as the reaction time was prolonged, indicating the occurrence of the non-productive decomposition of H2O2. In the case of R-Ti-MWW-PI, the CPE conversion at a reaction time of 0.5 h exceeded that over Ti-MWW at a reaction time of 5 h (Figure 9B). For R-Ti-MWW-PI, both the CPE and H2O2 conversion increased with the reaction time prolonged, and the CPO selectivity as well as the H2O2 efficiency could be maintained at a high level.</p><!><p>Dependence of CPE conversion, H2O2 conversion, H2O2 efficiency, and CPO selectivity on the reaction time over Ti-MWW (A) and R-Ti-MWW-PI (B). Reaction conditions: catalyst, 50 mg; CPE, 10 mmol; H2O2 (30 wt.%), 10 mmol; MeCN, 10 mL; temp., 333 K.</p><!><p>The reaction temperature had a significant influence on the catalytic performance. For Ti-MWW, both the CPE and H2O2 conversion increased with the reaction temperature increasing, meanwhile the CPO selectivity was basically unchanged. However, the H2O2 efficiency decreased gradually from 313 to 343 K, indicating that H2O2 ineffective decomposition was accelerated at a higher reaction temperature. Also, it can be seen that as the reaction temperature increased, the growth rate of the conversion was improved and the CPE conversion was increased to 24.4% at 343 K (Figure 10A). For R-Ti-MWW-PI, the CPE and H2O2 conversion was greatly increased to nearly 100% at 343 K, and the CPO selectivity was maintained at 99.9% (Figure 10B).</p><!><p>Dependence of CPE conversion, H2O2 conversion, H2O2 efficiency, and CPO selectivity at different reaction temperatures over Ti-MWW (A) and R-Ti-MWW-PI (B). Reaction conditions: catalyst, 50 mg; CPE, 10 mmol; H2O2 (30 wt.%), 10 mmol; MeCN, 10 mL; time, 2 h.</p><!><p>The regeneration and recycling of R-Ti-MWW-PI are shown in Supplementary Figure 5. The CPE conversion decreased gradually by 3–8% after each reaction run while the CPO selectivity was maintained at 99.9%. After six runs, it was regenerated by calcination and PI treatment again, and the activity was restored in the seventh run.</p><!><p>For the epoxidation of cyclopentene, Ti-MWW provided relatively lower CPE conversion due to the diffusion constrains. However, it showed the advantages in product selectivity in the aprotic solvent like MeCN. The structural rearrangement upon PI treatment converted the 3D MWW structure to a 2D lamellar one, which enlarged the interlayer space and greatly alleviated the diffusion constrains of cyclic cyclopentene. Besides, the newly formed hexa-coordinated Ti active species, bearing PI molecules as the ligand, exhibited higher catalytic activity. Moreover, the enhancement of the catalytic performance in cyclic CPE epoxidation by 7.5 times through the PI-assisted structural rearrangement was the most significant compared to other linear alkenes.</p><!><p>All datasets presented in this study are included in the article/Supplementary Material.</p><!><p>PW conceived and planned the research. WT prepared the catalysts and performed the characterization and catalytic experiments. JY and LD contributed to the catalyst preparation. WT and HX prepared the manuscript with contributions from the other authors.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

In Vivo Manifestation of Notch Related Phenotypes in Zebrafish Treated with Alzheimer\xe2\x80\x99s Amyloid Reducing \xce\xb3-Secretase Inhibitors

\xce\xb3-Secretase is responsible for the final cleavage of amyloid precursor protein to generate the amyloid-\xce\xb2 protein, the major component of plaques in the brains of Alzheimer\xe2\x80\x99s disease patients. \xce\xb3-Secretase inhibitors (GSI) have been explored for therapeutic inhibition of A\xce\xb2 generation, but mechanistic toxicity has been documented due to its blockage of \xce\xb3-secretase cleavage of several dozens of substrates including Notch. This becomes the primary obstacle for most inhibitors during the preclinical development and the main concern for several compounds in the clinical trials. To predict potential side effects related to Notch signaling, we examined global effect of GSIs in vertebrate animal zebrafish. We have used two potent GSIs (GSI A and GSI 18) with a sub-\xc2\xb5M effective concentration for 50% A\xce\xb2 inhibition (EC50). Zebrafish embryos were treated with GSI A, 18 or a well characterized GSI DAPT, and transparent animals were examined for up to 7 days. GSI A had less abnormal phenotype in zebrafish, compared to GSI 18-treated embryos that displayed curved tails, a loss of pigmentation, and reduced swim bladder and heart rate. To understand mechanistic effect at the molecular level, we examined Notch signaling in these GSI-treated zebrafish. Notch phenotypes were observed in embryos treated with 50 and 10 \xc2\xb5M GSI 18, but not with 10 \xc2\xb5M GSI A. In accordance, in situ hybridization with a probe against Notch target gene her6 showed a weaker staining in embryos treated with 10 \xc2\xb5M GSI 18 than those treated with 10 \xc2\xb5M GSI A. In conclusion, phenotypic profile in whole animals offers important information on Notch related pathways and provides prediction of safe compounds during early development stages of therapeutic GSIs.

in_vivo_manifestation_of_notch_related_phenotypes_in_zebrafish_treated_with_alzheimer\xe2\x80\x99s_a

INTRODUCTION<!>Embryo Treatment<!>Blocking A\xce\xb2 production by \xce\xb3-secretase inhibitors<!>In Vitro \xce\xb3-Secretase Activity Assay<!>Conventional Microscope Imaging<!>In situ Hybridization<!>Heart rate, pigmentation and swim bladder Analysis<!>Inhibition of \xce\xb3-secretase activity in cultured cells treated with GSIs<!>Phenotype alteration in embryos treated with increasing concentrations of potent GSIs<!>Heart rate analysis of zebrafish embryos<!>Size of swim bladder was reduced in embryos treated with GSIs<!>Relative levels of pigmentation in embryos treated with GSIs<!>Co-relate Notch signaling to global phenotypic alteration<!>DISCUSSION

<p>Alzheimer's disease (AD) is pathologically characterized by the presence of extracellular neuritic plaques and intracellular neurofibrillary tangles (Selkoe 1999). While the neurofibrillary tangles are mainly composed of hyperphosphorylated Tau protein, the neuritic plaques are formed by a gradual accumulation of amyloid β protein (Aβ). Among various Aβ isoforms, the most common ones are 40-residue Aβ (Aβ40) and 42-residue Aβ (Aβ42). Aβ is produced by sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase (Selkoe 1999, Xia 2001), and the γ-secretase is responsible for the final cleavage to generate Aβ at residue 40 or 42. The γ-secretase is composed of presenilins (PS1 or its analogue PS2), presenilin enhancer (Pen-2), nicastrin, and Aph-1 (Wolfe et al. 1999, Francis et al. 2002, Yu et al. 2000). So far, all autosomal dominant mutations have only been found in PS and APP genes, and missense mutations in PS and APP genes account for the majority of early onset familial AD cases. Therefore, γ-secretase is considered a key protease involved in the pathogenesis of AD and is one of the most promising therapeutic targets for AD treatment.</p><p>The identification of γ-secretase as the target for blocking Aβ production was established by earlier discoveries that loss of PS1 (De Strooper et al. 1998) or its critical aspartate residues (Wolfe et al. 1999) leads to a blockage of Aβ generation. Besides APP, γ-secretase cleaves many substrates such as Notch (De Strooper et al. 1999). The protease complex cleaves Notch to generate Notch intracellular domain, which is critical for proper neuronal development. The differentiation of these two substrates by the γ-secretase complex is under intensive investigation, and selective compound that blocks Aβ production without affecting Notch signaling would be ideal.</p><p>Regulation of γ-secretase cleavage of APP and Notch could be modulated by co-factors like TMP21 (Chen et al. 2006) or by pharmacologic manipulation. In a cell free system, cultured cells including rat primary neuronal cultures and in guinea pig brain, the Abl kinase inhibitor Gleevec (imatinib mesylate) has been shown to reduce Aβ production (Netzer et al. 2003). This is not related to the Abl kinase activity, as no difference in Aβ reduction was detected in fibroblasts cultured from wildtype versus Abl knockout mice, indicating a unique mechanism independent of its kinase inhibitory effect. Importantly, Gleevec does not inhibit the γ-secretase mediated S3 cleavage of Notch-1 (Netzer et al. 2003). Therefore, Gleevec functions as a selective γ-secretase inhibitor that specifically blocks Aβ production without affecting the γ-secretase cleavage of Notch.</p><p>It is believed that selective GSI like Gleevec does not bind to the active site of the protease, but evidence is absent for its binding to the substrate. On the contrary, previous studies have shown that another group of APP selective GSIs, NSAIDs, could specifically bind to APP, which makes it distinguishable from other substrates like Notch (Kukar et al. 2008). By a mechanism of selectively binding to APP, NSAIDs specifically block Aβ production without affecting the Notch cleavage and downstream signaling (Weggen et al. 2001, Kukar et al. 2008).</p><p>Altered phenotypes from abnormal Notch signaling are among the most studied molecular events in animal models. In zebrafish, a number of Notch mutants display defective anteroposterior polarity and increased neurogenin 1 (ngn1) positive cells. Defective somitogenesis and neurogenesis lead to curved tails and reduction in neural crest cell migration, which further cause a loss of pigmentation (Jiang et al. 1996, van Eeden et al. 1996). These phenotypes can be replicated in zebrafish treated with a potent GSI, DAPT, at the late blastula stage (Geling et al. 2002). Besides DAPT, the Aβ-lowering JLK non-peptidic isocoumarin inhibitors (Petit et al. 2003) and compound E (Yang et al. 2008) were also tested for their effect on the Notch pathway responsible for somitogenesis in the zebrafish embryo.</p><p>The use of zebrafish for toxicity assessment has been widely accepted and put in practice (Zon & Peterson 2005). Mechanistic toxicity associated with GSI has been the main concern for compounds that are undergoing preclinical development and clinical trials, as the GSIs block γ-secretase that cleaves several dozens of substrates (Xia & Wolfe 2003). Treating mice with a potent γ-secretase inhibitor for 15 days results in many unwanted side effects, such as impaired lymphocyte development, and increased goblet cell number in intestine with abnormal tissue morphology (Wong et al. 2004). In zebrafish, intestinal development is most likely tied to swim bladder development, as both intestine and swim bladder arise from the same progenitor cells (Holtzinger & Evans 2005). It has been shown that a downstream effecter of Notch, Hey-2, regulates Gata4 activity, and both Gata4 and Gata6 regulate the formation of multiple organs in zebrafish, including the swim bladder (Holtzinger & Evans 2005). Zebrafish cardiovascular system is also regulated in part by Notch signaling. For example, a zebrafish mutant termed gridlock exhibits disrupted aortic blood flow that mimicked features of aortic coarctation in humans, and the mutant gene is at the downstream of Notch signaling (Zhong et al. 2001).</p><p>In this study, we characterized two potent GSIs, GSI A and GSI 18, in zebrafish. GSI A is identical to compound X, which was used to explore adipsin as a non-invasive Notch responding marker protein from plasma and feces of compound-treated animals (Searfoss et al. 2003). Treatment of rats with compound X at doses much higher than those required for Aβ42 reduction leads to a gastrointestinal toxicity characterized by an increase in goblet cell number (Searfoss et al. 2003). GSI 18 has been used to block Notch signaling in earlier studies (Fan et al. 2006, Lewis et al. 2005). Because most side effects associated with a new compound are almost unpredictable before being dosed to animals, an alternative approach would be to treat transparent vertebrate zebrafish and predict possible side effects. In this study, we used GSI A, GSI 18 and DAPT to treat zebrafish and analyzed various phenotypes, some of which are not directly related to Notch signaling. We found that GSI A, with an EC50 at 1.6 nM in cultured cells, caused less phenotypic alteration in zebrafish, comparing to GSI 18 that showed stronger phenotypes.</p><!><p>Embryos were placed in a 24-well plate (5–6 embryos/well). Compounds were dissolved in 1 mL of egg water (final concentration at 50 µM, 10µM and 1µM for DAPT {N-[N-(3,5-Difluorophenacetyl-L-alanyl)]-S-phenylglycine t-Butyl Ester}, GSI A (Searfoss et al. 2003) and GSI 18 (Fan et al. 2006, Lewis et al. 2005), 0.1% DMSO was used as a negative control). Embryo medium was replaced with the compound containing egg water, and the embryos were incubated at 28°C overnight before survival rate was recorded and photographic images were taken. Compounds were applied at 24 hours post-fertilization (hpf). Prior to the treatment at 24 hpf, embryos were de-chorionated in pronase.</p><!><p>Compounds were dissolved in the DMEM growth media and applied to ~90% confluent APP-expressing CHO cells in 96-well plates. After incubation for 4–5 hours at 37°C, cells were centrifuged for 5 minutes at 6000 g, and supernatant media were collected for Aβ measurement by ELISA. Sandwich ELISAs for monomeric Aβ were performed as described (Johnson-Wood et al. 1997). The capture antibodies 2G3 (to Aβ residues 33–40) and 21F12 (to Aβ residues 33–42) were used for Aβ40 and Aβ42 species. The detecting antibody was biotinylated 266 (to Aβ residues 13–28). These antibodies were kindly provided by Dr. P. Seubert and Dr. D. Schenk (Elan, plc).</p><!><p>The E. coli generated APP-based, 100-residue γ-secretase substrate C100 -Flag was purified as previously described (Esler et al. 2002, Fraering et al. 2004, Campbell et al. 2005). C100-Flag substrate contains an initiating methionine, 99 amino acids that start at the BACE cleavage site, and a Flag tag. The membrane vesicles were solubilized in 1% CHAPSO-HEPES and diluted in a final concentration of 0.2% CHAPSO-HEPES. Phosphatidylethanolamine (PE) and phosphatidylcholine (PC) were added to the final concentration of 0.02% PE and 0.08% PC. After adding DMSO or test compounds to the solubilized γ-secretase complex, substrate C100-Flag was added to the mixture, then followed by incubation at 37°C for 4 hour. AICD was detected by Western blot using antibody against the Flag tag, as previously described (Esler et al. 2002).</p><p>The Notch signaling activity was measured in human embryonic kidney (HEK) 293 cells expressing Hes-1 reporter construct (Hes-Luc) that was generated by inserting three of Su(H) binding sequence in the pGL3-pro luciferase reporter vector (Promega, Madison, WI). Transfected cells were treated with γ-secretase inhibitors GSI A, GSI 18 or DAPT for 8 hr, followed by the measurement of luciferase activity (Luciferase Assay System, Promega, Madison, WI), as previously reported (Yang et al 2008).</p><!><p>Compound-treated embryos were observed under an OLYMPUS SZX12 microscope. For examination, embryos were removed from the compound-containing medium and placed in 0.4% tricane (3-amino benzoic acid ethyl ester, Sigma, St. Louis, MO) solution. Upon anesthetizing, embryos were placed in 3% methylcellulose for positioning and images were recorded with an OLYMPUS Q-COLOR3 camera.</p><!><p>In situ hybridization of compound-treated embryos was carried out at 2 dpf using the probe against her6 gene. Single-stranded RNA probes against her6 were synthesized from a cDNA clone (provided by Dr. P Raymond, University of Michigan, Ann Arbor, MI) using T7 RNA polymerase after linearization by restriction digest. The probe was then labeled with digoxigenin-UTP (Roche, Basel, Switzerland). At least 10 to 20 embryos were examined for each experiment. Images were taken at 64x magnification for stained embryos.</p><!><p>Zebrafish embryos were treated with secretase inhibitors at various concentrations. The embryos were placed on their side for videotaping. Heart rate, in beats per minute, was determined by extrapolating the heart rate per 15 sec on the video. The intensity of pigmentation was quantified in a semi-automatic approach by first drawing region of interest (ROI) on an image followed by segmentation from other areas. After segmenting the pigmentation, the total area and average pixel values of pigmentation were calculated. The values of the DMSO treated embryos were used as the benchmark for comparison. The size of swim bladder was quantified by drawing a region of interest over the swim bladder followed by the calculation of the area. All calculations were performed using MATLAB (MathWorks, Natick,MA).</p><!><p>Two GSIs (Fig. 1A) and a widely used control GSI, DAPT, were applied in our studies. An APP overexpressing CHO cell line 7W was treated with individual compounds and the levels of secreted Aβ in the media were measured by ELISA. Levels of Aβ40 and Aβ42 in the media of 7W cells that were treated with 0.1% DMSO were normalized to 1 and used to calculate the relative levels of Aβ from cells treated with DAPT, GSI A, or GSI 18. As expected, cells treated with DAPT showed an inhibition of the generation of Aβ40 and Aβ42 (Fig. 1B, C). Interestingly, GSI A showed a much stronger inhibition on Aβ40 and Aβ42 production than DAPT, while GSI 18 was less potent than DAPT in inhibiting Aβ40 and Aβ42 production. While all three GSIs had sub-µM effective concentration of 50% inhibition of Aβ generation (EC50, GSI 18=0.78 µM, DAPT=0.1 µM), GSI A showed strongest inhibition with EC50 at 1.6 nM.</p><p>When the E. coli generated APP-based, 100-residue γ-secretase substrate C100-Flag was mixed with the membrane vesicles solubilized in CHAPSO, AICD could be detected by Western blotting with a Flag antibody in the presence of DMSO (Fig. 2A). DAPT at 10 µM also inhibited AICD generation, while substrate alone was not converted to AICD in the absence of γ-secretase (Fig. 2A, "Sub alone"). A dose-dependent inhibition of AICD generation by GSI A was detected (Fig. 2A), and generation of AICD was inhibited in the presence of 10µM of GSI 18 (Fig. 2B).</p><p>We further examined an inhibitory effect of GSIs on the γ-secretase cleavage of Notch. Notch signaling and levels of NICD can be quantified using a Hes-1 reporter construct (Hes-Luc) that was generated by insertion of three Su(H) binding sequences in the pGL3-pro luciferase reporter vector, as we have previously reported (Yang et al, 2008). A construct encoding a truncated, γ-secretase immediate substrate NotchΔE was transiently co-transfected with Hes-Luc reporter construct into HEK293 cells, and transfected cells were treated with different concentrations of GSIs. We found that luciferase activities were inhibited by high doses of GSI A, GSI 18 and DAPT (Fig. 2C). While the inhibition of Notch signaling in these cells was less efficient compared to Aβ blockage, essentially we did not see a dramatic difference in potency among three GSIs in cultured cells (Fig. 2C).</p><!><p>To predict in vivo Notch related side effect, we tested these GSIs in a whole animal, zebrafish. A large cluster of zebrafish embryos were routinely generated, and several dozen embryos were treated with each compound. First, we used a conventional microscope to monitor embryo survival from 1 dpf to 7 dpf and assess the effects of these compounds on the zebrafish death rate. Two treatment paradigms were applied, i.e., embryos treated at 6 hours post fertilization (hpf) or 24 hpf. We found that treatment of embryos during earlier developmental stages (6 hpf) caused severe damage to embryos, and a high number of embryos could not survive through 2 or 3 dpf (data not shown). When embryos were treated at 24 hpf, much less embryos were succumbed to the compound and died. Therefore, we examined all embryos treated with GSIs at 24 hpf.</p><p>The zebrafish embryos were treated with different concentrations of DAPT, GSI A or GSI 18. The phenotypes of zebrafish embryos treated with increasing concentrations of three compounds were compared at 2 dpf (Fig. 3) and 3 dpf (Fig. 4). The major phenotypes we examined were curved tail and pigmentation. Images of the treated embryos were acquired using a stereomicroscope, and both dorsal and lateral views of zebrafish embryos were acquired.</p><p>Embryos treated with DAPT showed curved tails, bent trunks, smaller eyes (Fig. 3A), compared to control embryos (treated with 0.1% DMSO) that showed a wild-type phenotype (Fig. 3B). The curvature was obvious when a lateral view of zebrafish was obtained. Embryos treated with 50 µM GSI A (Fig. 3C) or GSI 18 (Fig. 3D) showed defective phenotypes. GSI 18 caused stronger phenotypes in zebrafish than GSI A and DAPT did. Embryos treated with 10 µM of GSI 18 showed curved trunks, less pigmentations, smaller eyes, curved and short tails (Fig. 3D). These phenotypes were not observed in embryos treated with 10 µM GSI A or DAPT (Fig. 3A and C).</p><p>Abnormal phenotypes of embryos treated with 50 µM DAPT persisted into 3 dpf (Fig. 4A), while DMSO did not have any effect on zebrafish (Fig. 4B). Embryos treated with 50 µM or 10 µM GSI 18 continued to show the curvature of the tails, and even more obvious than that at 2 dpf (Fig. 4D). For GSI A-treated embryos, most fish displayed curved and short tails, smaller eyes at 50 µM, but none at 10 µM (Fig. 4C).</p><p>The dramatic difference between GSI A and GSI 18 treated embryos could be further illustrated by acquisition of images of all embryos treated with each compound at 10 µM (Fig. 4E). Apparently, all embryos treated with 10 µM GSI 18 showed curved tails, while none of GSI A treated embryos showed curved tails. Therefore, 10 µM GSI A did not affect animals to a level that would cause significant impairment in normal embryonic development.</p><!><p>When we examined transparent GSI-treated embryos, we noticed a weaker heart beat in some of GSI-treated embryos. We video-recorded the heart beats of groups of GSI-treated embryos and searched for abnormal phenotypes associated with heart development. Heart rate, in beats per minute, was determined by extrapolating the number of heart beats per 15 sec on the video. We found that the reduction of heart rates in the presence of GSIs were dose dependent (Fig. 5A and B). In particular, DAPT had most severe effect at later development stages (Fig. 5C). All DAPT-treated embryos did not show clear heart beat at 4 dpf (Fig. 5C), although the blood flow was not disrupted. The DAPT-treated embryos showed abnormal heart movement that pushed blood flow through heart chamber, which kept animal alive (data not shown). At 2 and 3 dpf, 50µM DAPT-treated embryos showed significantly slower heart beat than those treated with GSI A or GSI 18. GSI 18 had more severe effect than GSI A, and the heart rate in 50 µM GSI 18-treated embryos was significantly lower than that of 50 µM GSI A-treated embryos (Fig. 5C). Comparing to DMSO treated embryos, all GSI-treated embryos had a significant drop of heart rate at 2, 3 and 4 dpf.</p><!><p>The air-filled swim bladder first formed as a single chamber, which inflated at 1–3 dpf, when the body length reached 3.5–4 mm. Embryos treated with 50 µM GSIs did not reveal any swim bladder and could not be quantified (data not shown). When 10 µM GSIs were utilized and compound treated embryos were kept until 7dpf, we found that each compound had different effect on the loss of swim bladder during different development stages. When the size of swim bladder was quantified using MATLAB, we normalized the size of swim bladder from embryos treated with DMSO to 1. At 3 dpf, GSI A did not alter the size of swim bladder (92±6%, mean±SEM), while GSI 18 reduced the size of swim bladder to 73±11% compared to those of DMSO treated embryos. However, the difference between GSI and DMSO treated embryos was not statistically significant. At 4 dpf, swim bladders of embryos treated with GSI A or GSI 18 remained similar sizes. Only at 5 dpf did embryos treated with GSI A show a significant reduction in size of swim bladder (37±14%). Similarly, the size of embryos treated with GSI 18 reduced to 18±4%, only ~1/5th of those of DMSO treated embryos. The swim bladders of embryos treated with GSIs remained at the same small size through day 6 and 7. The difference between GSI A and GSI 18 treated embryos was not significant. DAPT treated embryos showed a significant reduction of size and had swim bladder at half size of those treated with DMSO (56±9%) at 3 dpf. The swim bladders of these embryos remained at the same small size from day 3 to day 7. Therefore, embryos treated with GSI 18 had relatively smaller size of swim bladder, comparing to those of embryos treated with GSI A.</p><!><p>Black pigment cells, or melanocytes, are the major contributing cells to pigmentation in vertebrate organisms. To explore the effect of compound on pigmentation of zebrafish, we used a conventional microscope and quantified segment with MATLAB from 4dpf to 6dpf. Embryos were treated with these three compounds at 50 µM, 10 µM and 5 µM. Embryos treated with GSI 18 at 50 µM were transparent, and we defined the level of pigmentation as 0. The level of pigmentation of embryos treated with DMSO was normalized to be 100%.</p><p>Embryos treated with 10 µM DAPT showed a relative ~70% pigment density compared to the levels of pigment in embryos treated with DMSO (Fig. 6A). At 50 µM, DAPT treated embryos only showed ~30% relative levels of pigment compared to control DMSO treated embryos. Similar reduction of pigmentation was observed at the later stages (Fig. 6B and C). At 6 dpf, embryos treated with 50 µM GSIs showed similar levels of reduction in pigmentation that resulted in almost transparent animals. Apparently, treating embryos with GSIs at a high concentration for a longer period, e.g., 5 days, had a dramatic effect on pigment formation, and its reduction reached the maximum level to make the animal transparent. To search for statistically significant difference in the efficacy of these GSIs, we examined the approximate concentrations of GSIs that could reduce 50% of pigmentation. We found that the effective concentration for 50% reduction of pigmentation was 5–10 µM for GSI 18, which was lower than those for GSI A and DAPT. On average, DAPT and GSI A had similar effect on pigment formation, and the effective concentration to achieve 50% pigment reduction was above 10 µM but below 50 µM. Overall, GSI 18 showed relatively more potent inhibition on pigmentation during embryonic development.</p><!><p>The overall phenotypes associated with GSI-treated zebrafish reflected an abnormal Notch signaling, e.g., zebrafish rely on Notch signaling activity throughout embryonic and metamorphic development for the formation of pigmentation. To corroborate the Notch phenotypes associated with curved trunk/tail and decreased pigmentation, we analyzed mechanistic effect on Notch signaling by GSI A and GSI 18, i.e., the expression levels of the Notch downstream target gene her6 was measured by in situ hybridization using a her6 probe.</p><p>In DMSO-treated embryos, her6 expression was mainly clustered in the ventral midbrain and ventral hindbrain. When embryos were treated with GSI A at 10 µM, a weaker staining of her6 was observed. When embryos were treated with a lower concentration of GSI A at 1 µM, those embryos showed a very similar her6 staining pattern to the control embryos. However, in the presence of 10 µM GSI 18, the her6 expression was much reduced in most areas, reflecting a strong inhibition of γ-secretase activity. At the lower concentration of GSI 18 (1 µM), almost no difference was observed between GSI 18 and DMSO treated embryos (Fig. 7A). We segmented the regions of interest, i.e., regions with high her6 expression such as dorsal diencephalon, retinas, ventral midbrain and hindbrain, telencephalon, olfactory vesicles, branchial arches, and pectoral fins. When the expression levels of her6 in DMSO treated zebrafish were normalized to 1, a significant reduction in relative levels of her6 expression in zebrafish treated with 10 µM GSI A or GSI 18 was observed. The inhibitory effect of GSI 18 was significantly stronger than that of GSI A (Fig. 7B). When the her6 staining is linked to morphological alterations (Fig. 3 and Fig. 4), the level of reduction in Notch signaling is closely linked with the severity of phenotypes that was observed in these zebrafish. For example, a loss of her6 staining in the presence of 10 µM GSI 18 corresponded to stronger phenotypes at 2 and 3 dpf, comparing to those treated with 10 µM GSI A (Fig. 3C, D and 4C, D, E).</p><!><p>Identifying AD targets for therapeutic intervention has been an ongoing endeavor for the past century, and enzymes responsible for Aβ generation are among the most promising ones. The amyloid hypothesis has evolved to the stage that is widely supported by genetic, biochemical and immunohistochemical evidences (Hardy & Selkoe 2002). While activation of α-secretase will theoretically increases non-amyloidogenic processing of APP, amyloidogenic β- and γ-secretases are two prime targets for blocking Aβ generation.</p><p>The crystal structure of β-secretase has been elucidated (Hong et al. 2000), but identifying a potent β-secretase inhibitor that can efficiently cross blood brain barrier is still a challenge. The crystal structure of the γ-secretase, on the other hand, is difficult to obtain, and previous studies have started to shed light on its structural arrangement of all four components (Lazarov et al. 2006). While a reasonable number of potent GSI have been synthesized, an excellent GSI selective for APP processing yet awaits for identification and further optimization. Non-selective blockage of Notch signaling by existing GSIs has been the major obstacle and accounts for the most mechanistic toxicities observed in GSI-dosed animals.</p><p>To predict toxicity of GSIs in a vertebrate animal, we treated zebrafish with two GSIs that showed potent EC50 when used to treat cultured cells (Fig. 1). The standard procedures for testing compounds in zebrafish have been applied in this study, and we found that these GSIs did not cause extensive embryonic lethality when embryos were treated at 24 hpf. GSIs treated embryos survived through day 7, which provided us a wide window to observe the anatomy of developing zebrafish (Fig. 3 and Fig. 4). Apparently, microscopic images of zebrafish have revealed much detailed information about potential abnormalities caused by an inhibition of γ-secretase. While a loss of swim bladder may not be the cause of embryonic lethality, it reflects a system-wide alteration in the presence of GSI. Mechanistic analysis of the phenotypic profile suggests that most abnormalities were related to the inhibition of γ-secretase cleavage of Notch by GSIs.</p><p>In zebrafish, the same progenitor cells develop into swim bladder and intestine, which are downstream of Notch signaling (Holtzinger & Evans 2005). The reduction of heart rate, which might be the leading cause of death in a small number of embryos, is also linked to Notch signaling. The gridlock gene is at downstream of Notch signaling (Zhong et al. 2001), and the dysfunctional gridlock in the absence of Notch signaling might be in part responsible for these phenotypes (Fig. 5). Apparently, the development of zebrafish cardiovascular system is extremely complicated, and the gridlock mutant zebrafish showed disrupted aortic blood flow that only partially resembled the phenotype we have observed in GSI-treated embryos (Zhong et al. 2001). Thus, it is unlikely that dysfunctional gridlock would be the sole cause for these phenotypes.</p><p>Direct effect from abnormal Notch signaling is evident in GSI-treated embryos. We have previously reported phenotypes of zebrafish that were knocked down of individual γ-secretase components (Campbell et al. 2006) or expressed truncated Pen-2 (Zetterberg et al. 2006). These phenotypes caused by dysfunctional γ-secretase and subsequent Notch signaling are consistent with earlier reports on Notch mutant zebrafish (Jiang et al. 1996, van Eeden et al. 1996). Those embryos treated with high concentrations of GSI failed normal somitogenesis and neurogenesis, two key events that lead to curved tails and reduction in neural crest cell migration, which caused a loss of pigmentation (Fig. 6). Using these two readouts, we characterized the properties of GSI A and GSI 18 and examined their effect on Notch signaling in a whole animal.</p><p>In situ hybridization of GSI-treated zebrafish with a probe against Notch target gene her6 (Fig. 7) provided a molecular basis to the abnormal phenotypes associated with defective Notch signaling during zebrafish development. Both GSI A and GSI 18 were able to block γ-secretase in whole animals and reduce her6 staining. Comparing to embryos treated with GSI A at 10 µM, GSI 18 was more potent in inhibiting Notch signaling in embryos, which showed a stronger reduction in her6 staining. This was consistent with GSI 18-induced stronger phenotypic changes in developing zebrafish embryos. Interestingly, cultured cell-based Luciferase activity assay did not reveal significant difference in their inhibition of Notch signaling. These results emphasize the need of animal test to determine the mechanistic toxicities associated with Notch signaling. The difference might come from different absorption and metabolization of the compounds. In contrast to mice and guinea pigs, it is difficult to harvest brains from zebrafish embryos to measure the drug levels, making it impractical to compare the exposure of our compounds in zebrafish and mammals.</p><p>Our results indicate that GSI A was more potent in inhibiting Aβ generation but induced less phenotypic changes in developing zebrafish embryos than GSI 18. Further studies are needed to identify the target of GSI A by performing binding assays to understand the site of action within γ-secretase complex. Previous report has shown that nicastrin is not only required for γ-secretase cleavage of APP and Notch (Francis et al. 2002, Lee et al. 2002, Siman & Velji 2003, Shirotani et al. 2003, Li et al. 2003) but also serve as an initial binding partner for γ-secretase substrates like APP and Notch (Shah et al. 2005). Another γ-secretase component, Pen-2, has been found to modulate the formation of PS1 versus PS2 containing γ-secretase complex (Placanica et al. 2008), and an artificial elongation of the Pen-2 N terminus increased Aβ42 production (Isoo et al. 2007). In addition, C-terminus of Pen-2 is critical for intermolecular interactions and function of presenilin complexes (Hasegawa et al. 2004, Kim & Sisodia 2005). Therefore, Pen-2 might play a role to influence the selective cleavage of APP by γ-secretase. Recent studies have shown a critical role of Aph-1B in regulating the γ-secretase cleavage of APP (Serneels et al. 2005). Knockout of each of the three Aph-1 homologous genes (Aph-1A, B, and C) in mice leads to divergent phenotypes, suggesting that different γ-secretase complexes in vivo may exert separate biological functions (Serneels et al. 2005). In mammalian cultured cells and zebrafish, it is not clear whether GSI A specifically blocked one isoform of γ-secretase that is responsible for APP processing. The structure of GSI A is different from coumarin and does not like coumarin dimer-based compounds that bind to the allosteric site of the γ-secretase (Shelton et al. 2009). However, its structure is similar to that of compound E, which was shown to bind to PS1 (Seiffert et al. 2000). It is conceivable that GSI A may similarly bind to PS1 fragments. Alternatively, GSI A may have a substrate preference like some NSAIDs which prefer APP over other substrates (Kukar et al. 2008), and a direct interaction of GSI and the APP inhibitory domain (Tian et al. 2010) could also lead to a modulation of γ-secretase cleavage and Aβ production.</p><p>It is important to understand how zebrafish absorb and metabolize GSIs that showed significant impact on embryonic development. As two or more species are used for bioefficacy determination, our test in zebrafish provides important information on GSIs that warrants further studies in a second animal model, such as transgenic mouse or guinea pig. Zebrafish essentially provide a unique tool to predict potential outcomes for future animal studies, where positive outcomes will lead us one step closer to a successful amyloid-based therapy.</p>

PubMed Author Manuscript

The pKa Distribution of Drugs: Application to Drug Discovery

The acid-base dissociation constant (pKa) of a drug is a key physicochemical parameter influencing many biopharmaceutical characteristics. While this has been well established, the overall proportion of non-ionizable and ionizable compounds for drug-like substances is not well known. Even less well known is the overall distribution of acid and base pKa values. The current study has reviewed the literature with regard to both the proportion of ionizable substances and pKa distributions. Further to this a set of 582 drugs with associated pKa data was thoroughly examined to provide a representative set of observations. This was further enhanced by delineating the compounds into CNS and non-CNS drugs to investigate where differences exist. Interestingly, the distribution of pKa values for single acids differed remarkably between CNS and non-CNS substances with only one CNS compound having an acid pKa below 6.1. The distribution of basic substances in the CNS set also showed a marked cut off with no compounds having a pKa above 10.5.The pKa distributions of drugs are influenced by two main drivers. The first is related to the nature and frequency of occurrence of the functional groups that are commonly observed in pharmaceuticals and the typical range of pKa values they span. The other factor concerns the biological targets these compounds are designed to hit. For example, many CNS targets are based on seven transmembrane G protein-coupled receptors (7TM GPCR) which have a key aspartic acid residue known to interact with most ligands. As a consequence, amines are mostly present in the ligands that target 7TM GPCR’s and this influences the pKa profile of drugs containing basic groups. For larger screening collections of compounds, synthetic chemistry and the working practices of the chemists themselves can influence the proportion of ionizable compounds and consequent pKa distributions. The findings from this study expand on current wisdom in pKa research and have implications for discovery research with regard to the composition of corporate databases and collections of screening compounds. Rough guidelines have been suggested for the profile of compound collections and will evolve as this research area is expanded.

the_pka_distribution_of_drugs:_application_to_drug_discovery

Introduction<!>Drug-likeness<!>pKa data sources and analysis<!>Methods<!>(a) Acid and base proportions<!>(b) pKa Distribution of single acid containing compounds<!>(c) pKa Distribution of single base containing compounds<!>(d) pKa Distribution of simple ampholytes<!>Overview of findings<!>Application of findings<!>Perspectives and future directions<!>Conclusion<!>

<p>An awareness of the influence of the acid-base dissociation constant, pKa, on the biopharmaceutical properties of drugs and chemicals has long been established within the pharmaceutical and chemical industry. As the majority of drugs are weak acids and/or bases, knowledge of the dissociation constant in each case helps in understanding the ionic form a molecule will take across a range of pH values. This is particularly important in physiological systems where ionization state will affect the rate at which the compound is able to diffuse across membranes and obstacles such as the blood-brain barrier (BBB). The pKa of a drug influences lipophilicity, solubility, protein binding and permeability which in turn directly affects pharmacokinetic (PK) characteristics such as absorption, distribution, metabolism and excretion (ADME)1–5. The well established association between pKa and PK has also resulted in the requirement for pKa values to be measured for regulatory compliance (e.g. FDA6). Formulation procedures for optimizing drug delivery also benefit from the determination of the pKa. Given the importance of this parameter to the drug industry7, it follows that an ability to estimate or measure8 the pKa, together with a knowledge of their distribution, will be of great benefit. This is particularly important when contemplating the large number of compounds that can be considered for screening purposes (e.g. combinatorial libraries, third party compound collections). Ideally, these sets of compounds should be representative of drug-like substances as a whole with regard to the proportion of ionizables and the distribution of the pKa values themselves.</p><p>An estimate of likely ADME characteristics can be obtained using pKa values and various other properties such as molecular weight (MW), partition coefficient (logP), number of hydrogen bond donors (hdon) and acceptors (hacc), and polar surface area (PSA)9. The pKa values themselves represent useful pieces of physicochemical information but in isolation they have limited value. From the perspective of designing combinatorial libraries or buying sets of compounds from third party suppliers then it is important to know what the overall profile of a collection should resemble with regard to a range of physicochemical properties. Therefore, in order to complement properties such as MW, logP, hdon, hacc and PSA, information regarding the proportions of acids and bases, and the distribution of pKa values is required. In medicinal chemistry there are many instances where research is influenced by rules of thumb. This could be described as a collective wisdom amongst the medicinal chemistry community where the 'rules' have not been fully researched or described. Such might have been the case with the Lipinski study10 where some of the underlying principles were roughly known and applied prior to their publication. Certainly for pKa distributions, these have not been fully documented in the literature. It is on this basis that the current study has sought to explore the proportions of acids and bases and to detail the distribution of pKa values for a set of general drug-like molecules.</p><!><p>In recent years there have been numerous studies exploring methods to improve the efficiency of the early stages of new medicines research. The aim of all these studies has been to reduce the development time from the initiation of a project through to the selection of a clinical candidate. Much of it has focused on the 'drug-like' or 'lead-like' nature of screening compounds or synthetic candidates10–14. The argument raised was that if compounds were selected for optimization that required a considerable number of synthetic cycles to produce novel analogues that address ADMET (T = toxicity) deficiencies then this lengthened the time needed to arrive at a clinical candidate. If, however, the compound was 'drug-like', or perhaps more preferably 'lead-like'15 from the outset, then it should be easier to arrive at the appropriate biopharmaceutical properties and in a shorter timeframe16. Such aspirations are based on sound logic and have been implemented within the current practices of the pharmaceutical industry10,17. One of the simplest of these procedures is a structure and functional group filter that removes compounds considered unsuitable as hits such as those containing toxic functional groups18.</p><p>Research into drug-like and lead-like concepts has explored a range of ideas looking at structural characteristics and physicochemical properties. These studies have included examinations of molecular frameworks19,20, molecular properties12–14, 21, 22 and the prediction of ADME parameters23 to name but a few. In addition, compounds that target the CNS have also been analyzed to profile their physicochemical characteristics and to predict CNS activity24–26. As such, it is becoming entrenched within the medicinal chemistry community to look extremely closely at the characteristics of the molecules they deal with and to work on those known to have suitable properties. Once again, it makes logical sense to operate most of your time in areas where there is a history of successful outcomes and where efficiencies can be garnered.</p><p>Our knowledge of the overall proportion of acids, bases and pKa distributions is less understood than other aspects of drug and lead-likeness. For example, statements often describe drugs as 'typically weak acids and/or weak bases'. The proportion of drugs with an ionizable group has been estimated at 95%27 while an analysis of the 1999 World Drug Index (WDI28) showed that only 62.9% of that collection were ionizable between a pH of 2 and 1229, 30. Wells also estimated that 75% of drugs are weak bases, 20% weak acids and the remainder contained non-ionics, ampholytes and alcohols27. A breakdown of the WDI set of ionizable compounds showed that two thirds of them had either a single basic group or two basic groups (Figure 1A). The next major group of compounds containing one or two acids made up 14.6% of this set while simple ampholytes with one acid and one base comprised 7.5%. To analyze the WDI database (51,596 compounds) the Chem-X software31 was used to discriminate acids and bases. The details of which functional groups were used is not easily discernable, however the concept of exploring a pKa range of 2–12 is admirable given that the term ionizable used by Wells may possibly have encompassed a greater proportion of compounds. This may also suggest why only 62.9% of compounds in the WDI were considered of interest compared to Wells figure of 95%27. It should be noted (and presumed) that the two sets of drugs considered by the individual authors would have differed. On a smaller set of compounds (n = 53) with known capacity to cross or not cross the BBB it was32 concluded that "compounds with minimally one charge with a pKa <4 for acids and correspondingly a pKa >10 for bases do not cross the BBB by passive diffusion." The references cited above are among the few that touch on both pKa and the proportion of ionizable compounds within a set of drugs. It may be that dealing with pKa is occasionally troublesome for a number of reasons, e.g. access to measured data is not simple, calculation of large numbers of pKa values is cumbersome and compounds may contain variable numbers of ionizable groups. Consequently the pKa does not lend itself to simple calculation and comparison, such as molecular weight or polar surface area (PSA) might allow.</p><!><p>In order to conduct an analysis of the proportion of acids and bases, and pKa distributions, suitable databases of pKa values are required. Several sets of pKa values are available such as PhysProp (Syracuse Research Corporation, North Syracuse, USA), Williams compilation in Foye's textbook33, the Merck Index34, Avdeef 35, IUPAC and related compilations36–41, CRC Handbook42, Lange's Handbook of Chemistry43, ACD/labs software and database44 as well as the general literature. In some cases these data resources do not assign pKa values to particular functional groups. The Williams set (see Methods for details)33 used in this current study simply specifies whether the pKa value is derived from an acid or a base and this feature was an important factor in selecting this dataset for the analysis. Other issues to keep in mind are data quality as these compilations stem from many laboratories. In an ideal world it would be prudent to return to the original study to investigate how the measurements were undertaken and how problems (e.g. apparent pKa values, decomposition, precipitation, poor UV absorbance, use of co-solvents, complex multi functional compounds) were handled. This perhaps is another reason why the pKa distribution of drugs has not been described in detail for the analysis of drug-like character.</p><p>The goal of these analyses is to provide an indication of the spectrum of pKa values and the proportion of acids and bases within a drug discovery environment. This is with particular regard to drugs that have made it to the marketplace so that this may influence drug discovery processes in general. It could be envisaged that analyses of corporate collections, third party suppliers and combinatorial libraries (real or virtual) are undertaken to determine whether their distributions match that of marketed drugs. Following this, decisions could be made to add to collections where certain classes of compounds or pKa ranges are underrepresented and to influence synthetic directions. In the simplest sense it may add information regarding the overall composition of compound collections which can be discussed accordingly. Computational tools oriented to looking at ionizable groups as well as tautomer states45 have recently been established. One example is the ProtoPlex module within Sybyl46 which can populate a database with alternative tautomers and protomers for each compound. Other workers have also striven to represent compounds in the most appropriate way by considering ionizable groups and tautomers. Kenny and Sadowski47 described their technique which is able to apply formal charges to selected functional groups. They also emphasized the importance of their work in procedures such as virtual screening. Pospisil and co-workers also showed that tautomer state affected docking scores in virtual screening45 thus emphasizing the importance of considering pKa on how we conduct drug discovery. Overall it is clear that the pKa value(s) of a substance is fundamental to many areas of early and late stage discovery and that knowledge of pKa distributions will be similarly important to improve how we discover and develop new medicines.</p><!><p>To explore the proportion of ionizable compounds to non-ionizable compounds the World Health Organization's (WHO) essential medicines list was employed (March 200548). This represents a list of "minimum medicine needs for a basic health care system", together with a set of complimentary medicines for priority diseases. It may be viewed as a mini-pharmacopoeia, however the makeup of the set will differ somewhat to more extensive lists of drugs. Nevertheless it serves to encompass a range of drug classes for a wide range of medical needs. Compounds were classified into three groups: those with an ionizable group within the pKa range of 2–12 (determined using the ACD/labs software44), those without an ionizable group and a miscellaneous set containing proteins, salts and others (e.g. gases, mixtures, polymers, metal complexes, etc). The proportion of ionizable compounds was determined for the entire set and a selected subset that excluded the miscellaneous set.</p><p>The list of pKa values compiled by Williams33 was used as the source of data for the present study. An examination of the list was undertaken and the original set of 599 compounds was reduced to a final set of 582 for analysis. Within this list the source references are given and most of the values come from Hansch in Comprehensive Medicinal Chemistry Volume 649 which is itself a secondary literature compilation. The Williams list33 was chosen for its assignment of acids and bases, accessibility and representation of a range of compound classes. The initial curation step included removing duplicates (e.g. bupivacaine and levobupivacaine; where the pKa is equivalent) and those compounds without a pKa value. For inclusion the compound was required to have a clinical use (either past or current use) or was considered safe for human consumption or represented an interesting chemo-type (e.g. saccharin). Data misplaced in columns was adjusted and where pKa values for acid and base groups had been swapped this was amended. In some cases incorrect values were revised (e.g. tiaprofenic acid) and compounds with non-standard names were excluded where this led to ambiguity of the correct substance.</p><p>In addition to this examination, an assessment was made regarding whether the compound was intended for CNS use. In some cases this was not easy to define particularly when the drug has been targeted towards peripheral sites but has CNS side effects. A classic example is the first generation of histamine H1 receptor antagonists that were developed for the treatment of hay fever but often caused drowsiness. Where sedative activity was listed as an indication for the drug then it was annotated as a CNS drug (e.g. trimeprazine). Cocaine, albeit used clinically as a local anaesthetic, has well known CNS effects and was also classified as a CNS substance. In some cases the classification was difficult to assign and, for the most part, the decision was based on the intended uses of the drug.</p><p>Analysis of the distribution of pKa values was applied to three groups of compounds: those containing a single acid, a single base and ampholytes with 1 acid and 1 base. Histograms for the distributions required binning the compounds into ranges (i.e. 0.5 < X ≤ 1.5, 1.5 < X ≤ 2.5, etc). In each case column heights were expressed as a percentage. Ampholytes (1 acid, 1 base) were also further classified as either ordinary (base pKa < acid pKa) or zwitterionic (base pKa >acid pKa) compounds. In order to plot and compare the ampholytes the isoelectric point was determined ([acid pKa + base pKa)/2] and the values binned in a similar manner to the pKa values.</p><!><p>The proportion of acids and bases in the Williams33 dataset of 582 compounds was determined by reviewing the pKa data and summing the number of compounds containing a single base, single acid, and so forth. Table 1 (Entire dataset) shows that almost half the compounds had a single base (45.4%) while single acid compounds made up about a quarter of the total (24.4%). Ampholytes comprised 14.8% of the total of which 65 compounds (11.2%) were considered to be simple ampholytes containing a single acid and base. The other major group was those compounds with two basic groups representing 10.5% of the total. Figure 1B clearly shows the distribution of the 582 compounds demonstrating that over half the compounds are basic in nature (56.5%) [i.e. containing 1, 2 or 3 basic groups without an acidic group].</p><p>Splitting the entire list into CNS (n = 174) and non-CNS (n = 408) compounds allowed the construction of pie charts for each of these individual groups. Figure 1C, together with Table 1 (CNS subset) show that the CNS class of compounds is dominated by those containing a single basic group (62.1%). If these compounds are combined with those possessing 2 bases this represents 75.3% of the total. The proportion of compounds containing a single acid was 15.5% while ampholytes (13 compounds) only made up 7.5% of this subset.</p><p>The non-CNS group of compounds showed a distribution similar to the entire dataset of 582 compounds and this no doubt was influenced by the large number of compounds that make up this set (n = 408). Figure 1D and Table 1 (Non-CNS) demonstrate that compounds with one or two basic groups now comprise less than half the total (47.5%). The single acids comprised 28.2% and if combined with compounds containing two and three acids these make up about one third of the total. Simple ampholytes on the other hand made up 12.7% of this subset consisting of 52 compounds. Table 2 compares the percentage of compounds containing acids and bases between the Williams lists33 and the analysis conducted on the WDI29,30. In general the WDI has fewer compounds containing a single acid and a greater number of compounds with two basic groups. The number of compounds with a single basic group was similar between the entire Williams list and the WDI.</p><p>The Williams33 compilation did not, of course, list non-ionizable compounds as its prime interest was in those substances with a pKa value. To estimate the proportion of non-ionizable compounds in a similar manner to the analysis by Comer and Tam29,30 the WHO essential medicines list was used as a minimum set of therapeutic substances and compounds. The WHO list was consolidated to 301 compounds from their March 2005 edition. Of these, 196 (65.1%) contained an ionizable group with a pKa in the range 2–12. This result is very similar to that obtained by Mitchell of 62.9%29,30. If we remove the miscellaneous compounds (e.g. proteins, salts, mixtures, polymers, gases, etc) from the analysis then we obtain a figure of 77.5% of compounds that contain a relevant ionizable group. This is in contrast to the 95% estimate of Wells27 and may be a consequence of the small size of the WHO dataset and the inherent limitations for compounds to be included in the list. Alternatively, Wells27 may have included compounds with ionizable groups outside the pKa range of 2–12.</p><!><p>From the Williams set33 single acid containing compounds consisted of 142 substances and a representative sample of these is shown in Figure 2. The distribution of pKa values is shown in Figure 3 and this also illustrates both the CNS and non-CNS classes. Each column is given as a percentage to allow for the differing sizes of each group. An examination of all 142 acids shows that there is a bimodal distribution with a dip in numbers at a pKa of around 7.0. Compounds at the lower end of the scale largely contain carboxylic acids while those peaking around a pKa value of 8.0 contained a large proportion of barbiturates.</p><p>Within the CNS class only 27 compounds had a single acid. While this is a low number, the distribution of pKa values was nonetheless very interesting. Figure 3 shows that the majority of acids had a pKa above 7 and only one fell below 6.1 (valproic acid = 4.8).</p><p>When the non-CNS class was inspected the bimodal distribution of pKa values was again portrayed showing the dip in frequency close to 7.0. Within this set of 115 compounds those with lower pKa values were predominantly carboxylic acids.</p><!><p>In contrast to the distribution of acids and perhaps as expected, the base pKa values peaked at a value of 9.0. The majority of compounds had a pKa value above 6.5 and these compounds typically contained a basic amine group. At the lower end of the pKa scale various functional groups were represented (e.g. nitrogen containing heterocycles). Figure 4 shows a set of representative bases containing various heterocycles and amines. In all, 264 compounds contained a single base making up just under half of the total set analyzed. Figure 5 shows the distribution of base pKa values ranging in value from 0.1 to 12.3. Once again the CNS and non-CNS classes have been included to allow a comparison of the three groups.</p><p>The CNS class (n = 108) showed a clear cut off at the high end of the pKa scale. Indeed, there were no bases with a value above 10.5. Once again the majority of compounds had a pKa above 7 and mostly consisted of amines. The distribution for the non-CNS class closely matched the overall pattern found for the entire dataset with a peak in pKa values at around 9.0. pKa values for the non-CNS compound set (n = 156) ranged from 0.3 to 12.3.</p><!><p>In order to analyze the distribution of simple ampholytes (i.e. single acid and base) they were first classified as either ordinary or zwitterionic ampholytes and the isoelectric points were calculated. Figure 6 illustrates the range of isoelectric points for both the ordinary and zwitterionic ampholytes. While no clear pattern emerges this may be a reflection of the limited number of compounds (65) available for this analysis. The larger number of ordinary ampholytes at the high end of the scale represent simple phenols with alkylamine side chains (e.g. phenylephrine). If these compounds are left aside, those that remain tend to have isoelectric points between 3.5 and 7.5.</p><p>When the CNS and non-CNS drugs were compared interesting differences were observed. For the CNS class there were 13 simple ampholytes which made up only 7.5% of the 174 CNS compound subset. Of these 13 compounds there were six opioids and six benzodiazepines all of which were ordinary ampholytes. In contrast, the non-CNS subset contained 52 ampholytes comprising 20 zwitterions and 32 ordinary ampholytes. No doubt the predominance of ordinary ampholytes in the CNS class reflects the neutral character of these compounds at their isoelectric point where neutrality would favour CNS penetration.</p><!><p>One concern over the analyses conducted in this study may be the choice of datasets used. This is a problem that plagues any analysis of drug sets that aim to tease out trends in physicochemical characteristics. The set employed should of course be representative of drugs as a whole to enable reasonable conclusions to be drawn. To look at the proportion of ionizables the WHO essential medicines list48 was used which represents a small pharmacopoeia for priority health care needs. It is overrepresented in certain drug classes (e.g. antibiotics) and lacks a range of medicines which are costly or merely enhance the quality of life (e.g. selective serotonin reuptake inhibitors, HMG-CoA reductase inhibitors, PDE 5 inhibitors, etc.). Nevertheless it is a well thought-out list covering the majority of therapeutic classes. In contrast, the WDI dataset used by Comer and Tam29, 30 consisted of 51,596 compounds and could be viewed perhaps as a master list of drugs. The WDI, however, includes pesticides, herbicides and compounds that did not reach the market place. Given our desire to be representative of drugs it is not an ideal set and may be considered too encompassing. Our analysis therefore of the proportion of compounds that are ionizable is very dependent on the dataset used and provides results specific to that set. Another option is to examine all the drugs used commercially around the world such as those listed in Martindale50. This contains over 5000 drug monographs and an analysis based on this set would be an onerous task. The obvious alternative is to choose a smaller set that has undergone an evolutionary process to select useful therapeutic substances (e.g. through evidence-based therapy), such as the AHFS Drug Handbook51 (a subject of future research in this laboratory). Until such time that an agreed set of compounds can be selected to determine how many are ionizable the numbers generated here using the WHO list (65.1%) is comparable to the WDI findings of Comer and Tam29,30 (62.9%) and is far less than the 95% estimate described by Wells27. It is not clear which compounds Wells considered or how an 'ionizable compound' was defined. A more interesting analysis might be where strict criteria are used for compounds to be included in a survey. For example, organic compounds of molecular weight <1000 together with a use in mammalian therapy in an oral (or injected) form. For small organic substances this would give a better indication of the proportion of compounds possessing an ionizable group.</p><p>The Williams list of compounds33 could also be scrutinized in the same manner as the WHO essential medicines list. It is however, an extensive set of substances and represents a wide range of therapeutic classes. Once again better and more recent sets could be devised for this study and the Williams set was selected as a useful representative set and for the large number of compounds it contained. As mentioned above this aspect of the study is being addressed in future work in these laboratories using the compounds listed in the AHFS Drug Handbook51.</p><p>Until such time that these larger and more recent data sets are analyzed this present study provides an interesting insight into both the proportion of ionizable substances and the distribution of pKa values. The catch all phrase describing drugs as mainly 'typically weak acids and/or weak bases' certainly holds true when the pKa distributions are viewed (Figures 3 and 5). The power of the present analysis is to flesh out the bones to this simplistic description and provides a starting point for discussing pKa distributions. In particular, the apparent biphasic distribution of acid pKa values needs to be investigated further. Another important aspect to this research has been the scrutiny applied to CNS compounds. While, there is a general understanding concerning the principles behind the distribution of acid and base pKa values for CNS drugs, this has not been well documented or presented in the literature. For example, it is known about the paucity of CNS compounds with acid pKa values below 4.0 and base pKa values above 10.032. Also recognized is the sensibility of these values as charged substances do not easily cross the BBB. Acids with pKa values below 4 will be in a charged state over 99% of the time at physiological pH as will bases with a pKa above 10. The cutoff values described by Fischer and coworkers32 concur with the observations presented here, although only one compound had an acid pKa below 6.1. The important aspect of this present study was to outline the distributions themselves to demonstrate the spectrum of pKa values. Indeed, the overall implication is that this is valuable information when contemplating the properties needed for a drug or sets of screening compounds.</p><!><p>The utility of the distributions described here may be applied to third party supplier databases for purchasing decisions regarding screening compounds. Either the ratio of ionizable to neutral compounds could be applied or the pKa distributions could be used in the selection process. One thing that needs to be borne in mind is that the work described in this study has emerged from an analysis of drugs. Given that current screening efforts are oriented to lead-like molecules15 then the distributions need to be considered in this light. Certainly an analysis of an ideal screening set of lead-like compounds would yield the appropriate data. In the absence of this we need to look at the guidelines suggested for lead-like character. These follow the criteria outlined here: MW < 350, logP < 3 and affinity approximately 100 nM16. In other words there is scope for chemists to take a small molecule with reasonable activity and enter this into rounds of optimization for activity, selectivity and biopharmaceutical properties. The physicochemical criteria listed above are very simple, however pKa and logD are not considered. Perhaps a simple ratio of ionizable to non-ionizable compounds needs to be suggested (e.g. 3:1, respectively). Furthermore the makeup of the ionizables also needs to be considered by selecting compounds with single acids, single bases and ampholytes, in approximately the ratios outlined in Table 2. More complicated combinations of acids and bases or those with 2 or more acids and bases should be kept to a minimum. These suggestions are purely speculative and are open to debate; suffice to say that the compounds should contain a mix of neutral and ionizables in roughly the ratios seen for drugs as well as allowing chemists the possibility of adding further ionizable groups to enhance activity and biopharmaceutical characteristics as part of the optimization process.</p><!><p>Ionizable groups on drug molecules have two principal functions. The first is to modify overall polarity, which in turn controls other physicochemical properties, such as aqueous solubility or hydrophilicity. The second is to provide functional groups that can interact with target macromolecules in specific ways. Organic chemists, on the other hand, do not necessarily consider ionizable groups as first priority groups to include on a novel compound. A chemist, for ease of synthesis may prefer to work with non-polar compounds that are soluble in organic solvents. Another human consideration is the simplicity of the chemistry. Straightforward synthetic schemes will no doubt predominate to reduce the number of steps required. Given that ionizable groups often require protection means that additional synthetic steps are needed and introduces a further level of difficulty. Taking all this together suggests that organic compounds made to date will largely be lacking in ionizable groups. Furthermore, many of the third party suppliers need a large number of new substances for their catalogues which means that a high throughput is required from their chemists. High throughput will be a driver for simpler chemistry and, using the argument above, will result in compounds lacking ionizable groups. Of course, this trend has been identified and is being specifically addressed for compounds with utility in medicinal chemistry. This refers to Lipinski's10 observations but the historic collections available will certainly be influenced by the (Darwinian) principle of 'simple chemistry wins'.</p><p>Medicinal chemists also follow the principles of organic chemistry and prefer to introduce polar (ionizable) groups in the latter stages of a synthesis (e.g. protecting group removal). The last step of a synthesis can also be engineered to be one that can introduce diversity to generate a set of analogues. Third party screening compound suppliers, however, obtain a proportion of their catalogue from organic chemists rather than medicinal chemists. As such it may be that these offerings do not follow the same acid/base/pKa distributions as drugs. Consequently, an examination of acid/base/pKa distributions will be beneficial to ensure that a suitable mix of compounds is chosen for screening, irrespective of the source.</p><p>An overriding question fundamental to this study concerns the pKa distributions themselves. Two separate influences will ultimately shape these findings. The first is chemical in nature concerning the functional groups that comprise the acid and base moieties. If we took the universe of organic compounds (a good representative subset might be the organic compounds contained in the CAS collection) and produced pKa distribution plots then it would be possible to see how drugs compare. It may be that single acid containing compounds don't exhibit a bimodal distribution and that drugs specifically lack groups with pKa values around 7.0. Similar arguments could be directed at basic compounds and that the distributions we observe for drugs are a function of the regularly seen groups used in these compounds. Certainly, toxic functional groups will be very limited in the Williams set33 and this may also affect the pKa distribution. The second driver for the pKa distributions is biological in nature and is affected by membrane properties and the drug targets themselves. It is known that 7-transmembrane G-protein coupled receptors (7TM GPCR's) have a key aspartic acid residue to recognize the amine group on their endogenous ligands52. The need for an amine in drugs that interact with 7TM GPCR's is almost an absolute requirement. If we combine this with the fact that a high percentage of drug targets are 7TM GPCR's53 then it will follow that amines will be well represented (particularly for CNS compounds) in the Williams set33. Our knowledge of pKa distributions for a number of functional groups is quite reasonable but not when these are considered collectively. Presumably the pKa value is a quantity which does not have a smoothly distributed continuum of values, but is necessarily multimodal because of the types of functional groups that exist in organic chemistry. In that sense, it is unlike logP, which has a much more broadly distributed set of values. This is a research area that will no doubt develop as larger populations of compounds are studied.</p><p>The task of identifying acids and bases in a database is a readily achievable task. A more difficult procedure is to estimate the pKa values for these compounds. With regard to accuracy we preferably seek to predict within one log unit of the measured value. A variety of computational approaches are available and this topic was reviewed recently by Wan and Ulander7. A number of methods are used within the commercial packages (e.g. ACD/Labs44) such as the use of QSAR models based on Hammett analyses. Typically, a molecule is fragmented and the pKa of the functional group is estimated by referring to a database of values with associated QSAR equations. Artificial neural network methods have also been used to estimate pKa and the software available from Simulations Plus is one such example54. The ADME Boxes package from Pharma Algorithms55 also estimates the total number of ionizable groups and predicts the principle pKa values. The other primary method of estimating pKa values is through quantum mechanical techniques. The advantage here is that they can adapt to new chemical classes and do not necessarily need prior examples within the algorithm. In each case, and to differing degrees, estimates can be complicated by conformational flexibility, solvent handling, conjugated systems and a lack of relevant examples. The needs of the pharmaceutical industry are challenging as they regularly explore novel structural scaffolds to enter new patent territory. If the software requires prior examples of a functional group or scaffold then accuracy may be compromised. For the purposes of characterizing a database, speed of calculation is a priority and may take precedence over accuracy. There are many computational hurdles yet to be tackled to provide a chemist friendly, fast and accurate system of estimating pKa values within large databases (100,000's compounds). Among the considerations are problems such as conformational flexibility, internal hydrogen bonding, solvent effects and multiprotic influences7. Fortunately, several groups are working on better prediction methods and this will ultimately influence how we undertake research for new medicines.</p><!><p>This study has begun to explore the overall composition of drugs with regard to the proportion of those compounds containing an ionizable group. Within the WHO essential medicines list 65.1% of compounds had an ionizable group with a pKa in the range 2–12 and this number rises to 77.5% when non drug-like compounds are removed. Other estimates give this number as anywhere between 62.9%29,30 and 95%27. It is certainly clear that this figure is influenced by the collection being studied and how 'ionizable' is defined, and will be the subject of future research from our laboratories.</p><p>Analysis of Williams collection of drugs33 has led to a description of the relative proportions of compounds containing acidic and basic functionality. More importantly, the distribution of pKa values has been outlined in detail for the first time. Two clear findings emerged upon examination of the distributions particularly when a distinction was made between CNS and non-CNS drugs. Firstly, acid pKa values for CNS drugs rarely fell below 6.0 and secondly, base pKa values for CNS drugs were not observed above a value of 10.5. From an ionization viewpoint these observations are entirely reasonable when considering the nature of the BBB and the passage of charged substances across membranes. As such, these observations consolidate current wisdom in the area and open the way for larger collections to be compared to these distributions.</p><p>Without doubt pKa is of paramount importance to the overall characteristics of a drug and has considerable influence on biopharmaceutical properties. Current trends indicate that future research is placing an increased focus on pKa with the advent of high throughput measurement techniques and improvements to computational prediction software7. By taking pKa into account allows the researcher to begin ADME profiling early in the discovery process. Moreover, with large collections of compounds such as corporate databases, third party supplier offerings and virtual sets of compounds (e.g. virtual combinatorial libraries), the researcher can examine both the proportion of ionizable compounds and with prediction methods can start to look at pKa distributions. If these differ largely from the observations outlined in the current study then it allows the opportunity to amend synthetic directions or screening compound selections.</p><p>The drive to consider the physicochemical properties of drugs to understand biopharmaceutical characteristics began many years ago (e.g.10). This has fundamentally changed how discovery work is undertaken and was oriented to improving the efficiency and productivity of pharmaceutical companies. Likewise, the need to explore pKa will begin to influence how we work. The findings presented here go some way to understanding the distribution of pKa values and further guidelines will evolve as larger datasets are analyzed.</p><!><p>The Williams33 dataset has been provided as supplementary material.</p>

PubMed Open Access

Haloboration: scope, mechanism and utility

Haloboration, the addition of B–X (X = Cl, Br, I) across an unsaturated moiety e.g., C <svg xmlns="http://www.w3.org/2000/svg" version="1.0" width="13.200000pt" height="16.000000pt" viewBox="0 0 13.200000 16.000000" preserveAspectRatio="xMidYMid meet"><metadata> Created by potrace 1.16, written by Peter Selinger 2001-2019 </metadata><g transform="translate(1.000000,15.000000) scale(0.017500,-0.017500)" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg> Y or C <svg xmlns="http://www.w3.org/2000/svg" version="1.0" width="23.636364pt" height="16.000000pt" viewBox="0 0 23.636364 16.000000" preserveAspectRatio="xMidYMid meet"><metadata> Created by potrace 1.16, written by Peter Selinger 2001-2019 </metadata><g transform="translate(1.000000,15.000000) scale(0.015909,-0.015909)" fill="currentColor" stroke="none"><path d="M80 600 l0 -40 600 0 600 0 0 40 0 40 -600 0 -600 0 0 -40z M80 440 l0 -40 600 0 600 0 0 40 0 40 -600 0 -600 0 0 -40z M80 280 l0 -40 600 0 600 0 0 40 0 40 -600 0 -600 0 0 -40z"/></g></svg> Y (Y = C, N, etc.), is dramatically less utilised than the ubiquitous hydroboration reaction. However, haloboration of alkynes in particular is a useful tool to access ambiphilic 1,2-disubstituted alkenes. The stereochemical outcome of the reaction is easily controlled and the resulting products have proven to be valuable building blocks in organic synthesis and materials chemistry. This review aims at providing the reader with a brief summary of the historic development and of the current mechanistic understanding of this transformation. Recent developments are discussed and select examples demonstrating the use of haloboration products are given with a focus on the major areas, specifically, natural product synthesis and the development of boron-doped polycyclic aromatic hydrocarbons (B-PAHs).

haloboration:_scope,_mechanism_and_utility

Introduction<!>The early work<!>Mechanistic studies<!>Recent studies into the bromoboration of simple alkynes with BBr3<!>1,1-Bromoboration of internal alkynes<!>Other alkyne haloboration reactions<!>Borocation mediated chloroboration of alkynes<!>1,2-trans-Chloroboration of alkynes<!>1,3-Chloroboration of alkynes<!>Chloroboration of diynes<!>Directed trans-bromoboration of alkynes<!>Haloboration of CC double bonds<!>Haloboration of EC bonds (EO, NR)<!>Application of alkyne haloboration products in organic synthesis<!>Haloboration as a tool in natural product synthesis<!>Haloboration in the synthesis of B-doped PAHs<!>Conclusion<!>Conflicts of interest

<p>Since the end of the last millennium, the principle of sustainability and atom economy increasingly has impacted the way scientific research is done.1 A chemical transformation that is 100% atom efficient is the addition reaction, in which a reagent is added across a multiple bond (e.g., CC, CC, or CE, E: O, NR). One very important addition reaction is the Nobel Prize winning hydroboration reaction.2 Initially, it was almost exclusively used to access alcohols from alkenes by oxidative B–C bond cleavage. However, organic transformations like the Matteson homologation,3 Petasis variant of the Mannich reaction,4 Chan–Lam coupling,5 and, of course, the Suzuki–Miyaura reaction6 all utilise substrates that can be accessed by hydroboration reactions, rendering it a powerful tool in the synthetic chemist's toolbox. Unsurprisingly, researchers still strive to develop new hydroboration methods, e.g., by expanding the scope or reducing the environmental impact.7 In contrast, haloboration – although discovered at roughly the same time – has remained a niche technique that has gained only a small fraction of the attention even though it adds an additional highly valuable group (a halide) in the same step. The concomitant installation of a boron unit and a halide generates functionality rich molecules, containing a nucleophilic C–B and an electrophilic C–X unit. Thus, it is surprising that this reaction is so under-utilised, despite being potentially useful to many.</p><p>In this review, we give a brief discourse of the historic development of the haloboration reaction, from the curiosity driven fundamental research mainly by the group of Lappert, to the usage of Pd catalysed cross-coupling reactions to demonstrate the full potential of haloboration from the group of Suzuki who broadened the scope and deepened the understanding of this reaction.8 We also provide an in-depth discussion of the underlying mechanism and select applications of the products from the haloboration reaction in the field of synthesis. Recently, haloboration has started to gain wider interest through its use in natural-product synthesis to introduce CC double bonds stereoselectively, and in the synthesis of boron-doped polycyclic aromatic hydrocarbons (B-PAHs), thus these are the main applications focused on herein. B-PAHs are a relatively new class of organic materials with interesting optoelectronic properties and haloboration is a fast and convenient way to incorporate a borane unit and a halogen functionality into a PAH at the same time. Since the publication of the last reviews on haloboration, which were in the 1980s to the best of our knowledge,8d the scope and utility of haloboration in synthetic chemistry has increased significantly. We hope that this review, focused on the use of boron electrophiles to haloborate CY and CY nucleophiles (Y = C, N or O based substituents) facilitates the wider application of this useful, yet often overlooked, reaction.</p><!><p>Chloroboration of alkynes was first explored by H. R. Arnold in 1946.9 With mercury(i) chloride on activated carbon as the catalyst, chloroboration of acetylene with boron trichloride (BCl3) was achieved to afford 2-chlorovinyldichloroborane at 150–300 °C (Scheme 1a). In this patent, the stereoselectivity of chloroboration was not determined. Subsequently, Jensen et al. repeated the synthesis under similar conditions and measured the dipole moment of the obtained product.10 The experimentally determined dipole moment (1.06(0.05) D) was found to be very close to the predicted value of trans-product 1 (1.05 D). For comparison, the dipole moment of the cis-isomer was predicted to be 3.23 D. Thus, trans-product 1 was believed to be formed. In addition, the trans-chloroboration product 1 was found to be significantly more stable than the cis-isomer by 145 kJ mol−1 in electronic energy based on ab initio calculations.</p><p>Subsequent to Arnold's work, Gipstein et al. found that when EtBCl2 was used, in spite of the reduced Lewis acidity compared to BCl3, the chloroboration of acetylene in the presence of activated carbon could be realised at 70 °C, affording product 2 (configuration not determined) in 90% yield (Scheme 1b).11 Later, Lappert and co-workers studied the chloroboration reaction with a variety of alkynes and boranes.12 For instance, phenylacetylene was reported to undergo chloroboration with one equivalent of BCl3 readily even at −78 °C to afford the syn-addition product 3. The obtained product 3 was shown to react with another equivalent of phenylacetylene in a syn-manner to give compound 4 (Scheme 1c). In the initial report by Lappert and co-workers, the configurations of 3 and 4 were assigned with incomplete evidence. Subsequent studies confirmed that chloroboration of terminal alkynes with BCl3 proceeds in a syn-manner.13 Although the reaction between BCl3 and terminal alkynes such as phenylacetylene occurs promptly, no reactivity was observed when internal alkynes such as diphenylacetylene and BCl3 were mixed at 15 °C. In accordance with the reactivity of BCl3, PhBCl2 readily reacted with two equivalents of phenylacetylene and compound 5 was obtained (Scheme 2a).12 In contrast, when 1-hexyne was treated with half an equivalent of PhBCl2, both chloroboration and carboboration occurred to give the product 6 (Scheme 2b). In a controlled reaction of 1-hexyne with Ph2BCl, carboboration occurred exclusively yielding compound 7 (Scheme 2c).</p><p>Lappert et al. also investigated the haloboration of acetylene using BBr3. The increased Lewis acidity of BBr3 (relative to BCl3) drastically facilitated the transformation which proceeded at room temperature and the addition product 8 was obtained (Scheme 3a). Alcoholysis of compound 8 with n-butanol afforded the known compound E-9Bu with specified configuration. The configuration of E-9Bu led the authors to assign a trans-configuration to 8. However, a recent study suggested the bromoboration of acetylene typically gives a mixture of E/Z isomers at around 0 °C (for further details and mechanistic discussion, see Sections 2.2 and 2.3). Lappert et al. also found that the addition of pyridine (Py) to 8 resulted in the elimination of Py·BBr3 and regeneration of acetylene, which indicated that the bromoboration of acetylene might be reversible (Scheme 3a). The bromoboration of acetylene with BBr3 followed by esterification with alcohols provides a convenient route to halo-alkenylboronates that serve as versatile building blocks (vide infra).</p><p>Although BCl3 does not react with internal alkynes, Lappert and co-workers found that bromoboration of diphenylacetylene occurs readily in neat BBr3 at room temperature within one hour. In this case, syn-addition product 10 was formed as confirmed by subsequent protodeboronation reactions with acetic acid (AcOH) to give 11 (Scheme 3b), with protodeboronation known to proceed with retention.12,14a Blackborow performed detailed studies on the bromoboration of 1-hexyne under various conditions (Scheme 3c).14 Generally, the bromoboration of the terminal alkyne proceeds in a Markovnikov fashion. The stereoselectivity, however, was found to be highly dependent on the reaction conditions. For example, when the reaction was performed at −80 °C in petroleum or dichloromethane, syn-addition product 12 was found to be dominant (98%) as determined by analysis post protodeboronation with AcOD. In contrast, when the reaction was performed at −40 °C, the stereoselectivity decreased with the major product being the anti-bromoboration product 13 (64%) while only 30% syn-addition product 12 was observed under these conditions. In addition to E/Z isomers, multiple haloborations to form the respective divinylbromoborane and trivinylborane also were observed. However, as the formation of these multiple borylation products is relatively slow under the reaction conditions and the product distribution was not well defined, these details are not discussed further here.</p><p>Subsequent to Lappert's work with BBr3, Eisch and co-workers found that the less Lewis acidic borane PhBBr2 reacts with diphenylacetylene in a reversible manner (Scheme 4a).15 Upon mixing PhBBr2 and diphenylacetylene, cis-bromoboration product 14 was formed rapidly, which was confirmed by protodeboronation with acetic acid. However, prolonged storage of compound 14 in hydrocarbon solvents led to the irreversible formation of carboboration product 15. This suggests that the bromoboration of diphenylacetylene with PhBBr2 is a kinetically favoured but reversible process while the carboboration is a slower and irreversible competing process. Wrackmeyer studied the reaction of 3-hexyne with BBr3 at −78 °C (Scheme 4b).16 When the sample was kept at room temperature for one hour, the syn-addition product 16 was found to be the major product in the reaction mixture (16 : 17 = 15 : 1). However, after several days, the E-isomer 17 became dominant with the ratio of 16 : 17 switching to 1 : 7.</p><p>Eisch also studied the reactivity of MeBI2 with diphenylacetylene. In this case, iodoboration occurred rapidly and compound 18 was obtained (Scheme 5a).17 Siebert found that iodoboration of 3-hexyne with BI3 furnished the syn-addition product 19 rapidly, which, in line with Wrackmeyer's observations, underwent slow isomerisation to form the anti-addition product 20 at room temperature (Scheme 5b).18,19</p><p>As discussed above, bromoboration of terminal alkynes with BBr3 does not occur exclusively in a 1 : 1 stoichiometry due to further reactions of the vinylBBr2 species with additional alkyne. One solution to this problem is to use 9-halo-9-borabicyclo[3.3.1]nonane (9-X–BBN; X = Br, I). Suzuki and co-workers found that 9-Br–BBN could react with one equivalent of 1-octyne to afford 21 in high regio- and stereoselectivity (Scheme 5c).20 They also found that 9-Br–BBN is inert to internal alkynes likely due to its lower Lewis acidity. These early studies clearly demonstrated the viability of alkyne haloboration, albeit complicated in many cases by formation of different haloboration isomers. The origin of Z- and E-configured haloboration products was at the time unclear and required subsequent DFT calculations to provide mechanistic insight.</p><!><p>The haloboration of alkynes was investigated computationally initially by Uchiyama and co-workers.21Ab initio calculations with second-order Møller–Plesset perturbation theory (MP2) were performed on the haloboration of acetylene and propyne using a dichloromethane continuum solvent model (Scheme 6). The two alkynes first form loose van der Waals complexes A with BX3 (X = Cl, Br, I), which then may transform into π-bonded complexes B if X = Br or I but not Cl. Intermediates A (X = Cl) or B (X = Br, I) then convert into the syn-addition products cis-Pvia four-centred transition state TS. Consistent with the observed reactivity of BX3 with alkynes (BBr3 > BCl3), the reaction energy barriers (energy of TS) decrease in order of BCl3 > BBr3 > BI3 for the syn-addition pathway.</p><p>An energy barrier of 33.8 kcal mol−1 was determined computationally for the cis-chloroboration of acetylene, which agrees with the experimental observations that chloroboration of acetylene required a high reaction temperature and a catalyst. In addition, the haloboration of propyne was found to have a lower energy barrier than acetylene, which is ascribed to hyperconjugation stabilising the developing positive charge at carbon in TS (when R = Me). Furthermore, the anti-Markovnikov pathway for the chloroboration of propyne was also explored computationally. The transition state of anti-Markovnikov pathway TS-a (X = Cl, ΔG‡ = 35.6 kcal mol−1) was found to be much higher than the Markovnikov pathway (X = Cl, ΔG‡ = 15.5 kcal mol−1). The results fit well with the high regioselectivity of terminal alkyne haloboration reactions. For all transformations, the trans-haloboration products trans-P also were computed. For acetylene, they were found to be thermodynamically more stable than the cis-products, which is in agreement with the observation that the trans-chloroboration product was formed exclusively at high temperature in the aforementioned reports (cf. Section 2.1). In contrast, the syn-addition products of propyne haloboration are very close in energy to their anti-addition isomers. Again, this result is consistent with the observation that bromoboration of 1-hexyne at temperatures above −40 °C gave a mixture of both isomers. After the exploration of several different potential reaction pathways, Uchiyama and co-workers proposed that the stereoconversion proceeded via a haloboration/retro-haloboration mechanism of cis-P with BX3 (Scheme 7).</p><p>The chloroboration of the internal alkyne 2-butyne, and propene was also investigated. For both substrates, the chloroboration was found to be endergonic at 293 K (ΔG = 2.8 kcal mol−1 for 2-butyne; ΔG = 9.4 kcal mol−1 for propene) consistent with that lack of reactivity between BCl3 and internal alkynes and olefins.</p><!><p>In Lappert's initial studies, the stereoselectivity for the bromoboration of acetylene was determined by analysis of the post-esterification (conversion of C–BBr2 to C–B(OR)2) products. Recently, Mazal and co-workers carried out similar haloboration experiments at 0 °C and monitored the formation of E/Z vinylbromoborane 8 by NMR spectroscopy (Scheme 8a). With BBr3 distilled from Mg turnings, a mixture of E/Z isomers was obtained (E : Z = 15 : 85). Interestingly, addition of small amounts of water, NEt3 or [n-Bu4N]Br to the bromoboration reaction facilitated the formation of anti-addition product E-8. It is even more notable that the authors exclusively found the trans-vinylboronate E-9Pin post esterification workup. They proposed radical or polar addition mechanisms involving adventitious HBr to rationalise the observed reactivity.22 By modifying the workup procedures to avoid the formation of HBr, a mixture of E/Z-bromovinylboronate E/Z-9Et could be obtained, which was subjected to transesterification with pinacol, yielding E/Z-9Pin. Selective decomposition of the E-isomer (AcOK, MeOH) enabled the isolation of Z-bromovinylboronate Z-9Pin in useful yields (Scheme 8b).</p><p>In their proposed radical mechanism, a cis-bromoboration of acetylene occurs first to give Z-8 with an energy barrier of 24.1 kcal mol−1 (MP2/6-31+(d)/PCM(DCM)). Attack of a bromine radical (proposed to be generated from adventitious HBr) on Z-8 proceeds with almost no barrier (1.8 kcal mol−1). Bond rotation followed by bromine radical elimination was then assessed to afford the trans-bromoboration product E-8. An anti-addition of BBr3 and Br− to acetylene was also suggested for the formation of E-8. Acetylene was calculated to first form a π-bonded complex with BBr3, which was then attacked by Br− to form a borate intermediate. Abstraction of Br− with BBr3 from the intermediate gave E-8. The energy barrier for this process was determined to be 12.6 kcal mol−1.</p><!><p>Recently, the group of Ingleson have revisited the reaction of internal alkynes with BBr3. Consistent with Lappert's observations, they found that in non-polar solvents such as heptane, the reaction of diphenylacetylene with BBr3 at room temperature afforded the cis-1,2-addition product 10 within a few minutes.23 However, upon heating to 60 °C or prolonged standing at room temperature, the 1,1-addition product 22 was observed (Scheme 9a). When a polar solvent such as dichloromethane was used in the haloboration reactions, both 10 and 22 were formed within a few minutes with 22 being the major product (Scheme 9b). No trans-1,2-bromoboration product was observed by in situ NMR spectroscopy at any stage of the reaction. These observations suggest that 1,1-bromoboration proceeds through a polar transition state, likely a vinyl cation type intermediate(s) which is more stabilised by the more polar solvent dichloromethane. Upon reaction with pinacol and NEt3, compound 22 was converted into the corresponding pinacol ester 23 while 10 was converted back into diphenylacetylene. The 1,1-bromoboration could be extended to diarylalkynes and arylalkylalkynes, providing a convenient way to 1-bromo-2,2-diaryl substituted vinylboronate esters.</p><p>This is a further example that the reactions of alkynes and BX3 can give conditions dependent outcomes. Nevertheless, the use of the appropriate conditions and work-up can lead to isolation of a single haloboration product in useful yield. This diversity in outcome (1,1-, syn-1,2- or anti-1,2-haloboration products being accessible) arguably increases the power of the haloboration transformation.</p><!><p>This section covers recent synthetic reports that use other (i.e., not Y2B–X, Y = X or R) boron electrophiles or provides alkyne haloboration products that are distinct to those reported in the work discussed in Section 2.</p><!><p>As discussed in Section 2.2, Uchiyama and co-workers found the chloroboration of internal alkynes with BCl3 to be thermodynamically uphill. However, more electrophilic boranes such as BBr3 and BI3 react with internal alkynes readily. Therefore, Ingleson et al. envisioned the use of more electrophilic chloroborane species, such as borocations, to enable internal alkyne chloroboration.24 They prepared the boronium (tetracoordinate at B mono-cation) salt [Cl2B(2-DMAP)][AlCl4] (2-DMAP = 2-dimethylaminopyridine) by sequential addition of 2-DMAP and AlCl3 to BCl3 (Scheme 10a). Due to the strain within the four-membered boracycle, this complex showed a low energy barrier to ring opening and reacted as a masked borenium (= tricoordinate B monocation) ion. [Cl2B(2-DMAP)][AlCl4] reacted with one equivalent of a terminal alkyne at room temperature with high regio- and stereoselectivity. In contrast to the haloboration of alkynes with neutral BX3 which proceeded via a four-membered transition state with concerted formation of B–C and Cl–B bonds, chloroboration of phenylacetylene with [Cl2B(2-DMAP)][AlCl4] was calculated to proceed via a vinyl-cation intermediate, 24a. Intramolecular chloride transfer in 24a occurs with an energy barrier of 24.9 kcal mol−1 to give 24b (at the M06-2X/6-311G(d,p)/PCM(DCM) level of theory), which then rearranges to afford the chelated compound 24. Although the reaction between the boronium complex and terminal alkynes was facile, no reactivity was observed between [Cl2B(2-DMAP)][AlCl4] and internal alkynes. This is presumably due to the requirement to open the four-membered boracycle within [Cl2B(2-DMAP)]+ prior to the haloboration reaction, coupled with the significant N → B π donation (as shown in 24b) in the borenium isomer of [Cl2B(2-DMAP)]+ (reducing the Lewis acidity at B) leading to unfavourable energetics.</p><p>Ingleson and co-workers also reported that when the borenium salt [Cl2B(Lut)][AlCl4] (Lut = 2,6-lutidine) was used, syn-addition of the B–Cl bond across both terminal and internal alkynes occurred (Scheme 10b), presumably due to the enhanced electrophilicity at B in this borocation relative to the 2-DMAP analogue. Good chloroboration stereoselectivity was achieved for dialkyl, diaryl and arylalkylalkynes. Remarkably, for arylalkylalkynes, regioselective chloroboration could also be readily realised. All the products could be converted into the corresponding pinacol boronate esters by subsequent esterification with no loss in stereo-/regioisomeric purity.</p><!><p>Chloroboration of alkynes typically proceeds in a syn-manner. The group of Ingleson found that treatment of 2-dimethylaminotolan with BCl3 gave the unusual anti-addition product 25 (Scheme 11a).25 Subsequently, Pei and co-workers reported that 2-aminotolan also reacted with PhBCl2 to give the trans-chloroboration product 26 (Scheme 11b).26 The reaction was proposed to be initiated through the activation of the triple bond by the boron moiety, which was then followed by a nucleophilic attack of the alkyne with chloride. This method serves as a convenient way to prepare B,N-fused polycyclic aromatic hydrocarbons. The disparity between the formation of five membered 25 and six membered 26 is notable. This can be attributed to the all sp2-containing 26 having a strong preference for forming six membered boracycles via electrophilic borylation, while the incorporation of a single tetrahedral centre (as in 25) leads to five membered boracycles from electrophilic borylation being the favoured products.27</p><!><p>In 2018, Melen et al. reported a unique 1,3-chloroboration of propargyl esters.28 By treating propargyl benzoate with 1 equivalent of PhBCl2, an intermediate dioxolanonium ion was proposed to be formed via boron promoted cyclisation. The intermediate was assumed to subsequently undergo ring-opening and chloride migration to furnish the corresponding product 27 in high yield at room temperature (Scheme 12a). Interestingly, for a related propargyl ester with two methyl groups at the propargylic position, 1,1-carboboration occurred when PhBCl2 was added to give 27a (Scheme 12b), presumably due to dimethyl substituents leading to a higher barrier for the 1,4-chloride transfer.</p><!><p>Ingleson and co-workers found that 1,6-heptadiyne reacts rapidly with BCl3 at room temperature to afford a chlorinated cyclohexene featuring an exocyclic vinylBCl2 moiety.29 The corresponding pinacol protected compound 28 could be isolated in high yield post esterification with pinacol/NEt3 (Scheme 13a). In this case terminal alkyne 1,2-haloboration must have a higher barrier than intramolecular reaction of the alkyne–BCl3 adduct with the second alkyne. Furthermore, the reaction outcome was highly solvent dependent, with dichloromethane and dichloroethane affording 28 in good yield, whereas the use of chloroarenes resulted in very low yields of 28, suggesting the vinyl chloride is made via a carbocationic intermediate, which can engage in side-reactions with aromatic solvents.</p><p>Although BCl3 shows no reactivity towards internal alkynes, facile transformations between BCl3 and 1,2-dialkynyl benzenes have been reported by the groups of Erker, Yamaguchi and subsequently Ingleson.30,31 Presumably these proceed from the adduct between the internal alkyne and BCl3. In these reports, dibenzopentalenes or analogues were the major products in most cases (Scheme 13b). However, Ingleson et al. found that by introduction of electron donating groups such as p-methoxyphenyl (p-An) to 1,2-dialkynyl benzene substrates, the major product is the benzofulvene 29via a formal 1,4-chloroboration reaction. In this case the dibenzopentalene 30 is only observed as the minor product (Scheme 13c).31</p><p>Interestingly, the formation of 1,4-chloroboration products becomes favoured in other cases by the addition of an exogenous chloride donor such as [BCl4]− (Scheme 14). For example, 1,2-bis(p-tolylethynyl)benzene reacts with BCl3 affording the corresponding benzofulvene 31 and dibenzopentalene 32 in a 1 : 2 ratio. However, in the presence of three extra equivalents of a [BCl4]− salt, the ratio of 31 and 32 switched to 1.5 : 1, indicating the role of [BCl4]− in promoting the formal chloroboration reaction potentially by transferring chloride to the vinyl cation zwitterionic intermediate. Furthermore, precluding the presence of [BCl4]− or [RBCl3]− species in the reaction mixture by using boronium salt [Cl2B(2-DMAP)][AlCl4] significantly reduced the amount of the 1,4-chloroboration product observed. These studies therefore reveal that in the haloboration of diynes the halide source must be considered carefully to ensure a successful reaction outcome.</p><!><p>In addition to the aforementioned trans-bromoboration of acetylene and terminal alkynes, there are a limited number of other examples of internal alkyne trans-bromoboration reactions. Yamato and co-workers reported a BBr3 induced transformation of a o,o′-dimethoxy-substituted tolan derivative (Scheme 15).32 The highly Lewis acidic BBr3 induced a twofold ether cleavage and intramolecular trans-bromoboration, yielding benzofurochromene derivative 33.</p><p>Pei and co-workers also reported a directed trans-bromoboration similar to their trans-chloroboration reaction discussed above (cf. Scheme 11).26 Due to the similarities the details are not discussed again herein.</p><p>Sections 2 and 3 show the utility of alkyne haloboration, and this is by far the most developed reaction. The application of the haloboration reaction to other π systems is much less developed and the limited examples reported currently to the best of our knowledge are discussed in Section 4.</p><!><p>In their attempted hydroboration of vinyl chloride with B2H6 at −80 °C, DuPont et al. observed decomposition of the putative tris(2-chlorovinyl)borane upon warming to room temperature, whereas allyl chloride underwent hydroboration smoothly even at ambient conditions.33 Those findings were confirmed by Brown and Köster, who investigated the selectivity of allyl chloride hydroboration. Hydroboration resulted in a formal 6 : 4 anti-Markovnikov (34)/Markovnikov (35) selectivity. However, the Markovnikov product underwent rapid elimination of the vicinal BH2 and Cl groups to form H2BCl and propene (Scheme 16a).34,35 These observations foreshadowed the subsequent reports that found formation of olefin 1,2-haloboration products to be an energetically unfavourable process. Haloboration experiments on cyclohexene by Lappert et al. supported olefin haloboration being energetically uphill: only a mixture of products could be identified, with no α-haloalkyl borane (the primary product from haloboration) observed, indicating that additional reactivity has to take place to lead to an overall exergonic process (Scheme 16b).36</p><p>Rearrangements also can be used to trap initial olefin haloboration products, for example the reaction of BCl3 with suitable olefins such as norbornadiene or cycloheptatriene, furnishes tricyclene 36 or BnBCl2 (37, Scheme 16c).36,37</p><p>These observation are consistent with the ability of boron trihalides to function as initiators in alkene polymerisation (Scheme 16d), instead of resulting in simple olefin haloboration.38 These experimental findings were corroborated through the earlier discussed calculations by Uchiyama et al., who showed that haloboration of alkenes is thermodynamically unfavourable.21 This is further supported by the experimental finding that alkynyl substituted alkene 38 reacts selectively with BBr3via the alkyne moiety to yield 39 (Scheme 17a).39 Thus haloboration of olefins is an uncommon route to β-haloalkylboranes with only one inter- and one intramolecular synthesis reported to our knowledge.40,41 Other methods are preferred to prepare this versatile structural motif.42</p><p>While isolated olefins do not undergo haloboration, Lappert et al. showed that allenes reacted smoothly at −20 °C with BBr3 to give the respective 1,2 adduct. Isolation of the bromoborane, however, was problematic as polymerisation of the remaining alkene function occurred at elevated temperatures during attempted distillation.36 By esterification of the BBr2 group through reaction with anisole, polymerisation was prevented and the adduct could be isolated (as 40), thus providing stereoselective access to allylboronic esters (Scheme 17b).43 Iodoboration of terminal allenes with 9-I–BBN also can be a useful route to 2-iodoalkenes, if post haloboration the 9-BBN moiety is removed via acetolysis.44 Notably, if acetolysis is omitted, this reaction can furnish a sought after allylboronate without the need for allyl-metal species which are prone to 1,3 metallotropic shifts.45 If silylated allenes such as 41 are employed, the outcome of the reaction changes. Instead of the 1,2 haloboration product, the formal 1,3 haloboration product 42 is obtained (Scheme 17c). Quantum chemical calculations suggest silyl migration followed by sterically driven 1,3 boryl shifts to be responsible for this special stereoselectivity.46</p><!><p>Lappert et al. investigated the reactivity of aldehydes towards BX3 and suggested haloboration across CO to be a first step in a cascade of reactions that, depending on the nature of the aldehyde, eventually lead to borate esterification, formation of alkylhalides, haloalkylethers, or enolisation with concomitant polymerisation of the resulting vinylboric ester or alkenylether (Scheme 18a).47 The reaction of acetone with BCl3, however, only yielded an ill-defined mixture of products upon release of HCl, which precluded characterisation.48 Remarkably, when perhalogenated ketones (Hal = F, Cl, Br) were employed, usually haloboration of the CO bond occurred,49 but in some instances, simple halide exchange is favoured, giving a different boron halide and the respective perhaloketone.50 In the case of isocyanates and isothiocyanates (43), multiple CE double bonds exist. In these cases, haloboration proceeds stepwise via an R–NCE → BX3 (E = O, S) adduct 44, followed by 1,3 migration of X to C. The higher stability of a CO bond compared to a CN bond then leads to a B shift, giving aminoborane derivatives 45 (Scheme 18b).</p><p>Nitriles, which are isostructural and isoelectronic to alkynes can react with BX3 in a fashion related to their CC analogues. However, due to the lone pair at the N atom, the resulting aminoboranes 46 exist in an equilibrium with their cyclic dimers (47, Scheme 19a).51,52 In aminobenzonitriles, reactivity depends on the position of the two groups relative to each other. For para- and meta-substituted aminobenzonitrile, simple adducts of the type R–NH2 → BX3 form. In the case of ortho-aminobenzonitrile and PhBCl2, haloboration of the CN triple bond occurs, furnishing aminoborane 48 which at elevated temperatures cyclises to give the heterocyclic product 49 (Scheme 19b).53 In contrast to the meta- and para-substituted benzonitriles, ambidentate cyanamide reacts exclusively via haloboration of the CN triple bond giving dimeric iminoboranes, due to the strong and immediate mesomeric effect of the NH2 group on the CN triple bond and the thereby increased basicity of the cyano N-atom.54 Isonitriles form stable adducts 50 with the higher haloboranes BX3 (X = Cl, Br, I; for X = F, polymerisation occurs). If heated, these compounds undergo 1,1-haloboration and dimerisation to form 2,5-dihydrodiborapyrazines (51, Scheme 19c).55</p><p>Finally, reports on the reaction of BX3 with CNR double bonds are, just like in the case of CC double bonds, scarce, and limited to either highly electron deficient perfluorinated imines56,57 or chelating 1,4 diazabutadienes such as 52.58 The latter is an early example of a simple route to 1,3,2-diazaborolidines (53, Scheme 20), which play a crucial role in accessing nucleophilic boranes.59</p><!><p>As described in Sections 2 and 3, haloboration of terminal alkynes is a versatile tool to access selectively 1,1- or 1,2-difunctionalised alkenes. The stereoselectivity can be controlled and the resulting vinylboranes show ambiphilic reactivity: the halogenated C atom is a potential electrophile, whereas the boron-bonded C atom behaves as a nucleophile. In this section we focus on applications that take advantage of both these groups or use the electrophilic vinylBX2 intermediate (particularly in reactions other than esterification). The applications highlighted are distinct to the plethora of reports on forming and utilising vinyl-boronate esters, and the reader is directed to the excellent recent reviews on these topics.60,61</p><p>Haloboration initially was used to stereoselectively produce singly or doubly halogenated terminal alkenes by reacting either terminal alkynes or haloalkynes with e.g., 9-Br–BBN13,14,62 to give the intermediate alkenylborane 54 followed by acetolysis (55, Scheme 21a).63–65 1,2-Dihaloalkenes can also be accessed from terminal alkynes if post haloboration the boron moiety is transformed into an R–BF3K salt and then treated with an electrophilic halogenating agent.66 Suzuki et al. first employed vinylBBr2 derivative 56 in a one-pot two-steps Negishi/Suzuki–Miyaura cross-coupling sequence to access 1,2-disubstituted alkenes (57) selectively (Scheme 21b).67,68 Although yields were good, the β-bromoalkenyl dibromoboranes 56 were found to be prone to retro-haloboration in the presence of Pd complexes, making further derivatisation to boronic esters expedient to lower the Lewis acidity of the B atom.69–71 During their fundamental studies, Lappert et al. used esterification of R–BX2 with catechol or alkanols to transform their products into stable and conveniently analysed derivatives.12,37 Esterification by ether cleavage72 or by reaction with the respective alcohol73 gave boronic esters with prolonged shelf-life.25 Other functionalisation includes formation of R–B(dan) (dan = 1,8-diaminonaphthalen-N,N′-diyl),74 R–B(MIDA) complexes (MIDA = N-Methyliminodiacetate),75 or R–BF3K salts.66,76 As expected, these classes of compounds are versatile reagents in transition-metal catalysed transformations such as Suzuki–Miyaura cross-coupling or Rh-catalysed [2 + 2 + 2] cycloadditions owing to their ambiphilic nature (electrophilic C–X/nucleophilic C–B).39,77–80</p><p>The high B-centred Lewis acidity confers the alkenyl dihaloboranes a unique reactivity. The electrophilicity of the B atom paired with the nucleophilicity of the adjacent C atom enables the carboboration of alkynes. For example, the borocation [LutBCl2]+ (Lut = 2,6-lutidine) first reacts with R–CCH (R = alkyl, alkenyl, aryl) under 1,2-syn-haloboration to form compounds of general formula 58. Upon addition of Me–CC–SiMe3, 1,2-syn-carboboration takes place, furnishing a borylated butadiene 59 which can be transformed into the corresponding pinacol ester by reaction with pinacol/NEt3 (60, Scheme 22a).81 Similar reactivity was observed for (F5C6)2BCl.82 If, however, (F5C6)2BX (X = Cl, Br) is reacted with enynes or cyclopropylacetylene, oligomerisation of the alkyne moiety to give 61 without interference of the alkene part of the molecule occurs. In this process, the newly formed C–B bond is added across the CC triple bond in a 1,2 carboboration reaction (Scheme 22b).83 Experiments by Eisch et al. suggest that haloboration is kinetically favoured over carboboration, but due to its irreversibility the latter is often the observed reaction outcome.15 Taking advantage of boron's intrinsically high oxophilicity, haloboration can be exploited to form 1,4-dienes from alkynes, BX3 and aldehydes under deoxygenative conditions in a one-pot process without isolation of the haloboration product 62 that is the intermediate in this process. Remarkably, the stereoselectivity is dependent on the halide employed with BCl3 furnishing exclusively the (E,Z) diastereomer and BBr3 the respective (Z,Z) isomer of 63 (Scheme 22c).84,85</p><p>In a similar fashion, propargyl,86 benzyl,87 or allyl88 alcohols can be used to access propargyl-, benzyl-, or allyl-substituted styrenes 64 (Scheme 22d). If instead of BX3 9-I–BBN is used, haloboration of ethoxyethyne yields a haloboration product which reacts with aldehydes via a formal CO carboboration. The resulting secondary alkylborinic esters are readily hydrolysed to α,β unsaturated carbonic esters.89</p><p>The electron withdrawing nature of a BX2 group also renders alkenes like E-8 electron poor, making them good substrates in Diels–Alder reactions. Due to the instability of α-halogenated alkylboranes (cf. Section 4), BBr3 elimination transforms the intermediate cyclohexene 65 into a 1,4-cyclohexadiene 66 (Scheme 23).90</p><!><p>Polyenes are common substructures in natural products (Scheme 24).91,92 Usually, the double bonds are formed via Wittig-type olefinations,93 and thus can suffer from forming mixtures of both E and Z isomers. Using the appropriate conditions the haloboration of terminal alkynes, as discussed above, proceeds stereoselectively (usually >98%70,94,95) and furnishes ambiphilic halogenated vinyl boronic acid derivatives post workup.</p><p>Under the mild conditions of Pd catalysed cross-coupling reactions, the stereo information of the double bond is conserved.94,95 Thus, haloboration/cross-coupling sequences can be applied in the synthesis of olefinic natural products (Scheme 25).96 The inherent instability of polyene boronic acids can be circumvented by either using them directly without further purification or using the MIDA boronate derivatives. Indeed, only 12 different MIDA boronates derived inter alia from the haloboration product of acetylene are necessary to build most polyene natural products via consecutive Suzuki–Miyaura reactions.75,92</p><!><p>Besides providing a useful route to form β-functionalised boronic-acid derivatives, haloboration is an expedient tool to form boron-doped polycyclic aromatic hydrocarbons (B-PAHs), which are promising candidate materials in the field of organic electronics as they are electron deficient aromatics with a comparatively low LUMO energy.23,97 Haloboration of 1-alkynylnaphthalenes 67 can lead selectively (under appropriate conditions) to either trans-1,2-haloboration products (R = H, alkyl) or 1,1-haloboration products 68 (R = aryl, Scheme 26), which then undergo bora Friedel–Crafts reactions furnishing 1-boraphenalenes (69, Scheme 26a).97 If pyrene instead of naphthalene is used as the hydrocarbon core (70), singly or doubly (71) B-doped PAHs with very low LUMO energies are accessible.23 The utility of bromoboration is then demonstrated by usage of the vinyl-Br unit in a subsequent Negishi coupling enabling donor–acceptor–donor complex 72 to be formed readily (Scheme 26b). In other materials synthesis applications the high Lewis acidity of BBr3 allows for a one-shot double cyclisation of o,o′-dimethoxy-substituted tolan derivatives by ether cleavage and concomitant trans-haloboration, yielding benzofurochromene derivatives (cf.Scheme 15, Section 3).32 In a similar fashion, N-protected propargylamines underwent intramolecular N–B bond formation post haloboration.98</p><p>A related reaction sequence was used to construct even larger B,N doped PAHs.99 Besides being useful to incorporate boron into PAHs, haloboration has also been demonstrated to be a valuable tool to construct B-incorporated polymers. This was achieved by subjecting diynes such as 73 to multiple haloboration reactions using either BBr3 or R2BBr as the B source to yield polymers such as 74 (Scheme 27).100</p><!><p>Since its discovery almost 80 years ago, the haloboration of alkynes has developed into a reliable way to form bifunctional alkenes with excellent control of stereoselectivity possible. The haloboration of other substrates is more limited and further work is required to develop these into broadly useful transformations. Regarding alkyne haloboration, although some mechanistic details are still subject to debate, experimental evidence clearly demonstrates that the stereoselectivity of haloboration can be controlled. The addition of BX3 (X = Cl, Br, I) to a terminal alkyne proceeds via syn-addition of a B–X bond across the CC triple bond and is usually very fast, even at low temperatures. Thus, low-temperature quenching furnishes the Z-adduct selectively. At higher temperatures, isomerisation to the E-adduct can occur. The initial addition as well as the subsequent isomerisation are highly efficient, allowing access to the respective adduct in high yields with stereoselectivities often >98%. Haloboranes such as PhBBr2 or 9-Br–BBN can be employed in haloboration as well. For internal alkynes, stronger electrophiles than BCl3 are needed to effect haloboration, and most simply BBr3 can be used. The lower reactivity of internal CC triple bonds allows for the isolation of the syn-addition product even at room temperature within minutes. Yet, prolonged storage in solution or elevated temperatures (or more polar solvents) can lead to rearrangement of the 1,2-syn addition product to the 1,1-haloboration product in a reversible process. Thus, the addition of BBr3 to internal alkynes yields mixtures of both 1,1- and 1,2-adducts. Notably both the 1,2-adduct and the 1,1 adduct can be isolated selectively using the appropriate conditions.</p><p>The combination of halide and boron moieties in the addition product allows for broad diversification of the obtained olefin. For example, haloboration outperforms most other common CC bond formation reactions in terms of selectivity and it has proved its worth in the field of polyene natural product synthesis. Notably, the primary products from haloboration contain vinylBX2 units which often have distinct reactivity compared to vinylB(OR)2 analogues due to the stronger electron withdrawing nature of the BX2 unit. An emerging application of the haloboration reaction is in the incorporation of B atoms into large delocalised π systems. This may either be achieved by using strategically positioned heteroatoms (e.g., O, N) to direct alkyne haloboration, or by alkyne haloboration followed by a bora Friedel–Crafts reaction on alkyne-substituted PAHs. These are attractive as the formed B-doped PAHs are halogenated enabling facile subsequent diversification. We hope that further applications are forthcoming that help bring haloboration out of the shadow of the ubiquitous hydroboration reaction.</p><!><p>There are no conflicts to declare.</p>

PubMed Open Access

2-Sulfonamidopyridine C-region analogs of 2-(3-fluoro-4-methylsulfonamidophenyl)propanamides as potent TRPV1 antagonists

A series of 2-sulfonamidopyridine C-region derivatives of 2-(3-fluoro-4-methylsulfonamidophenyl)propanamide were investigated as hTRPV1 ligands. Systematic modification on the 2-sulfonamido group provided highly potent TRPV1 antagonists. The N-benzyl phenylsulfonamide derivatives 12 and 23 in particular showed higher affinities than that of lead compound 1. Compound 12 exhibited strong analgesic activity in the formalin pain model. Docking analysis of its chiral S-form 12S in our hTRPV1 homology model indicated that its high affinity might arise from additional hydrophobic interactions not present in lead compound 1S.

2-sulfonamidopyridine_c-region_analogs_of_2-(3-fluoro-4-methylsulfonamidophenyl)propanamides_as_pote

Introduction<!>Chemistry<!>Biological activity<!>Molecular modeling<!>Conclusion<!>General<!>Method A:<!>Method B:<!>2-(4-Methoxybenzyl)amino-6-(trifluoromethyl)nicotinonitrile (R1 = (4-OMe)Bn).<!>2-Methylamino-6-(trifluoromethyl)nicotinonitrile (R1 = Me).<!>2-Isopropylamino-6-(trifluoromethyl)nicotinonitrile (R1 = i-Pr).<!>2-Phenylamino-6-(trifluoromethyl)nicotinonitrile (R1 = Ph).<!>2-(4-Fluorophenyl)amino-6-(trifluoromethyl)nicotinonitrile (R1 = (4-F)Ph).<!>2-(Cyclohexylmethyl)amino-6-(trifluoromethyl)nicotinonitrile (R1 = (Cy)Me).<!>2-(Benzylamino-6-(trifluoromethyl)nicotinonitrile (R1 = Bn).<!>2-(4-Fluorobenzyl)amino-6-(trifluoromethyl)nicotinonitrile (R1 = (4-F)Bn).<!>2-(4-Chlorobenzyl)amino-6-(trifluoromethyl)nicotinonitrile (R1 = (4-Cl)Bn).<!>2-(4-Methylbenzyl)amino-6-(trifluoromethyl)nicotinonitrile (R1 = (4-Me)Bn).<!>General procedure for sulfonamidation<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-(4-methoxybenzyl)benzenesulfonamide (R1 = (4-OMe)Bn, R2 = Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-methylbenzenesulfonamide (R1 = Me, R2 = Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-isopropylbenzenesulfonamide (R1 = i-Pr, R2 = Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-phenylbenzenesulfonamide (R1 = Ph, R2 = Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-(4-fluorophenyl)benzenesulfonamide (R1 = (4-F)Ph, R2 = Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-(cyclohexylmethyl)benzenesulfon amide (R1 = (Cy)Me, R2 = Ph).<!>N-Benzyl-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)benzenesulfonamide (R1 = Bn, R2 = Ph).<!>N-Benzyl-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)methanesulfonamide (R1 = Bn, R2 = Me).<!>N-Benzyl-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)ethanesulfonamide (R1 = Bn, R2 = Et).<!>N-Benzyl-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)propane-1-sulfonamide (R1 = Bn, R2 = Pr).<!>N-Benzyl-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)propane-2-sulfonamide (R1 = Bn, R2 = i-Pr).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-(4-fluorobenzyl)benzenesulfonamide (R1 = (4-F)Bn, R2 = Ph).<!>N-Benzyl-4-chloro-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)benzenesulfonamide (R1 = Bn, R2 = (4-Cl)Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-4-fluoro-N-(4-fluorobenzyl)benzenesul-fonamide (R1 = (4-F)Bn, R2 = (4-F)Ph).<!>N-(4-Chlorobenzyl)-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)benzenesulfonamide (R1 = (4-Cl)Bn, R2 = Ph).<!>N-(4-Chlorobenzyl)-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)-4-fluorobenzenesul-fonamide (R1 = (4-Cl)Bn, R2 = (4-F)Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-4-fluoro-N-(4-methoxybenzyl)benzene-sulfonamide (R1 = (4-OCH3)Bn, R2 = (4-F)Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-N-(4-methylbenzyl)benzenesulfonamide (R1 = (4-Me)Bn, R2 = Ph).<!>N-Benzyl-N-(3-cyano-6-(trifluoromethyl)pyridin-2-yl)-4-fluorobenzenesulfonamide (R1 = Bn, R2 = (4-F)Ph).<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)-4-fluoro-N-(4-methylbenzyl)-benzene-sulfonamide (R1 = (4-Me)Bn, R2 = (4-F)Ph).<!>Procedure for N-PMB deprotection by ceric ammonium nitrate oxidation<!>N-(3-Cyano-6-(trifluoromethyl)pyridin-2-yl)benzenesulfonamide (R1 = H, R2 = Ph).<!>General procedure for nitrile reduction<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)benzenesulfonamide (R1=H, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-methylbenzenesulfonamide (R1 = Me, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-isopropylbenzenesulfonamide (R1 = i-Pr, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-phenylbenzenesulfonamide (R1 = Ph, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(4-fluorophenyl)benzenesul-fonamide (R1 = (4-F)Ph, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(cyclohexylmethyl)benzene-sulfonamide (R1 = (Cy)Me, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzylbenzenesulfonamide (R1 = Bn, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzylmethanesulfonamide (R1 = Bn, R2 = Me).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzylethanesulfonamide (R1 = Bn, R2 = Et).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzylpropane-1-sulfonami-de (R1 = Bn, R2 = Pr).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzylpropane-2-sulfonami-de (R1 = Bn, R2 = i-Pr).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(4-fluorobenzyl)benzenesul-fonamide (R1 = (4-F)Bn, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzyl-4-chlorobenzenesul fonamide (R1 = Bn, R2 = (4-Cl)Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-4-fluoro-N-(4-fluorobenzyl)be-nzenesulfonamide (R1 = (4-F)Bn, R2 = (4-F)Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(4-chlorobenzyl)benzenesul-fonamide (R1 = (4-Cl)Bn, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(4-chlorobenzyl)-4-fluorobe-nzenesulfonamide (R1 = (4-Cl)Bn, R2 = (4-F)Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(4-methoxybenzyl)benzene-sulfonamide (R1 = (4-OCH3)Bn, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-4-fluoro-N-(4-methoxybenzyl)-benzenesulfonamide (R1 = (4-OCH3)Bn, R2 = (4-F)Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-(4-methylbenzyl)benzenesul-fonamide (R1 = (4-Me)Bn, R2 = Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-N-benzyl-4-fluorobenzenesulfo-namide (R1 = Bn, R2 = (4-F)Ph).<!>N-(3-(Aminomethyl)-6-(trifluoromethyl)pyridin-2-yl)-4-fluoro-N-(4-methylbenzyl)be-nzenesulfonamide (R1 = (4-Me)Bn, R2 = (4-F)Ph).<!>General procedure for amide coupling<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(phenylsulfonamido)-6-(triflu-oromethyl)pyridin-3-yl)methyl)propanamide (6).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-methylphenylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (7).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-isopropylphenylsulfonamid-o)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (8).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-phenylphenylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (9).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-(4-fluorophenyl)phenylsulfonam-ido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (10).<!>N-((2-(N-(Cyclohexylmethyl)phenylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (11).<!>N-((2-(N-Benzylphenylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (12).<!>(S)-N-((2-(N-Benzylphenylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (12S).<!>N-((2-(N-Benzylmethylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (13).<!>N-[2-(Benzyl-ethanesulfonyl-amino)-6-trifluoromethylpyridin-3-ylmethyl]-2-(3-fluo-ro-4-methanesulfonylamino-phenyl)-propionamide (14).<!>N-((2-(N-Benzylpropan-2-ylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)-methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (15).<!>N-((2-(N-Benzylpropylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (16).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-(4-fluorobenzyl)phenyl-sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (17).<!>N-((2-(N-(4-Chlorobenzyl)phenylsulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (18).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-(4-methoxybenzyl)phenyl-sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (19).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-(N-(4-methylbenzyl)phenyl-sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (20).<!>N-((2-((N-Benzyl-4-fluorophenyl)sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (21).<!>N-((2-((N-Benzyl-4-chlorophenyl)sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (22).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-((4-fluoro-N-(4-fluorobenzyl)-phenyl) sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (23).<!>N-((2-((N-(4-Chlorobenzyl)-4-fluorophenyl)sulfonamido)-6-(trifluoromethyl)-pyridin-3-yl)methyl)-2-(3-fluoro-4-(methylsulfonamido)phenyl)propanamide (24).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-((4-fluoro-N-(4-methoxy-benzyl)phenyl)sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (25).<!>2-(3-Fluoro-4-(methylsulfonamido)phenyl)-N-((2-((4-fluoro-N-(4-methylbenzyl)-phenyl)-sulfonamido)-6-(trifluoromethyl)pyridin-3-yl)methyl)propanamide (26).<!>Molecular modeling

<p>TRPV1 has emerged as an exciting therapeutic target for chronic and inflammatory pain as well as for the numerous other conditions in which C-fiber sensory afferent neurons are involved.1–3 The natural products capsaicin4 and resiniferatoxin5 provided critical initial lead structures guiding the current vigorous efforts by many groups. It is now appreciated that the pharmacophore can be conceptualized as being subdivided into 3 regions, designated A, B, and C. Appropriate substitution in the A region can generate antagonistic activity, with the 3-fluoro-4-sulfonamidophenyl group being an early example.6 The chemical efforts have been significantly aided by structural insights into the TRPV1 binding domain provided by homology modeling,7 cryoEM structural analysis,8,9 and further modeling derived from the cryoEM structure.10 An on-going challenge for the field is to understand the integration of ligand–TRPV1 interactions with endogenous regulatory networks in the context of the whole animal.11 In particular, different antagonists differ in their tendency to induce the side effect of hyperthermia.12 The range of structures with potent TRPV1 antagonism being developed by different groups should provide the tools to address these issues as compounds move forward into clinical testing.13</p><p>Over the years, we have reported that a series of N-{(6-trifluoromethyl-pyridin-3-yl)methyl}2-(3-fluoro-4-methylsulfonamidophenyl)propanamides were potent hTRPV1 antagonists active against multiple activators.14–20 Initial analyses of the antagonistic template focused on the pyridine C-region where the structure activity relationships for the 2-substituent were extensively explored with a variety of functional groups. A prototype for these series is compound 1, which possesses a 4-methylpiperidinyl group as a 2-substituent. Compound 1 displayed highly potent and (S)-stereospecific antagonism of hTRPV1 activators including capsaicin, low pH, heat (45 °C) and N-arachidonoyl dopamine (NADA) (Fig. 1).14 In addition, in vivo analysis confirmed that compound 1 and congeners blocked capsaicin-induced hypothermia, consistent with their in vitro mechanism of action, and they demonstrated potent antiallodynic activity in a neuropathic pain model. Molecular modeling using our established hTRPV1 homology model indicated that the two principal hydrophobic interactions, between the 6-trifluoromethyl group and the 2-substituents in the C-region and the hydrophobic pockets composed of Leu547/Thr550 and Met514/Leu515, respectively, were critical for the potent activity of the antagonists.14</p><p>In continuation of our program to discover clinical candidates for antagonism of TRPV1 mediated neuropathic pain, we have sought to further optimize the above template by investigating 2-sulfonamidopyridine C-region derivatives in which hydrophobic R1 and R2 groups were incorporated through a polar sulfonamide linker (Fig. 1). In this study, we synthesized a series of 2-sulfonamido 4-(trifluoromethyl)pyridine C-region derivatives of the antagonistic template and evaluated their binding affinities and antagonism of hTRPV1 activation by capsaicin. With selected potent antagonists in the series, we further characterized their analgesic activities in animal models and performed a docking study with our hTRPV1 homology model to elucidate their binding mode to the receptor.</p><!><p>The 2-sulfonamidopyridine derivatives (6–26) were synthesized in 4-steps through a conventional approach starting from the commercially available 2-chloro-6-(trifluoromethyl)nicotinonitrile (2) (Scheme 1). Compound 2 was reacted with various amines (R1NH2) to produce the corresponding 2-amino derivatives (3) by one of two methods. They were then sulfonylated with a series of sulfonyl chlorides (R2SO2Cl) to provide 2-sulfonamido derivatives (4). For the synthesis of the secondary sulfonamide derivative (6), the 4-methoxybenzyl group in 4 was oxidatively deprotected. The nitrile of 4 was reduced to the corresponding amine (5), respectively, which were coupled with the racemic (or chiral S-form) propionic acid as previously reported14 to provide the final compounds (6–26).</p><!><p>The binding affinities and potencies as agonists/antagonists of the synthesized TRPV1 ligands were assessed in vitro by a binding competition assay with [3H]RTX and by a functional 45Ca2+ uptake assay using human TRPV1 heterologously expressed in Chinese hamster ovary (CHO) cells, as previously described.6,21 For the agonism assay, a saturating concentration of capsaicin (300 nM) was used to define maximal response. For the antagonism assay, the dose-dependent inhibition of the capsaicin (30 nM) stimulated calcium uptake was measured. The Ki values for antagonism take into account the competition between capsaicin and the antagonist. The results are summarized in Tables 1–3, together with the potencies of previous lead compound 1.</p><p>First, we investigated a series of phenylsulfonamide derivatives (R2 = Ph) in which a variety of N-substituents (R1) including alkyl and aryl groups were explored (Table 1). The secondary phenylsulfonamide derivative (6) was found to have little activity. This result was consistent with previous findings in which secondary amino derivatives14 as 2-substituents in the pyridine C-region showed only weak antagonism. In contrast, incorporation of hydrophobic groups on the nitrogen of the phenylsulfonamide, providing tertiary phenylsulfonamides (7–12), led to potent binding affinity and antagonism. The binding affinities increased with the size of the N-substituent: methyl (7) < isopropyl (8) < phenyl (9) < 4-fluorophenyl (10) < cyclohexylmethyl (11) < benzyl (12). Antagonism by the more potent compounds fell in the range of Ki(ant) = 5–10 nM. Among the compounds, the N-benzyl phenylsulfonamide (12) exhibited high affinity and potent antagonism with Ki = 1.99 nM and Ki(ant) = 5.9 nM, representing a 4-fold enhancement in binding affinity but a 2.5-fold reduction in antagonism compared to lead compound 1. The chiral S-isomer (12S), which has the active S-stereoconfiguration as described previously,14 was prepared and, as expected, showed enhanced potency relative to that of 12 with Ki = 0.54 nM and Ki(ant) = 1.81 nM, which also demonstrated a 5-fold increase in binding affinity but a 1.5-fold decrease in antagonism compared to 1S, S-isomer of lead compound 1.</p><p>Next, due to the high potency of 12, we further investigated the structure activity relationship of the phenyl moiety of the phenylsulfonamide in 12 (Table 2). The phenylsulfonamide group of 12 was replaced by the corresponding alkylsulfonamides. The binding affinities and antagonistic potencies were enhanced with the increased lipophilicity of the corresponding alkyl groups: R = Me (13) < R = Et (14) < R = iPr (15) < R = Pr (16). However, none of the derivatives were as potent as compound 12.</p><p>Finally, we investigated 4-substituted N-benzyl and phenylsulfonamide derivatives of 12 for further optimization (Table 3). Four different 4-substituted N-benzyl derivatives with 4-F, 4-Cl, 4-OCH3 and 4-CH3 (17–20) were explored first. The 4-chlorobenzyl derivative (18) showed slightly improved binding affinity compared to that of 12 with Ki = 1.29 nM, and the 4-methoxybenzyl derivative (19) exhibited ca. 3-fold more potent antagonism than that of 12 with Ki(ant) = 2.14 nM. The two 4-substituted phenylsulfonamide derivatives with 4′-F and 4′-Cl (21, 22) were also examined. The 4′-fluorophenyl derivative (21) displayed better binding affinity and antagonism with Ki = 1.56 nM and Ki(cat) = 3.87 nM compared to 12. This promising result prompted us to further investigate 4-substituted benzyl derivatives of 21 (23–26). The N-(4-fluorobenzyl)4′-fluorophenylsulfonamide (23) was found to be the most potent antagonist in this series with Ki = 0.71 nM and Ki(ant) = 2.99 nM, which was 10-fold more potent in binding affinity and similar activity in antagonism compared to compound 1.</p><p>We next evaluated the analgesic activity of compound 12 upon intraperitoneal administration in the formalin mouse pain model (Fig. 2).22,23 Compound 12 demonstrated excellent, dose-dependent analgesic efficacy in the second period (20–30 min after injection). The ED50 was 15.6 mg/kg.</p><!><p>To investigate the binding interactions of compound 12S, we carried out a flexible docking study using our human TRPV1 model14 built based on our rat TRPV1 model7 and compared its behavior to that of lead compound 1S. Previously we had demonstrated that the two principal hydrophobic interactions between the 6-trifluoromethyl group and the 4-methylpiperidinyl ring in the C-region of 1S and the two pockets composed of Leu547/Thr550 and Met514/Leu515, respectively, were critical for its high potency.14 Structurally, compound 12S has the two bulky substituents, including phenylsulfonamide and benzyl groups, at the 2-position of the pyridine C-region, whereas 1S has only a hydrophobic group having a 4-methylpiperidinyl ring.</p><p>As shown in Figure 3, the phenylsulfonamide group in the C-region of 12S extended toward the hydrophobic area composed of Leu547 and Thr550 similar to the 6-trifluoromethylpyridine ring in 1. Furthermore, the benzyl group in 12S was involved in the hydrophobic interaction with Met514 and Leu515 as was the 4-methylpiperidinyl group in 1S. However, the 6-trifluoromethylpyridine in 12S made additional hydrophobic interactions with Tyr554 and the residues Phe591, Phe587 from the adjacent monomer. These additional hydrophobic interactions might explain the higher binding affinity of 12S.</p><!><p>A series of 2-sulfonamidopyridine C-region derivatives of the 2-(3-fluoro-4-methylsulfonamidophenyl)propanamide template have been investigated for their activity on hTRPV1. Systematic modification on the 2-sulfonamido group provided compounds of high affinity and potent antagonism. Compared to lead 1, the N-benzyl phenylsulfonamide derivatives 12 and 23 showed upto a 10-fold increase in binding affinity. Compound 12 was evaluated in the formalin pain model and exhibited strong analgesic activity with ED50 = 15.6 mpk in the second phase. A docking study of compound 12S, the active isomer of 12, in our hTRPV1 homology model revealed three principal hydrophobic interactions of the C-region with the receptor. Among them, the additional hydrophobic interaction with a pocket composed of Phe587/Phe591 might explain the higher affinity of 12S compared to 1S.</p><!><p>All chemical reagents were commercially available. Melting points were determined on a Büchi Melting Point B-540 apparatus and are uncorrected. Silica gel column chromatography was performed on silica gel 60, 230–400 mesh, Merck. Nuclear magnetic resonance (1H NMR and 13C NMR) spectra were recorded on JEOL JNM-LA 300 [300 MHz (1H), 75 MHz (13C)] and Bruker Avance 400 MHz FT-NMR [400 MHz (1H), 100 MHz (13C)] spectrometers. Chemical shifts are reported in ppm units with Me4Si as a reference standard. Mass spectra were recorded on a VG Trio-2 GC–MS and 6460 Triple Quad LC/MS. All final compounds were purified to >95% purity, as determined by high-performance liquid chromatography (HPLC). HPLC was performed on an Agilent 1120 Compact LC (G4288A) instrument using an Agilent Eclipse Plus C18 column (4.6 × 250 mm, 5 μm) and a Daicel Chiralcel OD-H column (4.6 × 250 mm, 5 μm).</p><!><p>To a solution of 2-chloro-4-(trifluoromethyl)-benzonitrile solution (1.00 mmol) in acetonitrile was added potassium carbonate (3.00 mmol) and 18-crown-6 ether (0.10 mmol) and the resulting solution was stirred at room temperature for 30 min. Appropriate amine (NH2R1, 1.5 mmol) was added to the mixture and refluxed for 12 h. After being cooled down to ambient temperature, the reaction was quenched with water and extracted with EtOAc twice. The combined organic extracts were dried over MgSO4, filtered, and concentrated in vacuo. The residue was purified by flash column chromatography on silica gel using EtOAc/ hexanes (1:2) as eluant.</p><!><p>To a solution of 2-chloro-4-(trifluoromethyl)-benzonitrile solution (1.00 mmol) in toluene/THF (1:1 v/v) was added palladium(II) acetate (0.10 mmol), dppf (0.20 mmol), potassium carbonate (2.00 mmol) and the resulting solution was stirred at room temperature for 30 min. An appropriate amine (NH2R1, 1.50 mmol) was added to the mixture and refluxed for 12 h. After being cooled down to ambient temperature, the reaction was quenched with water and extracted with EtOAc twice. The combined organic extracts were dried over MgSO4, filtered, and concentrated in vacuo. The residue was purified by flash column chromatography on silica gel using EtOAc/hexanes (1:2) as eluant.</p><!><p>Yield 88%, yellow solid, mp = 70–82 °C; 1H NMR (400 MHz, CDCl3) δ 7.78 (d, J = 7.68 Hz, 1H), 7.29 (d, J = 8.32 Hz, 2H), 6.94 (d, J = 7.76 Hz, 1H), 6.86 (d, J = 8.40 Hz, 1H), 5.59 (br s, 1H), 4.62 (d, J = 5.44 Hz, 2H), 3.78 (s, 3H); MS (FAB) m/z 308 [M+H]+.</p><!><p>Yield 95%, pale yellow solid, mp = 65–73 °C; 1H NMR (300 MHz, CDCl3) δ 7.80 (d, J = 7.86 Hz, 1H), 6.94 (d, J = 7.71 Hz, 1H), 5.41 (s, 1H), 3.11 (d, J = 4.77 Hz, 3H); MS (FAB) m/z 202 [M+H]+.</p><!><p>Yield 70%, yellow solid, mp = 63–65 °C; 1H NMR (300 MHz, CDCl3) δ 7.78 (dd, J = 7.89 Hz, 0.75 Hz, 1H), 6.91 (d, J = 7.86 Hz, 1H), 5.15 (m, 1H), 4.34 (m, 1H), 1.28 (d, J = 6.57 Hz, 6H); MS (FAB) m/z 230 [M+H]+.</p><!><p>Yield 85%, yellow solid, mp = 52–65 °C; 1H NMR (300 MHz, CDCl3) δ 7.96 (dd, J = 7.86, 0.72 Hz, 1H), 7.66 (m, 2H), 7.40 (t, J = 7.53 Hz, 2H), 7.19 (t, J = 1.29 Hz, 1H), 7.15 (d, J = 8.97 Hz, 1H); MS (FAB) m/z 264 [M+H]+.</p><!><p>Yield 80%, yellow solid, mp = 64–72 °C; 1H NMR (300 MHz, CDCl3) δ 7.96 (d, J = 7.86 Hz, 1H), 7.60 (dd, J = 8.97, 4.59 Hz, 1H), 7.15 (d, J = 7.68 Hz, 2H), 7.09 (t, J = 8.79 Hz, 2H); MS (FAB) m/z 282 [M+H]+.</p><!><p>Yield 81%, yellow solid, mp = 65–78 °C; 1H NMR (300 MHz, CDCl3) δ 7.78 (d, J = 7.68 Hz, 1H), 6.91 (d, J = 7.71 Hz, 1H), 5.40 (s, 1H), 3.40 (t, J = 6.24 Hz, 2H), 1.76–1.61 (m, 4H), 1.26–1.21 (m, 4H), 1.05–0.98 (m, 2H); MS (FAB) m/z 284 [M+H]+.</p><!><p>Yield 83%, pale yellow solid, mp = 78–85 °C; 1H NMR (300 MHz, CDCl3) δ 7.81 (d, J = 7.86 Hz, 1H), 7.38–7.25 (m, 5H), 6.97 (t, J = 7.89 Hz, 1H), 5.70 (br s, 1H), 4.71 (d, J = 5.67 Hz, 2H); MS (FAB) m/z 278 [M+H]+.</p><!><p>Yield 70%, dark yellow solid, mp = 87–92 °C; 1H NMR (300 MHz, CDCl3) δ 7.82 (d, J = 7.7 Hz, 1H), 7.38–7.34 (m, 2H), 7.06–6.97 (m, 3H), 4.68 (d, J = 5.7 Hz, 2H); MS (FAB) m/z 296 [M+H]+.</p><!><p>Yield 70%, yellow solid, mp = 82–95 °C; 1H NMR (300 MHz, CDCl3) δ 7.85 (d, J = 7.71 Hz, 1H), 7.33–7.32 (m, 4H), 7.00 (d, J = 7.71 Hz, 1H), 5.73 (s, 1H), 4.69 (d, J = 5.67 Hz, 2H); MS (FAB) m/z 312 [M+H]+.</p><!><p>Yield 88%, yellow solid, mp = 91–97 °C; 1H NMR (400 MHz, CDCl3) δ 7.77 (d, J = 7.80 Hz, 1H), 7.26 (d, J = 7.72 Hz, 2H), 7.19–7.12 (m, 3H), 6.94 (d, J = 7.76 Hz, 1H), 5.72 (br s, 1H), 4.65 (d, J = 5.52 Hz, 2H), 2.33 (s, 3H); MS (FAB) m/z 292 [M+H]+.</p><!><p>A solution of 2-(alkyl/aryl amino)-5-(trifluoromethyl)nicotinonitrile (1.00 mmol) in DMF was cooled to 0 °C and sodium hydride (60% dispersion in oil; 2.50 mmol) was added. The resulting solution was stirred at 0 °C for 30 min and the appropriate sulfonyl chloride (R2SO2Cl) was added dropwised to the mixture and then stirred at 100 °C for 12 h. The reaction was quenched with water and extracted with DCM twice. The combined organic extracts were dried over MgSO4, filtered, and concentrated in vacuo. The residue was purified by flash column chromatography on silica gel using EtOAc/hexanes (1:4) as eluant.</p><!><p>Yield 78%, yellow solid, mp = 92–100 °C; 1H NMR (300 MHz, CDCl3) δ 8.10 (d, J = 8.07 Hz, 1H), 7.74–7.53 (m, 6H), 7.15–7.12 (m, 2H), 6.71–6.68 (m, 2H), 4.67 (s, 2H), 3.70 (s, 3H); MS (FAB) m/z 448 [M+H]+.</p><!><p>Yield 85%, orange solid, mp = 95 °C; 1H NMR (300 MHz, CDCl3) δ 8.29 (d, J = 7.86 Hz, 1H), 7.65–7.53 (m, 4H), 7.54 (t, J = 7.89 Hz, 2H), 3.22 (s, 3H); MS (FAB) m/z 342 [M+H]+</p><!><p>Yield 35%, yellow solid, mp = 96 °C; 1H NMR (300 MHz, CDCl3) δ 8.33 (d, J = 7.86 Hz, 1H) 7.86–7.77 (m, 4H), 7.63–7.50 (m, 5H) 2.71 (s, 3H), 1.08 (d, J = 6.78 Hz, 6H); MS (FAB) m/z 370 [M+H]+.</p><!><p>Yield 83%, red yellow, mp = 95–103 °C; 1H NMR (300 MHz, CDCl3) δ 8.15 (d, J = 8.07 Hz, 1H), 7.63 (d, J = 8.04 Hz, 2H), 7.67 (d, J = 8.07 Hz 1H), 7.62 (t, J = 7.35 Hz, 1H), 7.46 (t, J = 7.68 Hz, 2H), 7.41–7.31 (m, 5H); MS (FAB) m/z 404 [M+H]+.</p><!><p>Yield 77%, red yellow solid, mp = 95–103 °C; 1H NMR (300 MHz, CDCl3) δ 8.17 (d, J = 7.89 Hz, 1H), 7.74 (d, J = 7.53 Hz, 1H), 7.71 (d, J = 8.07 Hz, 2H), 7.64 (t, J = 7.32 Hz, 1H), 7.48 (t, J = 7.86 Hz, 2H), 7.31 (m, 2H), 7.05 (t, J = 8.43 Hz, 2H); MS (FAB) m/z 422 [M+H]+.</p><!><p>Yield 50%, yellow solid, mp = 83–94 °C; 1H NMR (300 MHz, CDCl3) δ 8.31 (d, J = 7.89 Hz, 1H), 7.77 (d, J = 8.04 Hz, 1H), 7.67–7.48 (m, 5H), 3.44 (d, J = 6.96 Hz, 2H), 1.76–1.65 (m, 4H), 1.28–1.20 (m, 4H), 0.88–0.86 (m, 2H); MS (FAB) m/z 424 [M+H]+.</p><!><p>Yield 80%, yellow solid, mp = 80–95 °C; 1H NMR (300 MHz, CDCl3) δ 8.11 (d, J = 8.04 Hz, 1H), 7.66 (d, J = 8.07 Hz, 1H), 7.75–7.67 (m, 2H), 7.60–7.50 (m, 3H), 7.24–7.15 (m, 5H), 4.74 (s, 2H); MS (FAB) m/z 418 [M+H]+.</p><!><p>Yield 74%, pale yellow solid, mp = 102–110 °C; 1H NMR (300 MHz, CDCl3) δ 8.11 (d, J = 8.04 Hz, 1H), 7.66 (d, J = 8.07 Hz, 1H), 7.20–7.33 (m, 5H), 5.03 (s, 2H), 3.16 (s, 3H); MS (FAB) m/z 356 [M+H]+.</p><!><p>Yield 55%, red yellow solid, mp = 82–98 °C; 1H NMR (300 MHz, CDCl3) δ 8.07 (d, J = 8.0 Hz, 1H), 7.62 (d, J = 7.9 Hz, 1H), 7.34–7.19 (m, 5H), 5.06 (s, 2H), 3.40–3.33 (q, J = 7.5 Hz, 2H), 1.48 (t, J = 7.5 Hz, 3H); MS (FAB) m/z 370 [M+H]+.</p><!><p>Yield 74%, yellow solid, mp = 95–103 °C; 1H NMR (300 MHz, CDCl3) δ 8.07 (d, J = 8.10 Hz, 1H), 7.62 (d, J = 7.90 Hz, 1H), 7.34–7.21 (m, 5H), 5.05 (s, 2H), 3.30 (t, J = 7.70 Hz, 2H), 2.06–1.94 (m, 2H), 1.12 (t, J = 7.50 Hz, 3H); MS (FAB) m/z 384 [M+H]+.</p><!><p>Yield 22%, yellow solid, mp = 79–86 °C; 1H NMR (300 MHz, CDCl3) δ 8.05 (d, J = 7.90 Hz, 1H), 7.60 (d, J = 8.10 Hz, 1H), 7.32–7.21 (m, 5H), 5.09 (s, 2H), 3.63 (m, 1H), 1.48 (d, J = 6.80 Hz, 6H); MS (FAB) m/z 384 [M+H]+.</p><!><p>Yield 98%, red yellow solid, mp = 92–98 °C; 1H NMR (300 MHz, CDCl3) δ 8.14 (d, J = 8.1 Hz, 1H), 7.73–7.54 (m, 6H), 7.24–7.19 (m, 2H), 6.90–6.85 (m, 2H), 4.70 (s, 2H); MS (FAB) m/z 436 [M+H]+.</p><!><p>Yield 87%, yellow solid, mp = 84–96 °C; 1H NMR (400 MHz, CDCl3) δ 8.09 (d, J = 7.96 Hz, 1H), 7.85 (d, J = 8.52 Hz, 2H), 7.48 (m, 3H), 7.19–7.15 (m, 5H), 4.70 (s, 2H); MS (FAB) m/z 452 [M+H]+.</p><!><p>Yield 89%, yellow solid, mp = 87–96 °C; 1H NMR (300 MHz, CDCl3) δ 8.16 (d, J = 7.86 Hz, 1H), 7.75 (m, 3H), 7.19–7.15 (m, 5H), 6.85 (m, 2H), 4.70 (s, 2H); MS (FAB) m/z 454 [M+H]+.</p><!><p>Yield 68%, yellow solid, mp = 78–87 °C; 1H NMR (300 MHz, CDCl3) δ 8.16 (d, J = 7.86 Hz, 1H), 7.79–7.64 (m, 4H), 7.59–7.50 (m, 2H), 7.23–7.15 (m, 4H), 4.70 (s, 2H); MS (FAB) m/z 452 [M+H]+.</p><!><p>Yield 85%, yellow solid, mp = 86–92 °C; 1H NMR (300 MHz, CDCl3) δ 8.16 (d, J = 7.86 Hz, 1H), 7.75 (m, 3H), 7.19–7.15 (m, 5H), 6.85 (m, 2H), 4.70 (s, 2H); MS (FAB) m/z 470 [M+H]+.</p><!><p>Yield 82%, yellow solid, mp = 78–93 °C; 1H NMR (300 MHz, CDCl3) δ 8.10 (d, J = 8.07 Hz, 1H) 7.98 (d, J = 8.07 Hz, 2H), 7.40 (m, 2H), 7.12 (m, 2H), 6.89 (m, 3H), 4.67 (s, 2H), 3.80 (s, 3H); MS (FAB) m/z 466 [M+H]+.</p><!><p>Yield 72%, yellow solid, mp = 84–94 °C; 1H NMR (300 MHz, CDCl3) δ 8.16 (d, J = 7.86 Hz, 1H), 7.79–7.64 (m, 5H), 7.59–7.50 (m, 2H), 7.23–7.15 (m, 3H), 4.70 (s, 2H), 2.19 (s, 3H); MS (FAB) m/z 432 [M+H]+.</p><!><p>Yield 75%, yellow solid, mp = 73–85 °C; 1H NMR (400 MHz, CDCl3) δ 8.09 (d, J = 7.96 Hz, 1H), 7.85 (d, J = 8.52 Hz, 2H), 7.48 (m, 3H), 7.19–7.15 (m, 5H), 4.70 (s, 2H); MS (FAB) m/z 436 [M+H]+.</p><!><p>Yield 72%, yellow solid, mp = 75–87 °C; 1H NMR (300 MHz, CDCl3) δ 8.16 (d, J = 7.86 Hz, 1H), 7.79–7.64 (m, 4H), 7.59–7.50 (m, 2H), 7.23–7.15 (m, 3H), 4.70 (s, 2H), 2.19 (s, 3H); MS (FAB) m/z 450 [M+H]+.</p><!><p>Ceric ammonium nitrate (2.10 mmol) was added to a solution of N-(3-cyano-6-(trifluoromethyl)py-ridin-2-yl)-N-(4-methoxybenzyl)benzenesulfonamide (1.00 mmol) in acetonitrile/H2O (4:1 v/v) at 0 °C. The resulting orange solution was stirred at 0 °C for 30 min, and then at ambient temperature for 1 h. The reaction mixture was diluted with EtOAc and saturated NaHCO3 was added. The resulting suspension was stirred for 30 min at room temperature and then filtered through a pad of celite. After the two layers were separated, the organic layer was washed with brine. The combined organic extracts were dried over MgSO4, filtered, and concentrated in vacuo. The residue was purified by flash column chromatography on silica gel using EtOAc/hexanes (1:4) as eluant.</p><!><p>Yield 97%, yellow solid, mp = 75–87 °C; 1H NMR (300 MHz, CDCl3) δ 8.22–8.20 (m, 2H), 8.02 (d, J = 8.04 Hz, 1H), 7.64–7.52 (m, 3H), 7.36 (d, J = 7.86 Hz, 1H); MS (FAB) m/z 328 [M+H]+.</p><!><p>To a stirred solution of nitrile (1.00 mmol) in anhydrous THF (10 ml) was added 2 M BH3·SMe2 in THF (1.10 mmol) at room temperature. After being refluxed for 8 h, the mixture was cooled to ambient temperature, 2 N HCl was added dropwise, and the solution was then refluxed for 30 min. After cooling to ambient temperature, the mixture was neutralized with 2 N NaOH and extracted with EtOAc several times. The combined organic layers were washed with brine, dried over MgSO4, and concentrated in vacuo. The residue was purified by flash column chromatography on silica gel using MeOH/DCM (1:10) as eluant.</p><!><p>Yield 32%, clear oil; 1H NMR (300 MHz, DMSO) δ 7.94–7.91 (m, 2H), 7.45 (d, J = 7.32 Hz, 1H), 7.32–7.30 (m, 3H), 6.81 (d, J = 7.50 Hz, 1H), 3.88 (s, 2H); MS (FAB) m/z 332 [M+H]+.</p><!><p>Yield 69%, clear oil; 1H NMR (300 MHz, CDCl3) δ 8.19 (d, J = 7.86 Hz, 1H), 7.67–7.61 (m, 4H), 7.50 (t, J = 7.68 Hz, 2H), 4.26 (s, 2H), 3.09 (s, 3H); MS (FAB) m/z 346 [M+H]+.</p><!><p>Yield 44%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.25 (d, J = 8.07 Hz, 1H), 7.80–7.83 (m, 2H), 7.72 (d, J = 8.07 Hz, 1H), 7.59 (m, 1H), 7.46 (m, 2H), 4.32 (m, 2H), 2.49 (s, 2H), 1.25 (m, 1H), 1.07 (d, J = 6.57 Hz, 1H), 0.86 (d, J = 6.42 Hz, 1H); MS (FAB) m/z 374 [M+H]+.</p><!><p>Yield 57%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.11 (d, J = 7.86 Hz, 1H), 7.68 (m, 2H), 7.67 (m, 1H), 7.58 (t, J = 7.32 Hz, 1H), 7.42 (t, J = 7.53 Hz, 2H), 7.37–7.28 (m, 5H), 4.05 (s, 2H); MS (FAB) m/z 408 [M+H]+.</p><!><p>Yield 52%, dark yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.14 (d, J = 7.89 Hz, 1H), 7.69 (d, J = 8.04 Hz, 1H), 7.67–7.57 (m, 4H), 7.54 (d, J = 8.04 Hz, 2H), 7.41–7.34 (m, 2H), 7.01–6.91 (m, 2H), 4.79 (s, 2H); MS (FAB) m/z 426 [M+H]+.</p><!><p>Yield 72%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.25 (d, J = 7.86 Hz, 1H), 7.66 (d, J = 7.89 Hz, 1H), 7.63–7.44 (m, 5H), 4.34 (s, 2H), 3.36 (d, J = 6.39 Hz, 2H), 1.67–1.59 (m, 4H), 1.12–1.06 (m, 4H), 0.86–0.88 (m, 2H); MS (FAB) m/z 428 [M+H]+.</p><!><p>Yield 37%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 7.98 (d, J = 7.86 Hz, 1H), 7.69–7.62 (m, 3H), 7.57–7.49 (m, 3H), 7.18–7.11 (m, 5H), 4.64 (s, 1H), 3.90 (s, 1H); MS (FAB) m/z 422 [M+H]+.</p><!><p>Yield 81%, clear oil; 1H NMR (300 MHz, CDCl3) δ 7.98 (d, J = 8.04 Hz, 1H), 7.63 (d, J = 7.89 Hz, 1H), 7.22–7.19 (m, 3H), 7.17–7.13 (m, 2H), 4,85 (s, 2H), 3.71 (s, 2H), 3.11 (s, 3H); MS (FAB) m/z 360 [M+H]+.</p><!><p>Yield 32%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 7.98 (d, J = 7.9 Hz, 1H), 7.61 (d, J = 7.9 Hz, 1H), 7.22–7.13 (m, 5H), 4.89 (s, 2H), 3.69 (s, 2H), 3.29 (q, J = 7.50 Hz, 2H), 1.49 (t, J = 7.50 Hz, 3H); MS (FAB) m/z 374 [M+H]+.</p><!><p>Yield 55%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 7.97 (d, J = 8.0 Hz, 1H), 7.61 (d, J = 7.5 Hz, 1H), 7.22–7.13 (m, 5H), 4.88 (s, 2H), 3.68 (s, 2H), 3.24 (t, J = 8.1 Hz, 2H), 2.04–1.90 (m, 2H), 1.08 (t, J = 7.4 Hz, 3H); MS (FAB) m/z 388 [M+H]+.</p><!><p>Yield 30%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.00 (d, J = 7.9 Hz, 1H), 7.60 (d, J = 8.1 Hz, 1H), 7.23–7.20 (m, 3H), 7.15–7.10 (m, 2H), 4.93 (s, 2H), 3.68–3.65 (m, 1H), 3.60 (s, 2H), 1.49 (d, J = 6.8 Hz, 6H); MS (FAB) m/z 388 [M+H]+.</p><!><p>Yield 39%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.04 (d, J = 7.30 Hz, 1H), 7.68–7.49 (m, 6H), 7.13–7.08 (m, 2H), 6.89–6.82 (m, 2H), 4.62 (br s, 2H). 3.92 (s, 2H); MS (FAB) m/z 440 [M+H]+.</p><!><p>Yield 75%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.01 (d, J = 7.86 Hz, 1H), 7.57–7.63 (m, 3H), 7.48–7.51 (m, 2H), 7.16 (m, 3H), 7.11 (m, 2H), 4.62 (br s, 2H), 3.70 (s, 2H); MS (FAB) m/z 456 [M+H]+.</p><!><p>Yield 64%, yellow oil; 1H NMR (400 MHz, CDCl3) δ 8.05 (d, J = 8.00 Hz, 1H), 7.64 (m, 2H), 7.62 (d, J = 7.96 Hz, 1H), 7.23 (m, 4H), 6.98–7.03 (t, J = 8.68 Hz, 2H), 4.62 (s, 2H). 3.92 (s, 2H); MS (FAB) m/z 458 [M+H]+.</p><!><p>Yield 67%, pale yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.05 (d, J = 8.04 Hz, 1H), 7.69–7.50 (m, 6H), 7.16–7.07 (m, 4H), 4.61 (s, 2H), 3.96 (s, 2H); MS (FAB) m/z 456 [M+H]+.</p><!><p>Yield 60%, yellow oil; 1H NMR (400 MHz, CDCl3) δ 8.05 (d, J = 8.00 Hz, 1H), 7.69–7.50 (m, 3H), 7.14–7.24 (m, 6H), 4.61 (s, 2H), 3.96 (s, 2H); MS (FAB) m/z 474 [M+H]+.</p><!><p>Yield 73%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.00 (d, J = 7.9 Hz, 1H), 7.68–7.62 (m, 3H), 7.57–7.49 (m, 3H), 7.03 (d, J = 8.6 Hz, 2H), 6.68 (d, J = 8.8 Hz, 2H), 4.58 (s, 2H), 3.91 (s, 2H), 3.70 (s, 3H); MS (FAB) m/z 452 [M+H]+.</p><!><p>Yield 85%, yellow oil; 1H NMR (400 MHz, CDCl3) δ 8.00 (d, J = 8.00 Hz, 1H), 7.69 (m, 3H), 7.62 (d, J = 7.92 Hz, 1H), 7.23 (d, J = 11.6 Hz, 1H), 7.14 (d, J = 8.12 Hz, 1H), 6.99 (m, 3H), 4.61 (s, 2H), 3.96 (s, 2H), 3.05 (s, 3H); MS (FAB) m/z 470 [M+H]+.</p><!><p>Yield 84%, yellow oil; 1H NMR (400 MHz, CDCl3) δ 8.05 (d, J = 8.00 Hz, 2H), 7.75 (m, 5H), 6.97 (m, 4H), 4.61 (s, 2H), 3.96 (s, 2H), 2.35 (s, 3H); MS (FAB) m/z 436 [M+H]+.</p><!><p>Yield 82%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.01 (d, J = 7.86 Hz, 1H), 7.57–7.63 (m, 2H), 7.50 (m, 3H), 7.16 (m, 3H), 7.11 (m, 2H), 4.62 (br s, 2H), 3.70 (s, 2H); MS (FAB) m/z 440 [M+H]+.</p><!><p>Yield 84%, yellow oil; 1H NMR (300 MHz, CDCl3) δ 8.00 (d, J = 8.00 Hz, 1H), 7.65 (m, 2H), 7.52 (m, 3H), 7.09 (d, J = 11.37 Hz, 2H), 6.77 (m, 2H), 4.61 (s, 2H), 3.96 (s, 2H), 2.24 (s, 3H); MS (FAB) m/z 454 [M+H]+.</p><!><p>A mixture of 2-(3-fluoro-4-(methylsulfonamido)phenyl) propanoic acid (1.00 mmol), amine (1.10 mmol), 1-(3-dimethylaminopropyl)-3-ethyl-carbodiimide hydrochloride (1.10 mmol) and 1-hydroxybenzotriazole hydrate (1.50 mmol) in DMF (5 ml) was stirred for 12 h at room temperature. The reaction mixture was extracted with EtOAc (10 ml). The aqueous phase was saturated with aq NaCl and extracted again with EtOAc (15 ml). The combined organic extracts were washed with 1 N HCl (5 ml) and brine (5 ml), dried over MgSO4, filtered, and concentrated in vacuo. The residue was purified by flash column chromatography on silica gel using EtOAc/hexanes (1:2) as eluant.</p><!><p>Yield 56%, white solid, mp = 102–109 °C; 1H NMR (300 MHz, CDCl3) δ 8.14 (d, 2H, J = 7.68 Hz, 2H), 7.56–7.38 (m, 5H), 7.16 (t, 2H), 7.04 (d, J = 7.86 Hz, 1H), 6.59 (br t, 2H), 4.33 (m, 2H), 3.55 (q, J = 7.5 Hz, 1H), 3.03 (s, 3H), 1.50 (d, J = 7.14 Hz, 3H), 1.26 (m, 1H); MS (FAB) m/z 575 [M+H]+.</p><!><p>Yield 48%, white solid, mp = 77–88 °C; 1H NMR (300 MHz, CDCl3) δ 8.06 (d, J = 7.86 Hz, 1H), 7.65 (m, 1H), 7.59 (d, J = 7.86 Hz, 1H), 7.52–7.48 (m, 5H), 7.13 (d, J = 11.37 Hz, 1H), 7.09 (d, J = 8.43 Hz, 1H), 6.71 (brt, 1H), 6.5 (br s, 1H), 4.69 (m, 2H), 3.57 (q, J = 7.32 Hz, 1H), 3.06 (s, 3H), 2.94 (s, 3H), 1.52 (d, J = 6.96 Hz, 3H); MS (FAB) m/z 589 [M+H]+.</p><!><p>Yield 54%, white solid, mp = 83–92 °C; 1H NMR (300 MHz, DMSO) δ 9.57 (s, 1H), 8.7 (br s, 1H), 7.9 (br s, 1H), 7.70 (m, 3H), 7.59 (d, J = 7.86 Hz, 2H), 7.45 (m, 1H), 7.25 (m, 1H), 7.19 (d, J = 11.37 Hz, 1H), 4.55 (m, 2H), 4.30 (m, 1H), 3.78 (q, J = 7.32 Hz, 1H), 3.02 (s, 1H), 1.40 (d, J = 6.96 Hz, 3H), 1.07 (s, 3H), 0.83 (s, 3H); MS (FAB) m/z 617 [M+H]+.</p><!><p>Yield 95%, white solid, mp = 98–102 °C; 1H NMR (300 MHz, CDCl3) δ7.96 (d, J = 7.86 Hz, 1H), 7.60 (m, 5H), 7.52 (d, J = 8.07 Hz, 1H), 7.44 (t, J = 8.43 Hz, 3H), 7.31 (m, 7H), 7.13 (dd, J = 12.7 Hz, 2H), 6.40 (t, 1H), 4.56 (m, 2H), 3.55 (dd, J = 6.09 Hz, 1H), 3.03 (s, 3H), 1.51 (d, J = 7.14 Hz, 3H); MS (FAB) m/z 651 [M+H]+.</p><!><p>Yield 65%, white solid, mp = 90–98 °C; 1H NMR (300 MHz, CDCl3) δ 7.96 (d, J = 7.89 Hz, 1H), 7.63 (m, 3H), 7.53 (d, J = 7.71 Hz, 3H), 7.47 (dd, J = 14.2 Hz, 3H), 7.34 (m, 3H), 7.15 (m, 2H), 6.97 (m, 2H), 4.60 (m, 2H), 3.59 (dd, J = 4.30 Hz, 1H), 2.99 (s, 3H), 1.53 (d, J = 6.33 Hz, 3H); MS (FAB) m/z 669 [M+H]+.</p><!><p>Yield 44%, white solid, mp = 85–91 °C; 1H NMR (300 MHz, CDCl3) δ 8.15 (m, 1H), 8.05 (m, 1H), 7.56 (m, 7H), 7.15 (d, J = 15.8 Hz, 2H), 6.72 (m, 1H), (s, 1H), 5.06 (br t, 1H), 4.39 (m, 1H), 3.57 (s, 1H), 3.36 (d, J = 6.06 Hz, 2H), 2.92 (s, 3H), 2.05 (m, 1H), 1.46 (m, 10H); MS (FAB) m/z 671 [M+H]+.</p><!><p>Yield 59%, white solid, mp = 75–88 °C; 1H NMR (300 MHz, CD3OD) δ 7.71 (m, 1H), 7.63–7.53 (m, 6H), 7.43 (t, J = 8.22 Hz, 1H), 7.22–7.13 (m, 7H), 4.66 (s, 2H), 4.52 (s, 2H), 3.67 (q, J = 7.14 Hz, 1H), 2.96 (s, 3H), 1.45 (d, J = 7.14 Hz, 3H); MS (FAB) m/z 665 [M+H]+.</p><!><p>Yield 62%, white solid, mp = 85–90 °C, [α]D20=−0.570 (c = 0.01, CHCl3); 1H NMR (400 MHz, DMSO) δ 9.53 (br s, 1H), 8.41 (t, J = 5.44 Hz, 1H), 7.76 (d, J = 7.80 Hz, 2H), 7.63–7.53 (m, 6H), 7.43 (t, J = 8.22 Hz, 1H), 7.22–7.13 (m, 7H), 4.62 (s, 2H), 4.42 (s, 2H), 3.70 (q, J = 6.72 Hz, 1H), 3.00 (s, 3H), 1.36 (d, J = 6.92 Hz, 3H); 13C NMR (300 MHz, CDCl3) δ 173.40, 171.15, 155.72, 152.48, 150.76, 146.57, 146.09, 141.71, 140.09, 140.00, 138.93, 136.32, 134.28, 133.62, 133.23, 129.49, 128.96, 128.57, 128.38, 124.30, 123.75, 120.61, 60.36, 54.13, 46.30, 39.55, 38.13, 21..02, 18.39, 14.16; MS (FAB) m/z 665 [M+H]+.</p><!><p>Yield 38%, white solid, mp = 65–72 °C; 1H NMR (300 MHz, CD3OD) δ 7.67 (d, J = 8.04 Hz, 1H), 7.57 (d, J = 7.86 Hz, 1H), 7.42 (t, J = 8.25 Hz, 1H), 7.23–7.10 (m, 7H), 4.86 (s, 2H), 4.30 (s, 2H), 3.64 (q, J = 7.14 Hz, 1H), 3.11 (s, 3H), 2.97 (s, 3H), 1.42 (d, J = 7.14 Hz, 3H); MS (FAB) m/z 603 [M+H]+.</p><!><p>Yield 59%, white solid, mp = 66–73 °C; 1H NMR (300 MHz, CD3OD) δ 7.65 (d, J = 7.89 Hz, 1H), 7.57 (d, J = 7.68 Hz, 1H), 7.42 (t, J = 8.43 Hz, 1H), 7.22–7.10 (m, 7H), 4.29 (d, 2H), 3.63 (q, J = 7.14 Hz, 1H), 3.34 (m, 2H), 2.97 (s, 3H), 1.42 (d, J = 7.14 Hz, 3H), 1.37 (d, J = 7.32 Hz, 3H); MS (FAB) m/z 617 [M+H]+.</p><!><p>Yield 49%, white solid, mp = 67–80 °C; 1H NMR (300 MHz, CDCl3) δ 7.91 (d, J = 7.68 Hz, 1H), 7.55 (d, 1H), 7.48 (d, 1H), 7.22 (m, 3H), 7.08–7.02 (m, 4H), 6.2 (br, 1H), 5.9 (br, 1H), 5.33 (d, 1H), 4.89 (d, 1H), 4.8 (m, 1H), (m, 1H), 3.01 (s, 3H), 2.01 (d, J = 7.14 Hz, 3H), 1.98 (d, J = 7.14 Hz, 3H), 1.40 (d, J = 7.14 Hz, 3H), 0.86 (m, 2H); MS (FAB) m/z 631 [M+H]+.</p><!><p>Yield 56%, white solid, mp = 62–70 °C; 1H NMR (300 MHz, CD3OD) δ 7.66 (d, J = 8.04 Hz, 1H), 7.57 (d, J = 5.04 Hz, 1H), 7.42 (t, J = 8.25 Hz, 1H), 7.22–7.10 (m, 7H), 4.89 (s, 2H), 4.28 (s, 2H), 3.63 (q, J = 7.14 Hz, 1H), 3.29 (m, 2H), 2.97 (s, 3H), 1.87 (sextet, J = 7.89 Hz, 2H), 1.42 (d, J = 7.14 Hz, 3H), 1.04 (t, J = 7.50 Hz, 3H); MS (FAB) m/z 631 [M+H]+.</p><!><p>Yield 46%, white solid, mp = 71–81 °C; 1H NMR (300 MHz, CDCl3) δ 7.92 (br, 1H), 7.67 (m, 1H), 7.56–7.47 (m, 7H), 7.13–7.03 (m, 4H), 6.84 (t, J = 7.35 Hz, 2H), 6.45 (br t, 1H), 4.90 (br s, 1H), 4.60 (br s, 1H), 4.40 (br s, 1H), 4.10 (br s, 1H), 3.46 (q, J = 7.14 Hz, 1H), 2.93 (s, 3H), 1.49 (d, J = 7.14 Hz, 3H); MS (FAB) m/z 683 [M+H]+.</p><!><p>Yield 36%, white solid, mp = 75–83 °C; 1H NMR (300 MHz, CDCl3) δ 7.92 (d, J = 5.01 Hz, 1H), 7.64 (m, 1H), 7.51 (m, 7H), 7.11 (t, J = 6.33 Hz, 3H), 7.00 (t, J = 7.35 Hz, 3H), 6.38 (s, 1H), 4.82 (m, 1H), 4.57 (m, 1H), 4.37 (s, 1H), 4.11 (m, 1H), 3.44 (dd, J = 10.1 Hz, 3H), 2.92 (s, 3H), 1.46 (d, J = 5.34 Hz, 3H); MS (FAB) m/z 700 [M+H]+.</p><!><p>Yield 89%, white solid, mp = 67–76 °C; 1H NMR (300 MHz, CDCl3) δ 7.90 (s, 1H), 7.59 (m, 7H), 7.11 (d, J = 11.6 Hz, 1H), 7.05 (d, J = 8.07 Hz, 1H), 6.98 (d, J = 8.40 Hz, 2H), 6.68 (d, J = 8.25 Hz, 2H), 6.35 (br s, 2H), 4.49 (m, 4H), 3.71 (s, 3H), 3.42 (s, 1H), 2.94 (s, 3H), 1.46 (d, J = 6.96 Hz, 3H); MS (FAB) m/z 695 [M+H]+.</p><!><p>Yield 82%, white solid, mp = 85–90 °C; 1H NMR (400 MHz, DMSO) δ 9.53 (br s, 1H), 8.41 (br t, 1H), 7.76 (d, J = 8.12 Hz, 2H), 7.59–7.62 (m, 6H), 7.32–7.36 (t, J = 8.24 Hz, 1H), 7.22 (d, J = 11.48 Hz, 1H), 7.15 (d, J = 8.16 Hz, 1H), 6.98 (br t, 3H), 4.57 (s, 2H), 4.44 (s, 2H), 3.70 (q, J = 6.96 Hz, 1H), 3.00 (s, 3H), 2.17 (s, 3H), 1.36 (d, 3H, J = 6.92 Hz); MS (FAB) m/z 679 [M+H]+.</p><!><p>Yield 54%, white solid, mp = 74–84 °C; 1H NMR (300 MHz, CD3OD) δ 8.47 (m, J = 5.67 Hz, 2H), 7.78 (d, J = 8.04 Hz, 1H), 7.69 (dd, J = 8.52 Hz, 2H), 7.61 (d, J = 8.07 Hz, 1H), 7.46 (t, J = 8.76 Hz, 2H), 7.34 (t, J = 8.22 Hz, 1H), 7.19 (m, 7H), 4.63 (s, 2H), 4.42 (s, 2H), 3.01 (s, 3H), 1.36 (d, J = 6.96 Hz, 3H); MS (FAB) m/z 684 [M+H]+.</p><!><p>Yield 76%, white solid, mp = 85–90 °C; 1H NMR (300 MHz, CDCl3) δ 8.47 (t, J = 5.67 Hz, 1H), 7.46–7.58 (m, 7H), 7.19 (m, 3H), 7.02–7.07 (m, 4H), 4.63 (s, 2H), 4.42 (s, 2H), 3.01 (s, 3H), 1.36 (d, J = 6.96 Hz, 3H); MS (FAB) m/z 670 [M+H]+.</p><!><p>Yield 85%, white solid, mp = 92–98 °C; 1H NMR (400 MHz, DMSO) δ 9.53 (br s, 1H), 8.45 (t, J = 5.32 Hz, 1H), 7.78 (d, J = 8.00 Hz, 1H), 7.66–7.69 (m, 1H), 7.62 (d, J = 8.00 Hz, 1H), 7.44 (t, J = 8.60 Hz, 2H), 7.33 (t, J = 8.28 Hz, 1H), 7.22 (d, J = 11.64 Hz, 1H), 7.13–7.18 (m, 3H), 6.98 (t, J = 8.60 Hz, 3H), 4.62 (s, 2H), 4.39 (s, 2H), 3.70 (q, J = 6.92 Hz, 1H), 3.00 (s, 3H), 1.36 (d, J = 6.92 Hz, 3H); MS (FAB) m/z 701 [M+H]+.</p><!><p>Yield 78%, white solid, mp = 90–95 °C; 1H NMR (400 MHz, DMSO) δ 9.53 (br s, 1H), 8.48 (t, J = 5.36 Hz, 1H), 7.78 (d, J = 8.00 Hz, 1H), 7.64–7.69 (m, 2H), 7.44 (t, J = 8.60 Hz, 2H), 7.33 (t, J = 8.28 Hz, 1H), 7.22 (d, J = 11.64 Hz, 1H), 7.13–7.18 (m, 3H), 6.98 (t, J = 8.60 Hz, 3H), 4.63 (s, 2H), 4.43 (s, 2H), 3.70 (q, J = 6.92 Hz, 1H), 3.00 (s, 3H), 1.36 (d, J = 6.92 Hz, 3H); MS (FAB) m/z 718 [M+H]+.</p><!><p>Yield 78%, white solid, mp = 85–90 °C; 1H NMR (400 MHz, DMSO) δ 9.51 (br s, 1H), 8.42 (t, J = 5.28 Hz, 1H), 7.84 (d, J = 7.24 Hz, 1H), 7.75 (m, 3H), 7.61 (d, J = 7.92 Hz, 1H), 7.42–7.46 (t, J = 8.64 Hz, 2H), 7.33 (t, J = 8.28 Hz, 1H), 7.22 (d, J = 11.60 Hz, 1H), 7.13 (d, J = 8.12 Hz, 1H), 6.99 (t, J = 8.60 Hz, 3H), 4.58 (s, 2H), 4.43 (s, 2H), 3.70 (q, J = 6.92 Hz, 1H), 3.00 (s, 3H), 2.18 (s, 3H), 1.36 (d, J = 6.92 Hz, 3H); MS (FAB) m/z 713 [M+H]+.</p><!><p>Yield 83%, white solid, mp = 85–90 °C; 1H NMR (400 MHz, DMSO) δ 8.42 (t, J = 5.28 Hz, 1H), 7.77 (d, J = 7.96 Hz, 1H), 7.66–7.69 (m, 2H), 7.59 (d, J = 7.92 Hz, 1H), 7.42–7.46 (t, J = 8.64 Hz, 2H), 7.33 (t, J = 8.28 Hz, 1H), 7.22 (d, J = 11.60 Hz, 2H), 7.13 (d, J = 8.12 Hz, 1H), 6.96 (d, J = 8.44 Hz, 2H), 6.73 (d, J = 8.36 Hz, 2H), 4.56 (s, 2H), 4.38 (s, 2H), 3.70 (q, J = 6.92 Hz, 1H), 3.64 (s, 3H), 3.00 (s, 3H), 1.36 (d, J = 6.92 Hz, 3H); MS (FAB) m/z 697 [M+H]+.</p><!><p>The 3D structures of the molecules were generated with Concord and energy minimized with MMFF94s force field and MMFF94 charge until the rms of Powell gradient was 0.05 kcal mol−1 A−1 in SYBYL-X 2.0 (Tripos Int., St. Louis, MO, USA). The flexible docking study on our hTRPV1 model14 was performed using GOLD v.5.2 (Cambridge Crystallographic Data Centre, Cambridge, UK), which employees a genetic algorithm (GA) and allows for full ligand flexibility and partial protein flexibility. The binding site was defined as 8 Å around the capsaicin complexed in the hTRPV1 model. The side chains of the nine residues which are important for ligand binding, (i.e., Tyr511, Ser512, Met514, Leu515, Leu518, Phe543, Leu547, Thr550, and Asn551) were allowed to be flexible with 'crystal mode' in GOLD. Compound 12S was docked using the GoldScore scoring function, and the other parameters remained as default. All the computation calculations were undertaken on an Intel® Xeon™ Quad-core 2.5 GHz workstation with Linux Cent OS release 5.5.</p>

PubMed Author Manuscript

Evolving Stark Effect During Growth of Perovskite Nanocrystals Measured Using Transient Absorption

Methylammonium lead triiodide (MAPbI3) nanocrystals (NCs) are emerging materials for a range of optoelectronic applications. Photophysical characterization is typically limited to structurally stable NCs owing to the long timescales required for many spectroscopies, preventing the accurate measurement of NCs during growth. This is a particular challenge for non-linear spectroscopies such as transient absorption. Here we report on the use of a novel single-shot transient absorption (SSTA) spectrometer to study MAPbI3 NCs as they grow. Comparing the transient spectra to derivatives of the linear absorbance reveals that photogenerated charge carriers become localized at surface trap states during NC growth, inducing a TA lineshape characteristic of the Stark effect. Observation of this Stark signal shows that the contribution of trapped carriers to the TA signal declines as growth continues, supporting a growth mechanism with increased surface ligation toward the end of NC growth. This work opens the door to the application of time-resolved spectroscopies to NCs in situ, during their synthesis, to provide greater insight into their growth mechanisms and the evolution of their photophysical properties.

evolving_stark_effect_during_growth_of_perovskite_nanocrystals_measured_using_transient_absorption

1. Introduction<!><!>1. Introduction<!><!>2.1. Materials<!>2.2. Nanocrystal Synthesis<!>2.3. Absorbance and Fluoresence<!>2.4. Single-Shot Transient Absorption<!>3. Results and Discussion<!><!>3. Results and Discussion<!><!>3. Results and Discussion<!><!>3. Results and Discussion<!><!>3. Results and Discussion<!><!>3. Results and Discussion<!>4. Conclusion<!>Data Availability Statement<!>Author Contributions<!>Conflict of Interest

<p>Hybrid organic-inorganic perovskite nanocrystals (NCs) are currently the focus of significant interest owing to their potential applications in optoelectronic devices. Their large absorption coefficients (Fu et al., 2015), high defect tolerance (Dirin et al., 2016), excellent photoluminescence quantum yield (PLQY) (Hassan et al., 2019), and potential for low-cost, facile production (Protesescu et al., 2015) coupled with a narrow, tuneable emission spectrum (Hassan et al., 2016) has driven a boom of research in the synthesis and characterization of these materials. These NCs are ordinarily grown through either a hot injection or reprecipitation style synthesis. In these solution-based syntheses the reaction is initiated when dissolved precursor reaches a critical threshold to cause LaMer nucleation (LaMer and Dinegar, 1950). Following this, NCs are allowed to grow until the desired size and morphology is reached. The morphology (Pan et al., 2016; Sun et al., 2016), stability (Huang et al., 2017), and photophysics (Peterson et al., 2014; Teunis et al., 2017) of NCs are strongly dependent on the surface owing to their large surface-to-volume ratios. Surface atoms lacking bonds to capping ligands exhibit localized electronic states with energies that can lie within the band gap. These mid-gap states act as traps for excited electrons or holes, suppressing radiative recombination and hampering performance in light emitting devices (Boles et al., 2016).</p><p>The quality of the NC surface during growth is still poorly understood and the timescales of nucleation and growth are prohibitively short for investigation using typical surface characterization techniques, such as X-ray photoelectron spectroscopy (Katari et al., 1994), electron energy loss spectroscopy (Wang et al., 1998), small-angle X-ray scattering (Mattoussi et al., 1998), and 2D nuclear magnetic resonance techniques (De Roo et al., 2016). Recently, use of a solvation-mediated synthesis (Wang et al., 2017), coupled to a rapid sampling technique (Sadighian et al., 2019), permitted the measurement of linear absorbance and fluorescence during growth. This study revealed that NCs initially grow in size while their surfaces remain poorly-capped by passivating ligands, and do not become well-capped until they are almost fully grown (Figure 1) (Sadighian et al., 2020). Visible absorbance and fluorescence measurements report on transitions from the ground and emissive band-edge states, respectively. The peak positions and lineshapes can provide insight into the NC size distribution, and fluorescence intensity is often used to infer the degree of NC surface passivation. However, these spectroscopies are insensitive to other important transitions, such as carrier trapping and non-radiative recombination, and the dynamics of the excited carriers. A comprehensive understanding of how NC photophysics evolves during synthesis may provide deeper insights into NC growth mechanisms, the nature of the NC surface, and how a synthesis can be tuned to achieve desired morphologies and optoelectronic properties.</p><!><p>Schematic of NC growth. (A) Following LaMer nucleation the immature NCs are well-capped by surface ligands throughout most of their subsequent growth. (B) Nascent NCs nucleate following the same LaMer-type mechanism, but surface ligation occurs primarily after NC growth. A terminal ligation stage is proposed in literature for CdSe and MAPbI3 NCs and is supported by the measurements in this work.</p><!><p>In this paper, we demonstrate a technique that can provide further insight into the evolving NC surface by probing the electric field generated by carriers localized at surface traps. Photogenerated electron-hole pairs become spatially separated when a carrier is trapped at these surface sites, creating an electric field inside the NC. The presence of an electric field can modulate the optical transitions of an NC via the Stark effect (Colvin and Alivisatos, 1992; Colvin et al., 1994; Klimov, 2000; Sharma et al., 2019). Analysis of the modulated absorbance spectrum lineshape can provide insight into the electric fields in the NCs (Bublitz and Boxer, 1997). The quantum-confined Stark effect (QCSE) changes the bandgap transition energy by shifting the electron and hole energy levels (Walters et al., 2018). This typically redshifts the bandedge absorption and causes the differential absorbance spectrum to exhibit the lineshape of the first derivative of the linear absorbance. In systems that lack any specific orientation, such as randomly distributed surface traps on NCs, the internal electric field generated by spatially separated, trapped carriers results in a population of randomly oriented dipoles in the sample. This would act to inhomogenously broaden the overall transition, and as a result the differential absorbance spectrum would resemble the second derivative of the linear absorbance (Tanaka and Kondo, 2003; Queloz et al., 2020).</p><p>Electroabsorbance measurements of 2D hybrid perovskites have exhibited lineshapes that could be fit to a weighted sum of first and second derivatives of the absorbance spectrum (Queloz et al., 2020). These two components were assigned to a spectral redshift arising from a QCSE and broadening due to loosely-bound, screened electron-hole pairs, respectively. This same lineshape was observed upon photogeneration of charge carriers in these perovskites during transient absorption (TA) measurements. This indicates that the presence of spatially separated electrons and holes in surface traps can cause internal electric fields that yield lineshapes characteristic of the Stark effect. Thus, the Stark lineshape measured by TA can report on the surface quality of NCs.</p><p>TA is a powerful time-resolved spectroscopy that has been used to understand excited state processes such as Auger recombination (Klimov and McBranch, 1998; Guyot-Sionnest et al., 1999), energy transfer to phonons (Urayama et al., 2001) or ligands (Guyot-Sionnest et al., 2005; Li et al., 2019), and carrier trapping (Mondal and Samanta, 2017) in NCs. Typically, this pump-probe technique is performed by varying the path length of one pulse relative to the other by use of a retroreflector on a motorized translation stage. The transmission of many successive laser pulses is recorded at each pump-probe time delay in series. This technique typically requires measurement timescales on the order of tens of minutes to several hours, depending on factors such as sample response and laser noise. As a result, in its typical implementations TA fails to accurately report on excited state dynamics in non-equilibrium systems that are chemically changing on timescales shorter than a few hours, such as growing NCs.</p><p>TA measurements can be conducted more rapidly by using a single-shot transient absorption (SSTA) spectrometer that enables an entire transient to be recorded from a single pump-probe pulse pair. This can be achieved by tilting the wavefront of the pump pulse relative to the probe (Fourkas et al., 1995; Makishima et al., 2006). In this case, the time delay range is determined by Equation (1):</p><p>where d is the length of overlap between pump and probe pulses, θ is the angle between the tilted pump pulse and the probe pulse, and c is the speed of light (Figure 2). Here, we use a recently developed broadband SSTA spectrometer (Wilson and Wong, 2018; Wilson et al., 2020) to track the evolution of exciton dynamics in methylammonium lead triiodide (MAPbI3) perovskite NCs as they nucleate and grow and as their surfaces are passivated with ligands. A complete TA spectrum with excellent signal to noise can be collected using this instrument in less than 1 min, allowing us to accurately measure immature NCs before they degrade (Sadighian et al., 2019). As a result, we are able to observe the surface of NCs being capped in real time by monitoring the evolving Stark lineshape. A carrier that has been photoexcited by the pump may localize on a surface trap state, creating an electric field within the NC. Using differential measurement, the probe then reports the effect of an ensemble of these electric fields on the absorption of the NC sample. These findings agree with previous reports of the growth mechanism of CdSe (Teunis et al., 2017) and MAPbI3 (Sadighian et al., 2020) NCs, and open up a new avenue for studying the surface of these materials during growth.</p><!><p>Sample plane in SSTA instrument showing pump (green) and probe (gray) focused to lines. Probe pulse is incident normal to the cuvette. Spatially encoded time delay, t, is generated by the angle of the pump pulse relative to the probe pulse, θ, and the length of overlap between the two pulses, d. Sample is injected into the flow-cell cuvette through septa to prevent solvent evaporation during the measurement.</p><!><p>All reagents were used as received: lead iodide (99.999%, trace metals basis, Sigma-Aldrich), methylammonium iodide (MAI, ≥99%, anhydrous, Sigma-Aldrich), octylamine (99%, Sigma-Aldrich), oleic acid (90%, technical grade, Sigma-Aldrich), and hexane (≥95%, laboratory reagent grade, Sigma-Aldrich). Cresyl violet (62%, J.T. Baker) in methanol (99.8%, Certified ACS, Fisher) was used to calibrate the beam profile and spatially encoded time delay of the SSTA spectrometer.</p><!><p>MAPbI3 NCs were synthesized using a previously reported solvation-limited synthesis (Sadighian et al., 2019, 2020). 460 mg of PbI2 and 127 mg of MAI were combined with 40 mL of hexane in a glass test tube and suspended in an ultrasonication bath (VWR, 97043-992) to provide constant mixing. The reaction was initiated with the simultaneous introduction of 150 μL octylamine and 300 μL oleic acid, and the recorded reaction time is in reference to this addition. These organic ligands act to solubilize PbI2 and MAI, which are otherwise insoluble in hexane (Wang et al., 2017). A recirculating chiller (VWR, 1165) in a closed-loop configuration with an aluminum block was used to maintain a temperature of 22°C in the ultrasonication bath. An HDPE syringe was used to withdraw aliquots of the reaction mixture at selected time points. Each aliquot was filtered through a syringe filter (VWR) with a 0.45 μm pore polytetrafluoroethylene (PTFE) membrane and into a 0.2 mm path length quartz flow cell cuvette (Starna Cells, 48-Q-0.2). Following the 15 min mark a 1.0 μm PTFE pre-filter (Whatman Rezist) was used in conjunction with the 0.45 μm filter to compensate for increased suspended particulate. An additional 5.0 μm filter (Whatman Rezist) was added after 60 min. The flow cell was emptied, rinsed with acetone and hexane, and dried with a stream of nitrogen before each successive measurement.</p><!><p>Absorbance and fluorescence of the filtered NC aliquots were simultaneously recorded on a homebuilt spectrometer (Supplementary Figure 1) using the same cuvette and sample described above. To measure absorbance, light from a tungsten-halogen lamp (Thorlabs, SLS201) was directed into the sample using a fiber optic cable (Thorlabs, M28L01) and the resulting transmission collected using a second fiber. A 405 nm laser (Thorlabs, CPS405) was used as the fluorescence excitation source. Emitted light was collected using a fiber optic cable (Thorlabs, M95L01) directed to the spot upon which the laser was incident on the cuvette and angled to avoid the specular reflection of the excitation source. Absorbance and fluorescence spectra were recorded using an Ocean Optics Flame-T-VIS-NIR and Flame-T-UV-VIS spectrometer, respectively. The spectrometers were operated using a homebuilt Python software package. Absorbance and fluorescence were recorded immediately before and after collecting SSTA measurements of each aliquot to make sure the spectra did not change significantly during the measurement. The pairs of spectra were then averaged together for analysis.</p><!><p>SSTA measurements were performed using a previously described homebuilt instrument (Wilson and Wong, 2018; Wilson et al., 2020). A 1 kHz Ti:sapphire laser (Coherent, Astrella) with an 800 nm output was used to pump an optical parametric amplifier (Light Conversion, Topas Prime Plus) to generate 520 nm pump pulses that were compressed to 50 fs using a prism pair. A 2 m focal length mirror focused part of the 800 nm fundamental in a 1.6 m homebuilt gas cell with 1.5 mm quartz windows and containing 0.55 bar differential pressure of argon (PurityPlus, 99.999%) to generate broadband probe pulses. The spectral profiles of both pulses are shown in Supplementary Figure 2. The pump and probe pulses were optically chopped at 250 and 125 Hz, respectively. The addition of a chopper in the probe line enabled the subtraction of background signals arising from pump induced fluorescence, scatter, stray light, and dark current from the camera (Wilson et al., 2019). A spatial light modulator (Meadowlark, 1920 × 1152 XY Phase Series SLM) placed after the choppers was used to reshape both beams to a flat-top intensity profile to provide a uniform excitation density across the entire spatially encoded time delay range.</p><p>The pump pulse energy at the sample was set to 410 nJ to prevent non-linear interactions. The pump and probe beams were focused to lines using cylindrical lenses with focal lengths of 200 mm and 150 mm, respectively, and overlapped on a 20 μm × 22 mm area of the cuvette. While the probe was incident normal to the sample, the pump beam was tilted at an angle of 55.5° to achieve a spatially encoded time delay of 60 ps. The probe beam at the sample plane was imaged onto the slit of a grating spectrograph (Princeton Instruments, Isoplane 160), where it was measured to be 10 nJ. The probe beam was slightly defocused at the sample plane such that the entire measured wavelength range overlaps well onto the slit of the spectrograph with sufficient intensity. The spectrograph was coupled to a CMOS camera (Andor, Zyla 5.5) with a 1.3 ms exposure time which acquires 180 x 2560 pixel (1.17 × 16.6 mm) images, with the signal at each pixel corresponding to a pump-probe time delay of 24 fs. One axis of the pixel array recorded wavelength resolution of the probe and the other captured the spatially encoded time delay. Each SSTA spectrum was recorded for 60 s to maximize signal-to-noise ratio while still avoiding sample degradation. The SSTA spectrometer was operated using homebuilt Python software. Spectral calibration was performed using a HgAr calibration source, which accounts for spherical aberrations in the imaging setup through the spectrometer. Calibration of the spatially encoded pump-probe time delay was performed using SSTA measurements of cresyl violet in methanol in the same cuvette used for the NC measurements. This process corrects for chirp in the broadband probe pulse. Both the wavelength and time delay calibrations are discussed in detail elsewhere (Wilson et al., 2020).</p><!><p>Absorbance and fluorescence spectra at various reaction timepoints show the evolving physical and electronic structure of PTFE-filtered NCs over 120 min of growth (Figure 3). Nucleation occurred within the first 5 min, evidenced by the appearance of a broad, low intensity emission centered around 595 nm and weak absorbance near 525 nm. The fluorescence of the reaction mixture significantly increased in intensity by the 10 min mark and began to exhibit two distinct peaks. A feature emerged at 575 nm in the absorbance spectrum, which we ascribe to nascent NCs. These absorbance and fluorescence features continued to grow in intensity, reaching a maximum at the 30 min mark. Following this, the sharp absorbance peak at 575 nm began to disappear and gave rise to a broad shoulder at 610 nm, indicative of the small, nascent NCs growing larger. Likewise, the fluorescence spectrum began to lose intensity at shorter wavelengths while the peak at 635 nm continued to grow and redshift until the final measured timepoint. The evolution of these spectra are in agreement with previously reported experiments performed under similar conditions (Sadighian et al., 2019, 2020).</p><!><p>Absorbance (Left) and fluorescence (Right) of PTFE-filtered reaction mixture sampled at different times during growth.</p><!><p>Select SSTA spectra for NCs at various stages of growth are shown in Figure 4. For each sample, the transient spectrum redshifts approximately 10 nm during the first 500 fs as a result of carrier cooling (Righetto et al., 2020). The spectra are quite stable for the remainder of the measured 60 ps time window. The spectrum of NCs grown for 120 min (Figure 4D) is typical of MAPbI3 perovskite NCs (Wang et al., 2017). The negative TA at wavelengths longer than 600 nm overlaps with the band-edge absorbance and the emission spectrum. This feature is typically ascribed to a combination of stimulated emission (SE) and ground-state bleach (GSB). The signal at shorter wavelengths is broad and positive, indicating a photoinduced absorption (PIA) to higher electronic states. The SSTA spectra of NCs grown for 20, 30, and 50 min (Figures 4A–C) show two distinct features not present in the 120 min spectrum; a strong, narrow, negative TA signal centered at 582 nm and a region of low signal intensity near 600 nm. This signal reached its maximum in the 30 min sample and had all but disappeared 50 min into the reaction. The negative signal at 582 nm does not coincide with the absorbance peak (575 nm) and the fluorescence spectrum has a shoulder at 595 nm, suggesting neither GSB nor SE can explain this signal.</p><!><p>SSTA spectra of NC aliquots measured after (A) 20 min, (B) 30 min, (C) 50 min, and (D) 120 min after starting the reaction.</p><!><p>First and second derivatives of the absorbance spectra for the 20, 30, and 50 min NC samples are shown in Figure 5. The lineshape of the derivatives is similar across the three selected timepoints, with the magnitude of the derivative traces reaching their maximum in the 30 min sample when the sharp absorbance peak at 575 nm is most intense. This peak is less intense and broader in width in the 50 min sample, resulting in smaller derivatives for this timepoint.</p><!><p>Absorbance spectra of NCs grown for 20 min (blue), 30 min (green), and 50 min (yellow). First (top) and second (bottom) derivative of the absorbance spectrum for each time point is shown in black.</p><!><p>In order to elucidate the origin of the TA lineshapes and gain additional insight into the electronic structure of growing NCs, a slice of the TA spectrum, reported in differential optical density (ΔO.D.) and averaged between 5 ps and 10 ps for each growth time, t, was fit using Equation (2).</p><p>The first two terms represent the first and second derivatives of the absorbance spectrum at the selected growth time and the third term is the analogous TA spectrum of the NC sample after 120 min of growth. This term accounts for the contribution of well-passivated NCs to the overall TA spectrum at each timepoint. The resulting fits are overlaid with TA slices in Figure 6. The colored, dashed lines are TA slices for the three time points from Figures 4, 5, and the fits (solid black lines) show good agreement. These slices reveal the evolution of the electric field induced by electron-hole pairs generated by the pump pulse in the nascent NCs. The negative TA signal at 580 nm was clearly visible after 20 min of NC growth and reached a maximum after 30 min, indicating the presence of growing, poorly-capped NCs. During the remainder of the reaction this feature lost intensity and by 50 min was barely discernible.</p><!><p>Averaged TA spectra from 5 to 10 ps for NCs grown for 20 min (blue), 30 min (green), and 50 min (yellow). Black line shows fit to Equation (2).</p><!><p>The values of the three coefficients from Equation (2) are displayed with fit errors in Table 1. Tracking their values during the reaction quantifies the evolving contributions to the TA lineshapes (Figure 7). The first term, A, relates the observed signal to the first derivative of the absorbance, which occurs when the field causes a shift in the transition energy for the NCs. Here, the presence of spatially separated electrons and holes at surface traps would induce a dipole that could stabilize the excited electronic states, potentially redshifting the optical transition. The second derivative term, B, has the largest contribution to the signal throughout nearly the entire measured range. This term arises from an overall broadening of the absorbance spectrum, suggesting the presence of many randomly oriented dipoles in the sample arising from surface-trapped carriers.</p><!><p>Best-fit values for parameters A, B, and C with one standard deviation error of the fitted variables (σX).</p><p>Fit coefficients from Equation (2) for NCs measured at different growth times. Contributions from the (A) first and (B) second derivatives, as well as the (C) 120 min NC component to the overall fit.</p><!><p>The electric field produced by a trapped carrier should become smaller as a NC grows larger, so the decreasing contribution of the derivative lineshapes during NC growth could be the result of both increasing NC size and improved surface capping, resulting in fewer NCs with internal electric fields. While the contributions from both derivatives decline to zero over the course of the reaction, B shows a brief period of growth between 30 and 70 min into the reaction. The electric field strength at any particular time point during NC growth could be estimated from these results if the NC size were known, assuming that one carrier is surface-trapped while the other is delocalized (i.e., on average centrally located within the NC). Future work will focus on concurrent measurements of NC size during the reaction, which will enable the magnitude of the electric field caused by a surface-trapped carrier to be modeled during NC growth. This will aid in the interpretation of the rise in B while A continually decreases. C, the contribution of well-passivated NCs, shows a fairly linear growth throughout the entire synthesis. By the end of the reaction the NCs are well-capped with ligands, and surface traps no longer contribute to the TA signal. Thus, our measurements indicate that poorly-capped NCs are dominant during the growth of perovskite NCs, becoming progressively better capped as the growth process continues, similar to the case shown in Figure 1B. Future studies using different polarities of filter media to separate well- and poorly-capped NCs (Sadighian et al., 2020) will seek to test this assumption and further isolate the evolving lineshapes of these sub-populations within the reaction mixture. As demonstrated here by the intriguing trends in the weights of the two derivative features, the ability of SSTA to measure lineshapes during a NC synthesis provides a new avenue to deeper insights into how NCs grow. Further analyses of both the lineshapes and the exciton dynamics hold promise for understanding the evolving nature of carrier traps in nascent NCs.</p><!><p>A novel, broadband, tilted-pulse SSTA spectrometer with a 60 ps time delay was used to investigate evolving excited state dynamics in NCs grown via a solvation-limited synthesis. Growing NCs were found to exhibit a unique TA lineshape indicative of the Stark effect. Fits of these data to a weighted sum of linear absorbance spectrum derivatives show that this lineshape is likely caused by spatially seperated charge carriers in surface trap states. This adds to the growing body of evidence that these NCs are poorly capped during most of their growth (Teunis et al., 2017; Sadighian et al., 2020). This work proves the applicability of this technique to the study of non-equilibrium systems such as growing NCs that were previously inaccessible with non-linear spectroscopies. The development of SSTA and this sampling technique provide powerful tools for understanding how the electronic structure and excited state dynamics of NCs change during their synthesis. These types of experiments may offer new insight into NC growth mechanisms and how reaction parameters can be changed to target desired photophysics.</p><!><p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p><!><p>JS optimized and executed the synthesis. KW optimized and operated the instrument. JS, KW, and MC executed the experiments. JS analyzed the data. JS and CW designed the research. All authors contributed to manuscript revision.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

Restricted Photochemistry in the Molecular Solid State: Structural changes on Photoexcitation of Cu(I) Phenanthroline metal-to-ligand-charge-transfer (MLCT) complexes by Time-Resolved Diffraction

The excited state structure of [Cu(1)[(1,10-phenanthroline-N,N\xe2\x80\x99) bis(triphenylphosphine)] cations in their crystalline [BF4] salt has been determined at both 180 and 90K by single-pulse time-resolved synchrotron experiments with the modified polychromatic Laue method. The two independent molecules in the crystal show distortions on MLCT excitation which differ in magnitude and direction, a difference attributed to a pronounced difference in the molecular environment of the two complexes. As the excited states differ, the decay of the emission is bi-exponential with two strongly different lifetimes, the longer lifetime, assigned to the more restricted molecule, becoming more prevalent as the temperature increases. Standard deviations in the current Laue study are very much lower than those achieved in a previous monochromatic study of a Cu(I) 2,9 dimethyl-phenanthroline substituted complex (J. Am. Chem. Soc. 2009, 131, 6566), but the magnitude of the shifts on excitation is similar, indicating that lattice restrictions dominate over the steric effect of the methyl substitution. Above all the study illustrates emphatically that molecules in solids have physical properties different from those of isolated molecules and that their properties depend on the specific molecular environment. This conclusion is relevant for the understanding of the properties of molecular solid state devices which are increasingly used in current technology.

restricted_photochemistry_in_the_molecular_solid_state:_structural_changes_on_photoexcitation_of_cu(

1. Introduction<!>2.1 Data collection<!>2.2 Data processing<!>2.3 Collection of monochromatic data<!>2.4 Measurement of emission lifetimes at different temperatures<!>2.5 Theoretical calculations<!>3.1 Photodifference maps<!>3.2 Least-squares refinement<!>3.3 Analysis of temperature differences due to laser exposure<!>4. Structural response to excitation<!>5. The effect of the crystalline environment<!>6. Time-resolved emission spectroscopy<!>7. Conclusions

<p>Electron injection from molecular sensitizers absorbed on semiconductor surfaces to the underlying substrate have become an increasingly important subject due to their relevance for the mode of operation of photovoltaic cells. The precise geometry of the binding modes of the sensitizers to the underlying substrate has now become accessible in the case of Ti/O nanoparticles aligned periodically in the crystalline nanoparticle phase.1-2 As a first step towards time-resolved studies of structural changes occurring on photo-excitation of electron donors absorbed on nanoparticles, we have previously studied the excited state structure of the Cu(I) complex [Cu(I)(2,9-dimethyl 1,10-phenanthroline)(1,2-bis(diphenylphosphino)ethane)][PF6] (1) by monochromatic time-resolved methods.3 The complex of which the changes on excitation are described in the current article, [Cu(1)[(1,10-phenanthroline-N,N') bis(triphenylphosphine) [BF4] (2), lacks the dimethyl substitution which interferes with the expected flattening, and is therefore expected to undergo a larger rearrangement upon formal oxidation of the Cu(I) atom on photo-induced metal-to-ligand-charge-transfer (MLCT).4-6 Cu(I) based chromophores have been proposed as promising and economically advantageous photosensitizers in photovoltaic cells.7</p><p>The monochromatic methods employed in our earlier studies suffer from two pronounced disadvantages. They require use of a stroboscopic technique in which a diffraction from a large number of pump-probe cycles is accumulated on the detector. This means that the excited state structure is recorded at a considerably higher temperature than the ground state structure due to the rapid sequence of laser pulses to which the sample crystal must be exposed. In the polychromatic Laue technique this is not the case because of the higher photon flux resulting from the increase in bandwidth. As a result with the 'pink' Laue method (ΔE/E ~8%) a diffraction pattern can be collected from a single, or at most a few 70 ps-length X-ray pulses. We have redesigned the Laue method for time-resolved applications to eliminate many of its conventional disadvantages.8 The result is a significant decrease in the excited state positional standard deviations of the more strongly scattering atoms from typically 0.02-0.05 Å in the most recent monochromatic studies to 0.006-0.008Å achieved in our recent Laue experiments.8</p><p>In the time-resolved Laue study of (2) described here a spatial resolution of 0.002-0.004Å is achieved at 90K for the excited state Cu atoms and 0.004-0.007Å for the lighter atoms in the excited-state structure. Like (1), (2) crystallizes with two independent molecules in the asymmetric unit, which allows analysis of the effect of the crystalline environment on the molecular changes.</p><!><p>Time-resolved intensity data were collected at the 14-ID beamline at the BioCARS station at the Advanced Photon Source at an undulator setting of 15keV. To select the optimal laser power short 10° φ scans were performed at different laser powers. Correlation plots between the resulting response ratios are shown in Fig. 1. As expected, an increase in laser power leads to a larger response. Full data collections were performed at two different temperatures. In the first, at 180K, 35 ps pulses from a Ti:sapphire laser tuned to a wavelength of 390 nm were used as the pump source with a pump-probe delay of 100 ps. Laser power varied between 0.6 and 1.1 mJ/mm2/pulse. The second set was performed at 90 K with 4 ns pulses of a Nd:YAG laser tuned to a wavelength of 420nm with a pump-probe delay time of 2 ns and a laser power of 1.6 mJ/mm2/pulse. The longer delay time causes a spot extension on the ON frames9 which is effectively taken care of by a new non-profile fitting spot-integration procedure to be described elsewhere. To maximize the number of weak reflections observed in both sets, the pump-probe cycle was repeated three times for each frame before detector read-out. Δφ values of 1° and 2° were used. Laser-OFF and Laser-ON frames were collected in immediate succession to minimize the effect of long range fluctuations in the beam's position or intensity. The ON/OFF pump-probe cycle was repeated ten times for each frame to allow subsequent statistical background estimation and filtering of the intensities. Further details are as described in reference 8. Specific information on each of the 12 data sets collected is given in Table S1.</p><!><p>The intensities from the Laue experiment were integrated and indexed by the newly developed LaueUtil toolkit,10 which includes both rapid orientation matrix determination suitable for intermediate size unit cell crystals and the novel spot integration technique. The integration method does not use profile-fitting techniques, nor does it require initial knowledge of the sample's cell dimensions as it is based on statistical analysis of the intensities of all the pixels on successive frames in the φ scans. hkl indices are assigned subsequently using the orientation matrix from LaueUtil. After statistical analysis of the ten repeated ON/OFF pair measurements of each frame, ratios were averaged with the program SORTAV.11 Details are given in Table S1. Results of different runs were examined by correlation similar to those depicted in Fig. 1.</p><p>Crystallographic information on (2) is summarized in Table 1. Cell dimensions did not change as a result of the laser exposure, a result attributed to the low conversion percentages. Bond distances and selected angles are listed in Table S2.</p><!><p>The RATIO method12 uses monochromatic intensities for reference. They are multiplied by the synchrotron-determined ON/OFF ratios to obtain reliable ION intensities, used for generation of photodifference maps such as shown in Fig 2. The monochromatic data were collected with Mo K radiation on a rotating anode generator equipped with a Bruker-Apex II area detector. At both temperatures five omega scans were collected each covering a 180° range with a step size of 0.5°. Bruker software was used for data collection and integration,13 while the data were merged with the program SORTAV.11 Refinements were performed with SHELX14 combined with a WinGX15 graphical overlay. Crystallographic information in listed Table 1.</p><!><p>Luminescence measurements were performed on a ~150×200×400 ×m single crystal of (2) in a Displex cryogenic cooler equipped with a shroud specially constructed for low-temperature emission spectroscopy. A vacuum chamber with quartz windows attached to the cryostat was evacuated to ~10−7 bar. The crystal was cooled to the desired temperature and excited with λex=366 nm light from a N2-dye laser pulses with a 1 Hz repeat frequency. The emission spectrum was passed through an Oriel grating monochromator, recorded with a Hamamatsu photomultiplier tube and processed by a DSO-2102S computer-based digital oscilloscope with 100MHz sampling rate.</p><!><p>Gaussian0916 was used for all reported calculations. Isolated molecule QM calculations were performed with a number of basis sets and with both the BP86 and B3LYP functionals. Cartesian xyz coordinate files were generated using Mercury 2.3.17 C-H bond lengths were extended to the standard lengths of 1.083 Å and 1.074 Å for aromatic and aliphatic carbons respectively, as derived from neutron diffraction experiments.18 QM/MM calculations were performed with the ONIOM module of Gaussian09, both without and with embedded charges on the crystalline shell surrounding the central molecule. The structure of the shell was kept fixed at the geometry as determined by X-ray diffraction. The UFF (Universal Force Field)19 force field as available in Gaussian09 was used for the MM region. As the surrounding shell was not varied in the calculation only the non-bonded interaction parameters of the atoms lining the cavity affect the results of the calculation. Hirshfeld charges from LANL2DZ-BP86 calculations were used for the Coulombic interactions of the surrounding shell with the central molecule in the QM/MM calculations.</p><!><p>As Fourier maps must be based on datasets of maximum completeness to be meaningful, merging of all collected data sets is indicated. To accomplish this individual sets were scaled according to the average values of the response ratios ∣<η>∣ in each set, where η is defined as (ION-IOFF)/IOFF8,20. The photodifference maps based on all independent reflections from the data sets collected at each of the temperatures are shown in Fig. 2. Isosurfaces are drawn at ±0.25 e/Å3 to highlight the Cu displacements. The agreement between the 180K and the 90K results supports the validity of the experimental methods used. At both temperatures a displacement of the Cu(1) atom roughly within the Cu-P-P plane and away from its associated phenanthroline ligand is evident, as well as a pronounced displacement of Cu(2) towards the phenanthroline ligand to which it is ligated. The two independent molecules clearly show a different response to the excitation.</p><!><p>The excites state structures were refined with the program LASER, which is based on the refinement of the response to light exposure, defined as η = (ION-IOFF)/IOFF=RON/OFF-1.22 The refinement procedure is based on a random spatial distribution of the excited state species in the crystal. Formation of domains sufficiently large to change the scattering formalism would lead to very different calculated intensities and in some cases a second set of reflections.23 No evidence for domain formation was found in the current study or any of our previous studies. The LASER program allows for simultaneous refinement of up to six data sets on the same structure. The variables in the refinement are, for each data set, the temperature scale factor, and the excited-state conversion percentage, plus the excited state structural parameters, including rigid body motions, for the combined data. The program calculates agreement-factors suitable for refinements based on the response ratios.24 Only data with ∣η∣/σ(η)>1 were used in the current refinement. The detailed refinement strategy is described in the supplementary material. Agreement factors and other information on the refinement are listed in Table S3.</p><!><p>An initial estimate of the temperature increase due to the laser exposure can be obtained from a photo-Wilson plot.23,25 The plot for the merged data collected at 90K is shown in Fig. 3.</p><p>The slope of the plot corresponds to twice the isotropic increase of the average Debye-Waller factor 2 ΔB. The slope in fig. 3 corresponds to ΔB =0.125Å2 from which an estimate of the relative temperature increase, expressed as a temperature scale factor kB, can be obtained. kB is included as a variable in the refinement procedure with the program LASER,22 which leads to a second estimate of the temperature increase. Observed and least-squares refined values of kB for each of the 6 data sets collected at each temperature, listed in Table 2, agree well. The refined values tend to be somewhat larger, especially at 180K. The difference is attributed to the omission of the reflections with ∣η∣/σ(η)<1 from the least squares refinement, while the Photo-Wilson plots are based on all observed reflections. As shown in Fig. S1, the temperature scale factors correlate with the excited state occupancy from the least-squares refinement, as expected as both are a result of the laser exposure. Both sets indicate the temperature increase to be larger at 90K than at 180K, possibly due to a temperature dependence of the thermal conductivity of the crystals.26 Even at 90K the increase in temperature in the classical limit (B proportional to T) is not more than about 10°, except for data set 90-1.</p><!><p>Absolute values of the maximal shifts of the core Cu, P and N atoms on excitation, listed in Table 3, range up to 0.140(13) Å for P at 180K and 0.098(4) Å for Cu at 90K. Except for Cu(2) the shifts are considerably larger at the higher temperature at which the crystals are softer, as evident also from the increase in the Atomic Displacement Parameters.</p><p>Specific information on the Cu coordination environment is provided by the changes in bond lengths and dihedral angles at the Cu atoms. Bond length changes are summarized in Table 4. In accordance with the maxima in the photodifference map, the changes at Cu differ drastically for the two independent molecules. For Cu(2) in the less confined molecule (labeled B) the Cu-N bonds shorten by ~0.04Å, whereas the Cu-P distances lengthen significantly, though the shifts are considerably smaller than calculated for the isolated molecule as further discussed in the next section. For Cu(1) (in the molecule labeled A) the changes in the bond lengths on excitation from the least-squares refinement are not significant, although the individual atom shifts are significant and clearly visible in the photodifference maps in a direction opposite to those at Cu(2). Bond-angle changes around Cu, listed in the last two rows of table 4, are generally significant, but again much larger for Cu(2).</p><p>The earlier results from a monochromatic time-resolved study on the Cu(I)(dmp)(dmpe)+ 1) 3 agree qualitatively on the elongation of the Cu-P bonds, but are not conclusive on the Cu-N distance changes due to much poorer accuracy than achieved in the current study.</p><p>The distortion of the Cu-coordination environment from perfect mm symmetry, with the mirror planes coinciding with the P-Cu-P and N-Cu-N planes, can be quantified by the flattening, rocking and wagging distortions, as described by Dobson et al.27 and illustrated in Fig. 4. The coordination environments of the Cu(1) and Cu(2) centers are already quite distinct in the ground state and respond differently to the electronic excitation as described in Table 5. The flattening distortion, expected because of the formal oxidation of the Cu(I) atom on excitation, is barely observable for Cu(1) but significant for Cu(2). However, as described in the next section, both distortions are much smaller than calculated for the isolated molecule and expected in solution. As observed in the 2,9 methyl substituted Cu(I)(dmp)(dmpe)+ cation (1) rocking and wagging distortions are also much less than those calculated for the isolated molecule.</p><!><p>An important conclusion to be drawn from the experimental results is the different behavior of the two independent molecules in the crystal. This is evident from the shifts on excitation (Table 3), the bond length changes (Table 4) and the flattening angles (Table 5). The Cu(2) atom moves towards the phenanthroline ligand with a C-N shortening of ~0.04Å and away from P(4), whereas the shifts for Cu(1) are much smaller and within the experimental errors. Examination of the packing of the two molecules reveals a pronounced difference. Whereas molecule A is π-stacked with a center of symmetry-related neighbor, forming a π-stacked chain with alternating phenanthroline and phenyl ligands, no such interaction exists for molecule B, as illustrated in Fig. 5. The distortions around the Cu atoms at 90K are illustrated in Fig. 6. Those of Cu(1) are very small, whereas those of Cu(2) are clearly visible.</p><p>The effect of the lattice is even more evident when the observed distortions are compared with those calculated for the isolated molecule for which we calculate a flattening of ~31°, (B3LYP, 6-31G*) compared with 3-5° observed in the present case. Interestingly, there is very little difference between the flattening distortions observed in this study and those in the 2,9-dimethyl substituted complex (1), suggesting that the dramatic influence of packing restrictions override those of the methyl substitution.</p><p>In previous studies we have estimated the constraining effect of the lattice by QM/MM methods in which the central molecule is treated quantummechanically, but the effect of the surrounding crystal is introduced by treating the molecule-lattice interactions by force-field atom-atom potential functions.8,28 Application of this method accounted almost quantitatively for differences between the observed and calculated Rh-Rh shortening in a binuclear rhodium complex.8</p><p>We have not been able to reproduce the experimental results with this method in the present case. While a reduction in the distortions is predicted, they are underestimated and the calculations failed to reproduce the pronounced difference between the two sites, at least when B3LYP-DFT methods were used with several different basis sets. This is possibly due to the effect of dispersion forces, which are poorly accounted for in the DFT calculations, but important in π-π stacking observed here. This effect will be investigated in future calculations.</p><!><p>Lifetime measurements were made at 50, 90 and 180K. Results at 90 and 180 K are shown in Fig. 7. At all temperatures a significantly superior fit was obtained with a bi-exponential decay as illustrated in the figure. Fitting constants indicate one short lifetime of ~12 ×s at 90K and a longer lifetime of ~116 ×s at the same temperature, with pre-exponential factors of 0.06 and 0.15 respectively. At 180K the two lifetimes are reduced to 8 and 72 ×s with pre-exponential factors of 0.026 and 0.144 respectively, indicating that the longer lifetime becomes relatively more dominant at the higher temperature. Full information is given Table S5 and Fig. S2. Interestingly, although the individual bond length changes at Cu(1) are not significant, they are consistently larger at 180K than at 90K, which is not the case for Cu(2). This suggest that longer lifetime is associated with the luminescence of complex with Cu(1) at its center, which is more confined in the crystal. This is in agreement with earlier conclusions of McMillin et al.29 that a smaller structural change of the Cu-phenanthroline complexes on excitation leads to a longer lifetime of the excited species, in accordance with the energy gap law,30-32 as a less relaxed excited state will have a higher energy. We conclude that the observed bi-exponential decay is to be attributed to the co-existence of two chemically identical, but structurally distinct molecules in the crystalline environment which show large difference in distortion on excitation.</p><!><p>The modified Laue method for collection of time-resolved synchrotron data leads to structural information of significantly higher accuracy than achieved in an earlier monochromatic study of a related solid. Although the previously investigated complex (1) is dimethyl-substituted in the 2,9 positions of the phenanthroline ligand, which inhibits the expected flattening on photo-oxidation of the Cu atom, while (2) is not, flattening distortions of both complexes are very similar and very much less than calculated for the isolated molecule, indicating the dominant effect of the crystalline environment. Both complexes crystallize with two molecules in the asymmetric unit and in both cases the two independent molecules show different distortions on excitation. In the current study in one of the molecules the Cu-N distances contract, whereas the dominant motion of Cu in the second molecule is towards one of the phosphorus atoms. The observed bi-exponential decay of the emission is attributed to the different distortions of the two molecules. In accordance with the energy gap law the longer lifetime is assigned to molecule (1) which undergoes a smaller distortion on excitation. The QM/MM treatment of the effect of the molecular surroundings significantly underestimates the reduction in the flattening, in contrast to earlier results on binuclear rhodium compounds, but does confirm the difference betweent he two independent molecules in the crystal.</p><p>Above all the study illustrates emphatically that molecules in solids have physical properties different from those of isolated molecules and that their properties depend on the specific molecular environment. This conclusion is relevant for the understanding of the properties of molecular solid state devices which are increasingly used in current technology.</p>

PubMed Author Manuscript

Using informative features in machine learning based method for COVID-19 drug repurposing

Coronavirus disease 2019 (COVID-19) is caused by a novel virus named Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This virus induced a large number of deaths and millions of confirmed cases worldwide, creating a serious danger to public health. However, there are no specific therapies or drugs available for COVID-19 treatment. While new drug discovery is a long process, repurposing available drugs for COVID-19 can help recognize treatments with known clinical profiles. Computational drug repurposing methods can reduce the cost, time, and risk of drug toxicity. In this work, we build a graph as a COVID-19 related biological network. This network is related to virus targets or their associated biological processes. We select essential proteins in the constructed biological network that lead to a major disruption in the network. Our method from these essential proteins chooses 93 proteins related to COVID-19 pathology. Then, we propose multiple informative features based on drug–target and protein−protein interaction information. Through these informative features, we find five appropriate clusters of drugs that contain some candidates as potential COVID-19 treatments. To evaluate our results, we provide statistical and clinical evidence for our candidate drugs. From our proposed candidate drugs, 80% of them were studied in other studies and clinical trials.

using_informative_features_in_machine_learning_based_method_for_covid-19_drug_repurposing

Introduction<!>Finding essential proteins related to COVID-19 pathology as candidate drug targets<!>Construction of COVID-19 related biological network<!>Disruption of COVID-19 related biological processes<!>Algorithm 1: spectral partitioning<!>Algorithm 2: betweenness value<!>Candidate essential proteins associated with COVID-19 pathology<!>Protein−protein interaction network<!>Interactive information between drugs and human protein targets<!>Construction of drug–target network<!><!>Evaluation essential proteins related to COVID-19<!><!>Evaluation essential proteins related to COVID-19<!><!>Evaluation of clusters with respect to proteins as drug targets<!><!>Evaluation of clusters with respect to related diseases<!><!>Discussion and summary<!>

<p>The pandemic situation for Coronavirus disease 2019 (COVID-19) causes more than 197 million infections and more than 4.2 million deaths in more than 200 countries worldwide (until the end of July 2021) and this number is increasing rapidly. Due to this rapid spread, researchers have been searching for therapeutic approaches in the past few months. At present, no medicine has been claimed to be effective in the treatment or even prevention of COIVD-19 [1]. On the other hand, producing new drugs with a complete drug profile is a tough task that requires extensive time and budget. Drug repurposing is the procedure of perusing new therapeutic uses for available drugs. This process can reduce a large amount of time, money, and danger of the traditional drug discovery process [2]. The main purpose of drug repurposing is to exceed the therapeutic use of the available drugs for more medical scope. Previous researches showed that drugs with similar profiles probably demonstrate similar behavior in the existence of similar targets like proteins [1–3]. Traditional drug repurposing methods are mainly based on finding the relationship between biological activity and the molecular structure of different drugs. However, newer data gathering and analysis shows the urgent need for using computational methods for drug design and repurposing. Computational methods are mainly used to discover different drug interactions that are not considered and found during the clinical trial process [4]. In drug repositioning, computational methods investigate the relationship between drug databases and genomic, transcriptomic, and other available information with the help of data and network analysis and machine learning methods [2]. Machine-learning based methods for drug repurposing reveal the connection between drugs, viral, and host proteins. In the life cycle of a virus, the viral proteins are associated with different human proteins in the infected cells through different interactions. Within these interactions, the virus hijacks the host cells for replication, and this process changes the regular function of these interacted proteins. Therefore, to design antiviral drugs, a complete understanding of the interaction between human proteins and viral is crucial [5]. It is worth mentioning, in drug repurposing to fight the virus, targeting just virus proteins is not the proper approach. Targeting single virus proteins can cause the viruses to escape this attack through some backup pathways. These backup pathways lead to increased virus resistance with the mutation. Host-directed treatments propose significant strategies [6]. These methods select human proteins as the main carriers for the virus to enter and control human cells. These host-directed treatments seem to be less susceptible to making resistance because human proteins are less influenced by mutations. Therefore, targeting human proteins as drug targets is a more sustainable strategy. In host-directed treatments, it is important to find proteins that are essential for the maintenance and persistence of the disease that is caused by a virus in the human cells. When these proteins are targeted as drug targets, the replication mechanism of the virus collapses. For all of the above-mentioned reasons, repurposing drugs with host-directed treatments against COVID-19 has major potential. Furthermore, drug repurposing methods provide hope for fast practical implementation with the minimum side effects. Molecular interaction and biological interaction networks as valuable resources are the foundation for drug repurposing methods [7]. This means that network-based drug repurposing methods propose novel opportunities for finding drug targets in host-directed treatments [8]. Recent studies show that valuable results are based on viral-host networks for treating HIV [9], Hepatitis C [10], and Ebola as well [11]. Since the outbreak of COVID-19 some research groups have been trying to develop network-based methods to find some repurposed drugs to operate against SARS-CoV-2. Zhou et al. [12] proposed a network-based method for the identification of some candidates as repurposable drugs and some potential drug combinations targeting. Li et al. [13] combined network data with a relative analysis of the gene sequences of the different viruses to find potential drugs for SARS-CoV-2. Gordon et al. [14] proposed a map from human proteins with SARS-CoV-2 proteins that were found to interact in the affinity purification mass spectrum method. Dick et al. [15] recognized high confidence interactions between human proteins and SARS-CoV-2 proteins with the help of sequence-based protein−protein interaction (PPI) predictors.</p><p>In this paper, we propose the four steps method. This method tries to identify novel drug targets and pathways associated with essential proteins in COVID-19. In the first step, we build a graph as a COVID-19 related biological network related to virus targets or their associated biological processes. In the second step, we use two effective algorithms [16, 17] to find the candidate set of proteins from biological networks that lead to a major disruption in the network. In the third step, we identify proteins in our candidate set that are associated with some underlying diseases related to COVID-19. Then, we select 93 proteins as a final set of essential proteins related to disease pathology. Identifying essential proteins may elucidate new drug targets and pathways related to COVID-19. In the fourth and last step, we propose informative features based on drug-protein and PPI networks and find five significant clusters that contain appropriate candidate drugs. Our results show that using our four steps method suggests some appropriate candidate drugs. Most of these candidate drugs are recommended in other studies.</p><!><p>Introducing the essential proteins related to COVID-19 pathology as candidate drug targets is one of the most used and appropriate ways to find suitable drugs for COVID-19 treatment. In this subsection, we describe the first, second and third steps of our proposed method. These two steps try to find the set of essential proteins related to COVID-19 pathology. In the first step, we use two effective algorithms [16, 17] for finding the minimum number of proteins that participate in a large number of biological processes. We use these algorithms to find sets of essential proteins based on the disruption of the COVID-19 related biological network. In the second step, we investigated COVID-19 associated protein sets. As a result of this step, we found a subset of essential proteins that are essential to disease pathology.</p><!><p>Suppose that informative biological processes (IBP) is a set of biological processes related to virus targets in COVID-19 that will be described in the next subsection. Two proteins are functionally interacted if they are connected through the same biological processes. A COVID-19 related biological network is considered as a weighted undirected graph \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G= (V, E, \omega )$$\end{document}G=(V,E,ω). In this graph, each node \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i \in V$$\end{document}vi∈V represents the protein and each edge \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$e_{ij} \in E$$\end{document}eij∈E represents a functional interaction between two nodes \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_j$$\end{document}vj. The \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\omega (e_{ij} )$$\end{document}ω(eij) shows the weight of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$e_{ij}$$\end{document}eij that demonstrates the number of biological processes that two nodes \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_j$$\end{document}vj participate in them. A path between two nodes \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_j$$\end{document}vj and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_k$$\end{document}vk in the graph is a sequence of edges that connect the number of distinct nodes through this path. In the weighted graph, the weight of the path between two nodes is defined as follows. Suppose that \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_j$$\end{document}vj and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_k$$\end{document}vk as the two ends of this path. Then, the sum of the weight of edges between these two nodes is the weight of this path. A path with the minimum weight between these two nodes is named the shortest path. Now, we define the betweenness value for each node, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi, in the graph in the following way:1\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} Betw ({ v_i}) = \sum _{ { {v_j}, {v_k}} \in {V} } rac{ heta _{e_{jk}} {v_i} }{ heta _{e_{jk}}}, \end{aligned}$$\end{document}Betw(vi)=∑vj,vk∈Vθejkviθejk,where \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ heta _{e_{jk}}$$\end{document}θejk shows the total number of shortest paths from node \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_j$$\end{document}vj to node \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_k$$\end{document}vk and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ heta _{e_{jk}} {v_i}$$\end{document}θejkvi indicates the number of shortest paths that pass through node \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi.</p><!><p>We adapt two algorithms to detect the essential proteins in the COVID-19 related biological network [16, 17]. These algorithms [16, 17] select some of the best candidates as removal proteins set from the COVID-19 related biological network to make a major disruption in it. We place the outputs of Algorithm 1 and 2 in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2, respectively.</p><!><p>Partitioning a simple graph, G, into disjoint balanced or nearly balanced parts with removing the minimum number of edges between these two parts is known as the NP-complete problem [16]. We try to approximate this partitioning problem with the spectral partitioning algorithm. This algorithm is based on eigenvectors of the Laplace of the graph, G, and divides the graph into two disjoint parts with respect to eigenvectors of a Laplacian matrix. It is worth mentioning that, the spectral partitioning algorithm is one of the best heuristic approaches for graph partition. Let \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$A= [a_{ij}]$$\end{document}A=[aij] shows the adjacency matrix of graph G such that,2\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} a_{ij} = {\left\{ egin{array}{ll} 1 &{} \quad extit{if } (v_i , v_j) \in { E} \ 0 &{} \quad extit{ otherwise} \end{array} ight. } \end{aligned}$$\end{document}aij=1if(vi,vj)∈E0otherwiseWe define a diagonal degree matrix \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$D = diag(d_i)$$\end{document}D=diag(di) for graph G. In this matrix value \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$d(v_i)$$\end{document}d(vi) shows the degree of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi in graph G. The Laplacian matrix of the graph G is defined by \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$L = D ackslash A$$\end{document}L=D\A and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$L(G)=[l_{ij}]$$\end{document}L(G)=[lij] where,3\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} l_{ij} = {\left\{ egin{array}{ll} 1 &{} \quad extit{if } (v_i , v_j) \in { E}\ d(v_{i}) &{} \quad extit{if } i=j\ 0 &{} \quad extit{ otherwise} \end{array} ight. } \end{aligned}$$\end{document}lij=1if(vi,vj)∈Ed(vi)ifi=j0otherwiseThe Laplacian matrix is a symmetric positive semi-definite matrix. This matrix has some important properties. Suppose that vector \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$u=(u_1, u_2, ..., u_n)$$\end{document}u=(u1,u2,...,un) shows the normalized eigenvectors of matrix L(G) and vector \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$(\lambda _1, \lambda _2, ..., \lambda _n)$$\end{document}(λ1,λ2,...,λn) demonstrates the corresponding eigenvalues of these eigenvectors. We first compute the eigenvectors of Laplacian matrix L(G), according to the second smallest eigenvalue of this matrix ,\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\lambda _2$$\end{document}λ2, and put them in vector \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$X=(x_1,..., x_n)$$\end{document}X=(x1,...,xn). Then, we sort the elements of vector X and insert half of the nodes in partition \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and the reminder of nodes in another partition \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2. This procedure divides the nodes of graph G into two partitions, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2 with nearly equal sizes. Removing the edges between these two parts through the cut edges \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$E(G_1, G_2)$$\end{document}E(G1,G2) makes these two parts disconnect. Suppose the vector \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$A = \{ lpha _1, ..., lpha _m \}$$\end{document}A={α1,...,αm} shows the vertices placed in part \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and vector \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$B = \{ eta _1, ..., eta _m \}$$\end{document}B={β1,...,βm} shows the vertices are placed in part \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2, respectively. To make these two parts, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2 disconnect, we choose vertices from vectors A and B repeatedly. The vertices are chosen with respect to their degrees and removed until the all edges in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$E(G_1, G_2)$$\end{document}E(G1,G2) are covered.</p><!><p>This algorithm [17] tries to make the maximum disruption in the network by removing the minimum number of essential proteins. The selection method in algorithm [17] is based on the betweenness value mentioned in Eq 1. The algorithm [17] has three parts. In the first part, the betweenness value for each node in the graph G is calculated. In the second part, to separate the graph G into two disjoint partitions \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2, the node with the minimum betweenness value in graph G is selected and placed in partition \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1. Then, from all of the neighbors of the selected node, the node with the minimum betweenness value is selected and placed in the other partition \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2. These procedures are repeated until all nodes are placed into two disjoint partitions \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2. In the third part, the minimum number of nodes from two constructed partitions \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2 is selected with respect to their betweenness values to remove all edges in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$E(G_1, G_2)$$\end{document}E(G1,G2). The third step of this algorithm is equivalent to the minimum bi-section problem that is an NP-complete problem [18].</p><!><p>COVID-19 is a pandemic disease and has different severity and symptoms for various patients. The severity of this disease can vary from asymptomatic to fatal for different people. Recent studies show that this disease has high severity in people with some underlying conditions. Some of the most related underlying diseases are Diabetes, Cardiovascular diseases, Lung diseases, Hepatitis, Kidney disease, and different types of cancer. Hence, we expect that the genetics of these underlying diseases has some correlations with the essential proteins in COVID-19. For finding these essential proteins, we use the relation between gene and disease from Database for Annotation, Visualization, and Integrated Discovery (DAVID). Then, we select some proteins through our two mentioned algorithms that are annotated to four out of five of these specific comorbid diseases. From these selected proteins, proteins with significant p-values as a set of essential proteins associated with COVID-19 are chosen and placed in E as a set of main target candidates of COVID-19 drugs.</p><!><p>We use 5 human high-throughput PPI networks in this work. The first one, Huri, contains 52,248 binary interactions [19]. The second one is collected from the biological general repository for interaction datasets (BioGRID) and contains 296,046 interactions [20]. The BioGRID dataset contains various interactions that are created from different techniques. In this work, we just use the physical interactions between proteins. The three other datasets are human integrated protein−protein interaction reference (HIPPIE) [21], agile protein interactomes dataanalyzer (APID) [22], and homologous interactions (Hint) [23] that contain 57,428, 171,448, and 64,399 experimental interactions, respectively. These interactions are derived from high-throughput yeast-two hybrid (Y2H) and mass spectrometry methods. We map all of the proteins from these five datasets to their corresponding universal protein resource (UniProt) ID [24]. We removed a protein if it could not be mapped to a Uniprot ID. Finally, in this study, we used 25,260 proteins and 304,730 interactions. For all of these proteins, we use biological process terms from gene ontology (GO) term [25] to point out the biological modules in humans. We find that 20,642 proteins from these 25,260 proteins or 81% of them are annotated. We consider a biological process annotation informative if it has these two properties. First, at least k proteins are annotated with it. Second, each of its descendant's GO terms needs to have less than k proteins annotated with them. We set 3 as a value of k and we note that 16,021 biological processes corresponding to these 25,260 proteins that are participating in our interactions. We also use 332 human proteins involved in 26 proteins of the SARS-CoV-2 virus that were revealed by Gorden et al. [14]. The set, T, shows these 332 proteins as possible targets of the SARS-CoV-2 virus. For this set of 332 human proteins, we also consider 1374 IBP GO terms as high-confidence SARS-CoV-2 Human PPI.</p><p>We define the overlap between two biological processes, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$p_1$$\end{document}p1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$p_2$$\end{document}p2 in the following way (| . | shows the size):4\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} Overlap(p_1,p_2 )=rac{|p_1igcap p_2|^2}{|p_1||p_2|}. \end{aligned}$$\end{document}Overlap(p1,p2)=|p1⋂p2|2|p1||p2|.Then, the processes with more than 15% overlaps have been removed. Through this filtering method, we have 1213 non-overlapping biological processes corresponding to COVID-19.</p><!><p>To evaluate our candidate targets, we use all drugs and their corresponding targets interactions that are reported in the UniProt [24]. These interactions contain 6163 drugs from All-Drug group that are reported in UniProt, these drugs have 2898 protein targets. We also use 44 experimental unapproved drugs for COVID-19 that are reported in DrugBank [26]. From these 44 drugs, 27 drugs have no target information and only 17 drugs have the drug target information. These 17 drugs can target 78 proteins in a cell. This group of drugs is denoted as Covid-Drug. The second group of drugs contains 590 drugs as clinical trials for COVID-19. From these 590 drugs, 328 drugs have targets in the PPI network denoted as Clinical-Drug. These 328 drugs can target 888 proteins in a cell.</p><!><p>We define some topological features in a PPI network for cluster identification of drugs. These features cluster the available experimental unapproved drugs for COVID-19 with respect to these topological properties of their associated targets in the PPI network. To do this, we define a drug–targets network in the following way.</p><p>Each drug–targets network is considered as a bipartite graph \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$H= <D, au , E^*>$$\end{document}H=<D,τ,E∗>. In graph H, nodes are divided into two different sets. The first one, D, demonstrates the set of experimental unapproved drugs for COVID-19, and the second one, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ au$$\end{document}τ, shows the experimental unapproved drug targets. Each edge \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$e_{vd} \in E^*$$\end{document}evd∈E∗ shows that two nodes \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v \in au$$\end{document}v∈τ and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$d \in D$$\end{document}d∈D are connected if the node v in a human cell be a target of drug d. In fact \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ au$$\end{document}τ, contains the proteins that are placed in the intersection of all drug targets with 2898 proteins and set E. Supposed that \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G=<V, E>$$\end{document}G=<V,E> is a PPI network that contains the set of virus targets (T) and the set of main targets (\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ au$$\end{document}τ). Two nodes \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_j$$\end{document}vj are neighbors if there is an edge between them. Suppose that \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$N(v_i)$$\end{document}N(vi) shows a set of all neighbors for a node \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi, therefore \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$d(v_i) = | N(v_i)|$$\end{document}d(vi)=|N(vi)| indicates the degree of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi.</p><!><p>\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$D_T (d)$$\end{document}DT(d): The average ratio of the number of neighbors for each protein \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i \in au _{d}$$\end{document}vi∈τd that is also placed in set T according to the degree of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi. 5\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} D_T (d) = rac{\sum _{i=1}^{m} { rac{|N(v_i) igcap T|}{ d(v_i)} }}{ | au _{d}|}, \end{aligned}$$\end{document}DT(d)=∑i=1m|N(vi)⋂T|d(vi)|τd|, where \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ au _{d} = \{ v_1, ....v_m \}$$\end{document}τd={v1,....vm} denotes the number of main targets for drug d.</p><p>The participation rate of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$ au _{d}$$\end{document}τd in set \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\pi$$\end{document}π defines as follow: 6\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} P_{IBP} (d) = 1- \sum _{p_i \in \pi } \left( { rac{ | p_i igcap au _{d} | }{ \sum _{p_i \in \pi } {| p_i igcap au _{d} |} } } ight) ^2, \end{aligned}$$\end{document}PIBP(d)=1-∑pi∈π|pi⋂τd|∑pi∈π|pi⋂τd|2, where set \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\pi = \{p_1,p_2, ...,p_k \}$$\end{document}π={p1,p2,...,pk} shows the non-overlapping biological processes corresponding to COVID-19. The possible values for \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$P_{IBP} (d)$$\end{document}PIBP(d) is between 0 and 1. If the value of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$P_{IBP} (d)$$\end{document}PIBP(d) is closer to 1, it means the neighbors of node d have higher distribution in the set of biological processes.</p><p>\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$D_P (d)$$\end{document}DP(d): The average ratio of the number of neighbors for each protein \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i \in au _{d}$$\end{document}vi∈τd that is also placed in set \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\pi$$\end{document}π according to the degree of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$v_i$$\end{document}vi. 7\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} D_P (d) = rac{\sum _{i=1}^{m} { rac{|N(v_i) igcap P|}{ d(v_i)} }}{ | au _{d}|}. \end{aligned}$$\end{document}DP(d)=∑i=1m|N(vi)⋂P|d(vi)|τd|. where \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$P=igcup _ {p_i \in \pi } p_i$$\end{document}P=⋃pi∈πpi.</p><p>Overall workflow. Our method integrates a drug–target network with a Human-virus network in the human PPI network. A. Human and coronavirus host proteins were collected from different datasets to generate a COVID-19 related biological network. B. Algorithm 1 (Alg 1) and 2 (Alg 2) detect the essential proteins in the COVID-19 related biological network. Three Informative features introduced. The Machine Learning method used these features and find three significant clusters. C. The resulted clusters evaluated with different measures. These measures are based on drug targets in these clusters. Finally, some candidate drugs recommended</p><!><p>The protein sets that are resulted from algorithms 1 and 2 are placed in the sets \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2, respectively. The union of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2 is placed in the \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{union}$$\end{document}Cutunion set and the intersection of them is placed in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{intersect}$$\end{document}Cutintersect, respectively. For more evaluation of essential proteins of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2 sets, we study the topological properties of these two sets. In this work, we claim that through our cut sets as results of two presented algorithms, the maximum number of IBP GO terms are disrupted. We also claim that the two disjoint sets of vertices \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2 (resulting from the cut set) are approximately equal in size. Moreover, each IBP GO term, like C has almost the same size on both sides of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_1$$\end{document}G1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$G_2$$\end{document}G2 sets. Suppose that C is a process from the IBP GO terms. The disruption score for this process is defined as follows [16]:9\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$egin{aligned} Score_{disrupt(C)} = rac{MAX \{ C \cap G_{1}, C \cap G_{2} \}}{|C|}, \end{aligned}$$\end{document}Scoredisrupt(C)=MAX{C∩G1,C∩G2}|C|,The closer value of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Score_{disrupt(C)}$$\end{document}Scoredisrupt(C) to \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$rac{1}{2}$$\end{document}12 indicates that process C is completely disrupted. However, if the \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Score_{disrupt(C)}$$\end{document}Scoredisrupt(C) for a process C is in the range \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$[0,rac{1}{2}+ \epsilon ]$$\end{document}[0,12+ϵ], we say that this process is \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\epsilon$$\end{document}ϵ-disrupted.</p><!><p>The number of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\epsilon$$\end{document}ϵ-disrupted processes for the selected cut sets</p><!><p>In Table 1 we compare the number of \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\epsilon$$\end{document}ϵ-disrupted processes for \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{hub}$$\end{document}Cuthub and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{weight}$$\end{document}Cutweight respectively. The results of Table 1 show that \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2 have better disruption properties and this confirms that the selection algorithm that we used for \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_1$$\end{document}Cut1 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_2$$\end{document}Cut2 are significantly better than other algorithms.</p><!><p>The first row shows the number of proteins in sets T, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\hbox {Cut}_{2}$$\end{document}Cut2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\hbox {Cut}_{{1}}$$\end{document}Cut1, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\hbox {Cut}_{{intersect}}$$\end{document}Cutintersect and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\hbox {Cut}_{{union}}$$\end{document}Cutunion, respectively.</p><p>The number of IBP GO terms overlapped with these subsets collected in the second row. The number of drug targets in each drug group that are associated with these subsets are reported in the third, fourth and fifth rows, respectively. The number of drugs in each drug group that are associated with these subsets are reported in the sixth, seventh and eighth rows, respectively</p><p>Essential protein related to COVID-19 pathology</p><p>Some of the significantly enriched pathways that are related to COVID-19 essential proteins (E)</p><p>The exceeding values (EV) for \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1 ,\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3 ,\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5</p><p>The number of All-Drugs, Covid-Drug and Clinical-Drug for \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5</p><p>The first row indicates the number of proteins as drug targets in our PPI network</p><p>From these proteins, the number of important ones in each cluster is reported in the second row. The number of human proteins that are targeted with the virus is reported in the third row. The fourth and fifth rows show the number of these proteins that are targeted through at least one drug in Covid-Drug and Clinical-Drug, respectively</p><p>The blue columns show the common drug targets for each cluster. The orange columns show the number of main targets that are common between drugs in each cluster. The green columns show all of the targets for drugs in each cluster</p><!><p>Figure  2 also shows the number of main targets in each cluster. Each drug in these five clusters has one or multiple main targets. From these main targets three of them are common among all drugs of each clusters. These three main targets are Vascular Endothelial Growth Factor (VEGF)-A, Cytochrome P450 3A4 (CYP3A4), and Prostaglandin-endoperoxide synthase 2 (PTGS2) or Cyclo-oxygenase2 (COX-2), respectively. Despite the lack of evidence for COVID-19, previous research shows that the VEGF family (VEGFs) has a connection with COVID-19. A recent study shows that VEGFs are involved in "cytokine storm" inflammatory response. They claim that these genes may be used as prospective biomarkers for early diagnosis in COVID-19 patients [32]. The VEGFs can also be used for targeted drug delivery in COVID-19 treatment.</p><p>The second main target is PTGS2 or COX-2, which has been the subject of many studies on its association with COVID-19 and is a pro-inflammatory enzyme. Some studies showed that the structural proteins of the SARS-CoV family are reported to influence the expression of COX-2 and the increased expression of plasma PGE2 in the blood of SARS-CoV-infected patients. It is also reported that COX-2 plays a crucial role in limiting the anti-viral cytokine response to viral infection. Therefore, the use of an effective COX-2 inhibitor during early viral infection could enhance interferon responses. It might also increase anti-viral immunity [33]. The result of [34] study shows the importance of VEGF-A and COX-2 in relation to COVID-19. In this study, PPI analysis was used to find the hub genes linked to COVID-19 and lung cancer. Among the suggested hub genes, VEGF-A and COX-2 have been confirmed and could be used as biomarkers for COVID-19.</p><!><p>The Venn diagram shows the relation of targets for \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5</p><p>The example of common targets and total number of targets in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1</p><p>The relationship between diseases that are associated with drug targets in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5</p><!><p>We have studied the diseases associated with each of the drugs in each cluster based on the information on the Drugbank website. The Venn diagram in Fig. 5 shows the relationship between diseases that are associated with drug targets in each cluster. Figure 5 shows that there is no specific disease that is associated with all clusters. Respiratory Tract Infections and Type 2 Diabetes are two of six diseases that have common targets in\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3. Diabetic Macular Edema (DME) is one of two diseases that have common targets in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5. Rheumatoid Arthritis and Ankylosing Spondylitis (AS) are two of twelve diseases that have common targets in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4 and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5.</p><!><p>List of the repositioning candidates, therapeutic category and the supporting published evidence in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1</p><p>The drug in Clinical-Drug group is highlighted in italic</p><p>List of the repositioning candidates, therapeutic category and the supporting published evidence in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2</p><p>Drugs in Clinical-Drug group are highlighted in italic</p><p>List of the repositioning candidates, therapeutic category and the supporting published evidence in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3</p><p>Drugs in Clinical-Drug group are highlighted in italic</p><p>List of the repositioning candidates, therapeutic category and the supporting published evidence in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4</p><p>Drugs in Clinical-Drug group are highlighted in italic</p><p>List of the repositioning candidates, therapeutic category and the supporting published evidence in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5</p><p>Drugs in Clinical-Drug group are highlighted in italic</p><!><p>Researchers have been searching for efficient medications to prevent or cure COVID-19 since the first case was discovered in 2019. To advance this goal, we introduced the four steps method. In the first step, the COVID-19 related biological network was constructed and the essential proteins that have a wide range of important functions in the biological network were detected. In the second step, we focused on finding the most effective essential proteins related to COVID-19. To do this, we used two different algorithms to identify the minimum number of proteins that participate in a large number of IBP GO terms and placed them in two distinct sets. Then, we evaluated proteins of these two sets with respect to the number of approved Covid-Drug and Clinical-Drug by them (Table 2). We placed the union of these two sets in the set \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{union}$$\end{document}Cutunion and studied set \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{union}$$\end{document}Cutunion with respect to the number of IBP GO terms that are disrupted. As a result, the selected proteins can be identified as a suitable candidate set for the COVID-19. It is noticeable that not every essential protein is an appropriate candidate as an essential protein for COVID-19 pathology. Some of these essential proteins are related to the cellular function of the cell and selecting them as drug targets may lead to disruption of cellular function. Considering that, in the third step, we picked candidate proteins directly related to COVID-19 pathology. For the final essential protein selection process in this step, we identified proteins that were associated with underlying diseases such as cardiovascular disease, diabetes, hepatitis, lung, kidney diseases, and various types of cancer. Among 3,002 essential proteins related to COVID-19 in \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$Cut_{union}$$\end{document}Cutunion, we detected 93 proteins associated with at least four of five underlying mentioned diseases as essential proteins related to COVID-19 pathology (Table 3). We evaluated these proteins with respect to the related pathways with DAVID tools (Table 4). As a result, these selected proteins could be suitable candidates as drug targets for COVID-19 treatment. In the fourth step, multiple informative topological features for drug–target and a PPI network were proposed. Our methods tried to find significant clusters containing appropriate candidate drugs through these features. These features cluster the available experimental unapproved drugs for COVID-19 into five groups (\documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_1$$\end{document}#Cluster1, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_2$$\end{document}#Cluster2, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_3$$\end{document}#Cluster3, \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_4$$\end{document}#Cluster4, and \documentclass[12pt]{minimal} sepackage{amsmath} sepackage{wasysym} sepackage{amsfonts} sepackage{amssymb} sepackage{amsbsy} sepackage{mathrsfs} sepackage{upgreek} \setlength{\oddsidemargin}{-69pt} egin{document}$$\#Cluster_5$$\end{document}#Cluster5). These clusters have a significant difference from random clusters (Table 5) and contain a significant number of Covid-Drug and Clinical-Drug (Table 6). We also used three different measures for validating the obtained clusters. The first measure was based on the proteins as drug targets in these clusters, we showed that the proposed clusters have meaningful targets that were known in recent studies as COVID-19 targets (Table 6 and Figs. 2, 3, and 4). The second measure was based on the related diseases that have drugs in our clusters. We found some related diseases like DME and Rheumatoid Arthritis that have drugs in two of our clusters (Fig. 5). The third measure was related to drugs as good candidates for drug repurposing in COVID-19 treatment.</p><p>In summary, the main advantage of our method in comparison to other studies was clustering FDA-approved drugs that are related to COVID-19 according to the biological and topological properties of their targets. It can be concluded that partitioning the drug-related network into smaller networks (clusters) can improve drug repurposing results for clinical trials. In this work, we proposed some good drug candidates as repurposing candidates for COVID-19 treatment. Our results showed that most of our drug candidates were used in clinical trials or suggested in at least one study as suitable drug repurposing candidates (Tables 7-11). Our results also revealed that the proposed informative features recommended some suitable candidate drugs like [37] and Rifampicin [38]. Finally, this study offered powerful network-based informative features for the fast identification of repurposable drugs as a potential treatment for COVID-19. The proposed method can effectively minimize the timing gap between preclinical testing conclusions and clinical results, which is a considerable problem in the fast development of efficient treatment strategies for the emerging COVID-19 outbreak.</p><!><p>The coronavirus disease 2019</p><p>Protein−protein interaction</p><p>Informative biological processes</p><p>Database for annotation, visualization, and integrated discovery</p><p>Biological general repository for interaction datasets</p><p>Human integrated protein−protein inter-action reference</p><p>Agile protein interactomes dataanalyzer</p><p>Homologous interactions</p><p>yeast-two hybrid</p><p>Universal protein resource</p><p>Gene ontology</p><p>Exceeding value</p><p>Cytochrome P450 3A4</p><p>Vascular endothelial growth factor</p><p>P450 3A4</p><p>Prostaglandin-endoperoxide synthase 2</p><p>Cyclo-oxygenase2</p><p>Cytochromes P450</p><p>Rosa Aghdam, Mahnaz Habibi and Golnaz Taheri have contributed equally to this work</p>

PubMed Open Access

A Crowding Barrier to Protein Inhibition in Colloidal Aggregates

Small molecule colloidal aggregates adsorb and partially denature proteins, inhibiting them artifactually. Oddly, this inhibition is typically time-dependent. Two mechanisms might explain this: low concentrations of the colloid and enzyme might mean low encounter rates, or colloid-based protein denaturation might impose a kinetic barrier. These two mechanisms should have different concentration dependencies. Perplexingly, when enzyme concentration was increased, incubation times actually lengthened, inconsistent with both models and with classical chemical kinetics of solution species. We therefore considered molecular crowding, where colloids with lower protein surface density demand a shorter incubation time than more crowded colloids. To test this, we grew and shrank colloid surface area. As the surface area shrank, the incubation time lengthened, while as it increased, the converse was true. These observations support a crowding effect on protein binding to colloidal aggregates. Implications for drug delivery and for detecting aggregation-based inhibition will be discussed.

a_crowding_barrier_to_protein_inhibition_in_colloidal_aggregates

INTRODUCTION<!>RESULTS<!>DISCUSSION AND CONCLUSIONS<!>Dynamic Light Scattering.<!>Enzyme Inhibition.

<p>Many organic molecules, including drugs, investigational new drugs, clinical candidates,1–4 and especially early leads in drug discovery,5–8 aggregate into densely packed colloids at micromolar or even submicromolar concentrations in bio-chemical buffers.9 These aggregates sequester 105 to 106 protein molecules,10,11 leading to their partial denaturation12,13 and typically their inhibition. Such inhibition is among the dominant mechanisms for false-positive results in early drug discovery.14–17 Understanding its mechanism has been key for avoiding this phenomenon and, increasingly, for exploiting the unusual properties of the colloidal particles for useful applications, such as drug delivery.18–22</p><p>A curious feature of colloidal inhibition is that it typically increases on pre-incubation of the protein with the particle, up to some saturating point.12 Why this should happen has remained unclear. Slow onset inhibition is well known in ligand binding and classically may be attributed to two mechanisms: very low concentrations, which slow the formation of encounter complexes via diffusional barriers (unusual for most ligand-protein systems), or slow off-rates, reflecting either kinetic barriers or simply very tight binding.23,24 Both mechanisms are plausible for colloidal-based inhibition. While the concentration of the aggregating monomer may be in the μM to the high-nM range, the concentration of the colloidal particles themselves is mid-fM to low-pM.10 Mean-while, the proteins being inhibited can easily be in the low-nM range; these concentrations plausibly are low enough to constitute kinetic barriers to associations (Derivation S1). Conversely, proteins bind tightly to colloidal aggregates, with KD values in the pM range or better,10,11 and protein partial unfolding on colloidal surfaces could be a kinetic barrier to association and disassociation.</p><p>These two mechanisms imply different concentration dependencies. Low concentration, kinetic barriers to association should be sensitive to concentration changes in either the colloid or the protein. Off-rate barriers to disassociation, either because of high affinity, or because of kinetic barriers to protein folding, should be pseudo-zero order in enzyme concentration. Said another way, increasing the concentration of either the colloid or protein should reduce the incubation effect if this effect reflects association barriers, while for the mechanism reflecting kinetic off-rates, the incubation effect should be insensitive to enzyme concentration.</p><p>To distinguish between the two mechanisms, we investigated concentration effects on the kinetics of the inhibition buildup between model enzymes and colloidal aggregators. Unexpectedly, our results were inconsistent with both mechanisms. Instead of classical concentration-rate effects, we observed that increasing enzyme concentration slowed inhibition buildup, increasing the incubation time necessary to achieve a certain inhibition level. This seemed most consistent with a third, non-classical mechanism, molecular crowding on the colloidal surface, something we explored in depth in subsequent experiments. Since an incubation effect has been a harbinger of colloidal aggregation since it was first described,9 this mechanism has implications for the rapid detection of aggregation in early discovery and may influence how we exploit drug colloid formation in formulation and delivery.</p><!><p>To distinguish between the two initial mechanisms—low concentration encounter barriers or off-rate effects—we first investigated increasing the concentration of the colloids. The effect of incubation was measured at increasing concentrations of aggregating small molecules, each above their critical aggregation concentration (CAC). Within a certain range, the concentration of colloidal particles depends linearly on the amount of the monomer added over the CAC;25 as more monomers are added over the CAC, more colloidal particles are formed. For both the model enzymes AmpC β-lactamase and malate dehydrogenase (MDH),26 tested against the well-studied colloidal aggregators Sorafenib and fulvestrant, the incubation time necessary to reach a certain amount of inhibition fell monotonically as the concentration of the colloidal particles increased (Figure 1A–D). For instance, we incubated the colloidal aggregator Sorafenib for varying times with AmpC and then measured the rate of hydrolysis by initiating the reaction with the substrate (Figure 1A). Especially at lower concentrations of aggregating Sorafenib, as the time of incubation increases (x axis), so does inhibition. At a 5 μM Sorafenib monomer (perhaps mid-fM colloid), the reaction is 40% inhibited after a minute of pre-incubation, 80% inhibited after 2 min of pre-incubation, and is nearly fully inhibited after 5 min. As one increases the concentration of Sorafenib, the inhibition at every incubation time point increases. Thus, as one increases the concentration of the aggregating molecule, the incubation period decreases (the onset of inhibition gets faster). This may be also seen as plots of the time of incubation necessary to achieve 90% inhibition (T90, Figure 1E,F; we note the effect plateaus, reflecting limits to our ability to distinguish among the very fast T90s at high colloidal concentrations). This supports an encounter reaction that is first order in the concentration of the colloidal particles and is at least consistent with a low concentration encounter barrier model for the incubation effect.</p><p>If the effect of increasing colloidal concentration readily fits at least one of our hypotheses, the results were unexpected when we turned to increasing enzyme concentration. In contrast to what classic rate kinetics would predict, the onset of inhibition—the length of incubation time necessary to reach a certain level of inhibition—increased with enzyme concentration, for both AmpC and MDH, in the presence of constant Sorafenib or constant fulvestrant colloidal aggregates (Figure 2). For instance, a 30 s pre-incubation of 2 nM AmpC with a 10 μM Sorafenib monomer (likely a mid-fM Sorafenib colloid) resulted in 67% inhibition, and a 5 min pre-incubation sufficed to essentially fully inhibit the enzyme. Doing the same at the 10 nM enzyme, however, led to only 40% inhibition after 30 s of pre-incubation, and even after 5 min, at least 20% of enzyme activity remained (Figure 2A). Quantitatively, T90 values monotonically increased with enzyme concentrations for both AmpC and MDH and for both colloidal aggregators (Figure 2D and Figure 2E, respectively). In short, as enzyme concentration increased, the onset of inhibition took longer. This is inconsistent with both classical models for the time dependence of colloidal inhibition.</p><p>This observation led us to investigate a protein crowding mechanism on the colloidal surface, where inhibition appears to occur.12,26 In this non-classical model, as protein binds to the particle surface, the rate at which the next protein molecule can bind is reduced by crowding. We therefore investigated how varying the colloidal surface area changed the incubation time—the onset of inhibition—using four different strategies. First, we changed the buffer ionic strength, with lower ionic strengths leading to smaller colloids with less available surface areas per particle (more crowding) and higher ionic strengths leading to larger colloids with more surface areas per particle9 (less crowding). Second, we pre-incubated the colloid with another, functionally inert protein to see how it would affect the inhibition onset of the monitored enzyme; this increases protein crowding on the colloidal surface. Third, we co-formulated the colloids with Congo Red, which substantially decreases colloid size, again increasing crowding. Fourth, we investigated the rates of the inhibition onset on an enzyme much larger than AmpC and MDH, β-galactosidase—the larger size of this enzyme should itself increase crowding leading to a slower inhibition onset (Figure 3).</p><p>In the first experiment, we measured inhibition at 5 mM KPi versus 50 mM KPi. At the lower ionic strength, Sorafenib colloids shrank to 48 from 121 nm radii at 50 mM KPi (Figure 3A and Figure S1 and Table S1), as expected.9 At this reduced size, inhibition increased more slowly, demanding longer incubation times (Figure 3B), and T90 values went from 5 min at the larger radii to >15 min at the smaller radii. Because ionic strength can affect other aspects of the kinetics of the inhibition onset, we also investigated the effects of reducing colloid size by co-formulating the Sorafenib colloids with the dye Congo Red.21 At a ratio of 500:1 Sorafenib to dye, the particle size shrank from a radius of 110 to 41 nm, and at a ratio of 25:1, the particles further shrank to a radius of 23 nm (Figure 3C and Figure S1 and Table S1). As particles shrunk, the onset of inhibition lengthened, and the time necessary to incubate to reach a certain level of inhibition increased, also consistent with the crowding hypothesis. This observation is striking because the concentration of these smaller co-formulated colloids scales as the cube of the ratio of the radii such that going from 110 nM to 23 will increase colloidal concentration by over 100-fold. All things being equal, the pseudo-first order reaction rate should thus increase by over 100-fold (Derivation S1), and the t1/2 should decrease by the same factor. Instead, the time over which the reaction occurred was substantially longer (the kinetics slowed). To quantify how the particle size affected the incubation time necessary to inhibit, we plotted the T50 of the reaction (the lengthening of the incubation time) against the particle size, where the latter was varied by changing the ratio of Sorafenib to co-formulated Congo Red. The T50 values scaled monotonically with the inverse of particle surface area (Figure 3J). The apparent exponential shape of the curve may reflect the severity of crowding as the particles shrink, and potentially saturation effects.</p><p>In a third set of experiments, we investigated the effect on the inhibition onset of pre-loading colloidal particles with an effectively inert protein before exposing them to the enzyme being monitored. If crowding affects the rate of the inhibition onset, then we would expect pre-loading the inert protein to reduce the onset of inhibition of the monitored enzyme without affecting the total level of inhibition ultimately achieved. We pre-loaded Sorafenib colloids with 2 nM MDH for 5 min and investigated how that affected the rate of the inhibition onset of AmpC by those colloids versus how they inhibited AmpC in the absence of MDH pre-loading. When pre-loaded with MDH, AmpC inhibition grew substantially slower than when the colloids had not been pre-loaded with MDH (Figure 3E). For instance, a 30 s pre-incubation of AmpC with Sorafenib colloids without MDH pre-loading led to 80% inhibition, and by a 5 min pre-incubation, enzyme activity was barely measurable. Conversely, the same 30 s pre-incubation after pre-loading the colloids with MDH led to only 45% inhibition, and even after a 5 min incubation with AmpC, the enzyme retained a still measurable activity. Correspondingly, T90 values lengthened from 1 min in the absence of MDH pre-loading to 5 min with MDH pre-loading. The same effect on MDH activity, when AmpC was used as the pre-loaded enzyme, was also observed (Figure 3F,G). These results, too, support the surface crowding hypothesis.</p><p>Turning to the enzyme size as a variable, the 0.5 megadalton (520 kDa) ß-galactosidase was used as an unusually large enzyme, compared to 35 kD MDH and the 40 kD AmpC, to induce more crowding on the colloidal surface per mol of the enzyme absorbed. At every concentration of β-galactosidase, the onset of inhibition was slower than MDH or AmpC with Sorafenib colloids (Figure 3I vs Figure 2A and Figure 2B), also consistent with the crowding hypothesis.</p><p>If decreasing colloid size, increasing protein crowding, slows the inhibition onset and increases incubation times, then we might expect that increasing colloid size and decreasing protein crowding should speed the inhibition onset, decreasing the incubation time necessary to reach a certain level of inhibition. Accordingly, we investigated two small molecules that naturally form larger colloids than Sorafenib (100 nm average radius) and fulvestrant (82 nm average radius): nicardipine (300 nm average radius) and clofazimine (570 nm average radius). In studies with MDH, inhibition kinetics by both of the larger colloids was bell-shaped, speeding up as enzyme concentration increased until reaching a minimum at around the 4 nM enzyme, after which the inhibition onset began to slow (Figure 4A,B). Unlike with the smaller colloidal particles, here in the first part of the curve, inhibition kinetics actually do increase with enzyme concentration, consistent with simple diffusion-governed inhibition in this domain. As higher concentrations of the enzyme are reached, for these larger particles, crowding-governed behavior seems again to take hold. Intriguingly, the larger β-galactosidase, even on the larger nicardipine colloids, retained the non-classical crowding mechanism throughout as the inhibition onset grew longer as the enzyme concentration increased (Figure 4C).</p><!><p>The slow onset of colloid-based inhibition—the incubation effect that has long been considered a characteristic of the phenomenon—reflects protein crowding on the colloidal surface. To our surprise, our results invalidated the two other hypotheses that we had favored to explain this effect: simple kinetic barriers deriving from femtomolar concentrations of the colloidal particles, or the kinetic barrier of enzyme unfolding. Although increasing colloidal concentration sped the enzyme inhibition onset (Figure 1), consistent with the kinetics of association hypothesis (Derivation S1), neither model explains the slowing of the inhibition onset, the lengthening of incubation necessary to reach a given level of inhibition, as enzyme concentration is increased (Figure 2). This observation led us to investigate a model of surface crowding, where as the colloidal surface becomes increasingly occupied with protein; the rate of new protein binding to that surface slows.</p><p>The crowding model made testable predictions: shrinking a colloid should increase crowding, slowing the inhibition onset, as should pre-loading the colloid with a second inert protein. Similarly, increasing the size of the enzyme, without changing the colloid size, should slow the inhibition onset, while larger colloidal particles should speed the inhibition onset, decreasing incubation times. Each of these was supported by the experiment. When colloids were shrunk by either decreasing ionic strength (Figure 3A,B) or by co-formulating the colloids with Congo Red (Figure 3C,D), the inhibition onset slowed dramatically. Similarly, pre-loading the colloids with a second inert protein had the same effect, lengthening incubation times necessary to reach a given level of inhibition (Figure 3E,F). Moving to the much larger β-galactosidase slowed the inhibition buildup compared to smaller AmpC and MDH, with the same colloidal particles (Figure 3I). Finally, relieving crowding with larger colloidal particles, as formed by nicardipine and clofazimine, led to faster inhibition onsets and, more compelling still, a return to a domain where increasing enzyme concentration increased the rate of the inhibition onset, leading to greater levels of inhibition in faster times, as would be classically expected. This held over a certain concentration domain, after which, presumably as crowding increased too far on the colloidal surfaces, the rate of the inhibition onset began again to slow, leading to bell-shaped curves with enzyme concentration (Figure 4). Integrating previous studies that investigated the stoichiometry and concentration of colloidal particles,10,27 the partial denaturation of proteins on colloidal surfaces12,13 with the current study, the model that emerges is one where the kinetics of protein binding to colloidal aggregates is at least influenced by, and in many domains dominated by, crowding on the surface of the particle (Figure 5).</p><p>It is interesting to model at what point protein saturation of the colloidal surface begins to slow the inhibition onset, lengthening the incubation time necessary to see a given level of inhibition. To do so, we must know not only the concentration of the enzyme and the surface area of the particles, which are readily known, but also the concentration of the colloidal particles themselves, which are difficult to measure. Fortunately, such measurements have been made for nicardipine colloids,10 which we also study here. It was found that, for every 1 μM nicardipine added over a critical aggregation concentration of 32 μM, 2000 colloidal particles were formed.10 From this, it could be calculated that each nicardipine colloidal particle adsorbed about 1.3 × 104 molecules of AmpC after a 5 min incubation. If each AmpC molecule was adsorbed along its longest axis (leading to the greatest coverage), then about 16% of the colloidal surface would be consumed. The MDH enzyme studied here with nicardipine is a dimer of monomers, each of which is only slightly smaller than AmpC; with the same assumptions, one nicardipine colloid should absorb about 0.6 × 104 MDH dimers. Thus, 100 μM nicardipine should lead to 8.9 × 107 colloidal particles in 1 mL, adsorbing 1 nM MDH, consuming between 6 and 15% surface area, depending on how the enzyme is oriented on the particle surface. Intriguingly, from 0.5 to 4 nM MDH, there is no evidence of crowding (Figure 4A). As MDH concentration increases further, however, we re-enter the crowding domain, with the rate of the inhibition onset slowing as the enzyme concentration increases (Figure 4A). By 10 nM MDH, the enzyme concentration might be within 50% of the total loading capacity of the particle after a 5 min incubation (50% surface area coverage), and by 20–50 nM enzyme concentration, the particles might be fully saturated. This is borne out by the course of the inhibition buildup, which by 50 nM enzyme is barely observed, presumably because the capacity to adsorb more enzymes, even for long incubations, has been exceeded. Obviously, these are rough calculations as the amount of space on the colloid consumed by each MDH molecule is uncertain. Taken at face value, they suggest that the time dependence of the inhibition onset may occur as the amount of the enzyme to be adsorbed begins to approach about 50% of the physical limits of the colloidal particle.</p><p>Other caveats also bear airing. Most importantly, none of the perturbations we make to the colloid size are perfect experiments—they all perturb more than one aspect of the system. For instance, changing the ionic strength changes gross aspects of the buffer, in addition to colloid size, while co-formulating Sorafenib with Congo Red likely changes the surface properties of the colloids (though the size change should dominate). Also, there are differences in behavior from protein to protein, something likely driven by the different properties of the proteins themselves,28 including their stability toward denaturation,13 and we do not pretend that crowding explains every aspect of protein-colloid association.</p><p>Notwithstanding these provisos, the main conclusion of this study should be clear: the onset of protein inhibition by colloidal aggregates typically does not follow classical kinetics of association but is instead usually dominated by surface crowding. This has several pragmatic implications. An incubation effect has long been considered a hallmark of colloidal aggregation and is used to recognize it in early discovery.11 What this study teaches is that this incubation effect is itself sensitive to enzyme concentrations. At higher enzyme concentrations, the typical 5 min incubation times advocated in the past may be too short; substantial inhibition may only build up over longer times. A better criterion might be observing the impact of enzyme concentrations on incubation times; only for a colloidal mechanism would one expect incubation times to increase with enzyme concentration. Correspondingly, simply incubating proteins with the colloids longer should increase the protein load harbored by the colloids, something useful for vehicles designed to deliver drugs and their targeting proteins, for instance, as colloid-antibody or colloid-transferin conjugates.29,20 Thus, we expect that this effort to understand the fundamental kinetic bases for colloid-protein association will have pragmatic implications, as has been true of previous mechanistic studies of colloidal aggregation12,13,30–32</p><!><p>Colloid radii were measured by dynamic light scattering (DLS) using a DynaPro Plate Reader II (Wyatt Technologies), with a 60 mW laser at a 830 nm wavelength and a detector angle of 158°; the beam size of the instrument was increased by the manufacturer to better enable detection of the larger colloidal species. Samples were measured in 384 well plates with 30 μL of loading and 10 acquisitions per sample. Compounds were dissolved in DMSO in 100× concentration and were further diluted by adding filtered 50 mM KPi (pH 7.0) to obtain a final 1% DMSO concentration. For the co-formulations, a 25:1 and 500:1 ratio of DMSO-dissolved Sorafenib and Congo Red were first mixed, and KPi was then added to this mixture to obtain a final volume of 1 mL, a final Sorafenib concentration at 10 μM, CR at 400 and 20 nM, and final 1.5% (v/v) DMSO.</p><!><p>Enzyme inhibition assays were performed at room temperature on an HP8453a spectrophotometer in kinetic mode using UV–vis Chemstation software (Agilent Technologies) in methacrylate cuvettes (Fisher Scientific, 14955128) with a final volume of 1 mL for both control and test reactions. Varying concentrations of the enzyme were mixed with varying concentrations of the small molecule in 50 mM KPi pH 7 buffer and were incubated at intervals between 30 s and 15 min. The enzyme-colloid aqueous solution was mixed by repeated pipetting of 150 μL before incubation. The substrate was added at the end of the incubation followed by mixing. The reactions were monitored for 150 s alongside a rate control reaction that lacked the colloidal aggregator, and initial rates were divided by the initial rate of the negative control to obtain % activity of the enzyme. The activity versus time plots were generated using GraphPad Prism.</p><p>For the AmpC ß-lactamase assay, CENTA (Millipore Sigma, 219475) at 70 μM was used as the chromogenic substrate and the change in absorbance was monitored at 405 nm. For malate dehydrogenase (MDH) (from Porcine Heart, 901643, Sigma-Millipore), the reaction was initiated by 200 μM nicotinamide adenine dinucleotide (54839, Sigma Aldrich) and 200 μM oxaloacetic acid (324427, Sigma Aldrich) and the rate was monitored at 340 nm. For ß-galactosidase (from Escherichia coli overproducer, 10105031001, Sigma Aldrich), the reaction was initiated by 300 μM ortho-nitrophenyl-β-galactoside and reaction was monitored at 320 nm. For assays where an inert enzyme was used, Sorafenib was first incubated with the inert enzyme for 5 min at room temperature, the second enzyme was then added, and the mixture was further incubated at room temperature for varying times.</p><p>For the 25:1 Sorafenib:Congo Red co-formulation, a DMSO stock was prepared with concentrations of 1 mM Sorafenib and 40 μM CR (Sigma C6277-25G). For the 500:1 formulation, a DMSO stock was prepared with concentrations of 1 mM Sorafenib and 2 μM CR. Sorafenib was added first followed by Congo Red and buffer. The solution was mixed well, and the enzyme was mixed with Sorafenib for various incubation times.</p>

PubMed Author Manuscript

Single-molecule photoredox catalysis

The chemistry of life is founded on light, so is it appropriate to think of light as a chemical substance? Planck's quantization offers a metric analogous to Avogadro's number to relate the number of particles to an effective reaction of single molecules and photons to form a new compound. A rhodamine dye molecule serves as a dehalogenating photocatalyst in a consecutive photoelectron transfer (conPET) process which adds the energy of two photons, with the first photon inducing radical formation and the second photon triggering PET to the substrate molecule. Rather than probing catalytic heterogeneity and dynamics on the single-molecule level, single-photon synthesis is demonstrated: the light quantum constitutes a reactant for the single substrate molecule in a dye-driven reaction. The approach illustrates that molecular diffusion and excited-state internal conversion are not limiting factors in conPET reaction kinetics because of catalyst-substrate preassociation. The effect could be common to photoredox catalysis, removing the conventional requirement of long excited-state lifetimes.

single-molecule_photoredox_catalysis

Introduction<!>Single-molecule imaging<!>(a)<!>Single-molecule photon-correlation spectroscopy<!>Discussion<!>Conflicts of interest

<p>Photosynthesis is the archetypal photocatalytic process. Having evolved from primordial life over billions of years, the conversion of sunlight into chemical energy remains enigmatic at once in its elegance and complexity. Whereas nature combines the energy of multiple photons to drive the conversion of carbon dioxide and water into carbohydrates, even the simplest articial models of consecutive photoelectron transfer (conPET) synthesis have proven challenging to realize in the laboratory. [1][2][3][4][5][6][7] Most photocatalysts involve expensive heavy-metal elements, but recently, the potential of hydrocarbon dyes in organic photocatalysis has emerged. [8][9][10][11] First reports have shown that even common organic dyestuffs such as perylene 12 or rhodamine [13][14][15] function as effective organic photocatalysts. Since one of the goals of photocatalysis is to achieve cheap large-scale conversion of materials, single-molecule techniques have received only limited attention as an avenue to exploring and optimizing catalytic efficiency. 16 But since, ultimately, photocatalysis is a molecular process, only microscopic spectroscopic techniques can provide truly mechanistic insights for quantumchemical models. [17][18][19] The main focus to date of the technique in the context of photocatalysis has been on exploring the spatial and temporal heterogeneity of reactions [20][21][22][23][24][25] involving either single-photon mediated processes, 26 or using chemical conversion of a dye molecule to track catalytic activity. [27][28][29][30] In addition, single-molecule techniques have proven versatile in imaging protein-based reactions, [31][32][33][34][35] and single-electron transfer events in general. 36,52 Little attention has been paid to actually driving chemical reactions on the single-molecule level, with most prior interest directed at the potential of scanning-probe techniques in electrically catalysed reactions for lithographic applications. [37][38][39][40][41] Few experiments illustrate the particle nature of light more directly than single-photon counting. Passing the uorescence of a single molecule through a semi-transparent mirror, a beam splitter, with single-photon detectors on either side will give rise to a pronounced anticorrelation in time between the two detectors: photon antibunching occurs, since the same photon cannot be picked up by both detectors. 42 This antibunching arises on timescales of the excited-state lifetime of the molecule, i.e. typically several nanoseconds. On longer timescales, the opposite effect occurs: the uorescent molecule undergoes quantum jumps between bright and dark states, for example between the singlet and the triplet manifolds of the excited state, leading to bunching of photons in time. 43 This cycling between emissive and non-emissive states of the uorophore provides crucial insight into the molecular quantum jumps responsible for the photosynthetic reaction. 44 Here, we exploit the versatile method of single-molecule spectroscopy to probe the conPET process, one photon at a time. Fig. 1a illustrates a prototypical model process of aqueous organic photocatalysis exploiting consecutive photoelectron transfer (conPET). 13 Absorption of a photon of energy hn 1 by a rhodamine-6G (Rh6G) dye molecule leads to the formation of an excited singlet state. This singlet can undergo either radiative relaxation to the ground state by uorescing, convert into a triplet by intersystem crossing, or interchange charge with reductants to form a radical. If the latter two processes occur, the dye molecule will cease to uoresce for a short period of time, on the order of a few microseconds up to milliseconds. 52 Addition of a reducing agent, ascorbic acid, promotes formation of the rhodamine radical from either the singlet or the triplet state. Since Rh6G in water is cationic, 45 electron transfer from the reducing agent will form the neutral Rh6G radical Rc. This radical is characterised by a certain lifetime, and will ultimately relax to the cationic ground state by shedding the additional electron to the environment. The reduction potential of the Rc ground state of À1 V vs. SCE 13 is too low for electron transfer to occur to a substrate molecule to cleave stable bonds in aryl halides, such as in the dehalogenation of 2-bromobenzonitrile. Such a reaction requires a reduction potential of À1.9 V vs. SCE. 13,46,47 The additional energy necessary to achieve this is made available by re-exciting the radical with a second photon of energy hn 2 . The reduction potential of the excited radical state of Rh6G, Rc*, is À2.4 V vs. SCE, 13 which is sufficient for dehalogenation of the substrate. The second photon, in combination with the electron transfer to the substrate, therefore removes the additional electron from the dye radical, returning the dye to the ground state and thereby reactivating the S 1 / S 0 uorescence cycle. The waterbased mechanism proposed here is, in principle, analogous to reaction cycles recently described in organic solvents. 13 Fig. 1b states the synthetic-scale C-H aromatic substitution reaction of 2-bromobenzonitrile in water, using a reaction mixture containing the dye, substrate, and reducing agent, along with an additional trapping agent, N-methylpyrrole. The reaction occurs under continuous illumination with two light-emitting diodes (LEDs). The conversion yield aer 24 hours determined by gas chromatography (GC) is 94%. Chromatograms of the product of this reaction and several control reactions are shown in Fig. S1 of the ESI. † This simple cycle constitutes one of the rst reports of a C-H arylation by an organic dye in water and is therefore likely to be of interest in a range of aqueous biochemical reactions. 13 Note that the additional trapping agent is only required in the ensemble reaction, where the product yield is monitored, and not in the single-molecule experiments, where the dye acts as the reporter on the reaction. Since the absorption spectrum of the radical is broad, the conPET cycle appears to work with a range of different photon energies. For experimental reasons, different light sources and wavelengths are used for the singlemolecule and synthetic-scale reactions.</p><p>Even though this conPET cycle apparently works, it is not at all clear how a conventional dye molecule actually enables consecutive photoredox catalysis. Internal conversion is the most efficient process of energy dissipation from higher-lying states in molecules, and a photoexcited radical is expected to shed excess energy to the environment within a few hundred femtoseconds, as documented by transient absorption spectroscopy. 48 Such ultrafast energy dissipation inhibits intermolecular photoreactions and would certainly prevent any diffusion-driven process from occurring in solution.</p><!><p>In order to study the conPET mechanism on the single-molecule single-photon level, the photocatalytically active dye molecules have to be immobilized on a surface to prevent diffusion in the solvent. 49 We therefore tether the dyes to DNA oligomers, functionalised with biotin-streptavidin linkers, as sketched in Fig. 2a. These linkers bind to biotinylated bovine serum albumin (BSA) covered glass substrates at sufficiently low concentration so that they can be resolved individually in</p><!><p>A cationic rhodamine 6G (Rh6G) dye molecule in phosphate-buffered saline (PBS) is excited by a photon of energy hn 1 and is subsequently reduced by ascorbic acid (AscA) to form a radical. A second photon hn 2 excites the radical, leading to PET to the halogenated substrate 2bromobenzonitrile (BrBN). Note that since in the single-molecule experiments it is the dye and not the product yield which is monitored, a trapping agent is not needed for this reaction. (b) Synthetic-scale C-H aromatic substitution of 2-bromobenzonitrile with an N-methylpyrrole trapping agent in an aqueous mixture of dye, substrate, reducing and trapping agent under two-colour LED illumination in the green (hn 1 ) and blue (hn 2 ). The conversion yield after 24 hours as determined by gas chromatography is 94%. Note that synthetic-scale reactions are usually carried out with LEDs rather than lasers. Lasers are necessary to focus light tightly in single-molecule experiments. Since the absorption spectrum of the radical state is broad, the reaction works for both blue wavelengths (hn 2 ) of 405 nm (laser) and 455 nm (LED).</p><p>a confocal uorescence microscope. Fig. 2b indicates the anticipated level scheme of the Rh6G dye molecules. Fluorescence is observed from the single molecules as long as they cycle between S 0 and S 1 states. Excursions to the triplet or the radical state lead to a disruption of this cycle and inhibit uorescence. The triplet can relax back to the ground state by reverse intersystem crossing with a rate of k T1 ISC ; or else be reduced to form the radical of the dye molecule. In the presence of a reducing agent, the singlet can also be reduced to form the radical, which can re-oxidise at an intrinsic rate, returning the dye molecule to its ground state; or else the radical can be photoexcited again to form Rc*, which can transfer its electron to the substrate molecule 2-bromobenzonitrile.</p><p>To test the feasibility of tracking the conPET cycle on the single-molecule level, we plot the uorescence of a single tethered Rh6G molecule in Fig. 2c as a function of time, binned in intervals of 5 ms, with alternating application of hn 2 . The uorescence intensity, stated in terms of the photon count rate, appears as bursts of approximately equal strength, separated by prolonged intervals of darkness. The average photon count rate, binned over intervals of 0.5 s, is superimposed in the plot as a red line. As the dye radical is re-excited by hn 2 , the number of uorescence spikes increases and the average brightness of the single molecule (red line) doubles. The height of the individual spikes remains almost constant, implying that it is not the number of photons absorbed by the dye which increases upon simultaneous excitation at two wavelengths. Rather, the intermittency between bursts is shortened. Panel d plots a twosecond interval of the uorescence trace of panel c, revealing distinct "on" and "off" periods of the molecular uorescence. Such intermittency can be used to analyse the uorescence to extract characteristic timescales s on and s off . Fitting directly to uorescence intermittency traces is cumbersome and limited in time resolution by the nite photon count rate. A versatile quantication of the uorescence dynamics is instead offered by a single-photon correlation analysis of the uorescence intensity. 50 As indicated in panel e, the correlation is computed by calculating the self-convolution, i.e. the time average of the product of the trace with itself, shied by a temporal offset of Ds. Fig. 2f shows the result of such a typical cross-correlation, plotted on a logarithmic time axis. The correlation can be tted with a single-exponential function of the form</p><p>, where A is the correlation amplitude, s corr is the characteristic decay time of the correlation, and the "on" and "off" times of the molecular uorescence are related by s on ¼ s corr (1 + 1/A) and s off ¼ s corr (1 + A). 50 By adding up s on and s off , we determine the single-molecule turnover frequency TOF SM ¼ 1/(s on + s off ). This number of cycles which one single dye molecule undergoes through the dark state sets the upper limit for synthetic-scale TOF. Details of the uorescence microscopy, including the background correction procedure, are summarized in the ESI. †</p><!><p>We analyse the photocatalytic cycle using uorescence intensity correlation spectroscopy. We stress that this analysis is only possible on the single-molecule level, since in the ensemble the molecular excursions to the dark state and the associated uctuations in uorescence intensity are averaged out. Each singlemolecule uorescence-intensity trace gives an individual photon correlation curve. To account for the statistical variation between different single molecules, we consider the median value of one hundred single-molecule correlation curves for each value of Ds, plotted with exponential ts in Fig. 3. We begin in panel a by examining the uorescence correlation in nitrogen-saturated phosphate-buffered saline (PBS) for the case of excitation with photon energy hn 1 . Under these conditions, the regular transitions of the dye molecule to the triplet manifold give rise to a well-dened "off" time, which can be attributed to the triplet-state lifetime or the lifetime of a radical formed out of the triplet. The temporal excursions to such a dark state are indicated in the cartoon to the right, with s on ¼ 2.22 AE 0.02 ms, s off ¼ 5.99 AE 0.09 ms, and TOF SM ¼ 123 s À1 . The Rh6G triplet state is quenched by molecular oxygen, by saturating the solvent with air. When this quenching occurs, the dye molecule cycles solely between ground and excited singlet state: no amplitude exists in the photon correlation signal in panel b, implying the absence of a dark state.</p><p>To monitor the molecular dynamics relating to PET, we carry out the following experiments under conditions where the dark state is stabilised, i.e. under nitrogen saturation. Panel c plots the photon correlation with addition of the reducing agent ascorbic acid. Now, the molecular dark state must be attributed to the radical with s on ¼ 1.73 AE 0.03 ms, s off ¼ 21.3 AE 0.5 ms, and TOF SM ¼ 44 s À1 . Adding the substrate compound 2-bromobenzonitrile in panel d has no effect on the correlation and the associated timescales. In contrast, exciting the radical with hn 2 in the absence of the substrate in panel e promotes depopulation of the radical state, shortening the dark-state lifetime to s off ¼ 8.4 AE 0.3 ms, with s on ¼ 1.5 AE 0.05 ms, and TOF SM ¼ 100 s À1 . 53 The dramatic effect arises upon simultaneous addition of the two reactantshn 2 photons and 2-bromobenzonitrile moleculesto the dye catalyst. The correlation amplitude in panel f is suppressed almost entirely, but characteristic "on" and "off" times can still be determined as s on ¼ 2.6 AE 0.2 ms, s off ¼ 4.7 AE 0.4 ms, and TOF SM ¼ 137 s À1 . The additional 37 photocycles per second undergone by the catalyst in the presence of the substrate provide a metric for the overall upper limit of the dehalogenation reaction efficiency. Under these reaction conditions, each single Rh6G molecule dehalogenates 37 2-bromobenzonitrile molecules per second.</p><p>In order to prove chemical specicity of the microscopic photocatalytic conPET cycle, it is necessary to demonstrate that the dark state of the dye is not quenched for substrate molecules which cannot be dehalogenated. The obvious material to test this is the non-halogenated compound benzonitrile. Fig. 4a plots the single-molecule correlation signal for the four conditions used in Fig. 3c-f, but with benzonitrile added as the substrate. As before, the correlation is identical with only the reducing agent ascorbic acid added (black curve) and with ascorbic acid and benzonitrile combined (red curve) in the solution. Excitation of the Rh6G radical with hn 2 shortens the dark-state lifetime by returning the dye from the radical state to the ground state (light-blue curve). However, in contrast to the situation in Fig. 3, addition of benzonitrile has no effect on the photon correlation trace (dark-blue curve). We conclude that benzonitrile does not interact with the photocatalyst since addition of it to the solution has no effect on the uorescence cross-correlation. This conclusion is crucial since otherwise product inhibition of the catalyst would occur by the dehalogenated substrate, disrupting the photon cycling process. Once bromine is cleaved from 2-bromobenzonitrile, the molecule disassociates from the catalyst of Fig. 1. An alternative test of the reaction is performed with 4-chloroanisole, as summarized in Fig. 4b. This substrate is energetically not expected to undergo bond cleavage by the excited radical Rc*, as the reduction potential necessary amounts to À2.9 V vs. SCE. 45 Indeed, in Fig. 4b no effect is seen on the correlation curves of addition of the 4-chloroanisole substrate at the same concentration as that used in Fig. 3.</p><!><p>The single-molecule conPET cycle demonstrated here effectively constitutes a single-photon chemical reaction: the rst photon hn 1 , in combination with a reducing agent, generates the photocatalystthe rhodamine radicalwhich subsequently reacts the two "compounds", the substrate 2-bromobenzonitrile and the photon hn 2 . An appealing aspect of the single-molecule single-photon double-excitation scheme is the potential ability to resolve in time the consecutive excitation processes. In a double-pulse experiment, for example, it should be possible to measure directly the lifetime of the photoexcited radical by varying the duration of the hn 2 pulse. In addition, tuning the energy hn 2 in a "photocatalytic action" experiment may even allow time-resolved probing of conformational relaxation dynamics of the catalytically active dye which would offer crucial insight for quantum-chemical modelling of the molecular dynamics of the catalyst-substrate interaction. In this context, we derive two conclusions from the observations. First, the photocatalytic reaction is not fundamentally diffusion limited. Since the lifetime of the photoexcited radical Rc* is expected to be extremely short, 48 the conPET process can only occur if the substrate molecule is preassociated with the dye catalyst. Second, to prevent product inhibition of the catalyst and enable continued observation of the photocatalytic cycle in uorescence, the reacted species must dissociate from the catalyst to allow the reaction to begin anew. We propose that the radical exerts an attractive force on the substrate, promoting preassociation, and speculate that such an effect may be more common to photocatalytic processes than previously thought. While we cannot conclusively prove that preaggregation does not occur in the dye ground state, we reiterate the observed reduction in turnover number upon dehalogenation of the substrate, implying that interaction with either form of the dye must be weakened. We note that the substrate is an aromatic system with two electron-withdrawing substituents. The interaction of such an electron-poor aromatic should be stronger with the neutral dye radical than with the cationic dye ground state. As discussed above, depending on the protonation balance, the rhodamine ground state may actually be neutral. In this case, the interaction of the dye with the electron-poor substrate would also be stronger in the anionic radical state than in the neutral ground state. Without precise determination of the different contributions from van der Waals interactions, pi-stacking and electrostatics, such arguments, however, remain qualitative. To further explore the microscopic origins of this phenomenon will necessitate the development of time-dependent density functional theory (TD-DFT) techniques which can take into account the strong polarization effects of the surrounding medium. 51 This can be achieved by implementing new theoretical methods to account for the complex excited-state geometry optimization arising from the non-adiabatic molecular dynamics. To arrive at such a microscopic theory of organic photocatalysis it is imperative to have access to truly microscopic experimental data, which only become available on the single-molecule level. An open question is whether the trapping agent N-methylpyrrole used in the ensemble experiments also sticks to the photocatalyst. This could conceivably be expected since dispersive interactions should be of a comparable nature to those of the substrate, but such an association could in turn block the photocatalyst. Given near-unity conversion yields found in the ensemble, such blocking is apparently unlikely. Our crucial conclusion is that in mechanisms which involve preassociation of substrate and photocatalyst, diffusion no longer appears to be the limiting factor so that long excitedstate lifetimes are not necessary to ensure effective photocatalytic transformation. This is an important point since most photoredox catalytic cycles involve long-lived triplet states. Triplets, however, limit the overall catalytic potential since electronic energy is inherently lost to the quantum-mechanical exchange interaction by satisfying Pauli's exclusion principle. Our work therefore encourages a renewed search for materials supporting singlet-based photoredox cycles. The dehalogenation reaction demonstrated here on the single-molecule singlephoton level constitutes a precursor to more complex photocatalytic mechanisms. We expect the cycle to work equally well in forming carbon-carbon bonds, opening up the possibility of multicolour directed synthesis 13 on the single-molecule level.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Peptide array–based interactomics

The analysis of protein-protein interactions (PPIs) is essential for the understanding of cellular signaling. Besides probing PPIs with immunoprecipitation-based techniques, peptide pull-downs are an alternative tool specifically useful to study interactome changes induced by post-translational modifications. Peptides for pull-downs can be chemically synthesized and thus offer the possibility to include amino acid exchanges and post-translational modifications (PTMs) in the pull-down reaction. The combination of peptide pull-down and analysis of the binding partners with mass spectrometry offers the direct measurement of interactome changes induced by PTMs or by amino acid exchanges in the interaction site. The possibility of large-scale peptide synthesis on a membrane surface opened the possibility to systematically analyze interactome changes for mutations of many proteins at the same time. Short linear motifs (SLiMs) are amino acid patterns that can mediate protein binding. A significant number of SLiMs are located in regions of proteins, which are lacking a secondary structure, making the interaction motifs readily available for binding reactions. Peptides are particularly well suited to study protein interactions, which are based on SLiM-mediated binding. New technologies using arrayed peptides for interaction studies are able to identify SLIM-based interaction and identify the interaction motifs.Graphical abstract

peptide_array–based_interactomics

Introduction<!><!>Immunoprecipitations and peptide pull-downs<!>Peptide pull-down meets mass spectrometry<!>Linear motifs as interaction mediators<!><!>Linear motifs as interaction mediators<!>Peptide array–based interaction screens<!>Outlook<!>

<p>Cellular signaling is in large parts based on a complex network of protein interactions with other proteins or other biological molecules. Studying protein-protein interaction (PPI) networks is pivotal for the understanding of cellular signaling [1–3]. Protein-protein interactions can be studied in different ways, including the genetic modification of the protein sequence, measurements by two-hybrid interactions, or chromatographic comigration [4–6]. The direct detection of interaction partners after isolating the protein of interest is the most common one [7]. The mass spectrometric measurement of interacting proteins has increased in popularity due to the increased sensitivity and possibilities of modern mass spectrometry–based proteomics [6, 8–10]. While many studies use whole proteins for interaction studies, the use of peptides in such studies has increased over time [11–16]. In this article, we will focus on the newly developing field of peptide array–based interaction studies.</p><!><p>a Protein immunoprecipitation. The protein of interest is captured by an immobilized antibody for the pull-down. b Peptide pull-down. A peptide and a PTM-modified version of the same peptide are immobilized on a bead. The PTM prevents in this case the binding of the protein. c Highly parallelized peptide pull-down. The peptides are carrying different PTMs or mutations (indicated by the colored pins), which are enabling (orange and red) or preventing (black) interaction. d Peptide array designed for a PrISMa screen. A SLiM-containing area in a protein of interest (dark blue) is covered by different tiling peptides. Each of the peptides covers a different part and only the second peptide contains the entire SLiM (dark blue shade). e Inclusion of PTMs in the peptide array designed for PrISMa analysis. For each of the tiling peptides, a peptide with and one without the PTM is included. f + g Identification of false-positive binders in a PrISMa setup. Neighboring peptides cover different parts of the SLiM allowing only partial binding. A protein peptide not showing this binding behavior is excluded as it has a high probability to be nonspecific binding</p><!><p>In parallel, advances in the chemical synthesis of peptides allowed the production of larger quantities and longer peptides. This enabled the use of peptides in pull-down assays as an alternative to the genetic generation of tagged protein fragments [19]. The chemical synthesis of peptides carrying amino acid exchanges provided a fast alternative to cloning techniques [20–22]. Several studies used arrays of synthetic peptides containing alanine exchanges for the corresponding amino acids as a binding matrix. Incubation of the matrix and detection of the protein interactors allowed the identification of essential amino acids for the interaction [23–26]. An alternative technique for the screening for the best interacting peptides is the phage display technique, where peptides are presented on a cell using phage expressing protein fragments [21, 27–29].</p><!><p>The full potential of a peptide pull-down is only utilized in combination with a powerful detection methodology, which allows the identification of new interaction partners. With the rise of mass spectrometry–based proteomics, interacting proteins can be identified in a peptide pull-down (reviewed in [13]). Differently from protein-based interaction studies, peptide-protein interactions are usually of low affinity, thus preferring high-affinity interactions with more abundant proteins [30]. This preference introduces a bias against the detection of low abundant interaction partners or transient interactions and thus limits the use of peptide pull-downs. At the same time, a peptide bait permits narrowing the interaction site down to a fraction of a protein, allowing the precise mapping of the interaction site without the need to generate protein truncations [31, 32].</p><p>A significant advantage of peptides over protein pull-downs is the possibility of including post-translational modifications (PTMs) in the peptide. As peptides are chemically synthesized, any PTM can be included as long as it is compatible with the synthesis technique. The binding surface is thus fully modified, which is usually not the case with complete proteins [33–36].</p><p>Fast regulation of biological networks relies on the rapid addition and removal of PTMs during signaling, leading in many cases to the formation or loss of protein interactions. Capturing these transient interactions is challenging [36, 37]. Dissecting the recruitment of proteins using PTM-containing peptides allows identifying different complexes involved in the interaction (Fig. 1b). The interaction of SH2 domains with the phosphorylated C-terminal tail of the epidermal growth receptor is such an example. Synthetic phosphotyrosine-containing peptides were used to show the specificity of Grp2's SH2 domains [38, 39]. To discriminate the different interactomes of the ErbB receptors for the phosphorylated versus the unphosphorylated state, phosphorylated peptides and their unmodified counterparts derived from the C-terminal region of ErbB receptors were used in a pull-down study, revealing the specific recruitment of Stat5 to the double phosphorylated C-terminus [40]. A systematic study of all 99 human SH2 domains probed their specificity in a system biological study. The binding patterns were confirmed by peptide pull-down experiments showing the regulation in a time-resolved manner [41]. Besides phosphorylations, other PTMs have been shown to change interactions. An example is the methylation at position three of the transcription factor C/EBPß, which leads to the loss of interaction with the SWI/SNF complex [42–44].</p><!><p>Many proteins adapt a defined fold, which is determined by their amino acid sequence. These folded domains are contrasted by regions lacking a specific fold, which are called intrinsically disordered regions (IDRs) [45]. Despite their lack of structure, IDRs are important docking sites for many proteins [46, 47]. They are often decorated with many PTMs indicating their importance for regulated interactions [45, 48–50]. IDRs can harbor many interaction motifs, which fall into three groups: short linear motifs (SLiMs), molecular recognition features (MoRFs), and intrinsically disordered domains (IDDs). The groups differ in length and how they support interactions. SLiMs are usually between three and 10 amino acids in length while MoRFs are slightly longer with 10 to 70 amino acids. MoRFs undergo a transition from the unordered to an ordered state while the ligand-binding takes place [51]. IDDs fold upon interaction with the binding partner [52].</p><!><p>Interaction of a SLiM with a specific binding site of an interacting protein. The SLiM consists of a specific amino acid pattern, which, in this case, is defined for a set of amino acids and interspaced with amino acids (X) with no contribution to the binding (here: LXXLLXXXLXXF)</p><!><p>Synthesized peptides covering short parts of a protein can contain complete SLiMs, making them the perfect carrier for SLiM-based interaction studies. This has been used in studies, where a known sequence with and without the PTM was used to identify the interaction partners, as demonstrated in a study using two different peptides derived from EGFR and Sos1 and 2. The peptides were synthesized in phosphorylated and unmodified form and used in a pull-down experiment utilizing SILAC-labeled (stable isotope labeling in cell culture) cell extracts. The interaction partners were identified using mass spectrometry [63].</p><!><p>The advancements of peptide synthesis by SPOT synthesis allow the creation of arrays holding many different peptides on a single membrane surface [23, 64, 65]. Cellulose membranes are an attractive alternative support to bead-based technologies, which can directly be used in biological assays, including immunological assays or parallelized peptide pull-downs [66]. The synthesis allows the inclusion of different PTMs in the membrane, permitting the systematic comparison of the interactome of a peptide sequence and its modified counterpart.</p><p>While peptide matrices have been used to find the optimal binding sequence [67–69], the true power of the approach emerges when it is combined with a proteomics readout. Meyer and coworkers use this principle to analyze mutations that cause neurological diseases [12]. One hundred twenty known disease-causing mutations were selected in extensive bioinformatics analysis. Peptides for the wild-type and mutated sequence were used to construct a peptide array and probed for differential binding with a proteomics readout (Fig. 1c). This created a PPI network of gained and lost interactions. A subnetwork of five interactors was related to clathrin-mediated transport. Three of the interaction nodes created a dileucine motif which is necessary for clathrin-dependent transport. In case of the glucose transporter GLUT1, the mutated version was wrongly localized to the endocytic compartment [12].</p><p>A screening technique targeting transient SLiM-based interactions along the primary structure was recently developed. The technique, PrISMa (Protein Interaction Screen on a Peptide Matrix), is based on a membrane-bound array of overlapping peptides, spanning the entire sequence of the protein of interest, creating a sliding window for the detection of SLiM-mediated interactions [11] (Fig. 1d, f). The interaction partners for each peptide were identified using mass spectrometry–based proteomics. The PrISMa technique provides a number of advantages over peptide pull-downs. The high concentration of immobilized peptides on the matrix allows the stabilization of the transient interactions, thus increasing the sensitivity for detecting these interactions. The overlapping peptide structure of the matrix offers the implementation of powerful filtering methods, based on the partial presence of the SLiM in the peptide adjacent to the main binding peptide. This allows separating unspecific background binding from SLiM-mediated interactions (Fig. 1g). The technique was used to map the interactome of the transcription factor C/EBPβ, identifying a large number of new interaction partners [11].</p><p>Additionally, the setup of the peptide array allows the inclusion of PTMs in the matrix to probe simultaneously for PTM-mediated interactions (Fig. 1e). For the C/EBPß study, several PTMs including methylation, citrullination, acetylation, and phosphorylation were included. This revealed the binding of the TLE3 complex specifically to the methylated form of C/EBPß.</p><p>A limitation of the method is the restriction of the screen: it can be only applied to intrinsically disordered regions, in which the structure depends only on the amino acid sequence. For interactions that depend on three-dimensional structures, this cannot be applied. To address this limitation, Ramberger and coworkers combined the PrISMa method with a BioID interaction screen to explore the C/EBPα interactome. They observed a significant overlap of the interaction partners between both technical approaches, and interestingly, common protein binders with C/EBPβ interactome [60].</p><!><p>Over time, peptide-based interaction studies have significantly helped to reveal interaction sites or confirm specific PTM-regulated interactions. The new matrix-based interaction screens open a new era of interaction studies allowing to test many SLiM-based interactions at the same time. Besides the costs for the peptide matrix, using a mass spectrometric readout, the time of the measurement for all the interaction screens is a major restriction. Although the measurement of certain interactions can be parallelized by the use of isotopic labeling techniques, like SILAC and maybe TMT/iTRAQ in the future, the measurement of a peptide matrix can consume weeks on data acquisition in the mass spectrometer. Here, the technical developments of fast liquid chromatography systems might reduce the time constraints and open the use of peptide matrices for more laboratories. This will broaden the use of these techniques to identify more, potential druggable, PPI-driven diseases and will promote the deeper understanding of PPI networks, which depend on low affinity interactions.</p><!><p>Publisher's note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p>

PubMed Open Access

One-pot multistep mechanochemical synthesis of fluorinated pyrazolones

Solventless mechanochemical synthesis represents a technique with improved sustainability metrics compared to solvent-based processes. Herein, we describe a methodical process to run one solventless reaction directly into another through multistep mechanochemistry, effectively amplifying the solvent savings. The approach has to consider the solid form of the materials and compatibility of any auxiliary used. This has culminated in the development of a two-step, one-jar protocol for heterocycle formation and subsequent fluorination that has been successfully applied across a range of substrates, resulting in 12 difluorinated pyrazolones in moderate to excellent yields.

one-pot_multistep_mechanochemical_synthesis_of_fluorinated_pyrazolones

Introduction<!>Results and Discussion<!>Conclusion

<p>Mechanochemical methods are emerging as an alternative approach to traditional solvent-based reactions for chemical synthesis. Under mechanochemical conditions reactions are performed between neat reagents and do not require a solvent. Processing chemical reactions in such a manner is desirable as reactions are consequently less wasteful and more environmentally benign than the analogous solution-based approaches, especially if the work-up and purification processes can also be made solventless or solvent minimised [1,2]. As such, there is now a significant number of mechanochemical synthetic transformations reported [3][4][5][6]. However, for the synthetic commu-nity, perhaps the most interesting examples of mechanochemical reactions are not those that are merely solventless but those in which different reactivity or selectivity arises, as well as those that are significantly shorter in reaction time than those conducted in solution. Indeed, there are several examples where reactions are clearly significantly faster under mechanochemical conditions [7,8].</p><p>One of several challenges to be overcome for the further development of mechanochemistry as an up to date tool for synthesis is to gain a better insight into the ability to run multistep proce-Scheme 1: Factors to be considered regarding the physical form in the one-pot two-step mechanochemical procedure.</p><p>dures. One-pot multistep procedures are particularly efficient, in that the same reaction vessel is used for each step, additional reagents are simply added to the reaction mixture at each stage with no isolation of intermediates or removal of side products [9]. One-pot procedures require the conditions for each step to be compatible with succeeding steps. Typical problems encountered when attempting to multistep reactions include solvent compatibility, or, issues with side products that can inhibit future steps, e.g., by providing access to alternative reaction pathways, poisoning catalysts or altering the pH unfavourably [9]. With regards to mechanochemistry such processing serves to amplify the sustainability metrics by running back-to-back solventless reactions. Multistep mechanochemical procedures have been successfully applied to the synthesis of O-glycosides [10], bioactive hydantoins [11], extended iptycenes [12] and organometallics [13] where problems can occur using solutionbased synthesis due to limited solubility. Whilst mechanochemical one-pot procedures offer the inherent ability to overcome the issue of identifying a solvent compatible with several consecutive steps, we envisaged alternative hurdles not previously described with regard to compatibility of chemical form. The state of reagents or chemical form is significant to reactions conducted under mechanochemical conditions, where liquids and solids behave differently. For instance, when liquid components are used it may be critical to add a solid auxiliary that helps the transfer of energy and mass (adequate mixing) throughout the mixture. In many cases, leaving out such an auxiliary material can result in a gum or a paste that does not mix well and results in low reaction conversions. Clearly the presence of such a material may have a knock-on effect on any multistep process. Liquid-assisted grinding (LAG) is another phenomenon that can provide enhancement to the reaction outcome and again should be considered for use in a multistep format [14][15][16].</p><p>Having recently begun our research programme in the area of mechanochemistry, we were particularly intrigued by the compatibility of differing chemical forms and additives across a two-step, one-grinding jar solventless process. To investigate this we designed a 2-step reaction related to our recent work on liquid assisted grinding effects of the fluorination of 1,3-dicarbonyl compounds, in which the dicarbonyl will initially form a pyrazolone in the first reaction prior to undergoing difluorination in the second step (Scheme 1) [17].</p><p>Notably this approach will likely require a grinding auxiliary in the first step where two liquid phases react and will be catalysed by an acid to afford a solid pyrazolone material. This will then be followed by a difluorination reaction between solid-solid reactants, this reaction may perform better in the presence of base in the second step. In this report, we present a systematic approach to finding the optimal conditions, which are most compatible with both steps. Notably, fluorinated pyrazolones have the potential to be useful pharmaceutical or agrochemical products, given the desirable properties that can be obtained on introduction of fluorine to a molecule [18][19][20][21][22][23][24][25]. However, there have been limited reports on the synthesis of fluorinated pyrazoles, but fluorinated pyrazolones remain poorly studied [26][27][28][29][30].</p><!><p>Initially the mechanochemical pyrazolone formation was investigated as the first step of the two step process, we opted to keep the ball size, ball number, jar size and jar and ball material as in our previous studies to reduce the number of variables for this analysis [17]. In the first instance, simply milling the two liquids in the absence of an auxiliary material resulted in a poor yield (Table 1, entry 1). Pleasingly, treatment of ethyl benzoylacetate with one equivalent of phenylhydrazine in the presence of sodium chloride afforded the desired pyrazolone product in 66% yield after milling for 10 minutes (Table 1, entry 2). The addition of a grinding auxiliary could play several roles. We propose that the key benefits are related to improved mixing, and aiding in energy transfer, specifically in mechanochemical reactions where the reaction mixture could be described as a gum, paste or liquid. Notably, the comparable reaction under solvent-based conditions (in toluene, under reflux) required 24 hours to achieve a similar yield (Table 1, entry 3). As pyrazolone formation can be catalysed by acid, a screen of both solid and liquid acids was next performed (Table 1, entries 4-9). In general, the weaker carboxylate acids performed better than mineral acids, with the highest yield obtained using acetic acid (Table 1, entry 9). The quantity of acid used was then varied. In general, the yield increased with an increase in the amount of acid used ( the larger amount of liquid altering the texture of the reaction mixture and thus reducing effective mixing. An alternative justification is that at higher acid equivalents in the solid state the 'on-off' protonation of the hydrazine is slow, meaning that the nucleophilicity is greatly retarded compared to lower acid loadings. Nonetheless, considering that the subsequent fluorination step should proceed optimally under basic conditions [17], the lowest amount of acid which also provided a good yield was thus chosen; 30 μL (Table 1, entry 9). Finally, the reaction time with this quantity of acid was then optimised, whereupon the reaction was found to be complete after 40 minutes producing 92% isolated yield of pyrazolone 1 (Table 1, entry 14). For comparison, these optimal conditions have been applied to a solution-based reaction, resulting in a poorer yield after 24 hours at reflux in toluene (Table 1, entry 17). Having achieved optimal conditions for the first step of the reaction, our attention turned to the second step.</p><p>Initial investigation of the fluorination of the pyrazolone focused on finding the optimum reaction time for the isolated step rather than two-step, i.e., the pyrazolone material was isolated from step one and purified before subjecting to this second reaction optimisation. With no additives, the fluorination was complete after 2 hours (Table 2, entry 4), notably an extra hour returned no further improvement (Table 2, entry 5). The fluorination reaction studied here proceeds via an enolate which is aromatic and therefore is relatively facile (compared to the fluorination of other heterocyclic systems). Introduction of a mild base, such as sodium carbonate to the reaction vessel Scheme 2: Optimised conditions for the one-pot synthesis.</p><p>served to enhance the rate of reaction, providing complete conversion after 1 hour (Table 2, entry 6).</p><p>With an understanding of the second step we then assessed the reaction whilst mimicking aspects of the first reaction in order to look for compatibility of a two-step one-jar process. The most important difference between the two steps is the physical state of the reactants. For the first step (Table 1), both reagents are liquids, and a grinding auxiliary was required to aid mixing and energy transfer. However, for the second step (Table 2), the reagents are solids, and the presence of a grinding agent could have a diluting effect. Indeed, addition of sodium chloride does slow down the fluorination, giving a poorer yield (Table 2, entry 7). Another factor to be explored was the effect of acetic acid on the second step. Again, this resulted in a decrease in yield of the fluorination reaction achievable within a two hour reaction time (Table 2, entry 8).</p><p>Pleasingly a combination of sodium carbonate with the sodium chloride grinding auxiliary resulted in complete reaction after one hour (Table 2, entry 9). The only compatibility issue remaining was the acid present from the first step. However, as a base improved the reactivity of the fluorination, the final conditions make use of enough sodium carbonate both to neutralise the remaining acid and accelerate the second step. By applying these compatible conditions to the one-pot procedure, the desired fluorinated pyrazolone was isolated in 75% yield (Scheme 2). Scheme 2 also shows the physical state descriptors and photographs of the practical experiment.</p><p>With suitable conditions in hand, the scope of this one-pot mechanochemical process was explored (Scheme 3). Initially, the scope of β-ketoesters was assessed and the procedure was found to be compatible with both the electron-withdrawing and electron-donating groups. However, a poorer yield was obtained for the electron-withdrawing trifluoromethyl substituent (5). The scope of phenylhydrazines was also briefly investigated, with several examples demonstrating good isolated yields, again an electron-withdrawing trifluoromethyl substituent was an exception to this (7) [31]. For this case, crude 19 F NMR after the first step shows a 41% conversion, suggesting that the pyrazolone formation is the limiting factor in this example. An alkyl β-ketoester (ethyl acetoacetate) was also used, affording methyl substituted difluoropyrazolone 12 in modest yield. Finally, an α-substituted β-ketoester was successfully converted to the pyrazolone before monofluorination using one equivalent of Selectfluor to prepare pyrazolone 13, also in moderate yield. In general the optimised approach seems to apply to a small range of compounds.</p><!><p>In summary, we have developed a one-pot, two-step mechanochemical synthesis of fluorinated pyrazolones. The experiments provide a logical approach to multistep solventless synthesis under milling conditions and more broadly will assist in the conversion of other processes to such a system. After careful consideration of physical form and additive compatibility the final protocol has been successfully applied to the preparation of a small library of 12 difluorinated pyrazolones, several of which are hitherto unreported.</p>

Beilstein

Multiscale simulations identify origins of differential carbapenem hydrolysis by the OXA-48 β-lactamase

OXA-48 β-lactamases are frequently encountered in bacterial infections caused by carbapenem-resistant Gram-negative bacteria. Due to the importance of carbapenems in treatment of healthcare-associated infections, and the increasingly wide dissemination of OXA-48-like enzymes on plasmids, these βlactamases are of high clinical significance. Notably, OXA-48 hydrolyses imipenem more efficiently than other commonly used carbapenems, such as meropenem. Here, we use extensive multiscale simulations of imipenem and meropenem hydrolysis by OXA-48 to dissect the dynamics and to explore differences in reactivity of the possible conformational substates of the respective acylenzymes. QM/MM simulations of the deacylation reaction for both substrates demonstrate that deacylation is favoured when the 6αhydroxyethyl group is able to hydrogen bond to the water molecule responsible for deacylation, but disfavoured by increasing hydration of either oxygen of the carboxylated Lys73 general base. Differences in free energy barriers calculated from the QM/MM simulations correlate well with the experimentally observed differences in hydrolytic efficiency between meropenem and imipenem. We conclude that the impaired breakdown of meropenem, compared to imipenem, which arises from a subtle change in the hydrogen bonding pattern between the deacylating water molecule and the antibiotic, is most likely induced by the meropenem 1β-methyl group. In addition to increased insights into carbapenem breakdown by OXA β-lactamases, which may aid in future efforts to design of antibiotics or inhibitors, our approach exemplifies the combined use of atomistic simulations in determining the possible different enzyme-substrate substates, and their influence on enzyme reaction kinetics.

multiscale_simulations_identify_origins_of_differential_carbapenem_hydrolysis_by_the_oxa-48_β-lactam

Introduction<!>Methods<!>Results & Discussion<!>Deacylation efficiencies for different orientations of the 6α-hydroxyethyl group<!>Comparison of carbapenem deacylation in orientation I<!>Comparison with experimental data<!>Conclusions

<p>The World Health organization describes antibiotic resistance as "...one of the biggest threats to global health, food security, and development today." 2 Antibiotic resistance arises naturally and evolved long ago, 3 but its emergence and dissemination have been considerably accelerated by the current excessive use of antibacterial drugs. 4,5 This evolving resistance not only complicates standard medical practices, but also has additional expensive implications e.g. for the global economy and food production. [6][7][8] Moreover, we are currently living in the so-called antibiotic discovery void 9 where discovering new and safe antibacterials, especially for Gram-negative bacteria, is difficult, time-consuming, and often unprofitable for big pharmaceutical companies. 10,11 β-Lactam antibiotics offer broad-spectrum antibacterial activity against Gram-negative bacteria and remain the most prescribed drugs in clinical practice. 12 The importance of β-lactams in healthcare has been highlighted by the World Health Organization, which includes multiple different β-lactam antibiotics in their Model List of Essential Medicine. 13 All of these antibiotics contain a four-membered β-lactam ring, which ensures antibiotic binding to penicillin-binding proteins and consequently inhibition of bacterial cell wall biosynthesis. 14,15 Clinically used β-lactam compounds can be divided into four different groups: penicillins, cephalosporins, carbapenems, and monobactams, of which carbapenems play a critical role as potent antibiotics reserved for the most serious Gram-negative infections where alternatives are limited. 16 Emerging resistance against β-lactams is evident, and especially in Gram-negative bacteria, βlactamase enzymes are the main resistance mechanism against these drugs. 17 β-Lactamases block antibiotic action by hydrolysing the β-lactam ring, which impairs efficient antibiotic binding to their ultimate target in cells. The Ambler sequence-based classification divides β-lactamases into four major subgroups: serine-β-lactamases (SBLs) comprising classes A, C, and D; and metallo-βlactamases (MBLs), class B. 18 The hydrolysis mechanism differs between SBLs and MBLs, as SBLs utilise a nucleophilic serine residue and MBLs employ zinc cofactors. 17 Class D SBLs are referred to as OXA (oxacillinase) enzymes, stemming from their activity against the isoxazolyl penicillin oxacillin, 19 and they are currently of interest due to their wide distribution and the ability of many members of the group to inactivate carbapenems. The OXA enzymes include five subgroups of recognised carbapenemases: the OXA-23, OXA24/40, OXA-51, and OXA-58 βlactamases are mainly found in Acinetobacter baumannii, while OXA-48-like β-lactamases are mostly encountered in Enterobacterales. 20 In Enterobacterales, OXA-48 β-lactamases are among the most commonly present carbapenemases in clinical samples. 21 Their activity is relatively specific towards imipenem, but other carbapenem substrates (such as meropenem and ertapenem) are also hydrolysed, albeit slowly. 22 The specific origin of this imipenemase activity is not well established, even though variations in measured hydrolysis rates between point variants of OXA-48 hint at structural moieties contributing to specific hydrolytic phenotypes (Figure 1). In OXA-163, a partial deletion of the β5-β6 loop (Arg214-Pro217) and one amino acid substitution (Ser212Asp) expands the hydrolysis profile to accommodate expanded-spectrum oxyimino cephalosporins (such as ceftazidime) at the expense of efficient imipenem breakdown. 23 Further studies show that the β5-β6 loop plays a role in acquired carbapenemase activity, as engineering the OXA-48 β5-β6 loop into the noncarbapenemase OXA-10 enhances its carbapenemase activity. 24 Conversely, replacing the β5-β6 loop in OXA-48 with that of OXA-18 also alters the measured carbapenemase activity (lower kcat values). 25 Site-directed mutagenesis studies of OXA-48 variants indicate that residue 214 (arginine in the wildtype OXA-48) is essential for efficient carbapenem hydrolysis. 26 In recent years, structural studies have yielded a variety of crystal structures of OXA-48 in complex with carbapenems, which shed new light on the acylenzyme (AC) intermediate state. 1,[27][28][29][30] Intriguingly, although the β5-β6 loop is suggested to influence carbapenem activity, the only interaction observed between the substrate and residues within this loop (Thr213-Lys218) is a water-mediated contact between the imipenem 6α-hydroxyethyl hydroxyl and Thr213. 1,30 Furthermore, bound carbapenem Figure 1. Crystal structures of OXA-48 complexed with carbapenems. Acylenzyme structures of OXA-48 with imipenem (PDB ID 6P97, green sticks) and meropenem (PDB ID 6P98, light pink sticks) show a highly similar binding pose for both substrates, where main differences lie in the orientation of carbapenem C2 "tail" group. 1 The Ω-loop is highlighted in orange, the β5-β6-loop in yellow, and relevant active site interactions with dashed black lines. The carbapenem pyrroline ring is modelled as the Δ2-tautomer in both structures.</p><p>tail groups (C2 substituents) seem to be dynamic and able to adopt multiple conformations, which suggests they do not form strong, specific interactions with the enzyme active site. 29 The generalized β-lactam hydrolysis mechanism for SBLs consists of acylation followed by deacylation (Scheme 1). 17 Both acylation and deacylation reactions include the formation of a shortlived tetrahedral intermediate (TI) through a nucleophilic attack; the respective TI species collapses to yield either a covalent AC structure (after acylation), or the final hydrolyzed product (after deacylation). In both reactions, the nucleophile (conserved serine (Ser70) in acylation and a water molecule (deacylating water, DW) in deacylation) is activated via proton abstraction by a general base. For OXA enzymes, this general base is a carboxylated lysine residue (Lys73). 31,32 Notably, Lys73 needs to be carboxylated for optimal activity; this carboxylation is reversible and pH dependent, i.e. more carboxylation is observed at higher pH values. 31 At lower pH values, protonation of the Lys73:Nζ would lead to decarboxylation. 33 Based on pH dependence studies of the reaction between OXA-10 and penicillin or nitrocefin, the pKa of the carboxylated Lys73 is expected to be ~5.8-6.2. 31 For carbapenems, the pyrroline ring can undergo Δ2 → Δ1 tautomerization in the AC state, the Δ1 tautomer also having two stereoisomers (R and S). For class A SBLs, the Δ2 tautomer has been suggested to be the catalytically competent form, whereas the Δ1 form would essentially inhibit the enzyme. 34 For OXA-48 enzymes, all three tautomers have Scheme 1. Top: Structures of meropenem and imipenem (with atoms numbered), the 6α-hydroxyethyl group is highlighted in red. Bottom: Deacylation mechanism in OXA-48 with a carbapenem substrate (Δ2 tautomer). Starting from the acylenzyme, the antibiotic is deacylated via tetrahedral intermediate formation (1 → 2), which collapses to yield the hydrolysed antibiotic (3).</p><p>been observed in AC crystal structures, 1, 28-30 but, based on NMR studies, the hydrolysis product is suggested to be either the Δ2 or R-Δ1 tautomer. 35 Kinetic measurements suggest that for OXA-48-like β-lactamases, deacylation is the ratelimiting step in carbapenem breakdown. 30 These authors suggested that the impaired imipenemase activity in the ESBL-like OXA-163, compared to OXA-48, is due to a larger active site, which would not constrain the substrate in deacylation-compatible conformations. Molecular dynamics (MD) simulations of the non-covalent complexes of OXA-48 and OXA-163 with meropenem and imipenem suggested some differences between the substrates in mobility. However, the measured KM values for OXA-48 with imipenem and meropenem are very similar (according to one assay, 11 and 13 μM, respectively) 22 , which indicates that there is unlikely to be any significant difference in the stabilities of the respective Michaelis complexes. The difference in the inactivation efficiency of imipenem compared to meropenem is thus primarily related to differences in the rate of the deacylation step, and it is therefore essential to consider this reaction when seeking to understand and explain activity differences. To analyse differences in activity for carbapenems in atomistic detail, we here simulate TI formation in deacylation, i.e. the expected rate-limiting step, of both imipenem and meropenem by OXA-48 using combined quantum mechanics/molecular mechanics (QM/MM) simulations. Our simulations support the hypothesis that the AC state arising from carbabenem acylation is dynamic in nature. Further, we identify conformations of the 6αhydroxyethyl group that allow for efficient deacylation. Additionally, active site hydration around the carboxylated Lys73 is observed to affect the calculated free energy barriers for deacylation, as we previously observed hydrolysis of the expanded-spectrum oxyimino cephalosporin ceftazidime by OXA-48 enzymes. 36 Analysis of the reaction simulations shows that efficient carbapenem breakdown results both from a decrease in hydration around carboxy-Lys73, and from subtle changes in hydrogen bonding between the substrate and the catalytic water molecule. These results provide detailed insight into the causes of differences in enzyme activity against different antibiotics, information potentially useful in understanding and combating antimicrobial resistance.</p><!><p>Computational methods and details of the system setup are described in detail in the Supporting Information (SI). To summarise, models of OXA-48 with imipenem and meropenem were prepared based on corresponding acylenzyme (AC) crystal structures (PDB IDs 6P97 1 and 6P98 1 for imipenem and meropenem, respectively). The ff14SB parameter set was used for the protein, 37 parameters and partial charges for non-standard residues (acylated carbapenems and carboxylated lysine) were derived with the R.E.D. Server. 38 Both systems were energy minimised, heated from 50 K to 300 K (in 20 ps), and their dynamics in the AC state were simulated for 200 ns using Langevin dynamics (collision frequency 0.2 ps -1 ) with a 2 fs timestep. Five independent simulations for each AC system were run. All bonds involving hydrogens were restrained using the SHAKE algorithm. Starting structures for QM/MM 39 modelling were chosen from MD simulations based on visual inspection of the active site hydration pattern and the 6αhydroxyethyl orientation; this orientation was kept from changing during subsequent QM/MM US MD by applying a weak dihedral restraint (except in the case of orientation I). Free energy barriers for the first (rate-limiting) step of deacylation for the different active site conformations were determined from three separate QM/MM umbrella sampling (US) calculations for each conformation. 40 Two reaction coordinates were employed in US, one for the nucleophilic attack and one for the proton transfer, as in previous simulations of deacylation in serine β-lactamases. 36,[41][42][43] Sampling time in each window was 2 ps, and DFTB2 (SCC-DFTB) [44][45][46] was used as the QM method for regions consisting of 43 and 46 atoms (including link atoms) for imipenem and meropenem, respectively (Figure S1). Free energy surfaces (FESs) were constructed from 399 individual US windows. The weighted histogram analysis method (WHAM) 47,48 was used to construct the free energy surfaces, and the minimum energy paths were analysed using the Minimum Energy Path Surface Analysis (MEPSA) program 49 . All simulations and trajectory analyses were done using the Amber18 software package 50 (pmemd.cuda [51][52][53] for MM MD, and sander for QM/MM calculations).</p><!><p>Conformational Dynamics of Carbapenem:OXA-48 Acylenzymes AC dynamics for both imipenem and meropenem complexed with OXA-48, each in the 2 (enamine) configuration, were explored by running five 200 ns MM MD simulations for each complex. The first 50 ns were excluded from trajectory analysis to allow time for equilibration. For both carbapenems, the salt bridge between the C3 carboxylate and Arg250 was preserved during simulations, and the C7 carbonyl stayed in the oxyanion hole formed by the backbone amides of Ser70 (nucleophile) and Tyr211. The carbapenem C2 (tail) substituents sampled a range of conformations during the simulations, consistent with previous suggestions based on structural analysis. 29 Clustering the substrate poses based on their heavy atom RMSD yielded four distinct clusters per substrate, which differ by 0.8-1.8 Å and 1.7-2.5 Å for imipenem and meropenem, respectively, from the poses in the corresponding crystal structures (Figure S2, Table S1 and SI section Acylenzyme Clustering). The main deviations between cluster centroids and the crystal structure coordinates are due to the positions of the C2 tail groups, as the pyrroline ring and its substituents are anchored in place by hydrogen bonds to the oxyanion hole and the salt bridge with Arg250. However, for the crystal structures 6P97 and 6P98 there is only limited electron density beyond the sulfur atom for both imipenem and meropenem, so the deposited coordinates may not completely reliably depict the actual substrate binding poses. Additional clustering on the active site residues (explained in further detail in the SI) implies that there may be slight differences also in the positions of active site residues Lys73, Tyr157, as well as of the substrate (Figure S3 and Table S2).</p><p>During MM MD, the carbapenem 6α-hydroxyethyl group was able to rotate to occupy three different orientations, which can be distinguished by the value of the C7-C6-C-O dihedral angle: around 50°, 180°, or 290°, henceforth referred to as orientations I, II, and III, respectively (Figure 3). The 6α-hydroxyethyl orientation affects interactions in the active site, because its hydroxyl group can hydrogen bond either with the DW (I), or with the Lys73 carboxylate (III), or stay close to the crystallographically observed pose, in which its methyl group is positioned next to the DW and points towards Leu158 (II, Figure 2). The starting orientation of the 6α-hydroxyethyl for both carbapenems is II, as in the crystal structures used in model construction. During MD si mulations, this sidechain is free to move and sample all three orientations. For meropenem, orientation I is sampled more than II, while III is sampled only minimally (Figure 2). Conversely, both orientations II and III are sampled more than I for imipenem. The free energy difference between the different orientations of the 6α-hydroxyethyl group was estimated by calculating the ratio of MD trajectory frames corresponding to each orientation (Z), and using ΔG=RTln(Z), where R is the molar gas constant and T the simulation temperature (300 K). For imipenem, the lowest free energy state is orientation II, with slightly higher relative energies of 0.6 and 0.2 kcal/mol for orientations I and III, respectively. For meropenem, orientation I has the lowest free energy, orientation II is slightly higher (0.6 kcal/mol) but orientation III is significantly higher (2.2 kcal/mol). The presence of a methyl group in the 1β-position in meropenem (instead of a 1β-proton in imipenem) may explain the relatively higher penalty for orientation III, as in this orientation the 1β-substituent is located directly next to the 6α-hydroxyethyl moiety.</p><p>Previously, our QM/MM simulations indicated that Leu158 may play an important role in modulating active site hydration in the deacylation of ceftazidime by OXA-48-like enzymes. 36 The orientation of Leu158 also differed initially between the two OXA-48/carbapenem systems, as the Cβ -Cγ bond has rotated by 180° in the meropenem structure. To study if Leu158 has a similar effect on carbapenem hydrolysis as observed for ceftazidime, its rotamers were first investigated by measuring the χ1 dihedral (N-Cα-Cβ-Cγ) in MM MD simulations. The distribution of sampled rotamers is presented in Figure S4. After the heating phase, Leu158 essentially always rotates away from the crystallographic g-orientation (χ1 ≈ 290°) to the t orientation (χ1 ≈ 180°) to allow space for the 6α-hydroxyethyl moiety, which in turn also permits for two water molecules to form hydrogen bonds with Lys73:OQ1. As the cephalosporin scaffold lacks a functional group similar to the 6αhydroxyethyl group of carbapenems, typically bearing larger substituents in the β orientation at the equivalent 7-position, it is likely that Leu158 does not possess a similar role in carbapenem hydrolysis to that suggested for cephalosporins.</p><!><p>Because the interactions of the 6α-hydroxyethyl group in the active site have been suggested to play a role in modulating β-lactamase activity towards carbapenems, 32 deacylation free energy barriers were calculated separately for all three orientations of both imipenem and meropenem acylenzymes observed in MD simulations. Starting structures for US were chosen from the 200 ns MM MD simulations following two criteria: that a potential DW was at a suitable distance for nucleophilic attack, and the 6α-hydroxyethyl orientation was that desired. For orientations II and III, the sidechain dihedral was restrained close to the reference values to avoid the substrate changing between orientations during the reaction (no restraints were needed for I, as no sidechain rotation was observed during US). Overall barriers for deacylation were determined by combining sampling from three separate US calculations for each AC conformation (with different starting structures), with standard deviations calculated between the free energy barriers for individual US simulations (Table S3). More details of the US setup and analysis are available in the SI. Calculated deacylation free energy barriers for the ACs formed by imipenem and meropenem with the 6α-hydroxyethyl in each of the three orientations are shown in Figure 3. For all orientations, two barriers are shown, corresponding to two different hydration states around the general base.</p><p>The lower barrier (in colour) corresponds to a state with only one water molecule hydrogen bonded to Lys73:OQ2, and one or two waters hydrogen bonded to Lys73:OQ1 while the higher barrier corresponds to a state with two water molecules hydrogen bonded to both carboxylate oxygens (Figure 4, carboxylate oxygens labelled in Scheme 1). For all hydration states, the calculated barriers follow the same trend of I < II < III, i.e. the lowest barriers are calculated for orientation I.</p><p>Notably, the barriers are consistently underestimated due to the QM method used (DFTB2), as is generally found for this method for similar reactions. 42,43 This underestimation likely also causes an underestimation of the stability of the TI compared to the TS (see e.g. the small molecule benchmark calculations the SI section "Benchmarking"), but TI minima were still located in our free energy surfaces (likely due to stabilization by the enzyme environment). As the overall shape of the QM/MM PES is consistent when using DFTB2 or M06-2X/def2-TZVP as the QM method, it is reasonable to expect that the underestimation of TI stability with DFTB2 does not affect trends in reaction barriers (SI section "Benchmarking"). Taking into account an underestimation of ~8 kcal/mol, as indicated by comparison of DFTB2 to SCS-MP2/aug-cc-pVTZ (SI section "Benchmarking"), the lowest barriers are in good agreement with experiment (see further the section "Comparison with experimental data"). Importantly, we expect our protocol for obtaining free energy barriers using semi-empirical QM methods to be a reliable indicator of relative energetic trends between different enzyme active site conformations; we have demonstrated this previously in studies of deacylation of β-lactam acylenzymes for both class A (with meropenem) and D SBLs. 36,43 As discussed above and in ref. 36 , increased hydration around the proton-accepting Lys73:OQ1 impairs deacylation in ceftazidime hydrolysis. A similar phenomenon was observed for carbapenems, with the additional observation that hydration around the second carboxylate oxygen (Lys73:OQ2) also affects reactivity. In orientation I, the average number of hydrogen bonds Lys73:OQ1 accepts during the reaction is 2.4 (± 0.1 standard deviation, calculated from the US minimum free energy path trajectories), which aligns with OQ1 being hydrogen bonded to two water molecules, and partly to Trp157. The two subpopulations with different deacylation barriers arise from a change in hydration around Lys73:OQ2. For the lower barriers in Figure 3, the number of hydrogen bonds to OQ2 is 1.3 (± 0.1) and for the higher barriers 2.2 (±0.1) for orientation I. The lowest calculated deacylation barrier, 8.4 kcal/mol, is for imipenem in orientation I with one water molecule hydrogen bonded to OQ2 and two to OQ1 (Figure 4). The barrier increases by 2.0 kcal/mol when another solvent molecule donates a hydrogen bond to OQ2. For meropenem, the barrier is raised by 4.1 kcal/mol upon introduction of an additional water molecule close to OQ2.</p><p>The hydration effect around Lys73:OQ2 indicated here has an apparently smaller effect on the calculated barriers than that of hydration around Lys73:OQ1, since the presence of an additional water molecule hydrogen bonded to OQ1 raised the barrier for ceftazidime deacylation by approximately 5 kcal/mol. 36 Orientation II (corresponding to a dihedral angle of between 147°-192° depending on the structure and protein chain) is observed in most OXA-48:carbapenem AC crystal structures. In this orientation, no part of the 6α-hydroxyethyl moiety interacts with either the DW or with Lys73, so the antibiotic may possibly not interfere with the reactive atoms. However, calculated deacylation barriers are increased by 2.1 kcal/mol for imipenem, and by 2.4 kcal/mol for meropenem, when comparing orientation II against I (in which only one water molecule is hydrogen bonded to OQ2).</p><p>Having two water molecules donating hydrogen bonds to both OQ1 and OQ2 further raises the calculated barriers to 13.6 and 16.0 kcal/mol for imipenem and meropenem, respectively. Therefore, our simulations suggest that II is not the most deacylation-competent AC orientation.</p><p>Additionally, orientation II might hinder the positioning of the DW in the active site in proximity to the electrophilic acyl carbon. For 93% and 87%, respectively, of the simulation times for the imipenem and meropenem acylenzymes in orientation II, the distance between the AC electrophilic carbon and the closest water molecule falls beyond 4 Å (an arbitrary threshold distance for a feasible nucleophilic attack; Figure S5). This is likely due to the 6α-hydroxyethyl methyl group partly occupying the space in the binding pocket for the deacylating water molecule, and thereby forcing this water further away from the AC. This is reflected in deposited crystal structures, as a DW candidate that is suitably positioned for nucleophilic attack is not observed in any OXA-48/carbapenem complex. 1,[27][28][29][30] In a previous study (mainly based on molecular dynamics), orientation II was observed to obstruct the positioning of the DW in the active site. 32 Docquier et al. concluded that only a slight repositioning of the methyl group of the 6α-hydroxyethyl sidechain is needed to better accommodate a water molecule at a suitable distance for nucleophilic attack.</p><p>However, these conclusions are based on a single 10 ns MD simulation, which likely gives insufficient time to sample all available substrate orientations. Based on our MM MD simulations, as well as the calculated free energy barriers, orientation II is less likely to contribute to efficient deacylation of the carbapenem ACs. This is due both to an increase in energy required for deacylation, as well as to a lack of sampling of active site configurations that would be suitable for the AC carbonyl to undergo nucleophilic attack by an incoming water molecule.</p><p>The largest increase in energetics between the two hydration states is calculated for orientation III, where the barriers increase by 9.6 and 5.6 kcal/mol for imipenem and meropenem, respectively, when the hydration state is changed. For the lower barriers, OQ1 and O Q2 form on average 2.0 (± 0.1) and 1.4 (± 0.1) hydrogen bonds, respectively, for the imipenem and meropenem complexes, while for the higher barriers the equivalent numbers are 2.8 (± 0.1) and 2.1 (± 0.2, data not shown).</p><p>For the lower barriers, Leu158 has not (yet) rotated from the g-to the t rotamer (Figure S4), as the starting structures were chosen almost directly after the heating phase. The g-rotamer of Leu158 allows space only for the DW positioned near Lys73:OQ1, which was inserted into the active site in the starting model. Further, only one water molecule is donating a hydrogen bond to OQ2. Upon MD equilibration, Leu158 rotates, allowing for active site hydration to change to two water molecules hydrogen bonding to both carboxylate oxygens each. Subsequently, only the 'high barrier' hydration state is sampled. This explains the large increase in activation free energy when comparing the two hydration substates for orientation III, as two water molecules are located near Lys73, as opposed to only one water molecule close to Lys73:OQ2 (as for orientations I and II). Therefore, our simulations indicate that III is the AC orientation that is the least competent for deacylation for the equilibrated system (in which Leu158 has rotated). Experimentally, this AC orientation is seen in the crystal structure of OXA-48 with hydrolyzed, non-covalently bound imipenem (PDB ID 6PK0) 28 , where the hydroxyethyl hydroxyl donates a hydrogen bond to the newly-formed carboxylate group. In our MM MD simulations of the AC, the exchange between 6αhydroxyethyl dihedral orientations is frequent (indicating a low energy barrier). This is probably true also for the hydrolyzed antibiotic, suggesting that rotation of this moiety can occur postdeacylation.</p><p>Further analysis of the US trajectories reveals that hydration around Lys73:OQ2 correlates with the rotamer of Val120. Valine has three rotamers for the χ1 dihedral (N-Cα-Cβ-Cγ1): the g+ rotamer around 50°, t around 180°, and g-around 300° (Figure 4, Figure S6). In the starting structures for simulations, Val120 is in the t orientation for both carbapenems (for meropenem, partial occupancy for both t and g-rotamers was observed in the deposited structure, but only the t rotamer was used in the computational model building). 1 The rotameric state can switch to either g+ or g-during MD simulations (Figure S6). For the g+ rotamer, one of the methyl groups points directly towards Lys73, which only leaves space for a single water molecule next to Lys73:OQ2; this water is positioned to accept a hydrogen bond from Gln124 and to donate one to Lys73. Conversely, the t rotamer allows for a second water molecule to occupy the space between Lys73 and Val120, and this water molecule is able to donate hydrogen bonds to both Lys73:OQ2 and the Val120 backbone carbonyl. Val120 is part of motif II, which is formed by residues Ser118 -Val120 and is conserved across class D β-lactamases. 32 Together with Leu158, it forms the so-called 'deacylating water channel' in the vicinity of Lys73; this hydrophobic patch partly shields the active site from bulk solvent. 1 For other OXA enzymes, a similar water channel has been proposed to open upon substrate binding to allow for water ingress into the active site and therefore for efficient deacylation. 54,55 For OXA-48, previous comparison of apoenzyme and acylenzyme structures shows that substrate binding shifts Val120 and Leu158 only slightly, and that the water channel is more open than e.g. in OXA-23. 1 Access of water into the catalytic position next to the substrate and Lys73 is necessary for antibiotic hydrolysis, but as we indicate above, any additional solvent in the active site will impair reactivity. In OXA-48, it appears that Val120 (and the specific rotamers that it samples) is an important gateway residue controlling approach of bulk solvent to Lys73:OQ2. Our previous work (on ceftazidime hydrolysis in OXA-48-like enzymes) indicates that Leu158 modulates hydration around Lys73:OQ1. 36 Notably, Val120 is mutated to a leucine in OXA-519, a single point mutant of OXA-48; this mutation results in an increase in measured hydrolysis for some 1β-methyl carbapenems, such as meropenem and ertapenem, but decreased imipenemase activity. Compared to OXA-48, OXA-519 also increases the proportion of β-lactone reaction products, rather than conventionally formed ring-opened species, hydrolysis products of meropenem. 56 Further, the Val120Leu mutation increases both kcat and KM for meropenem, indicating opposite effects on binding and hydrolysis. 57 The exact effect of the Val120Leu mutation on carbapenem hydrolysis on the molecular level is therefore complex and remains to be determined.</p><!><p>As presented above, orientation I of the 6α-hydroxyethyl moiety is calculated to give the overall lowest deacylation free energy barriers for both carbapenems. The combined FESs for the hydration state with lower free energy barriers are presented in Figure S7 for all three substrate orientations. In this section, we focus further on orientation I and the 'reactive' active site configuration in which only one water molecule is hydrogen bonded to Lys73:OQ1, and two to Lys73:OQ2 (unless otherwise stated). For this AC conformation, two different hydrogen bonding arrangements in the active site are possible: the DW can donate a hydrogen bond to the 6αhydroxyethyl hydroxyl group (named configuration 1), or the hydroxyl group can donate a hydrogen bond to the DW (configuration 2), see Figure 4. In MM MD, configuration (1) is sampled for 87% and 86% of simulation time for imipenem and meropenem, respectively. In addition to donating a hydrogen bond to the DW as in (2), the 6α-hydroxyethyl hydroxyl group can also donate a hydrogen bond directly to Lys73:OQ1 if the DW is displaced. This orientation of the carbapenem 6α-hydroxyethyl group may be the relevant one for β-lactone formation, which has been characterized as a side product for OXA-48-catalysed carbapenem turnover, particularly of 1βmethyl carbapenems (such as meropenem). 56,58 The β-lactone product has been proposed to form via intramolecular cyclisation, where the hydroxyl group acts as a nucleophile and donates a proton to Lys73. If the reaction occurs without a bridging water molecule, i.e. by a direct proton transfer between -OH and Lys73, lactonization is most likely lower in energy in orientation I than in III, based on the trends observed for deacylation energetics.</p><p>For imipenem deacylation, both configurations (1) and (2) were observed in umbrella sampling. The lowest free energy barrier of 8.4 kcal/mol was calculated for configuration (1), and the barrier was increased by 2.0 kcal/mol for configuration (2). In addition to raising the free energy barriers, changing from (1) to (2) shifts the location of the transition state on the FES. For (1), the TS is located approximately at values -0.1 Å and 1.7 Å for the proton transfer and nucleophilic attack reaction coordinates, respectively (Figure 5, left). However, for (2), the TS location on the FES shifts to around -0.5 Å and 2.0 Å Figure S8). With active site configuration (2), the proton transfer has progressed further at the TS, whereas the approach of the DW oxygen to the acyl carbon is less advanced. This is potentially due to the additional hydrogen bond from the 6α-hydroxyethyl moiety hydroxyl decreasing the nucleophilicity of the DW, requiring the proton transfer reaction to have progressed further from the starting structure in the TS. Notably, a similar shift in the TS position on the FES is observed also in orientation III, where a water molecule is donating a hydrogen bond to the DW instead of the 6α-hydroxyethyl group (Figure S7). Mulliken charge analysis of the key QM atoms does not reveal many significant differences for the calculated charges along the reaction when comparing US calculations with either configuration (1) or (2) (Tables S5-S8). The main difference is observed at the TS, where for Lys73:OQ1 the charge is more positive and for DW:O the charge is more negative for configuration (2), as expected by the shift in the TS location towards the TI.</p><p>For meropenem, the lowest calculated deacylation barrier is 11.2 kcal/mol with an average of 2.4 (± 0.1) and 1.4 (± 0.0) hydrogen bonds accepted by K73:OQ1 and OQ2, respectively. This barrier is 2.8 kcal/mol higher than the lowest calculated barrier for imipenem, or 2.2 kcal/mol including the free energy penalty (derived from MM MD for imipenem) for orientation I. In contrast to imipenem, the hydroxyl of the 6α-hydroxyethyl moiety in meropenem always rotates during unrestrained US sampling to hydrogen bond configuration (2), donating a hydrogen bond to the DW. This rotation occurs before the TS is reached even when configuration (1) is present in the starting structure. Enforcing the donation of a hydrogen bond from DW to the 6α-hydroxyethyl -OH, i.e. restraining the reaction simulations to configuration (1), affects the location of the TS in a similar manner to that observed with imipenem. TS locations for configurations (1) and (2) are at -0.2/1.8 Å and -0.5/2.0 Å (proton transfer/nucleophilic attack), respectively. However, changing the hydrogen bonding pattern between configurations has only a minimal effect on the energetics, as the barrier for (1) is 11.9 kcal/mol. Therefore, the decrease in activation energy for configuration (1) vs. (2) does not follow the same trend for meropenem as it does for imipenem. Possible reasons for this may include the presence of a 1β-methyl group in meropenem, as this may hinder the rotation of the 6α-hydroxyethyl group to better optimise further hydrogen bonds between active site residues and water molecules nearby. Such hindrance of 6α-hydroxyethyl rotation may also explain the preference observed for configuration 2 as the DW approaches the acyl carbon. A water molecule lodged between Tyr211 and Thr213 accepts a hydrogen bond from the carbapenem -OH moiety in configuration (1) or donates a hydrogen bond to it in configuration (2) (Figure 5 and Figure S8). The 1β-methyl group occupies the space above this water and may therefore induce its displacement or the re-organization of the surrounding water molecules to optimise hydrogen bonds between them, which could subsequently lead to a change from configuration (1) to (2).</p><p>Additionally, the initial nucleophilic approach of the DW (from 3.5 Å to 2.2 Å) with the 6αhydroxyethyl moiety in orientation I and hydrogen bond configuration (1) is calculated to be slightly lower in energy for imipenem (Figure S9). The DW remains hydrogen bonded to the hydroxyethyl oxygen during this approach, with the average distance to the hydroxyethyl methyl carbon reducing to about 3.3 Å. Notably, the initial approach between the DW and the carbapenem is also slightly higher in energy in orientations II and III than in orientation I, which may contribute to their overall energetics being less favorable for deacylation. However, the reasons for the preference for the imipenem, but not the meropenem, complex to adopt configuration (1) during deacylation are likely subtle and can result from small structural changes between the active site, substrate, and solvent molecules.</p><!><p>Most of the variants in the OXA-48 family are carbapenemases, with elevated imipenem hydrolysis rates when compared against other carbapenems. 59 For OXA-48, experimental measurements of kcat values for imipenem hydrolysis vary between 1.5 and 22.5 s -1 , which can be converted to free energy barriers for activation (Δ ‡ G) of 15.7 to 17.3 kcal/mol, using the Eyring equation. For meropenem, the measured kcat values range between 0.07 -0.16 s -1 , which converts to barriers of 18.7-19.2 kcal/mol. Using these figures as experimental estimates of free energies of activation, the difference (ΔΔ ‡ G) between imipenem and meropenem hydrolysis is between 1.4-3.5 kcal/mol, which is approximately the same magnitude as the strength of a single hydrogen bond (1- 3 kcal/mol). 60 Hence, structural factors contributing to more efficient breakdown of imipenem, compared to 1β-methyl carbapenems, are most likely to be subtle. Our QM/MM simulations suggest that orientation I of the 6α-hydroxyethyl group is the most likely AC orientation to undergo deacylation, when this exists in a state with decreased hydration around Lys73:OQ2 (i.e., with only one water molecule donating a hydrogen bond to this carboxylate oxygen). When comparing the lowest free energy barriers calculated in orientation I for imipenem and meropenem (Figure 3), the difference (ΔΔ ‡ G) for the two substrates is 2.8 kcal/mol; including the free energy penalty for the imipenem 6α-hydroxyethyl moiety adopting orientation I (0.6 kcal/mol, as determined from our MM MD simulations), the obtained ΔΔ ‡ G value drops to 2.2 kcal/mol. This is in excellent agreement with the experimentally determined range of ΔΔ ‡ G values. This strongly supports our assumption that TI formation is the rate-limiting process for carbapenem hydrolysis by OXA-48, consistent with similar findings for ceftazidime breakdown by OXA-48-like enzymes 35 and carbapenem breakdown by a range of class A serine β-lactamases. 41,42 The agreement further implies that the difference between imipenem and meropenem deacylation in OXA-48 may indeed be caused by the subtle difference in the preferred hydrogen bonding patterns involving the DW and the 6α-hydroxyethyl sidechain reported here. In turn, the presence of the meropenem 1β-methyl group apparently contributes to this difference by influencing both the orientation of the 6αhydroxyethyl group and the organization of water molecules in the near vicinity. (We further note that the underestimation of the absolute barriers can be fully accounted for by comparison of DFTB2 to higher level QM calculations, which indicates DFTB2 underestimates barriers by ~6.3-8 kcal/mol, see Table S4 & Figure S11. Thus, combined with the free energy penalty of 0.6 kcal/mol noted above, the corrected lowest barriers would be 15.3-17.0 and 17.5-19.2 kcal/mol for imipenem and meropenem, respectively.) Based on our MD simulations, the carbapenem tail groups are highly flexible and are thus unlikely to directly affect deacylation efficiency. Differences in kcat (reflecting the rate-limiting deacylation step) for carbapenems might therefore be explained similarly to our findings here, with differences largely caused by the presence or absence of the 1 β-methyl group. This is consistent with experimental data for OXA-48, which show higher kcat values for imipenem and panipenem vs. 1β-methyl containing carbapenems. 32,61 Overall, our analysis of the effects of active site conformations on carbapenem hydrolysis activity highlights the importance of controlling water access to the active site. On the one hand, it is crucial for the enzyme active site to support the binding of the deacylating water (through the aforementioned water channel). On the other hand, partial desolvation of the catalytic base (carboxylated Lys73) is required for efficient reaction. Such intricate control of active site solvation is a common feature of enzyme activity. For example, in ketosteroid isomerase, additional water molecules hydrogen bonding to the catalytic aspartate raise the barrier of reaction significantly. 62 Notably, this increased solvation occurs through water molecules hydrogen bonding to the carboxylate oxygen that is not receiving the proton, similar to what is observed here (difference between high and low barriers in Figure 3), but different from what we observed for ceftazidime hydrolysis. 36 Such additional hydrogen bonding will decrease the pKa of the catalytic carboxylate base, [63][64][65] weakening its proton affinity and thereby leading to higher barriers for the reaction. To avoid or limit the occurrence of additional hydrogen bonding to catalytic bases, enzymes have evolved active site architectures that can promote desolvation to increase carboxylate reactivity. Such desolvation can for example be achieved by loop closure (as in triosephosphate isomerase and dihydrofolate reductase) 66,67 or closure of the substrate binding cleft (as in ketosteroid synthase).</p><p>Here, subtle control of the solvation around the carboxylated Lys73 is related to nearby hydrophobic residues (Val120 and Leu158), which can adopt conformations that allow the presence of the deacylating water but avoid more extensive solvation of the catalytic carboxylate.</p><!><p>We have modelled carbapenem hydrolysis by the OXA-48 β-lactamase using QM/MM reaction simulations. The deacylation reaction was modelled for two carbapenem substrates, imipenem and meropenem, to deduce the origin of the higher activity towards imipenem compared to other carbapenems. MM MD simulations of the acylenzyme complexes demonstrate that the carbapenem tail (C2) groups are able to adopt many different conformations. In contrast, the carbapenem 6α-hydroxyethyl group is able to rotate and to adopt three specific different orientations, where it either interacts with the DW (I), Lys73 (III), or is rotated so that the methyl group is oriented towards Leu158 (II). Subsequently, deacylation was modelled using QM/MM for both substrates in these three orientations to investigate the effect of orientation upon deacylation efficiency. Our calculated free energy barriers indicate that the most deacylation-competent orientation is I, where the hydroxyl group interacts with the DW, and that the orientation III has the highest free energy barriers.</p><p>Detailed comparison of the simulations revealed two factors that significantly affect the reaction energetics: hydration around Lys73, and the hydrogen bonding pattern between the DW and substrate, specifically the 6α-hydroxyethyl group. Hydration around the general base has been proposed to affect the predicted hydrolysis rates for other β-lactam substrates; 36 here, we show that this is affected by hydration around both Lys73 carboxylate oxygens (not only the oxygen participating in proton transfer). Increased hydration around the non-reactive oxygen (Lys73:OQ2) correlates with higher calculated barriers; in turn, the orientation of Val120 correlates with the number of water molecules near this oxygen. Another aspect influencing deacylation efficiency is the pattern of hydrogen bonds in the active site that involve the DW and the carbapenem 6αhydroxyethyl sidechain. Imipenem shows a preference for a configuration in which the DW donates hydrogen bonds to Lys73 and the 6α-hydroxyethyl hydroxyl group; the free energy barrier is higher when the hydroxyl group instead rotates to donate a hydrogen bond to the DW. This preference is not observed for meropenem: simulations with both hydrogen bond configurations have comparable energy barriers, which are similar to that calculated for imipenem in the less favorable orientation. Therefore, we can conclude that the difference between hydrolytic activities for the two carbapenem substrates stems from subtle differences in the active site hydrogen bonding patterns, which affect the reactivity of the DW. Furthermore, our results indicate that active site hydration is an important determinant of catalysis in OXA-48 enzymes: increasing hydration around the general base impairs carbapenem hydrolysis. Our study highlights the importance of detailed atomistic modelling in addition to experimental research to determine the exact origins of catalytic activity. Simulation protocols such as those employed here can extend information from crystallographic studies to enable investigation of the strength and dynamics of specific active site interactions during the catalytic cycle and directly investigate determinants of activity in situ.</p>

ChemRxiv

Importance of the bioenergetic reserve capacity in response to cardiomyocyte stress induced by 4-hydroxynonenal

SYNOPSIS Mitochondria play a critical role in mediating the cellular response to oxidants formed during acute and chronic cardiac dysfunction. It is widely assumed that, as cells are subject to stress, mitochondria are capable of drawing upon a \xe2\x80\x9creserve capacity\xe2\x80\x9d which is available to serve the increased energy demands for maintenance of organ function, cellular repair, or detoxification of reactive species. This hypothesis further implies that impairment or depletion of this putative reserve capacity ultimately leads to excessive protein damage and cell death. However, it has been difficult to fully evaluate this hypothesis since much of our information about the response of the mitochondrion to oxidative stress derives from studies on mitochondria isolated from their cellular context. Therefore, the goal of this study was to determine whether \xe2\x80\x9cbioenergetic reserve capacity\xe2\x80\x9d does indeed exist in the intact myocyte and whether it is utilized in response to stress induced by the pathologically relevant reactive lipid species 4-hydroxynonenal (HNE). We found that intact rat neonatal ventricular myocytes exhibit a substantial bioenergetic reserve capacity under basal conditions; however, on exposure to pathologically relevant concentrations of HNE, oxygen consumption was increased until this reserve capacity was depleted. Exhaustion of the reserve capacity by HNE treatment resulted in inhibition of respiration concomitant with protein modification and cell death. These data suggest that oxidized lipids could contribute to myocyte injury by decreasing the bioenergetic reserve capacity. Furthermore, these studies demonstrate the utility of measuring the bioenergetic reserve capacity for assessing or predicting the response of cells to stress.

importance_of_the_bioenergetic_reserve_capacity_in_response_to_cardiomyocyte_stress_induced_by_4-hyd

INTRODUCTION<!>Materials<!>Neonatal rat ventricular myocyte primary cultures<!>Bioenergetic measurements<!>Protein-HNE and GSH measurements<!>Cell death assays<!>Statistical analysis<!>Protein HNE adducts and cell death increase with HNE treatment<!>Effect of HNE on aerobic metabolism in intact neonatal cardiomyocytes<!>Effects of HNE on glycolysis<!>Identification of mitochondrial defects incurred by HNE<!>DISCUSSION<!>Measurement of bioenergetic parameters in myocytes using extracellular flux technology<!>HNE promotes protein damage and myocyte cell death<!>HNE increases oxygen consumption in isolated myocytes<!>HNE increases glycolytic rate in isolated myocytes<!>Changes in the mitochondrial and glycolytic profiles due to HNE treatment<!>Specific defects in mitochondrial function caused by HNE

<p>Defining the role of mitochondria in various cardiovascular pathologies is currently an area of great interest, with many studies focusing on the properties of the organelle isolated from diseased or stressed cardiac cells. These studies now point to the importance of understanding how changes in isolated mitochondria translate to changes in bioenergetic events that take place in the myocardium during ischemia-reperfusion and heart failure. Cardiac tissue is rich in mitochondria, which are capable of dynamically responding to energy demand for increased work. This oxidative phenotype allows for rapid and substantial ATP production for cardiac function. It is clear from experiments using 31P NMR that, even under an increased work load in the physiological range, mitochondria appear to have a substantial "reserve capacity" which is depleted under conditions of severe stress such as pressure overload or ischemia [1, 2]. However, this concept has proved technically difficult to examine using direct indices of mitochondrial function in intact myocytes.</p><p>Data from mitochondria isolated from hearts subject to stress typically show changes in the activity of the respiratory chain, but the functional impact remains unclear once the organelles are removed from their cellular context [3, 4]. It is frequently the case that the activity of respiratory chain complexes of isolated mitochondria such as complex I are decreased in the diseased heart [5, 6]. It is challenging to extend these changes to the cellular setting since the control over metabolism is lost in isolated mitochondria. For example, it is known that the maximal capacity for oxidative phosphorylation is higher than that used under normal conditions [2]. This raises the question of the role of this reserve capacity and leads to the hypothesis that it is required by cells to respond to stress and that pathological events occur when this bioenergetic reserve is depleted.</p><p>The requirement of the reserve capacity for the response to stress, such as occurs in the ischemic and failing heart, has not been examined in intact cardiovascular cells or tissues. Since the diseased heart is associated with increased oxidative stress, exposure of cells to reactive species generated during pathology can be used as a model of pathology and to test the role of oxidative stress in myocyte dysfunction. The significance of these reactive species is evidenced by studies showing that overexpression of antioxidant enzymes such as Mn-superoxide dismutase (SOD) [7], catalase [8], extracellular-SOD [9], or glutathione peroxidase [10] protects the heart from ischemia-reperfusion injury. Moreover, partial deficiency of Mn-SOD [11] or the complete absence of glutathione peroxidase [12] or CuZn-SOD [13] renders the heart more sensitive to injury. Interestingly, volume and pressure overload [14–16] as well as ischemia [17, 18] result in an increased ability of myocytes to consume oxygen, which might suggest a mechanism for further depletion of the bioenergetic reserve capacity in an environment where oxygen availability may be already limiting.</p><p>Secondary products of oxidative stress such as 4-hydroxynonenal (HNE) are normally detoxified by energy requiring processes; however, under pathological conditions, these detoxification pathways fail leading to accumulation of oxidized lipids [19] that can damage key proteins in the mitochondrial respiratory chain. In humans and animal models, downstream products of oxidative stress such as oxidized lipids are abundant in the ischemic [19, 20] and failing heart [21, 22]. Therefore, the generation of lipid peroxidation products capable of reacting with cellular nucleophiles could be primary instigators of tissue injury [23]. The α,β-unsaturated aldehydes (e.g., HNE) are likely to be the most significant because they modify proteins which affect energy production [24–30] and cell death pathways [31, 32]. This is corroborated by studies showing that activation of a key enzyme required for the mitochondrial detoxification of HNE [19] protects the heart from injury [33, 34].</p><p>These findings raise two important questions: 1) Does bioenergetic reserve capacity exist in cardiac myocytes and 2) Does it modulate the response to stress associated pathology? The recent availability of technology which allows the non-invasive measurement of mitochondrial respiration and glycolysis offers the opportunity to address these questions. Therefore, we hypothesized that maintenance of mitochondrial function and the availability of a bioenergetic reserve capacity is critical to combat oxidative stress and that, when exceeded, protein damage and cell death occurs. To test this hypothesis, we used an emerging technology, high-throughput extracellular flux (XF) analysis, to quantify the bioenergetic changes that occur in intact cardiac myocytes exposed to HNE. By measuring XF, we were able to measure oxygen consumption and proton production, indicative of oxidative phosphorylation and glycolysis, respectively, in intact rat neonatal ventricular myocytes exposed to HNE.</p><p>Our data support the hypothesis that pathologically relevant concentrations of oxidized lipids exhaust the reserve capacity of mitochondria. When this capacity is depleted, cellular injury occurs accompanied by decreased mitochondrial oxygen consumption, decreased efficiency due to proton leak, and increased protein-HNE adduct formation. These results directly demonstrate the presence of a bioenergetic reserve capacity in intact myocytes. Furthermore, these findings suggest that oxidized lipids such as HNE, which accumulate in the heart during ischemia and heart failure, could cause, accelerate, or worsen myocardial injury by diminishing this reserve capacity.</p><!><p>Reagent HNE was obtained from Calbiochem (San Diego, CA). All materials and reagents for the Extracellular Flux assays were from Seahorse Biosciences (North Billerica, MA). Nonanal, oligomycin, thiazoyl blue tetrazolium, carbonyl cyanide p-[trifluoromethoxy]-phenyl-hydrazone (FCCP), and antimycin A were from Sigma (St. Louis, MO). Secondary HRP-linked antibodies and antibodies against actin were from Cell Signaling (Danvers, MA). Anti-protein HNE antibodies were a gift from Dr. Sanjay Srivastava at the University of Louisville. ECL plus reagents were from GE Healthcare (Pittsburgh, PA).</p><!><p>All animal experiments were approved by the University of Alabama Institutional Animal Care and Use Committee and conformed to the Guide for the Care and Use of Laboratory Animals, published by the National Institutes of Health (NIH Publication No. 85-23, Revised 1996). Primary cultures of neonatal rat ventricular myocytes (NRVM) were obtained from 2- to 3-day-old neonatal Sprague-Dawley rats and were cultured as described previously [35]. NRVM were seeded at 75,000 cells/well in collagen-coated Seahorse Bioscience V7 culture plates in growth medium containing 15% fetal bovine serum (FBS) on the first day. On the next day, medium was replaced, and cells were grown in the culture growth medium without FBS. Within 1–2 days of isolation, a confluent monolayer of spontaneously beating NRVM formed, and cells were used as described below.</p><!><p>An XF24 Analyzer (Seahorse Biosciences, North Billerica MA) was used to measure bioenergetic function in intact NRVM. The XF24 creates a transient, 7 μl chamber in specialized microplates that allows for oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) or proton production rate (PPR) to be monitored in real time [36]. For all bioenergetic measurements, the culture media was changed 1 h prior to the assay run to unbuffered Dulbecco's Modified Eagle Medium (DMEM, pH 7.4) supplemented with 4 mM L-glutamine (Gibco, Carlsbad, CA). First, the optimum number of cells needed for these experiments was determined. NRVM were seeded to a density of 25,000, 50,000, or 75,000 cells/well. Oxygen consumption in these cells was linear with respect to cell number within this range (Fig. 1A), and a seeding density of 75,000 cells/well was chosen for the remainder of the experiments.</p><p>Next, an assay was developed to measure indices of mitochondrial function. Oligomycin, FCCP, and antimycin A were injected sequentially through ports in the Seahorse Flux Pak cartridges to final concentrations of 1 μg/ml, 1 μM, and 10 μM, respectively. This allowed determination of the basal level of oxygen consumption, the amount of oxygen consumption linked to ATP production, the level of non-ATP linked oxygen consumption (proton leak), the maximal respiration capacity, and the non-mitochondrial oxygen consumption. As shown in Fig. 1B, three basal OCR measurements were recorded prior to injection of oligomycin. After mixing and recording the oligomycin-sensitive OCR, FCCP was injected and another OCR measurement was recorded. The OCR measured after FCCP injection represents the maximal capacity that cells have to reduce oxygen under the experimental conditions. Finally, antimycin A was injected to inhibit the flux of electrons through complex III, and thus no oxygen is further consumed at cytochrome c oxidase. The remaining OCR determined after this treatment is primarily non-mitochondrial and could be due to cytosolic oxidase enzymes.</p><!><p>Protein-HNE adducts were detected using a polyclonal anti-protein HNE antibody, as described in [37]. Briefly, cells were lysed in the 24-well XF plates using 20 μl/well of lysis buffer containing 20 mM HEPES, 1 mM DTPA, 1% NP-40, 0.1% SDS, and protease inhibitor cocktail. The lysates were then added to SDS Laemmli Buffer, and the proteins were separated on 10% SDS polyacrylamide gels. After transfer to PVDF membranes, HNE-modified proteins were detected using anti-protein-HNE primary and HRP-linked anti-rabbit secondary antibodies by chemifluorescence on a Typhoon Variable Mode Imager (GE Healthcare, Pittsburgh, PA). Relative levels of protein-HNE adducts were quantified by densitometry using ImageQuantTL software (GE Healthcare, Pittsburgh, PA). Total GSH (GSH+GSSG) was measured in cell lysates with and without treatment with HNE using the Tietze recycling assay [38].</p><!><p>Cell viability was measured by MTT assay as described previously [39], with the following modifications. NRVM were seeded as described above into V7 culture plates at 75,000 cells/well. At 8 and 16 h after HNE treatment, the assay media was replaced with media containing 0.4 mg/ml thiazoyl blue tetrazolium. The cells were allowed to incubate in a non-CO2 incubator at 37°C for an additional 2 h. The media was removed, and the resulting formazan crystals were solubilized in 250 μl DMSO. The absorbance was read at 550 nm and the data expressed as a percentage of control.</p><!><p>Data are reported as means ± SEM. Comparisons between two groups were performed with unpaired Student's t-tests. Comparisons among multiple groups or between two groups at multiple time-points were performed by either one-way or two-way analysis of variance, as appropriate. A p value of less than 0.05 was considered statistically significant.</p><!><p>NRVM were seeded at 75,000 cells/well and then treated with either HNE or the non-electrophilic C9 lipid analog of HNE, nonanal, for 2 h. For these experiments, we used concentrations of HNE that have been shown to occur in the ischemic and failing heart [19, 21, 40, 41]. The cells were harvested and proteins were separated by SDS-PAGE followed by Western blotting with anti-protein-HNE antibodies. As shown in Fig. 2A and B, HNE adducts accumulated in a concentration-dependent manner. The non-protein reactive analog of HNE, nonanal, was used as a structural control and did not promote the formation of protein-HNE adducts. Additionally, cell death as a result of the HNE treatment was examined at 8 and 16 h by the MTT assay. HNE exhibited both a concentration and time dependent effect on NRVM viability (Fig. 2C). HNE can be metabolized by a number of enzymes in the cell including the glutathione (GSH) dependent S-transferases [19, 42]. Accordingly, we measured total GSH (GSH + GSSG) levels in the lysates of cells treated with HNE for 90 min (Fig. 2D). As anticipated HNE treatment depletes GSH and this was maximal at the lowest concentration of HNE tested.</p><!><p>To determine if bioenergetic derangements preceded cell death due to HNE, we assessed oxygen consumption in NRVM treated under the same conditions as shown in Fig. 2. After basal oxygen consumption measurements, HNE was injected to give final concentrations of 0–30 μM. Control wells received vehicle (ethanol) or the structural control for HNE, nonanal (10 μM), in DMEM. As shown in Fig. 3A and B, HNE initially increased OCR in a concentration dependent manner. Myocytes treated with the lowest concentration of HNE tested (5 μM) resulted in a steady increase in the rate of mitochondrial oxygen consumption which plateaued after approximately 150 min of HNE exposure. Exposure to higher concentrations of HNE (10–30 μM) resulted in a maximal OCR that declined thereafter. Apparent maximal increases in OCR were reached with 10, 20, and 30 μM HNE approximately 130, 70, and 35 min after injection, respectively. Interestingly, the rate of increase in OCR (i.e., the slope of the initial stimulation of OCR by HNE) increased linearly with HNE concentration (Fig. 3B). Nonanal was used as a structural control for non-electrophilic effects of HNE and did not affect oxygen consumption by the myocytes (data not shown).</p><p>To quantify the overall increase in the amount of oxygen consumed by the myocytes due to each treatment, the OCR area under the curve for each group was calculated by multiplying the group average by the time interval for that rate and subtracting the baseline rate. The resulting value can be expressed in pmoles of oxygen consumed during the assay after injection of vehicle, nonanal, or HNE. As shown in Fig. 3C, exposure of the myocytes to HNE at 0–20 μM concentrations resulted in up to approximately 20 nmoles of oxygen consumed during the course of the experiment. The highest concentration of HNE used, i.e., 30 μM, showed no overall increase in oxygen consumption. At this concentration, OCR increased transiently, followed by a rapid decrease in oxygen consumption that was well below baseline (Fig. 3A).</p><!><p>In addition to OCR, the XF assay also allowed the measurement of protons that were produced by the cells, which reflects lactate production and is therefore an index of glycolysis [36, 43]. Figure 4A shows the extracellular acidification rate (ECAR) profile of control myocytes and myocytes treated with 0–30 μM HNE. Similar to OCR, HNE increased the ECAR in a concentration and time-dependent manner. Analogous to the OCR results (Fig. 3A), ECAR showed a biphasic response in the 10 and 20 μM HNE groups, indicating severe damage to bioenergetic components at later time points. As shown in Fig. 4B, the initial rate of increase in ECAR was linear and dependent on HNE concentration. Similar to that shown for OCR in Fig. 3C, the area under the curve of the proton production rate (PPR) was calculated to determine the overall increase in proton production over the time course of the experiment. HNE treatment resulted in an increase in proton production, indicative of an increase in glycolysis, over the course of the experiment (Fig. 4C). The maximal rate of proton production occurred in cells treated with 7.5–10 μM HNE.</p><!><p>Approximately 70 min after HNE addition (indicated by the dotted line in Fig. 5B), the ECAR and OCR were used to obtain a "metabolic image" of the cells in each treatment group. The image is divided in four quadrants, which relate the relative activities of the glycolytic and aerobic metabolism in response to HNE. As shown in Fig. 5A, HNE concentration-dependently stimulates both glycolysis and the aerobic consumption of oxygen, consistent with an increased energy demand of the cells as they respond to this stress.</p><p>To determine the specific mitochondrial derangements that occur in response to HNE, we used the mitochondrial function assay described in Fig 1B. For these experiments, myocytes treated with HNE to final concentrations of 0–20 μM were exposed to oligomycin, FCCP, and antimycin A at the timepoints indicated (Fig. 5B). The measurements taken after each injection were used to calculate the ATP-linked OCR, proton leak, reserve capacity, and non-mitochondrial OCR at 2h after the addition of HNE. As shown in Fig. 6A, OCR was stimulated in response to HNE by 263.1 ± 22.5 pmol/min above the baseline levels. On the addition of oligomycin, Fig 6B shows that the oligomycin-insensitive OCR in the presence of HNE increased significantly by up to 2.5-fold. To determine the individual parameters of mitochondrial function, the data shown in Fig. 5B were analyzed as described in Fig. 1. Proton leak was increased as by HNE in a concentration-dependent manner. Interestingly, the rate of ATP-linked oxygen consumption showed a biphasic response (Fig. 6D), where it increased by approximately 3-fold at the 10 μM HNE and decreased at 20 μM. These results suggest that HNE increases OCR both by increasing proton leak (thereby decreasing mitochondrial efficiency) and by increasing energy demand.</p><p>Next, the maximal respiratory rate was determined from the FCCP-stimulated rate. As shown in Fig. 5B, HNE at 0–10 μM concentrations had no effect on this maximal respiratory rate. However, concentrations of HNE in excess of 10 μM resulted in inhibition of oxygen consumption even after FCCP addition, suggesting overt damage to mitochondrial respiratory complexes (Fig. 5B). The reserve capacity was calculated based on the OCR immediately prior to oligomycin addition and the maximal respiratory rate. As shown in Fig. 6E, HNE decreased the mitochondrial reserve capacity in a concentration-dependent manner consistent with damage to the respiratory chain associated with increased protein adducts (Fig. 2A). The rate of oxygen consumption due to non-mitochondrial sources was determined in the presence of HNE using antimycin A and was unchanged (Fig. 5B, 6F).</p><!><p>Using extracellular flux analyses, we evaluated the effects of the electrophilic lipid HNE on bioenergetic function in intact myocytes. We show for the first time that oxidized lipids, at concentrations that accumulate under pathophysiological conditions in the heart, increase cardiomyocyte oxygen consumption and deplete the bioenergetic reserve capacity. We found that HNE stimulated the rate of cellular oxygen consumption in a concentration-dependent manner. This increase in oxygen consumption was due to both increased bioenergetic demand placed on the cardiac myocytes and decreased mitochondrial efficiency (i.e., proton leak). Glycolytic flux was also increased in response to HNE treatment, underscoring the integrated nature of the metabolic response to energy demand and expenditure in the presence of reactive lipid species. The HNE-induced increase in oxygen consumption was not compensated by an increase in the maximal respiratory capacity of the myocytes; consequently, HNE treatment resulted in depletion of the bioenergetic reserve capacity, overt respiratory failure, and cell death.</p><p>In the heart, mitochondria make up at least 20% of the myocyte volume [44, 45] and provide the unremitting energy required for contraction. Aerobic respiration is therefore indispensable to sustain cardiac function and viability. At rest, the heart consumes up to 0.15 ml O2/min/g tissue, which increases several fold with vigorous exercise by calling upon the reserve capacity of the mitochondria and glycolysis [46]. Interestingly, the diseased heart requires more oxygen to meet energy needs, which has led to the hypothesis that a state of energy starvation may underlie myocardial pathology [47]. In support of this concept, myocardial oxygen uptake is increased 2-fold in patients with left ventricular hypertrophy over normal subjects [14]; there is also an increase in the myocardial uptake of oxygen in experimental hypertrophy, congestive heart failure, and diabetes [15, 16, 48]. Furthermore, the postischemic heart uses more oxygen than the preischemic heart [18], and myocytes subjected to hypoxia-reoxygenation have an increased demand for oxygen [17]. It is reasonable to conclude, therefore, that bioenergetic dysfunction and the imbalance of oxygen supply versus demand is a basic defect in myocardial pathologies. However, the mechanisms underlying this increased demand for oxygen in the diseased heart are unknown. Increased tissue levels of reactive species such as HNE are associated with both acute and chronic cardiac disease [19–21, 41]. If, as shown here, such reactive species increase the rate of oxygen consumption and bioenergetic reserve capacity in the diseased heart, this could account for the contractile dysfunction associated with pathology.</p><p>While the idea that ROS play a fundamental role in cardiovascular disease is well accepted, the molecular mechanisms by which oxidative stress cause cardiac injury are not well defined. ROS can damage cellular components by direct oxidation; however, given the susceptibility of polyunsaturated fatty acids to oxidative attack, there is a strong rationale for invoking the involvement of secondary products of lipid oxidation such as HNE and acrolein in ROS-related injury. Indeed, adducts of such oxidized lipids with proteins have been detected in the diseased heart [19, 20, 28, 30, 41, 49–51] and myocytes exposed to similar compounds capable of modifying proteins promote a phenotype akin to myocardial stunning [52]. It remains unclear, however, whether oxidized lipids or their protein adducts are footprints of unquenched free radicals or if they indeed cause derangements in signaling or bioenergetics.</p><p>Recent studies showing that activation of enzymes critical for HNE detoxification protects the heart from ischemic injury suggest that electrophiles are significant contributors to myocardial damage [33, 34]. Many studies have shown that HNE damages electron transport chain complexes [3, 25–30], affecting both respiration and critical events such as calcium-induced permeability transition [32, 53]. These studies, however, were limited by their usage of isolated mitochondrial preparations. While useful for understanding putative defects caused by HNE, experiments with isolated mitochondria are generally performed under saturating substrate conditions and are outside their normal intracellular environment. This removes all influence of cell signaling, ion fluxes, and changes in intracellular substrate metabolism (e.g., glycolysis) on bioenergetic regulation. In contrast to the HNE-induced increase in oxygen consumption found here, most studies to date report that HNE primarily inhibits mitochondrial respiration. This is likely due to the fact that the majority of studies have assessed HNE-induced changes in respiration using isolated mitochondrial preparations [19, 25–27].</p><p>Here, we demonstrate that HNE increases oxygen consumption and bioenergetic demand and decreases mitochondrial efficiency (Figs. 3 – 6). These findings suggest that oxidized lipids contribute to myocardial injury by promoting an energy crisis. In support of this concept, we show that HNE at lower concentrations initially increased the OCR (Fig. 3), which was due to both increased proton leak and bioenergetic demand (Fig. 6). Using the process described in Fig. 1 we can assess the impact of HNE on key bioenergetic parameters in the cell. We have assumed for the purposes of this calculation that the oligomycin-insensitive OCR is attributable to proton leak in the basal condition. However, this is not strictly correct since oligomycin has been shown to increase mitochondrial membrane potential and the resulting OCR is likely to be an upper estimate of the contribution from proton leak. While the oligomycin-dependent hyperpolarization has no impact on the conclusion that HNE has increased proton leak (Fig. 6C), it will affect the value of the OCR which we attribute to ATP synthesis primarily through an underestimation of this parameter. Nevertheless, it is clear that a significant portion of the stimulation of the basal OCR was due to increased bioenergetic demand. The increased proton leak across the inner mitochondrial membrane may be mediated by uncoupling proteins or leakage through damaged respiratory complexes. In support of this, studies using isolated mitochondria have shown that HNE promotes uncoupling and mitochondrial proton leak [24, 54].</p><p>The biphasic nature of the HNE-induced changes in oxygen consumption (Figs. 3A and 5B) suggest at least two factors contributing to the effects of HNE. Initially, HNE increased the oxygen consumption rate in a concentration-dependent manner (Fig. 3B). We propose that this is an initial adaptive response to cellular stress induced by HNE and does not involve damage to the respiratory chain. The second phase, where the OCR decreased at the higher concentrations of HNE, is likely due to damage to respiratory complexes. Another possibility is that endogenous substrates became limiting as OCR increased. This is unlikely since 20 and 30 μM HNE, which quickly reached a peak respiratory capacity in the cells (Figs. 3A), resulted in a lower overall consumption of oxygen compared with myocytes treated with 5 and 10 μM HNE (Fig. 3C) and decreased the ability of the cells to respire maximally when treated with the uncoupler, FCCP (Fig. 5B). Furthermore, the concentrations of HNE that caused a transient breach of the reserve capacity (i.e., 10–30 μM HNE) were associated with substantially increased protein-HNE adducts, and this resulted in complete cell death (Fig. 2A and 2B). As anticipated GSH was rapidly depleted by HNE and was maximal at the lowest concentration of HNE tested. Since the major bioenergetic changes induced by HNE occurred without a significant change in these repressed GSH levels it is unlikely that GSH depletion plays a major role in the HNE-dependent bioenergetic dysfunction reported here. From these data, therefore, it is likely that extensive formation of protein-HNE adducts caused damage to respiratory complexes that resulted in inhibition of electron transport.</p><p>As discussed above, HNE levels are substantially increased in multiple myocardial pathologies [19–21, 41, 51], suggesting that HNE promotes tissue damage and dysfunction by decreasing the bioenergetic reserve capacity. Interestingly, myocardial oxygen consumption in the pressure-overloaded heart is increased to the maximal dinitrophenol-stimulated rate during high workloads produced by catecholamine infusion [2], suggesting that reserve capacity is depleted in the diseased heart under conditions of stress. This is particular interesting since even low dose catecholamine treatment promotes lipid peroxidation and the formation of protein-HNE adducts [22, 51]. While of particular relevance to cardiovascular disease, reduced bioenergetic reserve capacity has also been recognized in neurodegeneration. Specifically, reduction of the spare respiratory capacity has been shown to regulate glutamate excitotoxicity in neurons [55, 56]. Those studies suggested that dysfunction occurs when the ATP demand exceeds the maximal ATP supply put forth by glycolysis and oxidative phosphorylation, thereby implicating the spare respiratory capacity critical for maintaining ATP generation under conditions of increased demand [57]. Similarly, we show that the ability of cardiomyocyte mitochondria to respire collapses when the maximal reserve capacity is depleted due to the increase in oxygen consumption by HNE (Fig. 6C).</p><p>Taken as a whole, these data support the view that products of lipid peroxidation, in the concentration range reported under pathological conditions, contribute to myocardial injury by promoting bioenergetic stress. By evaluating mitochondrial function in intact cells, our findings reveal for the first time a dynamic response of cardiomyocytes to HNE, where oxygen consumption is increased through increased energy demand as well as via non-ATP-linked oxygen sinks (i.e., proton leak). Furthermore, these studies provide insight into a fundamental mechanism critical to the evolution of myocyte injury, namely the oxidized lipid-induced increase in oxygen consumption and depletion of the bioenergetic reserve capacity. Consequently, these findings have implications not only for our understanding of the pathophysiological processes underlying cardiac disease, but also in other disease states associated with increased oxidative stress.</p><!><p>Oxygen consumption rate (OCR) from isolated neonatal rat ventricular myocytes (NRVM): (A) NRVM were seeded at 25,000–75,000 cells/well and the oxygen consumption rate (OCR) was measured. y=0.0027x – 25.244, R2 = 0.99. (B) In situ mitochondrial function assay: After three baseline OCR measurements, oligomycin (1 μg/ml), FCCP (1 μM), and antimycin A (10 μM) are injected sequentially with OCR measurements recorded after each injection. ATP-linked oxygen consumption (ATP) and the OCR due to proton leak (leak) can be calculated using the basal and the oligomycin-sensitive rate. Injection of the uncoupling agent, FCCP, is then used to determine the maximal respiratory capacity. Lastly, injection of antimycin A allows for the measurement of non-mitochondrial oxygen consumption. The reserve capacity is calculated by subtracting the maximal rate of oxygen consumption by the pre-oligomycin rate.</p><!><p>NRVM were treated with the indicated concentrations of HNE or nonanal for 90 min for measurement of protein-HNE adducts or for 8 and 16 h for cell death assay. (A) Western blots of HNE-modified proteins: After treatment with the indicated concentrations of HNE, myocytes were lysed, and protein-HNE adducts were detected by immunoblotting. Actin was used as a normalization control for Western blotting experiments, and nonanal was used as a non-electrophilic analog control for HNE. (B) Relative quantification of protein-HNE modifications: Protein-HNE antibody immunoreactivity was quantified by densitometry, and the fold change of immunoreactivity over non-treated cells was plotted as a function of HNE concentration; y=1.4127x – 0.1261, R2=0.99. (C) Cell death assay of HNE-treated myocytes: NRVM were exposed to 0–30 μM HNE for 8h (■) and 16h (□), followed by measurement of cell death by MTT assay. The inset shows the micrograph of the control and HNE treated cells (magnification 10 x). D) Total GSH content was measured in NRVM cell lysates exposed to 0–20μM HNE for 90 min. Data are expressed as the nmol GSH/mg protein. All data shown are means ± sem, n≥3; *p<0.01 vs. non-HNE treated myocytes from each time point.</p><!><p>Oxygen consumption rate (OCR) plots from myocytes exposed to 0–30 μM HNE: (A) The basal OCR was measured followed by addition of 0 (filled squares, solid line), 5 (open squares, solid line), 10 (filled squares, dashed line), 20 (open squares, dashed line, and 30 μM HNE (closed squares, dotted line), as indicated by the arrow. The rate of oxygen consumption was then measured for the indicated time. The OCR values are shown as the percent of baseline for each group. For visual clarity, statistical indicators were omitted from the graph. (B) The slope of the initial increase in OCR due to HNE treatment was then measured and plotted as the rate of OCR increase; y=0.1065x + 0.1283, R2=0.99. (C) Area under the curve analyses were used to determine the overall amount of oxygen consumed with each treatment. In panels A–C, data shown are means ± SEM, n≥3. *p<0.05 vs. cells not treated with HNE; #p<0.05 vs. cells treated with 5–10 μM HNE.</p><!><p>Measurements of proton production from myocytes exposed to 0–30 μM HNE: (A) The basal extracellular acidification rate (ECAR) was measured followed by addition of 0 (filled squares, solid line), 5 (open squares, solid line), 10 (filled squares, dashed line), and 20 μM HNE (open squares, dashed line), as indicated by the arrow. The rates of extracellular acidification, indicative of changes in glycolytic flux, were then measured for the indicated time. For visual clarity, the 30 μM HNE group and statistical indicators were omitted from the graph. (B) The slope of the initial increase in ECAR due to HNE treatment was then measured and plotted as the rate of ECAR increase; y=0.0534x + 0.2751, R2=0.97. (C) Area under the curve analyses of the proton production rate were used to determine the overall amount of protons produced with each treatment. In panels A–C, data shown are means ± SEM, n≥3. *p<0.05 vs. cells not treated with HNE; #p<0.05 vs. cells treated with 7.5 and 10 μM HNE.</p><!><p>(A) Metabolic profile of the stimulatory effect of HNE on aerobic and anaerobic respiration: The OCR and ECAR were plotted against one another at the time where OCR was increased to the greatest extent in cells treated with 20 μM HNE (from experiment in panel B – dotted line at ~80 min timepoint). (B) After measurement of the basal OCR, HNE was injected to 0 (filled squares, solid line), 5 (open squares, solid line), 10 (filled squares, dashed line), and 20 μM (open squares, dashed line) final concentrations as indicated. Mitochondrial function assay was then performed by sequential injections of oligomycin, FCCP, and antimycin A to determine the level of proton leak and ATP-linked oxygen consumption, the maximal OCR, and the non-mitochondrial OCR, respectively. Data in panels A and B are means ± SEM, n≥3. *p<0.05 vs. cells not treated with HNE; #p<0.05 vs. cells treated with 5 μM HNE; @p<0.05 vs. cells treated with 5–10 μM HNE.</p><!><p>The HNE-induced changes in the following parameters derived from the data in Figure 5 are shown: (A) The HNE–dependent change in OCR relative to the initial basal OCR assessed immediately before the addition of oligomycin (B) the HNE-dependent change in the Oligomycin-insensitive OCR (C) The OCR ascribed to proton leak (D) The OCR ascribed to ATP-synthesis (E) bioenergetic reserve capacity, and (F) the non-mitochondrial OCR. Data represent means ± SEM. N ≥ 3/group. *p<0.05 vs. myocytes not treated with HNE.</p>

PubMed Author Manuscript

N7 Methylation Alters Hydrogen Bonding Patterns of Guanine in Duplex DNA

N7-Alkyl-2\xe2\x80\xb2-deoxyguanosines are major adducts in DNA that are generated by various alkylating mutagens and drugs. However, the effect of the N7-alkylation on the hydrogen bonding patterns of the guanine remains poorly understood. We prepared N7-methyl-2\xe2\x80\xb2-deoxyguanosine (N7mdG)-containing DNA using a transition-state destabilization strategy, developed a novel pol\xce\xb2-host-guest-complex system and determined eight crystal structures of N7mdG or dG paired with dC, dT, dG, and dA. The structures of N7mdG:dC and N7mdG:dG are very similar to those of dG:dC and dG:dG, respectively, indicating the involvement of the keto tautomeric form of N7mdG in the base pairings with dC and dG. On the other hand, the structure of N7mdG:dT shows that the mispair forms three hydrogen bonds and adopts a Watson-Crick-like geometry rather than a wobble geometry, suggesting that the enol tautomeric form of N7mdG involves in its base pairing with dT. In addition, N7mdG:dA adopts a novel shifted anti:syn base pair presumably via the enol tautomeric form of N7mdG. The pol\xce\xb2-host-guest-complex structures reveal that guanine-N7 methylation changes the hydrogen bonding patterns of the guanine when paired with dT or dA and suggest that N7 alkylation may alter the base pairing patterns of guanine by promoting the formation of the rare enol tautomeric form of guanine.

n7_methylation_alters_hydrogen_bonding_patterns_of_guanine_in_duplex_dna

<p>A large number of alkylating anticancer agents and mutagens such as the nitrogen mustards, azinomycins, leinamycin, styrene oxide and aflatoxin B1 attack the N7 of guanine, the most nucleophilic atom within DNA, to primarily generate N7-alkyl-2′-deoxyguanosines (N7-alkyl-dG).1,2 The positively charged N7-alkyl-dG has a half life of several hours to days in duplex DNA and can undergo spontaneous depurination to produce abasic sites, which can induce G to T transversion mutations and interstrand cross-links.3–5 In addition, N7-alkyl-dG can undergo imidazole ring opening to give alkyl-formamidopyrimidine lesions, which are highly mutagenic.6,7 Although N7-alkyl-dG has an unmodified Watson-Crick edge, it could affect the base pairing properties of guanine via its electronic and steric effects, thereby inducing mutagenesis. For example, the N7-dG adducts of the acridine half-mustard ICR-191 and aflatoxin B1 have been shown to induce G to A and G to T mutations, respectively.8–11 Currently, the base pairing properties of N7-alkyl-dG are largely unknown except for aflatoxin B1-N7-dG adducts.12</p><p>N7-Methyl-2´-deoxyguanosine (N7mdG) is the smallest N7-alkyl-dG and is the major adduct that is produced by endogenous and exogenous methylating agents (e.g., S-adenosylmethionine).2 The formal positive charge at N7 of N7mdG has been shown to lower the pKa of N1 of guanine by ~2 units (The pKa of N1 in N7mdG is ~7).13,14 The decreased pKa can facilitate the formation of the enolate or enol tautomeric form of N7mdG at physiological pH (Figure 1A). N7mdG has a half-life of several days in duplex DNA and is removed by alkyladenine DNA glycosylase (AAG) in humans and AlkA in E. coli.15,16 It has been proposed that N7mdG could promote mutagenic replication by forming Watson-Crick-like base pair with dT,13 but the three-dimensional structure of such base pairs has not been reported so far. Systematic investigation of base pairing properties of N7-alkyl-dG has been hampered due in part to the technical difficulty of site-specific incorporation of N7-alkyl-dG. In addition, the stability of N7-alkyl-dG is not suitable for the crystallographic experiments. We recently utilized a 2´-fluorine-mediated transition-state destabilization strategy (Figure 1B) to determine the structure of N7mdG:dCTP in the active site of human DNA polymerase β (polβ),17 which showed the formation of Watson-Crick N7mdG:dCTP base pair under the influence of the protein. As an initial step toward elucidating potential N7-alkyl-dG-mediated mutagenesis, we report herein the base pairing properties of N7mdG and the effect of N7mdG on the stability of duplex DNA.</p><p>To elucidate the base pairing properties of N7mdG in the absence of protein contacts, we have developed a novel polβ host-guest-complex (HGC) system,18 where the base pair of interest is in B-DNA and does not engage in any contacts with protein (Figure 1C). We determined eight crystal structures of guanine or N7mdG base-paired with dC, dT, dG, or dA using the polβ HGC system at pH 7.5 (Figure 2, see Table S1 for refinement statistics).</p><p>The N7mdG:dC structure indicates that N7mdG forms three hydrogen bonds with dC, suggesting that N1-H of N7mdG engages in hydrogen bondings (Figure 2B). Hydrogen bond distances in the N7mdG:dC base pair are 2.3 Å, 2.8 Å, and 3.3 Å, indicating that N7 methylation moderately alters the base pair geometry of dG:dC. By contrast, published structure of polβ with incoming dCTP base paired with templating N7mdG in the catalytic pocket showed that the distance for all three hydrogen bonds in the N7mdG:dCTP base pair is 2.9 Å.17 The difference in hydrogen bond distances of the N7mdG:dC and the published N7mdG:dCTP base pairs suggests that the N7mdG:dCTP with an ideal Watson-Crick geometry is induced by a protein contact. The presence of N7mdG:dC in DNA triggers a local conformational change near the lesion base pair. In particular, N7mdG:dC and dG:dC base pairs have considerably different parameter values for buckle (10.7° vs. −0.3°), propeller twist (−15.6° vs. −1.5°), and opening (14.1° vs. −0.5°) distortions (See Table S2).</p><p>The N7mdG:dT structure, refined to 2.2 Å resolution, shows the formation of a novel Watson-Crick-like N7mdG:dT base pair with an interbase hydrogen bond distance range of 2.5–3.2 Å (Figure 2D). The hydrogen bonding pattern of N7mdG:dT significantly differs from that of wobble dG:dT (Figure 2C). While the dG:dT base pair forms two hydrogen bonds between N1 and O6 of dG and O2 and N3 of dT, respectively, the N7mdG:dT base pair forms three hydrogen bonds between N1, N2 and O6 of N7mdG and N3, O2 and O4 of dT, respectively. The base pair geometry of N7mdG:dT including the C1´-C1´ distance and λ angles is very similar to that of a correct base pair (e.g. dG:dC). Published studies show that mismatches with Watson-Crick-like base pair geometry can occur in the presence of protein contacts19–22 but occur only transiently in the absence of protein contacts.23 Watson-Crick-like N7mdG:dT formation in the absence of protein contacts indicates that N7 methylation greatly increases the population of the Watson-Crick-like mispair that typically exists in low abundance. The Watson-Crick-like N7mdG:dT with three hydrogen bonds appears to arise through the enol tautomer of N7mdG rather than the keto tautomer that is involved in the N7mdG:dC base pair (Figures 3C and 2B). The conformation of the N7mdG:dT-containing DNA is essentially identical to that of the dG:dC-containing DNA (RMSD = 0.21 Å, Figure 3A). Taken together, the results imply that, during DNA replication, templating N7mdG may favorably base pair with both incoming dCTP and dTTP via its dual coding potential, which involves the keto and enol tautomers of N7mdG.</p><p>The N7mdG:dG structure shows that N7mdG adopts an anti conformation and forms two hydrogen bonds with syn-dG (Figure 2F), which is similarly observed in the dG:dG base pair (Figure 2E). The base pair geometry of N7mdG:dG is essentially identical to that of dG:dG, which indicates that the keto tautomeric form of N7mdG participates in the base pairing.</p><p>The N7mdG:dA structure indicates that the guanine N7-methylation significantly alters the conformation of dG:dA base pair (Figure 2H). In the dG:dA structure, O6 and N1 of dG are hydrogen bonded to N6 and N7 of dA, respectively (Figure 2G). By contrast, in the N7mdG:dA structure, N1 and N2 of N7mdG are hydrogen bonded to N6 and N7 of dA, respectively. The N7mdG in N7mdG:dA shifts ~2 Å toward the major groove relative to dG in dG:dA (Figure 3E). This shifted anti-N7mdG:syn-dA base pairing has not been observed before, and presumably occurs through the enol tautoermic form of N7mdG (Figure 3F). The shifted anti-N7mdG:syn-dA induces a relatively large distortion of neighboring base pairs (Figure 3D).</p><p>To evaluate the effect of guanine-N7 methylation on the stability of duplex DNA, we determined melting temperatures (Tm) for dG:dN-, N7mdG:dN-, and 2´-fluorine-2´-deoxyguanosine (FdG)-containing 16-mer duplex DNA using fluorescence measurement that involves the use of a double-stranded DNA-specific dye SYBR Green I.24 Control experiments with FdG-containing DNA show that the effect of fluorine atom on the melting temperature of duplex DNA is negligible (Table 1).25 The N7mdG:dC- and N7mdG:dG-containing DNA are slightly less stable than the corresponding dG:dN-containing DNA, whereas the N7mdG:dA-containing DNA is much less stable than the dG:dA-containing DNA. The lower melting temperature of N7mdG:dC-containing DNA as compared to the corresponding dG:dC-containing DNA is consistent with the considerably different parameter values for buckle, propeller twist and opening distortions (Table S2). The large destabilization by N7mdG:dA is consistent with the observed large distortion in DNA conformation (Figures 3D and 3E). On the other hand, N7mdG:dT-containing DNA is slightly more stable than dG:dT-containing DNA, which is consistent with the observation of Watson-Crick-like N7mdG:dT base pair and minimal distortion in the neighboring base pairs (Figure 3A). This suggests that the presence of N7mdG:dT does not significantly affect the stability of duplex DNA.</p><p>The differences between the hydrogen bonding patterns of the N7mdG:dN and dG:dN base pairs suggest that N7 methylation affects dG's base pairing properties by increasing the population of dG's enol tautomer, which is calculated to be ~million-fold less abundant than the keto tautomer.26 While the hydrogen bond donor/acceptor properties of the Watson-Crick edge in dG do not vary among the dG:dN base pairs, those in N7mdG vary, in an opposite-base dependent manner, among the N7mdG:dN base pairs. When paired with dT or dA, the enol tautomer of N7mdG involves in hydrogen bonds, whereas the keto tautomer involves when paired with dC or dG. The N7mdG's abilty to induce both Watson-Crick N7mdG:dC and Watson-Crick-like N7mdG:dT base pairs is reminiscent of the dual coding potential of the mutagenic lesion 2′-deoxy-8-oxoguanosine (8-oxodG), which can adopt both Watson-Crick 8-oxodG:dC and Hoogsteen 8-oxodG:dA base pairs.27 As 8-oxodG uses its anti or syn conformers to assume 8-oxodG:dC and 8-oxodG:dA with a normal base pair geometry, N7mdG uses its enol or keto tautomers to produce N7mdG:dC and N7mdG:dT with a normal base pair geometry. The dual coding properties of N7mdG probably result from N7-methylation-mediated stabilization of the enol tautomer of N7mdG. Such stabilization can reduce the free energy difference between the keto and enol tautomers of dG,26 which would enable a facile utilization of the both tautomers in base pairings in a way to form tighter interbase hydrogen bonds.</p><p>In summary, the results reported here show that guanine-N7 methylation alters hydrogen bonding patterns of the guanine and affects the stability of duplex DNA. Our study resulted in the first observation of Watson-Crick-like N7mdG:dT and the shifted N7mdG:dA base pairs, which presumably involve the enol tautomeric form of N7mdG. The formation of a stable Watson-Crick-like N7mdG:dT base pair in duplex DNA suggests that N7mdG, if not repaired, may induce G to A transition mutations. Non-bulky N7-alkyl groups (e.g. ethyl, propyl) are likely to exert a similar effect on hydrogen bonding patterns of guanine as the N7-methyl group. The predominant G to A mutations that are induced by the N7-dG adducts of acridine half-mustard8 might involve the enol tautomeric form of the modified guanine. The use of the polβ HGC system in combination with the transition-state destabilization strategy may enable the structure determination of various alkylation adducts that are produced by bulky alkylating mutagens and drugs (e.g., tobacco-specific nitrosamine (NNK), N-benzyl N-methyl nitrosamine, ptaquiloside, acridine half-mustards, nitrogen mustards), which would further our understanding on N7-alkyl-dG-mediated mutagenesis and facilitate the structure-based rational design of novel alkylating agents. Kinetic and structural studies of various DNA polymerases bypassing N7mdG lesion are in progress in our laboratory and the results will be reported elsewhere in due course.</p>

PubMed Author Manuscript

Discovery of cellular substrates for protein kinase A using a peptide array screening protocol

Post-translational modification of proteins is a universal form of cellular regulation. Phosphorylation on serine, threonine, tyrosine or histidine residues by protein kinases is the most widespread and versatile form of covalent modification. Resultant changes in activity, localization or stability of phosphoproteins drives cellular events. MS and bioinformatic analyses estimate that ~30 % of intracellular proteins are phosphorylated at any given time. Multiple approaches have been developed to systematically define targets of protein kinases; however, it is likely that we have yet to catalogue the full complement of the phosphoproteome. The amino acids that surround a phosphoacceptor site are substrate determinants for protein kinases. For example, basophilic enzymes such as PKA (protein kinase A), protein kinase C and calmodulin-dependent kinases recognize basic side chains preceding the target serine or threonine residues. In the present paper we describe a strategy using peptide arrays and motif-specific antibodies to identify and characterize previously unrecognized substrate sequences for protein kinase A. We found that the protein kinases PKD (protein kinase D) and MARK3 [MAP (microtubule-associated protein)-regulating kinase 3] can both be phosphorylated by PKA. Furthermore, we show that the adapter protein RIL [a product of PDLIM4 (PDZ and LIM domain protein 4)] is a PKA substrate that is phosphorylated on Ser119 inside cells and that this mode of regulation may control its ability to affect cell growth.

discovery_of_cellular_substrates_for_protein_kinase_a_using_a_peptide_array_screening_protocol

INTRODUCTION<!>Reagents and antibodies<!>Database searching<!>SPOT synthesis<!>Membrane phosphorylation and blotting<!>cDNA cloning<!>Phosphorylation experiments<!>Confocal microscopy<!>Cell growth assays<!>RESULTS AND DISCUSSION

<p>Protein kinases regulate all aspects of cellular behaviour. These key signal transduction enzymes act by phosphorylating target sequences in substrates. This results in modulation of protein function or stability, alterations in association with other proteins, or the movement from one cellular compartment to another [1]. The evolutionary advantage of protein phosphorylation as a versatile and simple form of post-translational modification is supported by evidence that protein kinase genes represent approximately 2 % of most vertebrate genomes. The human 'kinome' contains nearly 500 protein kinases, most of which target serine/threonine or tyrosine residues [2]. Historically, one of the first protein kinases to be investigated at the molecular level was PKA (cAMP-dependent protein kinase/protein kinase A). Peptide-based elucidation of the substrate specificity and X-ray crystallography of the catalytic subunit of PKA have provided a framework for understanding the molecular and cellular roles of this abundant enzyme [3].</p><p>Although some enzymes such as RAF and MEK [MAPK (mitogen-activated protein kinase)/ERK (extracellular-signal-regulated kinase) kinase] exhibit exquisite substrate specificities and generally phosphorylate single substrates, most protein kinases are promiscuous and modify a broad spectrum of proteins. Furthermore, many kinases share overlapping substrate specificity. Thus the same residues can be targeted by multiple kinases in vivo. For example, PKA phosphorylates sites that conform loosely to serine or threonine residues found just distal to basic residues. However, there are a number of other basophilic kinases that target similar sites, including Akt, PAK (p21-activated kinase) and RSK (ribosomal S6 kinase). Therefore a major challenge in deciphering the kinome is determining substrate specificity for particular kinases and identifying targets that may mediate the physiological effects of these enzymes.</p><p>Several technologies are currently available to facilitate the identification of phosphorylation sites in proteins [4]. In addition to advances in MS that have allowed optimized proteome-level characterization of phosphorylation events, peptide and protein arrays have become popular for determining substrate preferences and finding new potential target proteins [5,6]. Finally, phospho-specific antibodies directed against phosphorylation site motifs or individual phosphorylation sites are powerful tools for examining phosphorylation events [7,8].</p><p>In the present paper we describe a strategy for protein kinase substrate identification that combines solid-phase phosphorylation and blotting with phospho-specific motif-selective antibodies. These studies led us to further characterize phosphorylation sites in several proteins, including the PDZ-LIM protein RIL [encoded by PDLIM4 (PDZ and LIM domain protein 4)]. RIL is known to be associated with the actin cytoskeleton. RIL is phosphorylated on Ser119, just distal to the PDZ domain, both in vitro and inside cells. Finally, expression of a phosphorylation-site mutant of RIL in PC-3 prostate adenocarcinoma cells increases cell growth as compared with wild-type RIL.</p><!><p>Reagents for SPOT synthesis were purchased from Intavis. The polyclonal anti-phospho-PKA substrate antibody was from Cell Signaling Technology. The anti-phospho-RIL antibody was generated in rabbits against the peptide PATSRRS[pS]ISGISLE. Other chemicals and reagents were from Sigma–Aldrich, EMD Biosciences or New England Biolabs.</p><!><p>A number of different motif scanners available online were used to identify R-X-X-S/T motifs, including Scansite (http://scansite.mit.edu/) [9], eMotif (http://motif.stanford.edu/distributions/emotif/index.html) [10] and GenomeNet Motif (http://www.genome.jp/tools/motif/). Searches were performed using several different motifs that were variations on the basic R/K-R/K-X-S/T PKA phosphorylation-site motif. Among these were the following: R-X-R-R-X-S-Φ (where Φ is a hydrophobic residue), R-R-X-S-Φ and R-R-X-S/T. When using the Scansite motif scanner, we used both the PKA substrate motif residing in the program as well as the feature for creating new input motifs for uses by the scanner. Typically results from each database largely overlapped, although some hits were found in only a single database. Results from different searches were generally pooled; we were not concerned with categorizing the most reliable motif or program, but instead focused on large pools of candidates that could meet our criteria. The selection process was curated by individually analysing potentially interesting substrates that might reveal previously unrecognized cross-talk between cAMP/PKA and other signalling processes. Sequences of interest were copied into a text file used to program the AutoSpot synthesizer. The main criterion was that the sequence contained a R-X-X-S/T motif that might be phosphorylated by PKA and recognized by the anti-phospho-PKA substrate antibody.</p><!><p>Peptide arrays were synthesized on cellulose membranes using an Auto-Spot Robot ASP 222 (Intavis). After synthesis, the N-termini were acetylated with 2 % acetic acid anhydride in dimethyl formamide. Peptides were then deprotected by a 1 h treatment with dichloromethane/trifluoroacetic acid (1:1), containing 3 %tri-isopropylsilane and 2 %water [11].</p><!><p>Membranes were briefly wetted in ethanol and then placed in pre-incubation buffer [20 mM Hepes (pH 7.4), 100 mM NaCl, 5 mM MgCl2, 1 mM EDTA, 1 mM DTT (dithiothreitol) and 0.2 mg/ml BSA] for 1 h at room temperature (25 °C). Membranes were then blocked overnight in pre-incubation buffer supplemented with 1 mg/ml BSA and 100 μM Mg-ATP. Phosphorylation was performed in pre-incubation buffer containing 100 μM Mg-ATP (or 50 μM Mg-ATP and 10 μCi [32P]ATP) and the PKA C-subunit (catalytic subunit) (1:5000 dilution from bacterially purified stock) for 30 min at 30 °C with rocking. Membranes were then washed three times for 10 min each in 1 M NaCl and 0.2 %Triton X-100, three times for 2 min each in distilled H2O, three times for 10 min each in 1 M NaCl, three times for 2 min each in distilled H2O, and three times for 10 min each in TBST [Tris-buffered saline (50 mM Tris/HCl and 150 mM NaCl, pH 7.5) containing 0.1 % Tween 20]. For detection of [32P]ATP phosphorylation, membranes were rinsed in ethanol, dried and exposed for autoradiography. For Western blotting, membranes were blocked in 5 % non-fat dried milk/1 % BSA for 1 h, rinsed briefly with TBST, and incubated overnight at 4 °C in 5 % BSA containing anti-phospho-PKA substrate antibody (1:500). Membranes were then washed, incubated with the appropriate secondary antisera and developed using ECL (enhanced chemiluminescence).</p><!><p>cDNAs for putative PKA substrates were RT (reverse transcriptase)–PCR cloned from total RNA (Clontech). These cDNAs were inserted into the pcDNA3D-V5/HIS-TOPO vector (Invitrogen), which introduces a C-terminal V5/His tag. cDNAs for PKD (protein kinase D) were provided by Dr Vivek Malhotra (University of California San Diego, San Diego, CA, U.S.A.). Point mutations and deletions were introduced using the QuikChange® XL system (Strategene).</p><!><p>cDNAs for potential substrates were transiently transfected into HEK (human embryonic kidney)-293 cells using Mirus Transit-LT1. After 24 h, cells were washed in PBS, fed with fresh medium and incubated for a further 20–24 h. Cells were then stimulated with appropriate agonists (see Figure legends for details) or DMSO (vehicle control). After treatment, cells were placed on ice, washed with ice-cold PBS and lysed in lysis buffer [20 mM Hepes (pH 7.4), 150 mM NaCl, 1 % Triton X-100, 50 mM NaF, 100 nM okadaic acid, 1 mM orthovanadate, 1 mM PMSF, 2 mg/ml leupeptin, 2 mg/ml pepstatin and 1 mg/ml aprotinin]. After incubation on ice for 10 min, lysates were centrifuged at 15 000 g for 15 min at 4 °C. Substrate proteins were either immunoprecipitated using tag-specific antibodies or isolated using glutathione–Sepharose. Precipitated proteins were separated by SDS/PAGE, transferred on to nitrocellulose and immunoblotted with the anti-phospho-PKA substrate antibody. Membranes were then stripped and re-probed using tag-specific antibodies to determine total protein. In vitro phosphorylation and dephosphorylation was performed as described in [12].</p><!><p>Cells were plated on glass coverslips and incubated overnight at 37°C under 5 % CO2. Cells were starved for 6 h in serum-free DMEM (Dulbecco's modified Eagle's medium). Cells were then treated for 20 min with forskolin/IBMX (isobutylmethylxanthine) as indicated, followed by washing with PBS and fixation in PBS/3.7 % formaldehyde for 20 min. Cells were permeabilized and blocked with 0.1 % Triton X-100 in PBS containing 0.2 % BSA. Coverslips were incubated with specific primary antibodies in blocking buffer overnight at 4 °C. Cells were washed, incubated with Alexa Fluor®-conjugated secondary antibodies (Invitrogen) and Texas Red–phalloidin for 1 h, and washed. Coverslips were mounted using Prolong Antifade reagent (Molecular Probes) and visualized on a Bio-Rad 1024 UV laser-scanning confocal microscope.</p><!><p>WT (wild-type) and S119A RIL were transfected into PC-3 cells and stable lines were generated under neomycin selection. Clones expressing equal levels of WT or mutant RIL were then selected for further analysis. The growth rates of different RIL-expressing cell lines was measured using the CellTiter 96 AQueous Non-Radioactive Cell Proliferation Assay (Promega). Cells (1000 from each RIL line) were plated in triplicate on each of two 96-well plates. One plate was read immediately to confirm correct plating of cells. The second plate was read on day 7. Triplicate wells were averaged and day 7 readings for each cell line were normalized to original plating densities on day 1. Means for WT and mutant RIL lines were compared using an unpaired Student's t test with 0.05 as the level of significance.</p><!><p>We have developed a strategy that combines peptide array, in vitro phosphorylation and Western blotting with motif-selective antibodies to discover previously unidentified phosphorylation sites in proteins. The basic workflow of this method is outlined in Figure 1. We reasoned that membrane-immobilized phospho-peptides recognized by phospho-motif-specific antibodies might also be detected in the context of the full-length protein by Western blotting. Thus this approach could provide a valuable tool for rapid screening of potential phosphorylation sites without the use of large amounts of radiolabelled ATP.</p><p>We chose to look for PKA substrates owing to the availability of a well-characterized phospho-specific antibody that recognizes a canonical PKA target motif, R-X-X-pS/T. Several motif-based bioinformatic tools were used to look for sites matching this consensus PKA phosphorylation site. Peptides corresponding to 15 amino acids surrounding these sites were synthesized on cellulose membranes. Peptides containing alanine substitutions in potential phosphoacceptor serine or threonine positions were included as negative controls. Membranes were phosphorylated in vitro with recombinant PKA catalytic subunit and ATP. After extensive washing, membranes were subjected to Western blot analysis with the anti-phospho-PKA substrate antibody (Figure 2A and Supplementary Figure S1 at http://www.BiochemJ.org/bj/438/bj4380103add.htm). Peptides that were positive in the first round were collected and re-synthesized for confirmation in a second round of profiling.</p><p>Promising candidates were selected for further investigation, including the protein kinases PKD1 and MARK3 [MAP (microtubule-associated protein)-regulating kinase 3]/c-TAK1 (Cdc25C-associated kinase 1), and the adapter protein RIL (Figure 2A, spots I-11, S-4 and M-7 respectively). We were intrigued by the possibility that PKA might regulate signal flow through cascades involving PKD and MARK3. RIL (PDLIM4) was chosen because it is a small-molecular-mass protein that contains a PDZ domain and a LIM domain, both well-studied protein–protein interaction motifs [13].</p><p>PKD is a multifunctional kinase involved in cardiac remodelling and regulated by anchored PKA [12,14]. BLAST searching confirmed that the site in PKD that was identified in the original screen, Ser427, is conserved in vertebrate species (Figure 3A); however, PKD contains multiple potential PKA phosphorylation sites in addition to Ser427. In order to identify which of these could be phosphorylated and recognized by the anti-phospho-PKA substrate antibody, PKD was arrayed out sequentially as 20-mer peptides, with an overlap of three residues in each subsequent peptide (Figure 3B). Duplicate membranes were phosphorylated in vitro with the PKA C-subunit and [32P]ATP (Figure 3B, top panel), or unlabelled ATP followed by Western blot analysis (Figure 3B, bottom panel). Two distinct regions were phosphorylated and recognized by the antibody. These corresponded to peptides containing Ser203 and Ser427 (Figure 3B). Further analysis of these potential PKA sites showed that the anti-phospho-PKA substrate antibody could recognize both Ser203 and Ser427 when phosphorylated in vitro (Figure 3C). WT or KD (kinase-dead) PKD were expressed as GST (glutathione transferase) fusion proteins in HEK-293 cells. Cells were serum-starved and then stimulated with 20 μM forskolin/75 μM IBMX for 20 min at 37 °C. PKD was collected on glutathione agarose and separated by SDS/PAGE. Western blotting with the anti-phospho-PKA substrate antibody showed a clear increase in phosphorylation of PKD upon cAMP elevation and PKA activation (Figure 3D, top panels). In most cases there was a higher basal level of phosphorylation in WT PKD, indicating that this site may be an auto-phosphorylation site. For this reason, we continued our characterization using the KD mutant of PKD. Loading controls verified that equal amounts of total protein were present in each experiment (Figure 3D, bottom panels).</p><p>The sequence surrounding Ser427 contains the consensus PKA motif R-R/K-S-S. Since either serine residue could potentially act as a phosphoacceptor, we mutated either Ser426 or Ser427 to alanine, and performed similar experiments. Mutation of Ser426 had no effect on cAMP-mediated PKD phosphorylation, whereas the S427A mutation abolished phosphorylation, as detected by immunoblotting (Figure 3E, top panels). This result corresponds well with the peptide mapping shown in Figure 3(C).</p><p>MARK3 (also known as PAR-1 and c-TAK1) is a member of the microtubule-affinity regulating kinases. MARK3 contains a single kinase domain and a UBA (ubiquitin-associated domain) (Figure 3F). MARK3/PAR-1 homologues are important for establishing cellular polarity in Drosophila and Caenorhabditis elegans [15], whereas mammalian MARK/PAR-1/c-TAK kinases have been implicated in cell polarity [16], Wnt signalling [17], regulation of microtubule function [18] and cell-cycle regulation [19]. Our peptide array screening identified a potential PKA phosphorylation site at Thr507.</p><p>Peptides containing Thr507, as well as various mutated versions, were arrayed and probed for PKA phosphorylation by immunobloting. Replacement of the putative phosphoacceptor threonine residue with alanine results in loss of signal (Figure 3C, peptide 2). The signal was also lost following replacement with phosphomimetic amino acids (aspartate and glutamate; Figure 3G, peptides 3 and 4). Phosphorylation and antibody recognition of this peptide was also abolished by replacement of the − 3 and − 2 arginine residues with alanine (Figure 3G, peptides 6 and 7).</p><p>A cDNA for MARK3 was amplified from human brain cDNA and cloned for expression as a V5/His-tagged protein in mammalian cells. Cells expressing MARK3 were treated with vehicle or forskolin/IBMX, and MARK3 was immunoprecipitated with anti-V5 antisera. Following separation by SDS/PAGE, Western blot analysis with the anti-phospho-PKA substrate antibody revealed that MARK3 is phosphorylated in response to increases in cAMP concentration and PKA activation (Figure 3H, lanes 1 and 2). We also deleted the region surrounding this putative PKA phosphorylation site. Expression of MARK3Δphos results in loss of phosphorylation by PKA as detected using the anti-phospho-PKA substrate antibody (Figure 3H, lanes 3 and 4). These results further confirm the presence of a PKA site in the region of MARK3/c-TAK1 distal to the UBA.</p><p>Despite our strong evidence for PKA phosphorylation of both PKD and MARK3, so far we have not detected changes in kinase activity or localization in phosphorylation site mutants, and are thus unable to ascribe a convincing function to these phosphorylation events. This highlights the fact that a proportion of phosphorylation events in the phosphoproteome is likely to be structural or non-functional [20,21].</p><p>We next chose to focus on the signalling adapter RIL/PDLIM4. RIL is a member of a family of PDZ/LIM proteins that have been implicated in multiple cellular processes, including regulation of the actin cytoskeleton and Src kinase activation [22,23]. Our array analysis predicted a PKA phosphorylation site at Ser119, which is well conserved in mammalian species (but not in avian or amphibian sequences) (Figure 4A).</p><p>In vitro phosphorylation assays confirmed that RIL could serve as a PKA substrate. Mouse RIL was PCR cloned from a cDNA library. Next, Ser119 was mutated to alanine to abolish this putative phosphorylation site. HEK-293 cells were then transfected with vectors encoding epitope (V5-His)-tagged wild-type RIL or RIL S119A. Cells were lysed and RIL was immunoprecipitated with anti-V5 antisera. After washing, immunoprecipitations were incubated with purified PKA C-subunit and [32P]ATP. RIL was robustly phosphorylated by PKA (Figure 4B, lane 1), whereas RIL S119A was not labelled (Figure 4B, lane 2).</p><p>WT RIL or RIL S119A was expressed in HEK-293 cells. Cells were serum-starved and then treated with forskolin and IBMX to stimulate cAMP production and PKA activation. After cell lysis, RIL was immunoprecipitated as before. Precipitated protein was separated by SDS/PAGE followed by Western blot analysis with the anti-phospho-PKA substrate antibody. RIL was weakly detected in vehicle-treated samples, but was strongly phosphorylated upon PKA activation (Figure 4C, lane 5). Mutation of Ser119 abolished the signal, indicating that this site was solely responsible for detection of phosphorylated RIL by the anti-phospho-PKA substrate antibody (Figure 4C, lane 6).</p><p>In order to confirm that the antibody detection of RIL was dependent on phosphorylation, recombinant RIL was immunoprecipitated from HEK-293 cells and incubated with PKA C-subunit and unlabelled ATP or with λ-phosphatase. Untreated RIL gave a basal signal on Western blotting with the anti-phospho-PKA substrate antibody (Figure 4D, lane 1). Phosphatase treatment completely abolished the signal, indicating that the antibody is specifically detecting phospho-RIL (Figure 4D, lane 2). Furthermore, the signal was augmented by in vitro phosphorylation with PKA (Figure 4D, lane 3), suggesting that there is basal, but non-stoichiometric, phosphorylation inside cells.</p><p>Because the anti-phospho-PKA substrate antibody recognizes a general consensus motif and is not specific to RIL, we developed a phospho-specific antibody against phospho-Ser119. Initial testing of this antibody was performed on peptide arrays containing different variations on the WT sequence.</p><p>Peptides corresponding to the region around Ser119 were arrayed out in triplicate. Peptides were synthesized with a phospho-serine residue in either the 118 or 119 position. Membranes were then immunoblotted with the anti-phospho-RIL Ser119 antibody. This antibody recognized both phosphoserine-containing peptides, whereas non-phosphorylated and mutant peptides gave no signal (Figure 5A). Next, we assessed the antibody recognition of in vitro phosphorylated peptides. In addition to the WT peptide, several mutated peptides were also synthesized. First, Ser119 was changed to alanine. As position 118 is also a serine residue (in mouse RIL), this residue was changed to alanine as well. Finally, a peptide with both serine residues replaced with alanine residues was included. Membranes were phosphorylated in vitro with purified PKA C-subunit and either [32P]ATP or unlabelled ATP, followed by either autoradiography or immunoblotting with the anti-phospho-RIL Ser119 antibody. In both cases, strong phosphorylation was detected in WT or S118A peptides, but not in the peptides containing S119A (Figure 5B). Taken together, these results indicate that even though there is a serine residue at position 118, PKA seems to selectively phosphorylate Ser119, a site that is conserved across species.</p><p>We next tested the antibody on RIL expressed in cells. Treatment of cells expressing RIL–V5/His with 100 nM isoproterenol resulted in robust RIL phosphorylation (Figure 5C, lane 2). Pre-treatment with the PKA inhibitor H-89 blocked β-adrenergic-mediated RIL phosphorylation (Figure 5C, lane 3). Phosphorylation of RIL Ser119 appears to be somewhat selective for PKA, as stimulation of PKC with the phorbol ester PDBu (phorbol 12,13-dibutyrate) had minimal effect on RIL phosphorylation (Figure 5C, lane 4). Finally, as shown in Figure 4, forskolin/IBMX treatment resulted in robust RIL phosphorylation (Figure 5C, lane 5).</p><p>We also performed immunofluorescence analysis of endogenous RIL phosphorylation in REF52 cells. Cells were starved and treated with forskolin and IBMX. After fixation and permeabilization, cells were stained with the anti-phospho-RIL Ser119 antibody and Texas Red–phalloidin to label F-actin (filamentous actin). Confocal microscopy showed weak basal staining for phospho-RIL Ser119 in untreated cells (Figures 5D–5F). After PKA activation, levels of phospho-RIL Ser119 increased throughout the cells (Figures 5G–5I). Interestingly, phospho-RIL seems to be particularly concentrated at the tips of actin-rich projections that may represent sites of cell-substrate interaction (Figures 5G–5I).</p><p>Several recent reports have implicated RIL in control of cell growth and cancer [24,25]. Silencing of RIL expression through promoter methylation occurs in several types of cancers, suggesting that loss of RIL expression may be important for cancer progression and malignancy. Re-expression in several cancer cell types impairs proliferation and anchorage-independent growth through unknown mechanisms that may involve stabilization of F-actin or regulation of cell-cycle progression [24,25]. Vanaja et al. [25] showed that RIL expression in PC-3 prostate adenocarcinoma cells inhibits cell growth. In order to assess the function of Ser119 phosphorylation of RIL, we generated stable PC-3 cell lines expressing either WT RIL or RIL S119A. Cell lines were chosen for matched RIL expression (Figure 5J, top panel). Next, we performed MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium] assays to examine proliferation of the two cell lines. Cells expressing RIL S119A grew significantly faster than cells expressing WT RIL at 7 days after starting the assay (Figure 5K). Therefore we propose that mutation of Ser119 partially rescues the inhibitory growth effect of expressing RIL in these cells. This suggests that phosphorylation of Ser119 by PKA (or another kinase with similar motif preferences) may be required for suppression of growth by RIL.</p><p>The results of the present study show that combining phosphorylation of immobilized peptides and immunoblotting with motif-selective antibodies is an effective way to discover kinase targets. These methods should be easily extendable to a large number of kinase/antibody pairs, particularly as the inventory of phospho-specific antibodies expands and more information is forthcoming on so called 'orphan kinases'.</p>

PubMed Author Manuscript

Synthesis of disulfide-rich heterodimeric peptides through an auxiliary N, N-crosslink

Insulins, relaxins, and other insulin-like peptides present a longstanding synthetic challenge due to their unique cysteine-rich heterodimeric structure. While their three disulfide signature is conserved within the insulin superfamily, sequences of the constituent chains exhibit considerable diversity. As a result, methods which rely on sequence-specific strategies fail to provide universal access to these important molecules. Biomimetic methods utilizing native and chemical linkers to tether the A-chain N-terminus to the B-chain Cterminus, entail complicated installation, and require a unique proteolytic site, or a two-step chemical release. Here we present a strategy employing a linkage of the A-and B-chains Ntermini offering unrestricted access to these targets. The approach utilizes a symmetrical linker which is released in a single chemical step. The simplicity, efficiency, and scope of the method are demonstrated in the synthesis of insulin, relaxin, a 4-disulfide insulin analog, two penicillamine-substituted insulins, and a prandial insulin lispro.

synthesis_of_disulfide-rich_heterodimeric_peptides_through_an_auxiliary_n,_n-crosslink

<!>Results<!>Synthesis of relaxin. The synthesis of relaxin (Supplementary Figures<!>Discussion

<p>O ver the course of the last 50 years, the efficiency in linear peptide assembly has advanced through a series of innovations, most notably stepwise solid-phase synthesis and fragment ligation [1][2][3][4] . Still, precise control of higher order structure through directed disulfide bond formation remains challenging [5][6][7][8] . This is particularly the case with peptides such as insulin and relaxin given the additional complexity of their heterodimeric structures 9,10 . Biomimetic linkers have been introduced to address these issues. They share the native linear order of proinsulin where the N-terminus of the A-chain is indirectly connected to the C-terminus of the B-chain. Conversion to the two-chain form initially employed enzymatic conversion and was restricted by the requirement for a unique proteolytic site [11][12][13][14][15] . The more recent reports employing chemically labile linkers represent a leap forward by eliminating the need for a proteolytic site, and the enzyme itself. The Kent group described an insulinspecific linkage of GluA4-ThrB30, which was saponified following oxidative folding 16 . Subsequently, a sequence-agnostic approach to synthesis in the insulin-like peptide family was reported, which employed a reversible tethering of the A-chain N-terminus through a labile amide to the B-chain C-terminal ester 17,18 . In each instance, the strategies mimicked the linear order of the A-and B-chains found in proinsulin. While native, this linear orientation increases synthetic complexity in requiring either non-standard chemistry for linker installation, or a two-step linker excision. A straightforward, general synthesis would ideally align with conventional solid-phase methods and employ a single chemical step for removal.</p><p>We report the synthesis of insulin and a set of related peptides by a synthetic protocol that employs a reversible crosslink of the two N-termini through parallel extension of the respective A-and B-chains made by conventional Solid Phase Peptide Synthesis (SPPS). The N-N heterodimers of these insulin-related peptides efficiently fold under standard redox conditions, and subsequently convert to the native hormone under mildly alkaline conditions by virtue of two simultaneous diketopiperazine cyclizations. The efficiency and versatility of the method are demonstrated in the synthetic yield of insulin and the direct translation to the synthesis of relaxin. The non-native N-N linkage enables the synthesis of two site-specific penicillamine-substituted analogs 4 and 5, that fail when using a high-efficiency N-C folding intermediate, named des-DI insulin 15 . This synthetic approach is based upon an orthogonal, non-native N-N linkage of individual peptide chains that is synthetically straightforward and of high efficiency in synthesis of insulin-like peptides. The approach holds promise for translation within the broader class of disulfide-rich heterodimeric peptides.</p><!><p>Insulin synthesis. We explored the chemical synthesis of insulin, relaxin-2, and four insulin analogs (Fig. 1) through reversible crosslink of the two N-termini by parallel extension of insulin A-and B-chains made by conventional SPPS. A Lys-(iBu)Gly dipeptide extension at the N-termini was envisioned to provide a side-chain anchor for an OEG (polyethylene glycol)oxime-based crosslink (Fig. 2). Whether a suitably, sequence-extended N-N heterodimer of insulin A and B-chains might fold under standard redox conditions was a central uncertainty to be investigated.</p><p>The synthesis of the insulin A-chain began with the coupling of Fmoc-Asp-OtBu to Chemmatrix Rink amide resin to introduce the C-terminal Asn, and the remaining residues added by conventional automated Fmoc-based SPPS protocol (Fig. 3). The isoacyl Thr-Ser dipeptide at A8-A9 was incorporated as a means to enhance peptide assembly, solubility, and handling 19 . The Boc-Lys(iBu)Gly-OH dipeptide was installed through sequential α-bromoacetylation and isobutylamine treatment 20 of resin-bound A-chain 7 followed by 3-(diethoxyphosphoryloxy)-1, 2, 3-benzotriazin-4(3H)-one (DEPBT)-mediated coupling of Boc-Lys (Fmoc)-OH. Successive side-chain coupling of PEG 8 and bis (Boc)amino-oxyacetic acid provided resin-bound A-chain 8, which was deprotected and cleaved from the resin under standard conditions. The crude peptide, (Supplementary Figure 13) was purified by C8 reverse phase HPLC (RP-HPLC) to provide Achain 9 in 25% yield (Fig. 4 and Supplementary Figure 14).</p><p>The B-chain synthesis (Fig. 3) was initiated with loading of Fmoc-Thr(tBu)-OH on a ChemMatrix HMPB resin under Mitsunobu conditions to minimize racemization. The remaining residues (B1-B29), including the isoacyl Tyr-Thr dipeptide at B26-27 were incorporated by conventional Fmoc-based SPPS protocol. The Boc-Lys(iBu)Gly-OH dipeptide, PEG 8 (polyethylene glycol), and bis(Boc)amino-oxyacetic acid were sequentially coupled to resin 10, followed by cleavage and deprotection to afford 11. The free aminooxy-derivatized B-chain 11 was treated with Terephthalaldehyde (10 equiv.) in 0.1% TFA/70% aqueous acetonitrile (ACN) to provide the crude imino-benzaldehyde Bchain derivative 12 (Supplementary Figure 15), which was recovered in 15% total synthetic yield following RP-HPLC purification (Fig. 4 and Supplementary Figure 16). The oxime ligation of A-chain and B-chain was accomplished by combination of 9 and 12 in a 0.1% TFA containing 50% aqueous ACN, for 2 h (Figs. 3, 4 & Supplementary Figure 17). The PEG 8 was experimentally determined to be the minimal distance required between A-and B-chains to subsequently produce the properly disulfide-paired hormone.</p><p>The folding of the ligated A-B intermediate 13 was performed at pH 9 in an aqueous buffer with 2 mM cysteine and 0.5 mM cystine at 4 °C, to produce a single major product 14 (Figs. 3, 4 and Supplementary Figure 18). This properly folded, single-chain insulin was obtained in a 45% combined yield for ligation, disulfide-formation, and RP-HPLC purification (Supplementary Figure 19).</p><p>Single-chain insulin 14 was efficiently converted to two-chain insulin 1 using 0.5 M phosphate buffer (pH 7.0) at 56 °C (Fig. 3). The two simultaneous diketopiperzine (DKP) cleavage reactions were complete after 5 h to provide insulin 1 in 65% yield, following HPLC purification (Fig. 4, Supplementary Figures 20-21). The speed of DKP formation can be further accelerated by selection of dipeptides that favor cis-configuration, which can be achieved by alkylation at the alpha carbon of the first amino acid and more judicious N-alkylation at the second. When compared to our previous report employing an N-C insulin order, the yield was enhanced in a relative sense by 20% 17 . This improvement predominantly results from eliminating the more alkaline pH needed to cleave the ester bond. Overall, the synthetic yield of insulin was 30%, starting from purified A-chain. 1-2) began with A-and B-chains, respectively, utilizing Fmoc-Cys(Trt)-OH/ NovoSyn® TGA resin and Fmoc-Ser(tBu)-OH/ ChemMatrix HMPB esterified resin. The remaining amino acids were added by a conventional Fmoc protocol, with isoacyl dipeptides employed as Asp-Ser at B1-B2 and Ser-Thr at B26-B27. In addition, the N-terminal residue of the A-chain was introduced as Gln, which was subsequently cyclized to pGlu. The Boc-Lys(iBu)Gly-OH dipeptide, PEG 8 and bis-Boc-aminooxyacetic acid were introduced as reported in the insulin synthesis (Supplementary Figures 22-25). The oxime ligation 21 and peptide folding 22 (Supplementary Figure 3) were also conducted as previously communicated with a combined yield of 46% (Supplementary Figures 26-28). The DKP cyclization and the subsequent pGlu formation were completed in 7 h using 0.5 M phosphate buffer (pH 7.0, 56 °C) in a combined 65% yield (Supplementary Figures 29-30), and the overall synthetic yield of human relaxin-2, 2 was 30%, starting from A-chain. To minimize intermediate handling loss, we assessed the ligation, folding, and linker excision steps starting with pure A-and B-chains and chromatographically purifying only at the end (Fig. 5 and Supplementary Figure 4). This simplified protocol improved the total synthetic yield from 30 to 38%, and represents one of the most efficient chemical syntheses reported yet for human relaxin. The bioactivity of the synthetic relaxin-2 proved indistinguishable from an external native control hormone (Supplementary Figure 12). Synthesis of a four-disulfide insulin analog. To further explore the potential of the new methodology, we applied it to an insulin analog with an additional, fourth disulfide linking CysA10 and CysB4 (Supplementary Figure 5). This analog as prepared by biosynthesis is reported to possess reduced propensity to fibrillation, and full in vivo activity 21 . The first chemical synthesis of these four-disulfides (4-DS) insulin analog was achieved through sequential disulfide bond formation that included an iodine oxidation step. An iodine-free synthesis of this challenging target suggests that the methodology may prove useful in the synthesis of other peptides with multiple disulfides, especially those with methionine and tryptophan.</p><!><p>The insulin-extended A-chain S1 and B-chain S2 synthesis incorporated Fmoc-Cys(Trt)-OH at A10 and B4 but otherwise were identical to the previously presented insulin protocol, and they were, respectively, achieved in yields of 24% and 15% (Supplementary Figures 35 and 36). The ligated linear precursor S3 was folded without modification of the insulin protocol, and the single-chain, 4-DS analog S4 was obtained in 40% yield (Supplementary Figure 34 and 37). The excision step was achieved in 5 h to yield the pure 4-DS insulin analog 3 in 64% yield (Supplementary Figure 38). This peptide as assessed by LC-MS and in vitro potency was indistinguishable from the same insulin analog as prepared by orthogonal disulfide bond formation 22 , and only slightly less potent than native insulin (Supplementary Figure 10). The single-chain form of the 4-DS analog S4 was sizably less potent than the two-chain form, demonstrating the deleterious impact of an N-terminal constraint on bioactivity, but not on the ability to form native disulfides with a linker of appropriate length. Insulin with a comparable crosslink at the N-termini of A-and B-chains was suppressed</p><p>Four disulfide human insulin, 3 L B19(Pen)-insulin analog, 5 in bio-potency to nearly the same extent as observed in the 4-DS analog 14 (Supplementary Figure 10).</p><p>Synthesis of penicillamine-containing insulin analogs. The synthesis of the A7(Pen) A-chain S5 and B19(Pen) B-chain S8 (Supplementary Figure 6 and 7) employed the same protocol as employed for insulin, except for Fmoc-Pen(Trt)-OH at A7 or B19. The chain assembly yields following purification were 22% for the A-chain analog S5, and 14% for B-chain S8 (Supplementary Figures 40 and 45). The oxime ligation of S5 to 12 and S8 to 9 was conducted as previously achieved for native insulin, and the ligated purified synthetic intermediates S6 and S9 were obtained in respective yields of 55% and 50% (Supplementary Figures 41 and 46). The subsequent folding of S6 and S9 was without protocol modification as reported for native sequence and was complete with comparable efficiency in 12 h to provide S7 at 20% yield, and S10 at 19% (Supplementary Figures 39, 44, 42, and 47). The cleavage of the DKP-peg-bis linker was achieved in 9 h (pH 7.0, 56 °C), to provide analogs 4 and 5 in total yields of 30% and 28% (Supplementary Figures 43 and 48). The native disulfide pattern was implied by single LC-peaks in the Glu-C peptide mapping (Supplementary Figure 10, Supplementary Table 1), which was definitively confirmed for the Pen-A7 analog by comparison to disulfide isomers prepared by orthogonal synthesis (Supplementary Figures 60 and 61). The in vitro bioactivity of these novel insulin analogs was assessed and observed to be reduced to varying degrees relative to native hormone (Table 1, Supplementary Figure 11). The other four single-site, penicillamine insulin analogs (A6, A11, A20, and B7) were chemically synthesized using a linear desDI single-chain precursor without issue, (Supplementary Figures 55-59) 15 . The A7 and B19 proved to be synthetically accessible only by the Ntermini ligation approach we describe in this manuscript. The bioactivity of the penicillamine analog at A20 was least affected in a relative sense, especially when compared to the analogs at the other inter-chain cysteines (A7, B7, and B19). Interestingly, the placement of the gem-dimethyl substituent at A11 was approximately 100-fold more disabling than at A6, the other partnering residue in the single intra-chain disulfide.</p><p>Synthesis of Lys-Pro insulin. Lys-Pro insulin represents the first hormone analog produced by rDNA-technology approved for human use 23 . The inversion of the natural dipeptide to Lys-Pro eliminates trypsin-like proteolysis. Consequently, this analog should be equally accessible by an enzyme-based approach as a synthesis that is DKP mediated. To prove this point and assess the relative efficiency in the removal of the auxiliary N,N-crosslink, insulin 6 was synthesized (Supplementary Figure 8) as described for native sequence, but with replacement of the DKPsusceptible dipeptide with a Gly-Lys dipeptide. Peptide chain synthesis, oxime ligation and disulfide formation in insulin 6 were achieved as with native hormone in 46% yield (Supplementary Figures 49-52). The single-chain S14 was converted to the twochain form 6 by digestion (Supplementary Figure 54), in Tris buffer pH 8 for 1 h. The Lys-Pro insulin was obtained after purification by RP-HPLC in 66% yield (Supplementary Figure 53). The yield of 6 as produced by enzyme was 30% from purified A-chain, which is identical to the yield of 1 obtained by DKP-mediated chemical cleavage.</p><!><p>We report a general synthetic route to insulin-related peptides with likely application to the broader family of disulfide rich, twochain peptides. This straightforward method demonstrates the use of a non-native N-N linkage that is compatible with automated SPPS. The use of identical N-terminal A-and B-chain extensions and conventional ligation streamlines the assembly of the heterodimer, followed by single-step excision of the auxiliary tether. Insulin and relaxin, which have historically constituted</p><p>Human insulin, 1 Single chain insulin, 14 difficult synthetic targets, were produced by this procedure within a few days, in high yield. Notably, an initial attempt to synthesize insulin through an N-N linkage without an N-terminal extension was reported to be unsuccessful 16 . In our experience, the folding efficiency was dramatically enhanced by incorporation of the OEG-based N-terminal extensions. The central, enabling element of this approach is the reversible N-terminal crosslinking of the A-and B-chains to enable intramolecular native disulfide bond formation. The efficiency is highlighted in the synthesis of relaxin from A-and B-chains employing only a final chromatographic purification step in a 38% yield (Table 2). The use of OEG-extended linkers was found to improve handling of the individual peptide chains, the ligated intermediate, and to enhance the subsequent formation of native disulfides. These conditions were applicable to the native hormones and translated to a synthetic target that had previously required orthogonal stepwise synthesis, a four-disulfide containing insulin analog 22 . The successful syntheses of two individual penicillamine substituted insulin analogs, that we could not prepare by native folding using a bio-mimetically linked insulin precursor 15 , demonstrate a unique virtue to this synthetic approach. The analogs complete an otherwise full set of selective penicillamine substitutions for each of the native cysteines (Table 1). There was no direct relationship in the difficulty of synthesis relative to bioactivity, as the B19 analog was of intermediate potency to the full set while A7 was least potent.</p><p>We envision the application of this approach beyond the insulin/relaxin super family. The methodology is compatible with peptides produced by any method where the linker can be semisynthetically conjugated to a selective amine, preferably the Nterminus 24 . The linker can be further optimized to enhance the biophysical properties of synthetic intermediates. The synthetic approach is not limited to oxime linkage and could conceivably utilize other linkage chemistries. A sagacious aspect of the reported syntheses is the use of DKP formation, an adverse reaction in peptide synthesis 25 as controlling element in the removal of the auxiliary crosslink 17,18 . Further refinements in the propensity to cyclize will broaden the ability to accelerate or delay reversal of the crosslink. As exemplified in the synthesis of Lys-Pro insulin, the synthetic strategy is compatible with selective proteolysis. Notably, the synthetic yields in use of the chemical and enzymatic cleavage were comparable, attesting to the productivity of the former. nd not determined a Purified A-and B-chains b Purified A-B dimers following ligation and starting with purified A-and B-chains c Purified two-chain peptides following DKP-mediated cleavage of the purified folded single-chain A-B dimer d Total yield of purified peptides following ligation, folding, and DKP-mediated cleavage, starting with purified A-and B-chains e Purified single-chain disulfide-bonded A-B dimers following ligation and folding, starting with purified A-and B-chains f Purified two-chain peptide following ligation, folding, and DKP-mediated cleavage, starting with purified A-and B-chains g Purified peptides following folding, starting with purified ligated A-B dimer</p>

Nature Communications Chemistry

Analytical expressions for the homotropic binding of ligand to protein dimers and trimers

Cooperative binding of a ligand to multiple subsites on a protein is a common theme among enzymes and receptors. The analysis of cooperative binding data (either positive or negative) often relies on the assumption that free ligand concentration, L, can be approximated by the total ligand concentration, LT. When this approximation does not hold, such analyses result in inaccurate estimates of dissociation constants. Presented here are exact analytical expressions for equilibrium concentrations of all enzyme and ligand species (in terms of Kd values and total concentrations of protein and ligand) for homotropic dimeric and trimeric protein\xe2\x80\x93ligand systems. These equations circumvent the need to approximate L and are provided in Excel worksheets suitable for simulation and least-squares fitting. The equations and worksheets are expanded to treat cases where binding signals vary with distinct site occupancy.

analytical_expressions_for_the_homotropic_binding_of_ligand_to_protein_dimers_and_trimers

<!>The models<!>Theory<!>The L \xe2\x89\x88 LT approximation<!>The Excel worksheets<!>Application to spectroscopic methods<!>Conclusions

<p>Protein–ligand interactions are fundamental to numerous biological processes, including hormone signaling, allosteric regulation, metabolism, and cell-to-cell communication. A key metric for such interactions is the dissociation constant (Kd), which is often determined in equilibrium binding titrations where the concentration of saturated receptor or bound ligand is measured as a function of the total ligand (LT) concentration. Methods used to obtain ligand binding information include various forms of spectroscopy [1], surface plasmon resonance [2], calorimetry [3], radioactivity [4], and assays that couple protein saturation to biological or chemical– enzymatic signals. Such measurements report on the concentration of bound and/or free ligand and are often interpreted as the fractional saturation (Y) of protein.</p><p>The simplest equations for fitting ligand binding data (cf. Eq. (1)) require knowledge of free ligand (L), which may be either measured directly or estimated by virtue of experimental designs in which L can be approximated by LT such as when protein concentration (ET) is very low relative to Kd or LT. Signal detection limits often preclude the use of such designs. When L is not known, the data are best modeled using an expression for Y in terms of LT, ET, and Kd (Eq. (2)). Eq. (2) (obtained from mass conservation laws and the quadratic formula) provides such an analytical expression for the elementary case of ligand binding to a single site (or multiple noninteracting sites). Using such an expression, a best-fit Kd value can be extracted from titration data by least-squares fitting.</p><p>For higher order processes, such as cooperative binding to a multimeric protein (where ligand occupancy at one protomer alters ligand affinity at the others), fitting methods must take into account each of the multiply liganded forms. Such behavior manifests experimentally as multiphasic saturation curves or nonlinear Hill and Scatchard plots, whose shapes indicate enhanced (positive cooperativity) or diminished (negative cooperativity) binding of successive ligands [5,6]. Among the many proteins and protein classes that exhibit homotropic cooperativity are the dimeric G-protein-coupled receptors [7], sulfotransferases [8], trimeric metabolic enzymes [9–12], monomeric cytochrome P450s [13], AcrB bacterial drug efflux pump [14], bacteriorhodopsin trimers [15], and DegS protease that regulates the Escherichia coli stress response [16].</p><p>The Hill [17,18] and Adair [19] equations (Eqs. (3) and (4)) address the cases where L is known and report cooperativity either indirectly as the Hill coefficient (n) or explicitly as Kd values (given by Ki for the ith ligand to bind) that reflect changes in affinity between successive binding steps. Derivation of parallel analytical equations in terms of LT is nontrivial given that the equilibrium concentration of any species of a dimeric or trimeric protein is the root of a cubic or quartic polynomial, respectively. Analytical solutions for higher order oligomers are not possible, and fitting the titrations of such systems requires the use of numerical methods [20]: (1)Y=LL+Kd(2)Y=(ET+LT+Kd)−(ET+LT+Kd)2−4ETLT2ET(3)Y=LnLn+Kd(4)Y=LK1+2L2K1K22(1+LK1+L2K1K2)(5)Y=LK1+2L2K1K2+3L3K1K2K33(1+LK1+L2K1K2+L3K1K2K3)</p><p>Although analytical expressions for the roots of cubic and quartic functions have been known for 400 years [21–23], they require knowledge of advanced algebra. Recent articles have treated the cubic polynomial in ligand binding systems; Wang and Sigurskjold described competitive binding of two ligands to identical independent binding sites [24,25], and Whitesides and co-workers used exact analysis to describe binding of homodivalent ligands to monomeric proteins, producing expressions that apply equally to homodimeric proteins binding to monovalent ligands [26]. However, to our knowledge, application of the quartic polynomial to trimer–ligand binding has not yet been addressed, and no exact analysis has been applied to heteroligomers that exhibit homotropic cooperativity.</p><p>Current approaches to modeling trimeric systems rely on numerical methods that employ differential equations or stochastic models to estimate the equilibrium distributions of enzyme forms. Typically, these algorithms require the user to provide total reactant concentrations and equilibrium or rate constants [27–29]. Equilibrium distributions are then calculated at each "point" or condition in a titration, and the concentrations of the relevant species from the distributions are then compared with experimental measurements to assess how well a given set of input constants predicts binding behavior. These procedures can be iterated to produce a best-fit set of constants. Notably, such efforts typically require high-level mathematical software or original programming [30]. The analytical equations described here provide a relatively simple means of obtaining exact distributions. The equations take into account both positive and negative cooperativity and can be applied to any chemical equilibrium involving homotropic binding to a diva-lent or trivalent species. For convenience, the equations are provided in Excel worksheet implementations suitable for prediction and multiparameter estimation by least-squares fitting. An expansion of the equations and worksheets to treat spectroscopic titration is also described.</p><!><p>Early models of allostery proposed that linked subunits undergo concerted transitions between two conformational states, each with a different ligand affinity [31]. Later models allowed subunits to undergo independent, substrate-induced conformational changes and held that affinities at the unoccupied sites would change progressively as ligands added to the complex [19,32]. Even more general models allowed subunits to undergo conformational transitions with or without bound ligand and allowed the affinity of all sites to vary with each unique configuration of the system [33,34].</p><p>The dimer and trimer ligand binding models used as the basis for the algebra described below are presented in Fig. 1A and B. Oligomers are represented by intersecting lines; each line represents a subunit. Dotted lines indicate the subunits that may inter-convert via isomerization; however, subunits need not be identical. Site and dissociation constants are given by ki and Ki, respectively, where i represents the ith subunit to bind. Site constants are given for each subunit in all possible configurations and are related by cj values, which define the magnitude and nature of the cooperative interactions. The cj values are related by the fact that the product of the site constants connecting any two enzyme forms is path independent, a consequence of the first law of thermodynamics. The model assumes that ligand binding, which is stochastic, stabilizes a subunit in the state that it was in when binding occurred; hence, dotted lines become solid on the addition of ligand.</p><!><p>The equilibria describing binding of the first and second ligands L to a dimeric protein E are shown in Fig. 1A. When considering ligand binding to a multisubunit system, it is important to note that binding measurements yield aggregate constants (e.g., Kd values) that report on all enzyme forms capable of transitioning between two stoichiometric states (e.g., singly to doubly liganded) [35]. The dissociation constants for binding of the first (K1) and second (K2) ligands to a dimer are given by Eqs. (6) and (7). The denominator of Eq. (6) is the sum of all the singly liganded enzyme forms: (6)K1=E⋅LΣEL1=E⋅LEL+LE(7)K2=ΣEL1⋅LEL2</p><p>Complexes EL and LE represent ligand bound to different subunits of a heterodimer or to either symmetric subunit of a homodimer. By treating the subunits separately, we isolate the interaction of ligand with a single protomer. This interaction is defined by a "site" dissociation constant [35] that reports directly on the strength of the interaction at a particular binding site. These constants are given by lowercase ki for the ith ligand to bind and are modified by coefficients cj for heterodimeric proteins (Eq. (8)): (8)k1=E⋅LEL;c0k1=E⋅LLE;k2=EL⋅LEL2;c1k2=LE⋅LEL2</p><p>The aggregate constants Ki (Eqs. (6) and (7)) are a function of the individual site ki values at each ligand binding step. For multimeric proteins with n equivalent binding sites, cj = 1 and dissociation constants are related by a statistical coefficient (Eq. (9)): (9)Ki(stoichiometric)=ki(site)i(n−i+1) where i corresponds to the ith ligand to bind [36]. Equivalencies among aggregate and site constants in cases where cj ≠ 1 are described below (trimers) and in the Supplementary material.</p><p>For a trimeric protein, binding of both the second and third ligands may show ligand occupancy dependence. In this case, one additional equilibrium relationship is needed (Eq. (10)): (10)K3=ΣEL2⋅LEL3</p><p>Binding of ligand to a trimeric protein is shown in Fig. 1B. The affinity of the first ligand to bind is given by any of three site binding constants, k1 with or without coefficients c0 and c1. The site constant coefficients will differ in cases where, for example, isomerized subunits have distinct binding attributes prior to binding (cf. half- or third-site mechanisms [8,10,11] or the conformational coupling of energetics [37]) or where the protein is heteroligomeric. The second ligand may be presented with multiple binding sites of varying affinities depending on which subunit was bound first. Thus, the second binding step is composed of six possible site constant values, where variation in k2 is captured by the five coefficients c2 to c6. The third ligand binds to one of three possible protomers, with site constant k3 modified by coefficients c7 and c8 to describe these multiple forms; the end result of each process is the identical triply liganded species. Because the change in chemical potential of any of the six paths from unliganded to triply liganded is identical, the product of the equilibrium constants for one path is equal to that of any other path. The complete system can be described by 10 parameters: ET, LT, site constants k1 to k3, and coefficients c0 to c4. The values of coefficients c5 to c8 are defined by the following relationships: c5=c2c1;c6=c0c4c1;c7=c0c3c2;c8=c3c4</p><p>The relationships between aggregate (Ki) and site constants (ki) for a trimeric protein were obtained by deriving Eq. (16) using each kind of constant and then equating coefficients (Eqs. (11)–(13)): (11)K1=1αk1(site)(12)K2=αβk2(site)(13)K3=βk3(site) where α=1+1c0+1c1β=1+1c2+1c0c3+1c0c4+1c1c5+1c1c6</p><p>The mass conservation relationships for the trimeric system are given by Eqs. (14) and (15): (14)ET=E+ΣEL1+ΣEL2+EL3(15)LT=L+ΣEL1+2ΣEL2+3EL3 The system of equations (Eqs. (6), (7) and (10)–(15)) can be rearranged, resulting in a quartic polynomial in L (Eq. (16)): (16)L4+aL3+bL2+cL+d=0 where a=3ET+βk3−LTb=αk2k3+2βk3ET−βk3LTc=k1k2k3+αk2k3ET−αk2k3LTd=−k1k2k3LT</p><p>The solution of this quartic equation yields L (see Supplementary material), which is then used to determine the equilibrium concentrations of all other species in terms of the constant parameters (Eqs. (17)–(20): (17)E=k1k2k3ETk1k2k3+αk2k3L+βk3L2+L3(18)ΣEL1=αk2k3ETLk1k2k3+αk2k3L+βk3L2+L3(19)ΣEL2=βk3ETL2k1k2k3+αk2k3L+βk3L2+L3(20)EL3=ETL3k1k2k3+αk2k3L+βk3L2+L3</p><!><p>The Adair equation describes solution equilibria for cooperative binding to multi-subunit proteins (Eq. (3), dimer; Eq. (4), trimer). This equation can be rearranged, using mass conservation equations, into a polynomial in L (Eq. S5 in Supplementary material, dimer; Eq. (16), trimer) that can be solved to determine the equilibrium concentrations of species as a function of ET, LT, and ki values (Eqs. S6–S8 in Supplementary material, dimer; Eqs. (17)–(20), trimer). To demonstrate how the equilibrium distributions predicted by the Adair equation deviate from exact distributions (given by the analytical solutions) as L deviates from LT, distributions were simulated for a noncooperative trimer at four different ET/ki ratios (0.01–10). ET was held fixed (1.0 μM), and ki values were decreased in 10-fold increments from 100 μM to 100 nM. The results, given as fraction protein saturated (Y) versus concentration LT, are presented in Fig. 2A. At ET/ki = 10, the concentration of LT in the vicinity of ki is much greater than that of ET, the L = LT approximation holds well, and the two methods agree. However, as ET/ki increases, the bound ligand concentration becomes significant relative to LT when LT ≈ ki and the approximation begins to fail. As this happens, the Adair equation predicts saturation at erroneously low LT concentrations. For example, when ET/ki = 1, the ki values estimated by fitting fractional saturation to the Adair equation are more than 3-fold higher than the true ki and invoke 4-fold cooperativity for the third binding step where none exists. As can be seen in Fig. 2B, the fold difference in the Ki values predicted by the Adair and exact methods is significant when ET/ki ≈ 1 and increases sharply above this value. Thus, in situations where dissociation constants are comparable to the protein concentrations needed to observe signal, or in complex mixtures where affinities are high and protein concentrations are not known, the exact solutions are a far more accurate and reliable means of analyzing binding data.</p><p>The solution to the quartic equation provides a simple, virtually errorless means of simulating equilibrium distributions of species in complex binding scenarios that involve a single type of ligand. As such, it can be useful in optimizing experimental conditions. It is often of interest to maximize the concentration of a particular enzyme form, so that the properties of that species can be studied, or to understand the concentration dependence of a species; such dependencies can be used to test for the existence of a putative complex and/or to validate a given model. As an example, consider the LT dependence of the species of a trimer in a scenario where ligand binding at the high-affinity site results in a 100-fold negative cooperativity at the unoccupied sites and binding of the second and third ligands is independent (Fig. 3). The model clearly demonstrates how LT can be used to optimize, isolate, or otherwise control the level of a particular species. Notably, the behavior of systems in which successive ligand binding events do not contribute equally to the measured signal is readily simulated using the roots of the quartic equation by simply applying a scaling factor for each enzyme form and binding constant (see below); treating data in this way allows untransformed data to be fit directly without altering the error structure associated with the dataset.</p><!><p>Excel worksheets designed to simulate and/or least-squares fit homotropic ligand binding data for allosteric dimers and trimers are provided in the Supplementary material. As an example, these worksheets were used to simulate binding data for a negatively cooperative trimeric protein and to least-squares fit the resulting output (Fig. 4). ki values were chosen such that the affinities of the second and third ligands were 10- and 1000-fold weaker, respectively, than that of the first ligand (i.e., k2 = 10 × k1; k3 = 1000 × k1). The fractional saturation (Y) values were calculated with ±2% random error. The resulting best-fit ki estimates were within 7% of the true values. The worksheets can also treat models where the signals that report binding differ as each subunit becomes occupied.</p><!><p>Ligand binding is frequently monitored by spectral changes in the protein (e.g., absorbance, fluorescence, or magnetic resonance) across a range of ligand concentrations [1,38]. It is frequently assumed that the signal associated with the binding of a ligand to a given protomer is independent of ligand occupancy at the distal sites. The analytical method readily accommodates situations where bound species contribute different intensities to that signal. In this case, each protein species is assigned a relative signal value (Qi), which is analogous to the quantum yield in fluorescence. The signal intensity of the solution at a given concentration of protein and ligand (I) relative to that of the unliganded protein (I0) is equal to the fraction of bound protein, where each species is weighted by its Qi value (Eq. (21)): (21)II0=∑i=0nQiELiET Q0 (free protein) is defined as unity, Qi is equal to the I/I0 value for the species ELi, and Qn (fully liganded protein of n subunits) is equal to I/I0 at saturation. In the simplest case, where each ligand binding event contributes equally to the change in signal, the intermediate Qi values are proportional to ligand occupancy (Eq. (22)): (22)Qi=1+in(II0sat−1) When the intermediate Qi values diverge from the proportional values, least-squares fitting may be used to estimate them if ki values are known. Conversely, if preliminary experiments can establish Qi values, these can be taken into account when fitting for ki. In this way, spectroscopically silent steps may be accounted for in the model. As an example, cytochrome P450 3A4, an enzyme that metabolizes more than one-third of common drugs, exhibits cooperative homotropic binding of up to three ligands (e.g., testosterone), where each enzyme form ELi catalyzes the reaction at a different rate and exhibits an altered spin state of the heme iron [13]. Electron paramagnetic resonance experiments that report on the spin state require enzyme concentrations much greater than Kd, thereby precluding use of the Adair equation in analysis [29]. The method presented here allows both kinetic and spectral data to be fit (simultaneously if desired) to parameters that provide a detailed description of the system, including the heterogeneity and interaction of the binding sites as well as differential properties of each enzyme form. Finally, spectroscopic signals coming from the ligand may be monitored instead of protein; this modality may be treated by substituting L for E and LT for ET in Eq. (21).</p><!><p>Equations describing the exact concentrations of ligand and protein species at equilibrium as a function of their total concentrations and dissociation constants have been presented for the dimeric and trimeric cases. The equations provide a simple means of calculating the distribution of species in complex allosteric systems and of fitting ligand binding data to LT rather than assuming L = LT. Removing this assumption can significantly enhance accuracy of the fit estimates. The method is general in that it takes into account positive and negative cooperativity at each step and allows discrete signal contributions from each of the enzyme forms.</p>

PubMed Author Manuscript

Rates of insulin secretion in INS-1 cells are enhanced by coupling to anaplerosis and Kreb\xe2\x80\x99s cycle flux independent of ATP synthesis

Mechanistic models of glucose stimulated insulin secretion (GSIS) established in minimal media in vitro, may not accurately describe the complexity of coupling metabolism with insulin secretion that occurs in vivo. As a first approximation, we have evaluated metabolic pathways in a typical growth media, DMEM as a surrogate in vivo medium, for comparison to metabolic fluxes observed under the typical experimental conditions using the simple salt-buffer of KRB. Changes in metabolism in response to glucose and amino acids and coupling to insulin secretion were measured in INS-1 832/13 cells. Media effects on mitochondrial function and the coupling efficiency of oxidative phosphorylation were determined by fluorometrically measured oxygen consumption rates (OCR) combined with 31P-NMR measured rates of ATP synthesis. Substrate preferences and pathways into the TCA cycle, and the synthesis of mitochondrial 2nd messengers by anaplerosis were determined by 13C-NMR isotopomer analysis of the fate of [U-13C]glucose metabolism. Despite similar incremental increases in insulin secretion, the changes of OCR in response to increasing glucose from 2.5 to 15 mM were blunted in DMEM relative to KRB. Basal and stimulated rates of insulin secretion rates were consistently higher in DMEM, while ATP synthesis rates were identical in both DMEM and KRB, suggesting greater mitochondrial uncoupling in DMEM. The relative rates of anaplerosis, and hence synthesis and export of 2nd messengers from the mitochondria were found to be similar in DMEM to those in KRB. And, the correlation of total PC flux with insulin secretion rates in DMEM was found to be congruous with the correlation in KRB. Together, these results suggest that signaling mechanisms associated with both TCA cycle flux and with anaplerotic flux, but not ATP production, may be responsible for the enhanced rates of insulin secretion in more complex, and physiologically-relevant media.

rates_of_insulin_secretion_in_ins-1_cells_are_enhanced_by_coupling_to_anaplerosis_and_kreb\xe2\x80\x

Introduction<!>Cell culture<!>13C-Isotopomer studies of anaplerotic pathways<!>Metabolite Analysis<!>Oxidative Phosphorylation: 31P-NMR Measured Rates of ATP Synthesis and Fluorometric Measured Rates of Oxygen Consumption<!>Oxygen consumption rates<!>Viability of entrapped cells as determined by OCR<!>Statistical analyses<!>Media effects on insulin secretion rates, oxygen consumption rates (OCR), and rates of ATP synthesis<!>ATP synthesis in DMEM and KRB<!>Media effects on the correlation of Insulin Secretion Rates with Anaplerosis<!>

<p>Mechanistic models of glucose stimulated insulin secretion (GSIS) established in minimal media in vitro, may not accurately describe the complexity of coupling metabolism with insulin secretion that occurs in vivo. Central to the mechanism of nutrient-stimulated insulin secretion is that increases in mitochondrial oxidative phosphorylation lead to increases in cytosolic ATP concentrations that initiate the cascade of events leading to insulin exocytosis [1]. As a first approximation, one would predict that changes in the rate of oxidative phosphorylation should be directly proportional to changes in oxygen consumption rates (OCR) and insulin secretion. Surprisingly though, the correlation between OCR (and presumably oxidative phosphorylation) and insulin secretion has been shown to depend upon the complexity of the media [2]. In mouse βHC9 cells, Papas and Jerema [2] observed the change in insulin secretion was proportional to the change in OCR, when the cells were stimulated with 15mM glucose in minimal media (PBS). These results are in agreement with the predictions of the role of mitochondrial ATP production leading to closure of the KATP channel to increase Ca2+ and trigger insulin exocytosis. However, despite a 2-fold increase in insulin secretion in response to 15mM glucose, there was no observed change in OCR, and presumably oxidative phosphorylation, in more nutrient-complex Dubelco's Minimal Eagle Media (DMEM) buffer.</p><p>Possible explanations to account for this anomalous disassociation between insulin secretion rates and OCR include media-associated changes in 1.) mitochondrial coupling of ATP synthesis with flux of the electron transport chain and oxygen consumption, 2.) anaplerosis-dependant increases in the export of mitochondria 2nd messengers, or possibly 3.) the induction of other cytosolic signaling intermediates or pathways that are coupled to insulin secretion.</p><p>In order to shed light on which of these potential mechanisms may account for the disassociation of nutrient-stimulated insulin secretion from OCR and possibly oxidative phosphorylation, we evaluated the correlation of fuel-stimulated insulin secretion with 1.) the putative uncoupling of mitochondrial oxidative phosphorylation, and 2.) the rates of mitochondrial anaplerosis. We used 31P-NMR to measure rates of ATP synthesis and to measure the concentrations of ATP and intracellular Pi that occurred upon stimulating insulin secretion by increasing glucose from 2.5 mM to 15 mM [3, 4]. OCRs were measured under identical conditions fluorometrically in a sealed, stirred bioreactor [2, 5]. To assess the possibility that mitochondrial anaplerotic flux and the synthesis of putative 2nd messengers may provide an explanation for the disconnect between oxygen consumption and insulin secretion in the complex media, we used a 13C-isotopomer approach to determine pathways of anaplerosis in response to the secretagogues of glucose, glutamine and leucine [6, 7]. The studies described herein evaluated these correlations using the rat insulinoma cell line INS-1 832/13 [8] in the physiologically-complex DMEM for comparison to results obtained in KRB.</p><!><p>Initial stocks of clonal INS-1 832/13 cells, overexpressing the human insulin gene, were obtained from the laboratory of Dr. Christopher B. Newgard (Duke University School of Medicine) [8]. INS-1 cells were cultured as monolayers in RPMI-1640 as previously described [6].</p><p>Basal metabolic parameters were measured at 2.5 mM glucose, in order to maintain stable intracellular ATP concentrations, while avoiding nutrient-starvation. In preliminary NMR experiments, we observed that culture of the cells at 0 mM glucose in KRB led to a rapid fall in ATP concentrations and loss of cell viability. The addition of glucose to these ATP-deficient cells then led to a burst of ATP production to re-establish more physiologically-sustainable concentrations of ATP. In contrast, with 2.5 mM glucose, ATP concentrations remained stable and cell viability was maintained during a 24-hour perfusion.</p><!><p>Flux of metabolites via the anaplerotic pathways of pyruvate carboxylase (PC) or glutamate dehydrogenase (GDH), relative to the tricarboxylic acid (TCA) cycle, were determined by analysis and modeling of the 13C-isotopomer pattern in glutamate as previously described [6, 7]. Briefly, basal conditions were established with a 2 hr pre-incubation in DMEM with a sub-stimulatory concentration of glucose (2.5 mM). The cells were then washed with PBS, and then incubated for an additional 2 hrs in DMEM with [U-13C] glucose (Cambridge Isotope Laboratories, Miamisburg, OH, 99% 13C, 2.5 mM or 15 mM), alone or supplemented with 4 mM glutamine and 10 mM leucine. Media aliquots were taken and placed on ice for insulin analysis at 0, 1, and 2 hrs. At the end of the 2 hr isotopic labeling period, the cells were quenched and extracted for 13C-NMR analysis. Relative 13C enrichment and isotopomer distribution of glutamate was determined by 13C-NMR spectroscopy with an AVANCE 500-MHz spectrometer (Bruker Instruments, Inc. Billerica, MA) [6].</p><!><p>Total protein was measured spectrophotometrically, based on the method of Bradford (Bio-Rad). Insulin was determined by ELISA for rat insulin (100% cross-reactivity to human insulin, ALPCO).</p><!><p>ATP synthesis rates of alginate-encapsulated INS-1 cells were determined in real time using a 31P-NMR saturation transfer pulse sequence, as previously described [3, 4]. Briefly, INS-1 cells were perifused with KRB or DMEM (flow=1.0 ml/min, 37 °C) in the bioreactor in the bore of the AVANCE-500 NMR spectrometer. After a pre-equilibration period with 2.5 mM glucose, 31P-NMR spectra and saturation transfer experiments were acquired during step changes in secretagogues, glucose, and glutamine plus leucine. 31P-NMR spectra were continuously collected in 20-min experiments, with 3 to 4 measurements collected for each substrate level.</p><p>ATP synthesis rates were calculated from the intracellular Pi concentration and the ATP synthesis rate constant [3, 4]. Basal intracellular Pi (13.0±1.2 nmol/mg-protein) was measured using tandem mass spectrometry. The ATP synthesis rate constant was calculated from the longitudinal relaxation time of intracellular Pi, and the change in the intracellular Pi signal when the terminal phosphate of ATP is saturated compared to a control spectra (i.e., the saturation pulse is symmetrically offset from Pi resonance).</p><!><p>Oxygen consumption rates of freshly trypsinized cells or encapsulated cells were measured using a Fiber Optic Oxygen Monitor (Model 210, Instech Laboratories, Plymouth Meeting, PA) [5]. A 250 µl chamber was loaded with ~2×106 cells, or ~5 beads and changes in the oxygen concentration were monitored under buffer conditions and substrate additions identical to 31P-NMR experiments for measurement of ATP synthesis rates.</p><!><p>Freshly trypsinized cells were used for this work and the OCR was measured in three different media: DMEM, RPMI (as used for INS-1 cell culture) and G0-PBS. The fractional viability as measured with the Guava PCA (live/dead staining) was 97 ± 2% n=5 and was not significantly different in any of the three media. In addition viability measurements were conducted before and after the OCR measurement (by removing cells from the OCR chamber) and were not significantly different. OCR in glucose and glutamine-free PBS is 49±7 % (n=4) of that measured in RPMI and DMEM, and are in excellent agreement with measurements we have been making with entrapped INS-1 cells. We also conducted a measurement with pyruvate stimulation (2 mM) in G0-PBS and observed an increase of more than 100%, again in very close agreement with previous measurements in KRB and PBS with entrapped cells. These data suggest that the metabolic responsiveness of freshly trypsinized INS-1 cells is essentially the same as entrapped, overnight-cultured INS-1 cells used for our 31P-NMR studies of ATP synthesis.</p><!><p>All data are reported as means ± SEM. Unpaired two-tailed student's t-tests were used for comparisons between groups. Differences were considered statistically significant at P < 0.05.</p><!><p>As the original studies demonstrating the discrepancy between of correlation of OCR and insulin secretion rates in DMEM vs KRB were done in the mouse βHC9 cell line [2], we first needed to establish whether the observed media effects would hold true for β-cell lines from other rodent species. Over the past decade, the rat insulinoma cell line, INS-1 832/13 has become established as a valuable research tool to define the mechanisms of glucose-stimulated insulin secretion of human β-cells [8], and was therefore chosen for these studies.</p><p>In comparison to KRB, basal and stimulated insulin secretion rates from the INS-1 cells were higher in DMEM (Table 1). Basal ISRs were ~2.6-fold higher in DMEM. And increasing glucose to 15 mM, or the addition of 4 mM glutamine, led to a similar fold-increase in the insulin secretion rate for both KRB and DMEM. The responsiveness of OCR to changing glucose concentrations though, was different in KRB than in DMEM (Figure 1). Under both basal and stimulatory conditions, OCRs were consistently higher in DMEM in comparison to KRB (Figure 1). At 2.5 mM glucose, OCR was ~2-fold higher in DMEM in comparison to KRB. Raising glucose concentration to 10 mM in KRB, resulted in a robust 40% increase in OCR with a further ~10% increment upon increasing glucose to 20 mM. In contrast, in DMEM there was no significant change in OCR upon raising glucose from 2.5 mM to 10 or 20 mM. These results are consistent with those previously reported by Papas and Jarema [2], and prompted us to look more closely at the mechanisms responsible for the apparent discrepancy between the relatively large changes in glucose-stimulated changes in OCR and insulin secretion rates observed in KRB, when compared to a more physiologically relevant DMEM. The anomalies of OCR and ISR, led us to ask whether there were differences in the efficiency of coupling glucose metabolism with rates of mitochondrial oxidative phosphorylation in DMEM compared to KRB. To answer this, we used 31P-NMR saturation-transfer experiments to measure ATP synthesis rates in real time under basal and nutrient-stimulated conditions [3, 4].</p><!><p>Entrapped INS-1-derived cells were perfused in the bioreactor in the bore of the NMR spectrometer and 20-minute 31P-NMR spectra were acquired to measure intracellular Pi concentration and ATP synthesis rates during step changes in glucose and glutamine. From the saturation transfer experiments, the rate constant, kATP was measured (Figure 2A), and the rate of ATP synthesis (Figure 2C) was then calculated as the product of the kATP and the concentration of intracellular phosphate (Figure 2B). Although, kATP and ATP synthesis rates are proportional, the striking decrease in the intracellular Pi in response to secretagogues blunted the magnitude of changes in ATP synthesis in comparison to the much more dynamic changes in kATP.</p><p>In contrast to the elevated oxygen consumption rates in DMEM compared to that in KRB, we found that ATP synthesis rates were identical under all conditions in both KRB and in DMEM. The addition of glutamine, or raising glucose to 15 mM led to an identical increase in the ATP synthesis rate in both media. The rates of ATP synthesis led to similar levels of ATP at both low and high glucose in both media (G2.5: KRB=10.3±0.7 and DMEM=14.5±2.0, G15: KRB=10.3±0.7 and DMEM=13.8±0.7; KRB data from reference 6). The rates of ATP synthesis combined with the OCR results indicate a greater degree of mitochondrial uncoupling in DMEM relative to that in KRB.</p><p>The substantially elevated rates of both basal and stimulated insulin secretion in DMEM in comparison to KRB (Table 1), despite the similar of rates of ATP production at both 2.5 to 15 mM (Figure 2) and ATP concentrations (Table 2), implicates coupling mechanisms other than the recognized action of increased ATP to ADP ratio to affect closure of the ATP-sensitive potassium channel [1]. We, and others, have shown that in KRB (and other simple buffers such as PBS), rates of insulin secretion are tightly correlated with the rate of anaplerosis (via PC and GDH) [6, 9]. This observed correlation has led to the hypothesis that insulin secretion is coupled to the export of mitochondrial 2nd messengers, such as malate and citrate, resulting from the high rates of anaplerosis observed in the mitochondria of the β-cell [10, 11]. To test the hypothesis that increased rates of anaplerotic flux could account for the augmented insulin secretion observed in DMEM, we used a 13C-labeling approach to quantify the relative contribution of anaplerotic inputs into the TCA cycle.</p><!><p>At basal glucose (2.5 mM), only ~one-half of the acetyl-CoA originated from exogenous glucose (Figure 3A) in DMEM. In figure 3A, the fraction of acetyl-CoA originating from exogenous glucose is represented as "PDH: [U-13C]glc". Anaplerotic flux accounted for 52±10% of carbon entry into the Kreb's cycle flux (Figure 3B), with approximately equivalent contributions from each of the anaplerotic pathways (i.e., PC from glucose: "PC: [U-13C]glc", PC from unlabeled substrate: "PC: unlabeled", and GDH from glutamate). This flux distribution is essentially the same as what we previously observed in KRB [6].</p><p>With the increase of glucose to 15 mM, ~85% of the acetyl-CoA supplying the TCA cycle came from exogenous glucose (Figure 3B). In contrast to the 3-fold increase in anaplerotic flux with the addition of 4 mM glutamine to basal KRB [6], the addition of 4 mM glutamine to glutamine-free DMEM had negligible effect on the total anaplerotic flux (sum of PC: [U-13C]glc, PC: unlabled, GDH flux = 62±15%). In KRB, we found that the majority of the increased anaplerosis was attributed to increased GDH flux [6]. In DMEM though, a slight reduction in PC flux was balanced by an increase in GDH flux to maintain a constant anaplerotic flux. Increasing glucose concentration to 15 mM in glutamine-free DMEM increased anaplerotic flux ~2-fold, mostly through an increase in PC flux of [U-13C]glucose. Exogenous glutamine, with 15 mM glucose, further enhanced anaplerotic flux, both through GDH and from PC flux, whereas the addition of leucine had no detectable activation of GDH flux. As in KRB [6], in DMEM the addition of leucine, at both low and high glucose, did not result in the expected activation of GDH flux and entry of glutamine into the TCA cycle [12, 13], but rather led to an increase in PC flux.</p><p>As previously established, insulin secretion rates strongly correlated with anaplerosis via pyruvate carboxylase flux. The correlation with insulin resistance was further strengthened by the sum of the PC anaplerosis and PDH flux of exogenous glucose [6]. Here, we found that these correlations held for flux rates in DMEM as well (ISR vs PC flux, R=0.873, ISR vs PDH+PC flux, R=0.894). In fact, the correlation in KRB was congruent that the correlation in DMEM (Figure 4 A and B). Combining the results reported here for DMEM (solid diamonds) with those found in KRB (open squares, data from [6]), we found a strong correlation of insulin secretion with PC (R2=0.669). In contrast, the correlation of ISR vs ATP synthesis rates in KRB and DMEM fell on two distinct and approximately parallel lines (Figure 4C).</p><p>The strong correlation between anaplerosis and rates of insulin secretion in DMEM and KRB, and especially their congruency, supports the hypothesis that the export of mitochondrial 2nd messengers couples responsive changes in mitochondrial metabolism to insulin secretion [6, 9–11]. A strong case has been made that the transfer of mitiochondrial reducing equivalents to cytosolic NADPH, by means of mitochondrial-cytosolic substrate cycling via pyruvate [10, 11, 14–17] could serve the role as a 2nd messenger. Intriguingly, the studies of Kibbey et al. [18, 19] on the phospho-enol-pyruvate cycle point towards a coupling and/or potentiating factor other than NADPH. But as yet, neither the identity of a distinct mitochondria-derived 2nd messenger, nor a definitive biochemical mechanisms linking cycling with insulin secretion has been established. The results presented here, and previously [6], suggest that signaling mechanisms tied to the rates of anaplerosis and the TCA cycle augment the signaling provided by ATP production, and are responsible for the enhanced rates of insulin secretion in more complex and physiologically-relevant media.</p><!><p>We studied media effects on mechanisms of insulin secretion of INS-1 cells.</p><p>Insulin secretion was higher in DMEM than KRB despite identical ATP synthesis rates.</p><p>Insulin secretion rates correlated with rates of anaplerosis and TCA cycle.</p><p>Mitochondria metabolism and substrate cycles augment secretion signal of ATP.</p><p>This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.</p>

PubMed Author Manuscript

Evaluating the Viability of Successive Ring‐Expansions Based on Amino Acid and Hydroxyacid Side‐Chain Insertion

AbstractThe outcome of ring‐expansion reactions based on amino/hydroxyacid side‐chain insertion is strongly dependent on ring size. This manuscript, which builds upon our previous work on Successive Ring Expansion (SuRE) methods, details efforts to better define the scope and limitations of these reactions on lactam and β‐ketoester ring systems with respect to ring size and additional functionality. The synthetic results provide clear guidelines as to which substrate classes are more likely to be successful and are supported by computational results, using a density functional theory (DFT) approach. Calculating the relative Gibbs free energies of the three isomeric species that are formed reversibly during ring expansion enables the viability of new synthetic reactions to be correctly predicted in most cases. The new synthetic and computational results are expected to support the design of new lactam‐ and β‐ketoester‐based ring‐expansion reactions.

evaluating_the_viability_of_successive_ring‐expansions_based_on_amino_acid_and_hydroxyacid_side‐chai

<!>Introduction<!><!>Introduction<!><!>Introduction<!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Computational chemistry: Method evaluation<!><!>Computational chemistry: Method evaluation<!><!>Computational chemistry: Method evaluation<!>Conclusions<!>Conflict of interest<!>

<p>A. Lawer, R. G. Epton, T. C. Stephens, K. Y. Palate, M. Lodi, E. Marotte, K. J. Lamb, J. K. Sangha, J. M. Lynam, W. P. Unsworth, Chem. Eur. J. 2020, 26, 12674.</p><!><p>Rearrangements that allow ring‐enlarged products to be prepared from smaller cyclic systems have much utility in synthetic chemistry.1, 2 Ring expansions are particularly useful for the synthesis of medium‐sized rings (8‐ to 11‐membered) and macrocycles (12+ membered), as alternatives to direct end‐to‐end cyclisations.3 End‐to‐end cyclisations can be difficult and unpredictable processes due to competing intermolecular coupling and other side reactions, and they often necessitate the use of impractical high‐dilution (or pseudo‐high‐dilution) conditions.4 In contrast, high dilution can often be avoided completely in well‐designed ring‐expansion systems.1, 2, 5</p><p>Side‐chain insertion ring‐expansion reactions (Scheme 1 a) are a useful sub‐class of ring expansion, as the requisite precursors are generally straightforward to prepare. Various methods in which the ring expansion is accompanied by concomitant C−O, C−N and C−C bond formation are known, and this topic has been recently reviewed.1a Amongst this class of reaction, our group has developed a series side‐chain insertion ring expansion processes that can be performed iteratively. These methods, which we have termed "Successive Ring Expansion" (SuRE) reactions,5 enable the controlled, iterative insertion of amino acid or hydroxyacid‐derived linear sequences into cyclic β‐ketoesters (4→6, Scheme 1 b)5a, 5b or lactams (7→9, Scheme 1 c).5c, 5d</p><!><p>Side‐chain insertion ring‐expansion reactions and Successive Ring Expansion (SuRE).</p><!><p>In our experience, the most important factor in determining the outcome of new ring‐expansion reactions of the types summarised in Scheme 1 b and c is ring size. This is well demonstrated by the outcomes of our published lactone‐forming ring expansions of imides of the form 10 (Scheme 2).5d Thus, for both α‐ and β‐hydroxyacid derived linear fragments (3‐ and 4‐atom ring expansions, respectively), there is a clear point at which ring expansion "switches on"; the reactions work for starting materials with rings that are eight‐membered or more for three‐atom expansions (m=1) and rings that are six‐membered or more for four‐atom expansions (m=2). The analogous reactions fail for smaller ring variants. We have previously postulated that these reactions are under thermodynamic control, and hence that the reaction outcomes depend on the relative Gibbs free energies of the three isomeric forms that the substrate must pass through for ring expansion to occur. This idea is supported by calculations performed at the DFT/B3LYP/6‐31G* level of theory;5d, 6, 7, 8 thus, five‐membered ring‐open form imide 12RO (RO=ring‐opened) was calculated to be significantly lower in Gibbs free energy than its isomeric ring‐closed (12RC, RC=ring‐closed) and ring‐expanded forms (12RE, RE=ring‐expanded), and this was replicated in the synthetic results, with imide 12RO being isolated in 99 % yield following hydrogenolysis of the parent benzyl protected imide (10, where n=2, m=1). Conversely, in the case of the analogous eight‐membered starting material (10, where n=5, m=1), the ring‐expanded form 13RE was calculated to be the most stable isomer, and upon testing the reaction, 13RE was isolated in 89 % yield, meaning that the calculations again were in line with the synthetic results.</p><!><p>Ring‐size dependency on the outcome of the ring expansion of imides into aza‐lactones. ΔG∘rel values are given in kcal mol−1.</p><!><p>These calculations, which drew inspiration from a similar approach used by Yudin and co‐workers,2d were done primarily to validate our ideas about the reactions being under thermodynamic control. In this work, we have explored the validity of using calculations of this type predictively. As we continue to develop this research programme, having a reliable predictive tool to inform the likelihood of new SuRE variants working before committing to labour‐intensive synthetic efforts will be of value. The utility of this approach is demonstrated herein; in total, 52 new ring‐expansion reactions have been attempted, with 48 successfully furnishing the desired ring‐expanded product. Our DFT/B3LYP/6‐31G* method correctly predicted the reaction outcome in almost all cases, and compared favourably when benchmarked against other alternative methods, including those that model solvation and dispersion interactions. Thus, we believe that this widely available DFT/B3LYP/6‐31G* approach will be useful to help assess the viability of new ring‐expansion reactions before committing to synthetic efforts.</p><!><p>We started by examining the ring expansion of simple lactams with sarcosine derivative 15. We had already shown that this acid chloride is compatible with our standard lactam ring expansion method (14→16, Scheme 3 a), but prior to this work, 13‐membered lactam 14 was the smallest aliphatic lactam on which we have reported a successful ring expansion with any linear α‐amino acid chloride.</p><!><p>Ring‐size dependency on the outcome of the ring expansion of imides with N‐methyl sarcosine derivatives. ΔG∘rel values are given in kcal mol−1 with thermal corrections at 298 K.</p><!><p>Prior to doing the synthetic chemistry, we ran DFT calculations based on the method used in our earlier study. To summarise this method, each of the three components of the equilibria deriving from five‐ to eight‐membered ring imide precursors 17RO‐20RO were optimised at the DFT/B3LYP/6‐31G* level of theory in vacuum.6, 7, 8 Conformational searches of the optimised structures were performed at the Molecular Mechanics Force Field level. All the generated structures were retained, and their energies were calculated using DFT/B3LYP/6‐31G*. The lowest energy geometry in each case was selected, fully optimised and determined to be minima by the absence of negative vibrational modes, in vacuum using DFT/B3LYP/6‐31G*. In each case, the relative free energies of the imide (17RO–20RO), ring‐closed (17RC–20RC), and ring‐expanded (17RE–20RE) isomers were calculated, with ΔG∘rel values quoted in kcal mol−1 (Scheme 3 b). More information about the choice of this method and method effects are included later in the manuscript;7 until then, the discussion will focus on the synthetic aspects and DFT/B3LYP/6‐31G* calculations.</p><p>In the five‐ to seven‐membered series, the imide isomers 17RO–19RO were calculated to be the most stable, thus suggesting that ring expansion is unlikely to proceed in these examples. This prediction was verified by synthetic results; thus, none of the ring‐expanded products 17RO–19RO were obtained when attempts were made to prepare them using the standard conditions, with no tractable products isolated from these reactions (17RO–19RO , Scheme 3 c). Conversely, the ring‐expanded isomer 20RE was calculated to be the lowest in free energy in the eight‐membered ring series, and this again was borne out in the synthetic results, with 20RE isolated in 82 % yield. Thus, the use of an eight‐membered ring starting material (or larger) appears to be the 'switch on' point for this series, as it was for the analogous lactone systems in Scheme 2. This is supported by the high yielding (66–94 %) ring expansions of 9–12‐membered lactam systems to form products 21RE–24RE under the standard conditions.</p><p>Medicinal interest in medium‐sized rings and macrocycles has increased significantly in the last decade,9 and the reaction variant described in Scheme 3 appears to be well suited for use in the preparation of peptoid‐containing macrocycles,10 as long as the starting lactam is an eight‐membered ring or larger. Thus, to better demonstrate its potential utility, we went on to investigate the range of N‐substituents that can be tolerated on the linear unit 26, with these results summarised in Scheme 4. In total, 24 new ring‐expansion reactions of this type have been performed, to make 27 a–y (27 k was described previously)5c using various functionalised amino acid‐derived linear fragments (26). Most of the reactions proceeded in high yield (the yield quoted is for the full N‐acylation/protecting group cleavage/rearrangement sequence) under the standard reaction conditions, significantly expanding the range and diversity of amino acid derivatives that have been demonstrated in the SuRE method to date.</p><!><p>Scope of lactam ring‐expansion reactions with N‐functionalised amino acids.</p><!><p>All the new SuRE reactions presented in Scheme 4 worked (at least to some degree), although there were a few outliers that were lower yielding (e.g., furan‐derivative 27 v). In these cases, we believe that the lower yield is not caused by an inherent difference in the thermodynamics of the ring expansion equilibrium (i.e., the relative free energies of the analogous isomers 27 vRO, 27 vRC and 27 vRE are in line with those for the methyl analogue 20, see SI for full details)11 but can be explained by substrate‐dependent side reactions or problems with the preceding N‐acylation step. For example, in the case of furan derivative 27 v, the lower yield is largely due to incomplete N‐acylation (step i), which in turn is likely to be a consequence of the relative instability of the acid‐sensitive furan motif. Unexpected side reactions/degradation also cannot be ruled out during the ring‐expansion reaction (step ii) in cases where more reactive functional groups are involved.</p><p>Next, we examined the ring expansions of cyclic β‐ketoesters. These reactions were the subject of our first two publications in this area,5a, 5b which focused mainly on the insertion of β‐amino acid derived linear fragments; for example, five‐ to eight‐ and 12‐membered cyclic β‐ketoesters (28) were all found to undergo smooth ring expansion (to form products of the type 30) upon reaction under the reported conditions with β‐alanine derived acid chloride 29 (Scheme 5 a).5a DFT/B3LYP/6‐31G* calculations were performed to measure the energies of the equilibrating isomers of the five‐, six‐, and 12‐membered ring systems 31–33 as before. Pleasingly, the calculations suggest that the ring‐expanded isomers are lowest in energy by a clear margin, suggesting that there is a strong thermodynamic driving force for ring expansion in this series (Scheme 5 b). To complete the synthetic series, we went on to perform the ring expansion of nine‐ to 11‐membered β‐ketoesters for the first time, with these new synthetic reactions proceeding well, affording lactams 34–36 (52–74 %, Scheme 5 c).</p><!><p>Ring‐size dependency of the outcome of the ring expansion of β‐ketoesters with β‐alanine‐derived acid chloride 29. ΔG∘rel values are given in kcal mol−1.</p><!><p>The hydroxyacid‐based analogue of this cyclic β‐ketoester ring expansion was less well developed, with the expansion of seven‐membered 37 the only example of this type featured in our previous publications to have been performed on a simple cyclic β‐ketoester (Scheme 6 a). Given the importance of macrocyclic lactones in medicinal chemistry,12 we decided to test whether the scope of this variant could be expanded. As was done for the analogous amino acid system, DFT/B3LYP/6‐31G* calculations were performed to measure the energies of the equilibrating isomers of the five‐, six‐, and 12‐membered ring systems 40–42 (Scheme 6 b), which again suggested that there is a clear thermodynamic driving force for ring expansion. Pleasingly, the corresponding synthetic experiments all worked well, with five‐ to eight‐membered β‐ketoesters undergoing C‐acylation, hydrogenolysis and ring expansion to give ring‐expanded lactones 39, 40RE, 41RE and 43 all in comparable yields (Scheme 6 c). In a small change to the published conditions shown in Scheme 6 a, we found that performing the hydrogenolysis in ethyl acetate (rather than methanol) and then stirring with triethylamine in chloroform led to superior reaction yields. The main reason the isolated yields are in the 50–60 % range (and not higher) is due to loss of material during the C‐acylation step (especially the work‐up, during which the magnesium salts can cause problems with phase separation) and these results are in line with typical yields in our previous papers.5a, 5b</p><!><p>Ring‐size dependency of the outcome of the ring expansion of β‐ketoesters with β‐hydroxy acid chloride 38. ΔG∘rel values are given in kcal mol−1. i) β‐ketoester, 38, MgCl2, pyridine, CH2Cl2, RT; ii) Pd/C H2, EtOAc, 3 h, RT; NEt3, CHCl3, RT, 18 h.</p><!><p>We then went on to test other lactam‐based ring expansion systems with additional functionality present in the starting lactams. Hydroxyacid and amino acid derivatives 38 and 46 were used to exemplify the synthetic reactions, and in the calculations for 46, a simplified N‐methyl (rather than N‐benzyl) derivative was used (i.e., from 47) as this significantly reduced the computational time but was found to have very little impact on the calculations.13 Thus, we started by examining lactams containing α‐heteroatoms (52, 55, 58 and 60) with amino acid and hydroxyacid derivatives 38 and 46. The analogous heteroatom‐free variants of these reactions had been tested in our earlier work (Scheme 7 a) and were shown to be high yielding. Therefore, based purely on our chemical intuition at this stage, we did not expect to see much variation upon switching to these new systems. However, starting from six‐membered lactam 52, a much lower isolated yield (41 %) of the ring‐expanded product 53RE was obtained in the amino acid series, while the ring‐expanded lactone 54RE was isolated as an inseparable mixture with its ring‐opened imide form 54RO. The calculations give clues as to why these reactions did not proceed well; for example, the ring‐opened and ring‐expanded isomers 53RO and 53RE were calculated to have very similar Gibbs free energies, thus suggesting that both may be formed in this reaction, although only the relatively non‐polar product 53RE was isolated after chromatography, in modest yield. Compounds 54RO and 54RE were also calculated to be similar in free energy and in this case a mixture of products was isolated. Conversely, upon moving to seven‐membered starting material 55, a clear preference for the ring‐expanded isomer was predicted by the calculations, which manifested in much improved synthetic yields for the desired ring‐expanded isomers (70 and 75 % for 56RE and 57RE respectively).</p><!><p>Lactam ring‐expansion reactions and DFT calculations. ΔG∘rel values are given in kcal mol−1.</p><!><p>In contrast to oxygen‐containing 52 and 55, sulfur‐containing lactams 58 and 60 both performed well in the synthetic ring‐expansion reactions with 46;14 ring‐expanded products 59RE and 61RE were each formed in good yield. This was again mirrored in the calculations, with 59RE and 61RE calculated to be the lowest energy isomers in each case by clear margins. The difference in reactivity between 52 and 58, which is presumably a result of some relatively subtle stereoelectronic effects and/or differences in bond lengths, is not something that we would have predicted without the calculations.</p><p>We also examined benzannulated, fluorinated and branched lactam starting materials 62, 65, 68 and 70, and as before, the predictive ability of the calculations was retained. Indeed, the ability to predict when reactions will fail completely is also important; for example, the ring‐opened imide isomer 64RO was calculated to be the most stable isomer in this series, and this was corroborated by the synthetic results.</p><p>In general, we have found that for systems in which the ring‐expanded isomer is calculated to be the lowest in energy by more than 3 kcal mol−1, then the reactions tend to work reliably. In cases where the free energy difference is less than 3 kcal mol−1, the reaction outcomes are less predictable, often giving low yields of ring‐expanded products and/or mixtures. The reactions to form ring‐expanded products 69RE and 72RE, which were isolated in modest 30 and 45 % yields, respectively, are outliers in terms of yield, but the lower yields in these cases simply reflect the fact that the N‐acylation step did not proceed to completion in either case. Indeed, an important caveat to keep in mind when using this DFT/B3LYP/6‐31G* method is that it only gives an indication of the chances of achieving a favourable equilibrium. It does not account for the efficiency of the synthetic steps that take place before the equilibrium, the possibility of off‐equilibrium side reactions or other kinetic effects.</p><p>As all the ring‐expanded products described in this manuscript were made using SuRE methods, they are all, in theory, potential starting materials for further ring‐expansion reactions. Representative examples of products (73–77) that have been expanded for a second time in our earlier work are shown in Figure 1, with the second linear fragment inserted highlighted in red. After undergoing one ring expansion, the rings should all be large enough that they are beyond the "switch on" point for any of the ring‐expansion reaction types that we have studied and calculated (not withstanding any effects resulting from the additionally added functional groups) and should therefore be thermodynamically favourable. This is corroborated by our work to date in which several successful successive ring‐expansion reactions are reported. This does not mean that performing additional iterations is always routine (e.g., in some cases, the acylation reactions can be more difficult on these more functionalised systems, sometimes requiring additional equivalents of acid chloride),5c, 5d but once acylation has been achieved, ring expansion is typically straightforward. Three new examples of doubly ring‐expanded products (78–80, see the Supporting Information for reaction conditions), based on new substrates made for the first time in this manuscript, have been performed and are reported here for completeness.</p><!><p>Successive ring expansion products.</p><!><p>The DFT/B3LYP/6‐31G* methodology used has demonstrated, in both this and previous work,5d good success in predicting the outcome of SuRE reactions. Calculations at the B3LYP/6‐31G* level are relatively computationally efficient, but do not take into consideration effects such as solvation and dispersion. These additions are typically used to improve the accuracy of such calculations, therefore, we decided to benchmark their effects, along with a range of functionals, in order to determine any potential method‐effects in the calculations.</p><p>For this study general gradient approximation, GGA (BP86), hybrid (B3LYP and PBE0) and meta‐hybrid (M06 and M06‐2X) functionals were used. Solvation effects were applied using a PCM model with either dichloromethane or chloroform as relevant to simulate the reaction conditions. The effects of dispersion are inherently taken into consideration by the M06 and M06‐2X functionals.15 They were also applied using the Grimme's D3 method with Becke‐Johnson damping16 to a PBE0/def2‐TZVPP single‐point calculation, using the geometry and thermodynamic corrections from a BP86/SV(P) calculation; this method has been used successfully by our groups in previous projects,17 and also tests the effect of a large triple zeta basis set.18</p><p>Initially, a wide range of methods were benchmarked against structures 17–20, by reoptimising the structures from the B3LYP/6‐31G* calculations and comparing the relative energies with the experimental outcomes (Table 1). Structures with which the ring‐closed isomer has a larger energy than the ring‐opened or ring‐expanded isomers (17, 19 and 20), produced the most comparable results, with there being little difference when using GGA or hybrid functionals with the 6‐31G* basis set.</p><!><p>Relative difference of Gibbs energies at 298 K for structures 17–20 at different levels of theory. Solvent corrections were applied using a PCM model. * Geometry from the BP86/SV(P) level.</p><p></p><p>Compound</p><p>Functional</p><p>Basis set</p><p>Solvent correction</p><p>Empirical dispersion correction</p><p>RO [kcal mol−1]</p><p>RC [kcal mol−1]</p><p>RE [kcal mol−1]</p><p>Yield RE [%]</p><p>17 (n=1)</p><p>B3LYP</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>16.5</p><p>1.9</p><p>0</p><p>B3LYP</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>14.9</p><p>0.2</p><p>BP86</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>14.9</p><p>1.6</p><p>PBE0</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>14.1</p><p>1.2</p><p>M06</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>10.8</p><p>−2.1</p><p>M06‐2X</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>8.7</p><p>−1.6</p><p>BP86</p><p>SV(P)</p><p>PCM</p><p>N</p><p>0.0</p><p>11.5</p><p>−2.1</p><p>PBE0*</p><p>def2‐TZVPP</p><p>PCM</p><p>D3(BJ)</p><p>0.0</p><p>9.2</p><p>−3.3</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>18 (n=2)</p><p>B3LYP</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>3.9</p><p>2.1</p><p>0</p><p>B3LYP</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>2.2</p><p>−1.1</p><p>BP86</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>0.5</p><p>−1.1</p><p>PBE0</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>−0.6</p><p>−1.6</p><p>M06</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>−3.0</p><p>−3.8</p><p>M06‐2X</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>−4.5</p><p>−4.1</p><p>BP86</p><p>SV(P)</p><p>PCM</p><p>N</p><p>0.0</p><p>−1.2</p><p>−3.0</p><p>PBE0*</p><p>def2‐TZVPP</p><p>PCM</p><p>D3(BJ)</p><p>0.0</p><p>−3.0</p><p>−5.3</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>19 (n=3)</p><p>B3LYP</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>6.4</p><p>0.7</p><p>0</p><p>B3LYP</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>6.2</p><p>−0.3</p><p>BP86</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>5.5</p><p>−0.4</p><p>PBE0</p><p>6‐31G*</p><p>N</p><p>N</p><p>0.0</p><p>4.4</p><p>−1.3</p><p>M06</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>1.1</p><p>−3.8</p><p>M06‐2X</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>0.0</p><p>−0.5</p><p>−3.4</p><p>BP86</p><p>SV(P)</p><p>PCM</p><p>N</p><p>0.0</p><p>2.7</p><p>−1.8</p><p>PBE0*</p><p>def2‐TZVPP</p><p>PCM</p><p>D3(BJ)</p><p>0.0</p><p>0.7</p><p>−5.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>20 (n=4)</p><p>B3LYP</p><p>6‐31G*</p><p>N</p><p>N</p><p>7.3</p><p>14.1</p><p>0.0</p><p>82</p><p>B3LYP</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>9.9</p><p>16.1</p><p>0.0</p><p>BP86</p><p>6‐31G*</p><p>N</p><p>N</p><p>8.3</p><p>13.8</p><p>0.0</p><p>PBE0</p><p>6‐31G*</p><p>N</p><p>N</p><p>8.8</p><p>13.3</p><p>0.0</p><p>M06</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>12.2</p><p>12.8</p><p>0.0</p><p>M06‐2X</p><p>6‐31G*</p><p>PCM</p><p>N</p><p>11.4</p><p>10.5</p><p>0.0</p><p>BP86</p><p>SV(P)</p><p>PCM</p><p>N</p><p>11.1</p><p>13.6</p><p>0.0</p><p>PBE0*</p><p>def2‐TZVPP</p><p>PCM</p><p>D3(BJ)</p><p>13.4</p><p>14.0</p><p>0.0</p><!><p>Modelling the effects of solvation also had little effect on the relative energy differences when using the hybrid B3LYP functional. Comparable results are observed both with and without solvent corrections. However, this does not extend to the BP86/SV(P) calculations, with more significant relative energy differences observed when compared to the standard B3LYP/6‐31G* calculations, which appears to come from greater stabilisation of the ring‐closed and ring‐expanded isomers than the ring‐opened when solvent is included.</p><p>The effects of dispersion had the greatest impact on the expected outcomes of the experiments, with the M06, M06‐2X and D3(BJ)‐PBE0 calculations showing lower relative energies for the ring‐closed and ring‐expanded isomers, predicting that ring expansion should be comparatively more thermodynamically favourable in these examples, and in some cases contradicting the experimental results. We believe that due to the side chain present in the ring‐opened structures being directed away from the ring, there are fewer stabilising interactions present than compared to the ring‐closed or expanded isomers. As a consequence of these different molecule geometries, it appears that modelling the dispersion interactions may result in the stability of the ring‐expanded isomer being overpredicted when compared to the ring‐opened form. This alters the expected reaction outcome where the B3LYP/6‐31G* calculations predict these isomers to be similar in energy.</p><p>With dispersion effects having a large effect on the relative energy differences and the predicted thermodynamic outcomes on these examples, the study was extended to include these effects to several other systems, using the M06‐2X/6‐31G* methodology. A comparison between this method and B3LYP/6‐31G* is presented in Table 2. As observed with structures 17–20 (Table 1), the main difference between the two methods is that, when compared to the ring‐expanded form, the relative energies of the ring‐closed forms are lower at the M06‐2X/6‐31G* level (Δave=−5.2 kcal mol−1), and ring‐opened isomers increased (Δave=3.1 kcal mol−1). In most instances this doesn't change the expected outcome of the reaction, however, where there is a smaller difference in the energy of the ring‐opened and ring‐expanded isomers (see 53, 63 and 64), this does result in ring expansion being predicted to be favourable. Notably in some examples the intermediate ring‐closed isomer becomes lower in energy than the ring‐opened, however, this does not seem to correlate to any observable difference in how well the reaction proceeds experimentally (see 32, 40 and 69 for examples).</p><!><p>Relative difference of Gibbs energies at 298 K. Solvent corrections were applied using a PCM model with either dichloromethane or chloroform as relevant for the M06‐2X/6‐31G* calculations. See the Supporting Information for absolute energies. Blue numbers denotes the most significant differences between the two methods >3 kcal mol−1. Δave is defined as the mean value of the energy at M06‐2X/6‐31G*—energy at B3LYP/6‐31G*.</p><p>Compound</p><p>Functional/</p><p>RO</p><p>RC</p><p>RE</p><p>Yield</p><p></p><p>basis set</p><p>[kcal mol−1]</p><p>[kcal mol−1]</p><p>[kcal mol−1]</p><p>RE [%]</p><p>31</p><p>B3LYP/6‐31G*</p><p>10.0</p><p>12.6</p><p>0.0</p><p>675a</p><p>M06‐2X/6‐31G*</p><p>12.5</p><p>10.2</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>32</p><p>B3LYP/6‐31G*</p><p>8.1</p><p>9.7</p><p>0.0</p><p>825a</p><p>M06‐2X/6‐31G*</p><p>10.5</p><p>3.7</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>33</p><p>B3LYP/6‐31G*</p><p>36.6</p><p>45.4</p><p>0.0</p><p>805a</p><p>M06‐2X/6‐31G*</p><p>38.0</p><p>34.7</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>40</p><p>B3LYP/6‐31G*</p><p>9.3</p><p>11.8</p><p>0.0</p><p>59</p><p>M06‐2X/6‐31G*</p><p>11.7</p><p>8.1</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>41</p><p>B3LYP/6‐31G*</p><p>10.8</p><p>10.3</p><p>0.0</p><p>56</p><p>M06‐2X/6‐31G*</p><p>10.3</p><p>3.7</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>42</p><p>B3LYP/6‐31G*</p><p>35.2</p><p>39.8</p><p>0.0</p><p>–</p><p>M06‐2X/6‐31G*</p><p>32.6</p><p>30.5</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>53</p><p>B3LYP/6‐31G*</p><p>0.0</p><p>9.7</p><p>0.0</p><p>41</p><p>M06‐2X/6‐31G*</p><p>6.9</p><p>7.1</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>54</p><p>B3LYP/6‐31G*</p><p>2.9</p><p>9.2</p><p>0.0</p><p>67[a]</p><p>M06‐2X/6‐31G*</p><p>5.0</p><p>4.5</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>56</p><p>B3LYP/6‐31G*</p><p>5.5</p><p>17.9</p><p>0.0</p><p>70</p><p>M06‐2X/6‐31G*</p><p>11.7</p><p>13.8</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>57</p><p>B3LYP/6‐31G*</p><p>10.4</p><p>19.6</p><p>0.0</p><p>75</p><p>M06‐2X/6‐31G*</p><p>11.2</p><p>13.8</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>59</p><p>B3LYP/6‐31G*</p><p>6.7</p><p>18.4</p><p>0.0</p><p>99</p><p>M06‐2X/6‐31G*</p><p>12.0</p><p>13.1</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>61</p><p>B3LYP/6‐31G*</p><p>10.9</p><p>20.3</p><p>0.0</p><p>73</p><p>M06‐2X/6‐31G*</p><p>14.5</p><p>15.1</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>63</p><p>B3LYP/6‐31G*</p><p>−2.5</p><p>13.4</p><p>0.0</p><p>40</p><p>M06‐2X/6‐31G*</p><p>2.8</p><p>10.0</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>64</p><p>B3LYP/6‐31G*</p><p>−3.3</p><p>10.6</p><p>0.0</p><p>0</p><p>M06‐2X/6‐31G*</p><p>0.5</p><p>6.8</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>66</p><p>B3LYP/6‐31G*</p><p>5.9</p><p>24.2</p><p>0.0</p><p>77</p><p>M06‐2X/6‐31G*</p><p>9.4</p><p>19.1</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>67</p><p>B3LYP/6‐31G*</p><p>3.9</p><p>17.7</p><p>0.0</p><p>71</p><p>M06‐2X/6‐31G*</p><p>6.0</p><p>12.8</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>69</p><p>B3LYP/6‐31G*</p><p>3.9</p><p>11.2</p><p>0.0</p><p>30</p><p>M06‐2X/6‐31G*</p><p>9.2</p><p>5.7</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>71</p><p>B3LYP/6‐31G*</p><p>3.5</p><p>19.6</p><p>0.0</p><p>84</p><p>M06‐2X/6‐31G*</p><p>9.8</p><p>14.5</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p>72</p><p>B3LYP/6‐31G*</p><p>4.8</p><p>14.5</p><p>0.0</p><p>45</p><p>M06‐2X/6‐31G*</p><p>6.6</p><p>9.2</p><p>0.0</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>Δave</p><p>3.1</p><p>−5.2</p><p>0.0</p><p>[a] Isolated as a mixture (54RE/54RO 4:3).</p><!><p>Thus, for either method, both the B3LYP and M06‐2X functionals correctly predicts the expected reaction outcomes in the majority of cases, although on average, it is the B3LYP method that more closely correlates with the experimental findings, despite the fact that the M06‐2X functional usually performs better for organic molecules due to the inclusion of dispersion corrections.15, 19 Therefore, we believe that these results clearly demonstrate that the B3LYP/6‐31G* methodology is suitable as an aid for predicting the outcome of SuRE reactions, balancing computational efficiency with good prediction of reaction outcome. The observation that a greater than 3 kcal mol−1 energy difference between ring‐opened and ring‐expanded isomers is needed to more confidently predict the outcome of the reaction, is based upon the inherent computational accuracy of these calculations</p><!><p>In summary, we have significantly expanded the scope of various classes of SuRE reaction, and have shown that the reaction outcomes can be predicted based on the relative Gibbs free energies of three isomeric species in equilibrium by using DFT calculations.20 Useful conclusions can also be drawn from the significantly expanded synthetic scoping reactions and a total of 48 new ring‐expanded products are reported in this manuscript. In most cases, the isomer calculated to be lowest in energy was the major product obtained in the corresponding synthetic results.</p><p>Of course, any computational predictive method of this type will never be 100 % accurate, especially given how difficult it is to model the properties and conformations of relatively flexible systems like macrocycles.21 In view of this, the approximations involved in the calculations and the possibility that kinetic effects might prevent equilibrium being reached in some reaction systems, we do not recommend using the calculations to make quantitative predictions on reaction yields or the Boltzmann distribution of the isomers in the presumed equilibria. The guideline that a free energy difference of more than 3 kcal mol−1 in favour of the ring‐expanded isomer when using the B3LYP/6‐31G* methodology usually leads to a successful reaction is a qualitative observation, that this was true in all such cases tested in which the preceding acylation step was efficient. It should not be considered a hard rule. However, as a guide to assessing the viability of new ring‐expansion reactions before embarking on synthetic effort, we do believe that this DFT/B3LYP/6‐31G* method, which is widely implemented across the vast majority of computational chemistry packages, has practical utility and will be useful in directing future synthetic efforts, in our group and others.</p><!><p>The authors declare no conflict of interest.</p><!><p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p><p>Supplementary</p><p>Click here for additional data file.</p>

PubMed Open Access

Ultra-long Magnetic Nanochains for Highly Efficient Arsenic Removal from Water

The contamination of drinking water with naturally occurring arsenic is a global health threat. Filters that are packed with adsorbent media with a high affinity for arsenic have been used to de-contaminate water \xe2\x80\x94 generally iron or aluminium oxides are favored materials. Recently, nanoparticles have been introduced as adsorbent media due to their superior efficiency compared to their bulk counter-parts. An efficient nanoadsorbent should ideally possess high surface area, be easy to synthesize, and most importantly offer a high arsenic removal capacity. Achieving all the key features in a single step synthesis is an engineering challenge. We have successfully engineered such a material in the form of nanochains synthesized via a one step flame synthesis. The ultra-long \xce\xb3-Fe2O3 nanochains possess high surface area (151.12 m2 g-1), large saturation magnetization (77.1 emu g-1) that aids in their gas phase self-assembly into long chains in an external magnetic field, along with an extraordinary arsenic removal capacity (162 mg.g-1). A filter made with this material exhibited a relatively low-pressure drop and very little break-through of the iron oxide across the filter.

ultra-long_magnetic_nanochains_for_highly_efficient_arsenic_removal_from_water

Introduction<!>Chemicals<!>Synthesis of High Surface Area Magnetic Nanochains<!>Characterization<!>Arsenic Adsorption Test<!>Results and Discussion<!>Conclusion

<p>Arsenic-contaminated drinking water is a serious global health concern due to its high toxicity and carcinogenicity.1-5 The contamination in drinking water sources is estimated to affect over 144 million people around the world,6, 7 spurring the development of numerous water treatment technologies to limit negative health impacts associated with exposure to arsenic contaminated water including cancer, skin lesions, and neurological disorders. These technologies include ion exchange, adsorptive media filtration, coagulation and flocculation, electrocoagulation, and anaerobic removal with iron sulfides. Adsorptive media filtration has been one of the most attractive approaches amongst the extant technologies due to its low cost, high efficiency, ease of processing and versatility for different water streams.2, 3, 5, 7-9</p><p>Inorganic arsenic is the predominant form of arsenic found in natural waters; it is found in two different oxidation states: As (III) and As (V). It was classified as the number one toxin in the U.S. Environmental Protection Agency (USEPA) list of prioritized pollutants.10 As (III) shows higher mobility in soils and higher toxicity compared to As (V). However, pentavalent As (V) is stable in oxygen-rich aerobic environments and thus it is the predominant arsenic species under oxidizing environments. Pentavalent arsenic is therefore generally found more frequently than the trivalent form in seawater, lakes and rivers.10 There has been a growing effort worldwide to develop efficient materials to remove arsenic from water sources to meet the maximum allowable limit in drinking water (i.e. 10 μg L-1) set by the world health organization (WHO).</p><p>Nano-adsorbents offer significant improvements over conventional adsorbents due to their extremely high mass specific surface area, short inter-particle diffusion distance, and tunable size and surface chemistry.11-13 A high specific surface area is mainly responsible for their high adsorption capacity. In addition, the large surface energy and size dependent surface structure, at the nanoscale, may create highly active adsorption sites, resulting in higher adsorption capacity per unit surface area.14, 15 One of the major limitations of using nano-adsorbents is difficulty in their application to flow-through systems. Due to their nanoscale size, they can be released from the filter or are difficult to separate, hence causing secondary pollution. To address this problem, there has been considerable effort to use support materials such as carbon, carbon nanotubes, graphene, and porous materials to contain the nano-adsorbents.3, 4, 16 However, fabrication of such complex-structured materials can be difficult, not economical, time consuming, and often can suffer from a low mass loading of the nano-adsorbents. Therefore, an easy to synthesize, high surface area material with magnetic properties to aid in separation and assembly of structures is highly desirable in the treatment of arsenic-contaminated drinking water.</p><p>We report the one-step synthesis of high surface area (151.12 m2g-1), highly magnetic (77.1 emug-1), ultra long γ-Fe2O3 nanochains (> 100 μm) decorated with ultra-small (∼4 nm) γ-Fe2O3 nanoparticles. Iron oxide has a high adsorption capacity and excellent selectivity for arsenic.17 Our magnetic chains with a heterogeneous surface were prepared in a facile, controllable flame synthesis under a magnetic field. The nanochains were demonstrated in a flow-through water filtration system (Scheme 1), which showed an extraordinary arsenic removal capacity (162 mg g-1) with low-pressure drop and very little break-through of the iron oxide.</p><!><p>All chemicals were analytical grade and used as received without further purification. Iron pentacarbonyl (Fe(CO)5, AlfaAesar, 99.5%) was chosen as the iron precursor. Compressed H2 gas was supplied from Praxair Inc. (San Ramon, CA) with stated purity of 99.5% or higher. For As (V) adsorption isotherm experiments, As (V) stock solutions were prepared from reagent grade Na2HAsO4·7H2O (AlfaAesar) in deionized water (MilliQ, Millipore Corp., Billerica, MA). The ionic strength of the test solution was adjusted using sodium nitrate (NaNO3, Sigma Aldrich). HEPES sodium salt (Fisher Scientific) used as a buffer at pH 7. 70% HNO3 (trace metal grade concentrated nitric acid, Optima, Fisher Scientific) was used to digest the sample for analysis by inductively coupled plasma mass spectrometry (ICP-MS).</p><!><p>The magnetic nanochains were synthesized in a H2/air diffusion flame as previously reported by our group with some modification.18, 19 H2 was bubbled though the liquid Fe(CO)5 precursor at room temperature at a rate of 0.12 liter min-1 and the precursor-laden H2 stream was passed through the central annulus in a co-annular burner (Figure 1). HEPA filtered, particle-free air was co-flowed though the outermost honeycomb annulus of the burner at a speed of ∼2.2 m s-1 which maintain a uniform laminar flow in the working section. An additional H2 gas stream (0.25 liter min-1) was flown though the middle annulus of the burner to dilute the precursor-laden H2 stream (a 4-channel MKS 647C (MKS Instrument Inc., MA) mass flow controller was used to control all flow rates). The concentration of Fe(CO)5 in the fuel gas was estimated from the mixing ratio of the Fe-laden H2 and pure H2, assuming that the carrier gas was saturated with Fe(CO)5 vapor.</p><p>A stable, self-sustaining laminar diffusion flame (height ∼50 mm) was established on the tubular burner that generated the iron oxide nanoparticles. A homogeneous magnetic field was established by placing two 300 mm tall stacks of magnetic bars (Rare Earth Neodymium Magnets, dimension: 25 × 6 × 6 mm) on each side of the flow, parallel to each other with a spacing of 10-20 mm. The magnets were as tall as the exhaust stream of the flame gas and particles before it entered to the filter housing for collection. Iron oxide nanoparticles were generated as individual particles in the flame; however, under the magnetic field they aligned and assembled in to ultra-long nanochains. The chains were then collected on filter paper (Whatman® qualitative filter paper, Grade 1, Sigma-Aldrich) in a system consisting of a funnel that was mounted co-axially with the flame, a filter housing, and a vacuum system.</p><!><p>The flame-synthesized iron oxide nanochains were characterized by a FEI/Philips XL-30 Field Emission Scanning Electron Microscope (SEM) operated at 5 kV. Transmission Electron Microscopy (TEM) images were acquired using a Phillips CM-12 TEM operating at 120 kV. Higher resolution TEM experiments were carried out with an aberration-corrected JEOL JEM 2100F/Cs scanning transmission electron microscope (STEM) operated at 200 kV. Electron energy loss spectroscopy (EELS) data of the Fe L2,3 absorption edges were recorded with a Gatan Tridiem parallel electron energy-loss spectrometer that is attached to the JEOL JEM 2100F/Cs instrument. Crystallinity was identified using a Scintag powder X-ray diffractometer (XRD) with Cu Kα radiation operated at 45 kV and 40 mA. The powder was scanned for 2θ = 20°- 70°. The scanning step size was 0.015° in 2θ with a counting time of 1 s per step. Brunauer–Emmett–Teller (BET) surface area measurements were carried out using N2 gas adsorption in an AUTOSORB-1 using an optimized protocol (Quantachrome Instruments, Boynton Beach, FL, USA). The samples were de-gassed at 120 °C for 24 h prior to the adsorption-desorption cycle. The magnetic characterization of the nanochains was carried out with a Princeton Measurements Corp. 3900 vibrating sample magnetometer (VSM). The measurements were carried out on powdered samples, with chains oriented randomly in the magnetic field. Arsenic concentrations were analyzed using ICP-MS (7500i, Agilent Technologies, Wilmington, DE, USA).</p><!><p>Arsenic adsorption isotherms were acquired separately in flow-through and batch experiments. Arsenic adsorption kinetics were determined in a batch experiment by mixing 20 mg of iron oxide nanochains with 10 ml of arsenic water with a concentration of 100 mg L-1. The suspension was placed in a rotary shaker with a speed of 200 rpm at room temperature for 3 h. The nanoparticle adsorbents were then separated by centrifugation and the liquid collected for analysis. For the flow-through filtration experiments, 200 ml of water containing arsenic of different concentrations (ranging from 0.25 to 300 mg L-1) was filtered though a filter paper (Whatman® qualitative filter paper, Grade 1, Sigma-Aldrich) with a uniformly covered layer of 20 mg iron oxide nano-chains as shown in Figure S1. The flow rate of the liquid was determined (from the batch experiment) to maintain a fixed contact time of 90 min in all the experiments. The filtered water was collected for analysis. All the experiments were conducted at pH 7.0. The solution pH was maintained using 1 mM HEPES. All the treated water collected after filtration and centrifugation was dissolved in 70% HNO3 and analyzed in ICP-MS. The equilibrium-sorption capacity (Qe) was calculated from the following equation:20</p><p>C0 and Cv represent the concentration of As(V) before and after removal, respectively. V is the volume of the solution and m is the mass of the adsorbent.</p><p>The Langmuir model was used to fit the experimental data according to the following equation:</p><p>where Qe is the adsorption capacity of the adsorbent (γ-Fe2O3 nanochains) at equilibrium. Ce is the equilibrium concentration of arsenic in the solution, Qmax is the saturation adsorption capacity of the γ-Fe2O3 nanochains, and b is the Langmuir equilibrium constant.</p><!><p>The flame synthesis produced very long nanochains as shown in the SEM image of Figure 2 and Figure S2. The chains consisted of individual nanoparticles (∼ 50 nm) that self-assembled into structures that were several hundred microns long with an aspect ratio in the order of 103 - 104. Ultra-small nanoparticles were also present and were associated with the 50 nm primary nanoparticles – they were not visible in the SEM image. Therefore, transmission electron micrographs were taken. The high resolution TEM micrograph in Figure 3a shows a small part of the long nanochains which are covered with ultrasmall (∼ 4 nm) nanoparticles and dangling clusters of ultrasmall nanoparticles. A high angle annular dark field (HAADF) STEM image was taken (see Figure 3b) as a survey image for subsequent EELS experiments. The HAADF STEM image confirms the presence of the ultrasmall nanoparticles that decorate the surface of the nanoparticles. EELS measurements of the O K and Fe L2,3 absorption edges were carried out from a number of different individual nanoparticles (Figure 4). The near-edge fine structure of the O K edge shown in Figure 4a is excellent agreement with previously reported studies of γ-Fe3O4.21 The acquired Fe L3 and L2 edges were subsequently fitted, after background subtraction, by either a single or two Gaussian peaks whichever yielded the best quality fit. The L3/L2 intensity ratio was determined by the ratio of the integrated areas beneath the absorption edges. The observed L3/L2 intensity ratio of 5.50 ± 0.04 is in excellent agreement with previously reported data for FeIII+ in γ-Fe2O3 hence confirming that the nanochains are formed from γ-Fe2O3 nanoparticles.22-24</p><p>The BET method was used to obtain the surface area of the chains. Figure S3a shows that the BET surface area was 151 m2 g-1. In a study with similar nanoparticles synthesized in the gas phase, Guo et al. 18 showed that about 80% of the surface area was accounted for by the small particles. Therefore, we believe that the high surface area obtained for the nanochains is mainly due to the large coverage of the ultra-small nanoparticles on the nanochains. The large surface area can offer a great advantage for efficient arsenic removal.</p><p>The crystallinity of the nanochains was analyzed by powder XRD. The XRD pattern (Figure S3b) showed that the crystalline phase of the nanochains was γ-Fe2O3 (PDF # 39-1346) which is in perfect agreement with the EELS data. Magnetic properties of the particles were analyzed by VSM. The room temperature M-H hysteresis loop of the nanochains (Figure 5) shows a saturation magnetization of 77 emu g-1, consistent with bulk value.25 The coercivity is 290 Oe, enhanced over typical values in bulk materials due to the finite size of the nanoparticles.26-28 The large magnetization with modest coercivity is highly desirable for many practical applications so that a strong magnetic response can be obtained at a low applied magnetic field.</p><p>To understand the mechanism of the formation of the nanochains, samples were taken from different points in the flame and in the exhaust stream. The flame was about 50 mm long. Aerosol samples were collected thermophoretically and examined by TEM. We found most of the nanoparticles formed between the mid-flame region to the flame tip, in a reducing environment. A typical TEM image taken at the visible tip of the flame is shown in Figure S4. Both ultra-small nanoparticles and primary nanoparticles formed at this point, but they had not formed long chains. The observed results are in good agreement with the previous studies.18, 29 From the mid-flame zone, nanoparticles started to form due to reduction of the iron precursor Fe(CO)5 followed by oxidation closer to the reaction zone where OH can be present.29 As per our observation, nanochain formation took place mostly in the exhaust stream under the magnetic field, growing longer with greater retention time as they were transported by the flow. Based on our observation and the literature data,18, 29-31 we propose a formation mechanism of chains under such magnetic field. The mechanism is schematically shown in the Figure 1.</p><p>First, deep on the fuel side of the flame, the precursor Fe(CO)5 pyrolyzed into elemental Fe and CO. As Fe moves along the flame axis, Fe oxidizes to FeO due to increased temperature and oxidizer concentrations (primarily OH with some O). Then in the maximum temperature reaction region in the flame, some of the condensed phase FeO converts to vapor FeO. The majority of the FeO is oxidized in the reaction zone to crystalize into 50 nm particles. In the post-flame region, the Fe and FeO vapor nucleate to form very small particles that are transformed to γ-Fe2O3 due to super-stoichoimetric oxygen – these ultra-small particles are scavenged by the larger particles. Up to the point of the visible tip of the flame, there was no substantial difference in particle assembly or chain formation with or without a magnetic field (Figure S5). However, in the post-flame zone, nanoparticles self-assembled and aligned as long nanochains under a magnetic field as shown in the Figure 2. At the center-line of the flow, the magnetic flux was measured to be 350 mT with a 5180 Hall Effect/Tesla Meter with a resolution of 100 μT. Interestingly, in the absence of a magnetic field, chains were still formed but in the form of fractal aggregates32, 33 (Figure S6).</p><p>Deposition on cooled metal surfaces, produced by thermophoresis, resulted in branch random aggregation of nanoparticles. This kind of fractal aggregate has been reported for other oxide-based nanoparticle aggregates and supported by theoretical understanding of nanoparticle formation and aggregation.32-36 In the absence of a magnetic field, the magnetization directions of the particles are random and dipole interactions amongst them could be either magnetizing or demagnetizing.37 Overall the interaction among the adjacent particles favors bridging and interconnection which result in fractal aggregates. However, an external magnetic field in a gas phase process strongly influenced the alignment and the growth mechanism of nanoparticles. The 350 mT magnetic field along the flow path was three order of magnitude larger than the particle coercivity and fully saturates the particles in the single domain state. These particles then preferentially aligned along the field direction where the dipole interactions were magnetizing,37 favoring linear chain growth along the magnetic-field flux lines,38 and leading to the formation of long straight chains.39, 40 The as-formed particle-chains strongly enhanced the local magnetic field and rapidly attracted the nearby ultra-small magnetic nanoparticles, which ultimately resulted in efficient scavenging of the smaller aerosol mode and the formation of decorated long magnetic chains. In fact, the large ferromagnetic nanoparticles could independently attract and attach the ultra-small superparamagnetic nanoparticles. The creation of the two co-located size modes is a key advantage of using this technique to generate nanochains with a large surface area without a tedious multi-step processes.</p><p>The heterogeneous surface of the nanochains with large specific surface area and large magnetization make them very promising for application to the removal of arsenic from water. We started testing this material by looking at the adsorption kinetics of the nanochains. The time course of the adsorption of the As (V) by the γ-Fe2O3 nanochains is shown in Figure 6. It can be seen that the first 15 min corresponded to a rapid adsorption stage. Thereafter, the adsorption rate decreased and equilibrium was reached in about 45 min. The residual concentration at equilibrium was found to be 16.1 mg L-1 from an initial concentration of 100 mg L-1. The adsorption kinetics indicated that the adsorption of As(V) occurred on the surface of the nanochains rapidly, which we attributed to the surface-bound ultra-small particles and the associated heterogeneity. Thereafter, the adsorbent sites on the particle surface competed with the rest of the ions, giving rise to low adsorption rates. In comparison to other adsorbents reported in the literature, the γ-Fe2O3 nanochains showed very high adsorption rates. For example, bioadsorpbents41, 42 required several hours to reach equilibrium, activated alumina43 required about 2 days. However, the quick adsorption of our nanochains was accomplished in about 30 - 45 min, which offers promise in practical applications such as a flow-through filter system.</p><p>The adsorption isotherm of the nanochains was determined for the flow-through filter system for different concentrations of arsenic in water (0.25 to 300 mg. L-1). The amount of As(V) that was adsorbed on the γ-Fe2O3 nanochains at equilibrium (Qe) increased with increasing Ce. In our experimental range, the maximum Ce we obtained was 141 mg L-1. The isotherm between Qe vs Ce is presented in Figure 7. As seen in the figure, the nanochains showed an excellent maximum adsorption capacity which was calculated to be 162 mg L-1. A comparison of our chains with other reported or available materials is presented in Table 1. Generally, a large specific surface area (SBET) is primarily responsible for the strong adsorption behavior of metal oxides. However, as seen in the Table 1, nanoparticles possessing similar or higher SBET showed different adsorption capacity, which suggest that mass specific surface area may not be the only determining factor for high adsorption capacity. According to previous reports, the other critical factor is the presence of active sites on the adsorbents that is influenced by the synthesis methods. Previous studies showed that the removal of arsenic from aqueous solution by iron oxides or hydroxides depends on active sites such as surface density of hydroxyl groups (-OH), which can form complexes with arsenic ions.44-46 The ultra-small nanoparticles decorated on the long nanochains created a heterogeneous surface which generated more active sites than a homogeneous surface of similar size and specific surface area. The abundance of active sites is thus believed to be primarily responsible for such high adsorption capacity. To understand the type of adsorption, a Langmuir adsorption isotherm were fitted to the experimental data points. The details of the Langmuir parameters are summarized in the Figure 7. The maximum adsorption constant obtained for the Langmuir model is 162 mg g-1. As we can see, the fitted curve matches very well with the Langmuir isotherm (R2 > 0.97) which suggests that the adsorption of arsenates occurs mostly by monolayer formation. We note that although we did not examine the effect of pH and the impact of competitive ions on adsorption of arsenic on γ-Fe2O3 , these issues have been studied elsewhere46 and have confirmed the excellent selectivity of this material for arsenic removal.</p><p>In addition to high adsorptivity, the nanochains present less pressure drop to flow compared to the constituent nanoparticles that were simply packed into a bed, probably as a result of a greater void volume. The fine spacing of the nanochains in the filter did not lead to a diffusional barrier to adsorption. The comparative pressure drop was assessed by creating filters of similarly-sized nanoparticles that were synthesized with and without applying the magnetic field. A large area SEM image of the nanoparticles deposited on the filter is shown in Figure S7. Water flowed through the filters (i.e. nanochains or deposited nanoparticles) for a given period of time. The height of the water column was maintained constant by continuously adding make-up water during the experiments in order to maintain a constant head on the filter. As shown in Figure 8, the volume of collected water using nanochains as a filter material was as much as twice that of non-chain simply aggregated nanoparticles. The low-pressure drop is a key for any filtration system. Therefore, we believe that the nanochains offer an advantage compared to the nanoparticles in terms of handling more filtrate in a given time.</p><p>We have also examined how much iron oxide particles are released from the filter at a moderate flow condition. For this experiment, arsenic contaminated water was passing through the filter covered with (i) nanoparticle, and (ii) nanochains as adsorbent, at a rate of 0.5 L min-1 for a fixed total time. Equal volumes of filtered water were analyzed for both cases by ICP-MS. The result presented in Figure 8 shows that for a given mass of adsorbent material, Fe ions were detected in water at a concentration 12.7 times higher for nanoparticles compared to the nanochains (for the given dilution used in ICPMS, Fenanoparticles = 660 ± 120 ppb; Fenanochains = 51.9 ± 20.2 ppb). The data were obtained in three independent experiments. The result shows that the nanochains could not entirely eliminate the break-through of particles from the filter. However, the difference is significant. Complete sintering of the chains, in principle, could possibly eliminate the break-through of iron nanoparticles, through a modification of the synthesis conditions, primarily flame temperature.</p><!><p>In summary, we present a very simple strategy to produce a highly efficient material (Qm = 162 mg g-1) with a heterogeneous surface for arsenic removal. High efficiency is attributed to the ultra-small nanoparticles that decorate larger nanoparticles, along with the increase in the active sites for arsenic binding. The arsenic adsorption process obeys the Langmuir isotherm model suggesting a monolayer adsorption. The magnetically-assembled nanochains offer low pressure drop and less release of iron nanomaterial from the filter than simple aggregated nanoparticles. The high magnetism and high adsorption capacity make the nanochains an ideal magnetic adsorbent for As(V) removal by filtration with the possibility of down-stream magnetic separation.</p>

PubMed Author Manuscript

Anlotinib combined with temozolomide suppresses glioblastoma growth via mediation of JAK2/STAT3 signaling pathway

PurposeAnlotinib protects against carcinogenesis through the induction of autophagy and apoptosis. The current study evaluated the role and molecular mechanisms of anlotinib in glioblastoma, and the effects of anlotinib in combination with temozolomide (TMZ).MethodsCell Counting Kit-8 and colony-forming assays were used to evaluate cell viability. Cell migration and invasion were assessed by wound-healing, Transwell migration, and Matrigel invasion assays. Cellular apoptosis and cell cycle analysis were determined by flow cytometry. Angiogenesis was assessed using human umbilical vein endothelial cells (HUVECs). Vascular endothelial growth factor A (VEGFA) was measured by enzyme-linked immunosorbent assay. Protein expression was determined by western blotting or immunofluorescence staining. The in vivo anti-glioblastoma effect was assessed with live imaging of tumor xenografts in nude mice.ResultsAnlotinib restricted the proliferation, migration, and invasion of glioblastoma cells in a dose-dependent manner. Tumor supernatant from glioblastoma cells treated with anlotinib inhibited angiogenesis in HUVECs. Anlotinib induced autophagy in glioblastoma cells by increasing Beclin-1 and microtubule-associated protein 1 light chain 3B (LC3B) levels. Mechanistically, anlotinib inhibited the Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3)/VEGFA signaling pathway. STAT3 inhibition by S3I-201 decreased VEGFA and suppressed cellular proliferation and movement. TMZ enhanced the anti-glioblastoma ability of anlotinib. Finally, anlotinib inhibited tumor growth and JAK2/STAT3/VEGFA signaling in xenografts.ConclusionAnlotinib exerts anti-glioblastoma activity possibly through the JAK2/STAT3/VEGFA signaling pathway. TMZ potentiated the anti-glioblastoma effect of anlotinib via the same signaling pathway, indicating the potential application of anlotinib as a treatment option for glioblastoma.

anlotinib_combined_with_temozolomide_suppresses_glioblastoma_growth_via_mediation_of_jak2/stat3_sign

Introduction<!>Cell culture<!>Reagents and antibodies<!>Cell viability assay<!>Colony-forming assay<!>Wound-healing assay<!>Migration and invasion assay<!>Flow cytometry<!>Western blot<!>ELISA and tubular formation assay<!>Immunofluorescence<!>Xenograft experiments and IHC<!>Statistical analysis<!><!>Anlotinib suppressed the proliferation of glioblastoma cells<!><!>Anlotinib induces apoptosis and autophagy in glioblastoma cells<!>Anlotinib inhibits tubular formation of HUVECs and glioblastoma through JAK2/STAT3/VEGFA pathway<!><!>Anlotinib inhibits tubular formation of HUVECs and glioblastoma through JAK2/STAT3/VEGFA pathway<!><!>The combination of anlotinib and TMZ enhances the anti-glioblastoma effects<!><!>Discussion<!><!>Author contributions<!>Funding<!>Conflict of interest<!>Ethical approval

<p>Gliomas are the most common primary intracranial tumor. More than half of all gliomas are malignant in adults, and comprise more than 80% of malignant tumors in the central nervous system. Glioblastoma multiforme (GBM) accounts for more than 50% of total gliomas [1]. The standard treatment option of GBM is surgery accompanied by chemotherapy and radiotherapy. However, the poor prognosis of patients with GBM is commonly attributed to its high rates of malignancy and its insensitivity to chemoradiotherapy. Despite therapeutic advances including accurate surgical techniques and additional chemotherapeutic options, the median survival from the time of diagnosis is only 12–15 months [2], and the 5-year survival rate is below 5% [3]. According to the currently accepted standard protocols, temozolomide (TMZ) is the first-line chemotherapeutic agent for GBM and increases survival to approximately 14 months [4]. Therefore, new strategies for the treatment of GBM are urgently required.</p><p>Angiogenesis has a crucial role in tumorigenesis and metastasis is an important component of various tumor types that needs to be understood for proper treatment. Resistance to classical treatment can be due to the formation of abnormal vasculature and local tumor cell metastasis [5]. Vascular endothelial growth factor (VEGF), and its high affinity receptor (VEGFR), dramatically enhances the capacity of angiogenesis. Thus, VEGF overexpression often results in worse clinical outcomes for glioma patients [6, 7]. Indeed, the concentration of VEGFA (one of five members in the VEGF protein family) is increased in higher grade glioma tissue [8]. Anti-angiogenic therapy is one of the most promising approaches to glioma treatment; however, there currently is no efficacious therapeutic anti-angiogenesis drug for clinical use to treat gliomas.</p><p>Anlotinib is a novel multi-targeted tyrosine kinase inhibitor that has shown significant and positive results in a variety of tumors [9], and can target VEGFR2, fibroblast growth factor receptor 1, platelet-derived growth factor receptor β, and the stem cell factor receptor. Anlotinib may inhibit endothelial cell migration and angiogenesis via extracellular signal-regulated kinase (ERK) signaling [10]. Recently, the anticancer function of anlotinib has been highlighted in lung cancer [11, 12], liver cancer [13], and osteosarcoma [14]. Although the inhibitory effects of anlotinib on U87 (human primary glioblastoma cell line) cellular proliferation have been previously reported [15], the underlying molecular mechanisms of anlotinib in glioblastoma and its effects in combination with TMZ need additional research to enhance preclinical understanding prior to clinical studies. Importantly, the potential mechanisms of anlotinib underlying the anti-GBM effects and its effects on A172 and U251 cells (human glioblastoma cell lines) remain unclear. In addition, the mechanism of the synergistic effect between anlotinib and TMZ is not clear.</p><p>Accumulating evidence has suggested that the Janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) pathway is important during tumorigenesis and angiogenesis [11, 16, 17]. Hence, the current study evaluated the relationship between the JAK2/STAT3 pathway and anti-angiogenic effects, with a focus on VEGFA expression. It was also demonstrated that combined with TMZ, the therapeutic efficacy of anlotinib was enhanced, in terms of its anti-proliferative, anti-apoptotic, and anti-angiogenic effects.</p><!><p>A172, U87, and U251 human glioblastoma cell lines were purchased from the Cell Bank of Type Culture Collection of the Chinese Academy of Sciences (Shanghai, China). Human umbilical vein endothelial cells (HUVECs) were purchased from Jin Yuan Organism (Shanghai, China). The human glioblastoma cells were cultured in Dulbecco's Modified Eagle Medium (DMEM; Thermo Fisher Scientific, Waltham, MA, USA), supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific) and 100 units/mL penicillin/streptomycin (HyClone, GE Healthcare Life Sciences, Logan, UT, USA) at 37 °C in a humidified atmosphere of 95% air and 5% CO2. Then, HUVECs were cultured in Endothelial Cell Medium (ECM; ScienCell, Carlsbad, CA, USA) with 5% fetal bovine serum (FBS; ScienCell, Carlsbad, CA, USA), 1% endothelial cell growth supplement (ECGS; ScienCell, Carlsbad, CA, USA) and 1% antibiotic solution (P/S; ScienCell, Carlsbad, CA, USA) at 37 °C in a humidified atmosphere of 95% air and 5% CO2. Media was changed every 48–72 h. For each passage, cells were washed twice with phosphate-buffered saline (PBS; HyClone), then incubated at 37 °C with 0.25% trypsin–EDTA (Sigma-Aldrich Co.) to lift the cells. For experiments, cell monolayers were grown to approximately 70% confluence in culture medium prior to the initiation of experimental conditions.</p><!><p>Anlotinib, TMZ, S3I-201, and 3-methyl adenine (3-MA) were obtained from Selleckchem (Houston, TX, USA). Anlotinib was prepared as a 10 mM stock solution in dimethyl sulfoxide (DMSO). TMZ was prepared as a 50 mM stock solution in DMSO. Antibodies against phosphorylated (p)-JAK2, STAT3, p-STAT3, microtubule-associated protein 1 light chain 3B (LC3B), Beclin-1, and caspase-3, as well as goat anti-rabbit and anti-mouse immunoglobulin G (IgG; H&L) secondary antibodies were obtained from Cell Signaling Technology (Danvers, MA, USA). Antibodies against B cell lymphoma 2 (Bcl-2) and Bcl-2-associated X protein (BAX) were purchased from Santa Cruz Biotechnology (Delaware, CA, USA). The anti-VEGFA antibody was from Abcam (Cambridge, MA, USA). Antibodies against cyclin A2, cyclin D1, high mobility group box protein 1 (HMGB1), and matrix-metalloprotease 2 (MMP2) were obtained from ProteinTech Group Inc. (Chicago, IL, USA). The β-actin antibody was purchased from Bioworld Technology (Louis, MN, USA). The anti-Ki-67 antibody (Absin; Shanghai, China) was used for immunohistochemistry (IHC). Horseradish peroxidase (HRP)-conjugated goat anti-rabbit IgG and FITC-conjugated anti-rabbit IgG antibodies were from Jackson ImmunoResearch Laboratories Inc. (West Grove, PA, USA).</p><!><p>The Cell Counting Kit-8 (CCK-8, Dojindo, Kumamoto, Japan) was used to determine cell viability following the manufacturer's instruction. A172, U87, and U251 cells were seeded in 96-well plates (3 × 103 cells/well) for 24 h. Anlotinib was diluted in DMEM to achieve final treatment concentrations of 0, 1.25, 2.5, 5, 10, and 20 µM for either 24, 48, or 72 h. In combination drug studies, TMZ (100 µM) and anlotinib (2 µM) were added to the media for 48 h. Next, 100 µL of 10% CCK-8 solution diluted in DMEM was added into each well. After incubating at 37 °C for 2 h, the plates were analyzed with the Bio-Rad enzyme-linked immunosorbent assay (ELISA) microplate reader at 450 nm (OD450). Cell viability was determined using the following formula: cell viability = (OD450 of treated groups/OD450 of control group) × 100%.</p><!><p>A172, U251, and U87 glioblastoma cells were seeded into six-well plates (1,000 cells/well) and treated with anlotinib (0, 2, and 4 µM). The media and treatment were refreshed every 3 days. After incubation at 37 °C for 14 days, the colonies were washed with PBS and fixed with methanol for 20 min. After staining with 0.1% crystal violet (Sigma-Aldrich Co.), the colonies were visualized and quantified.</p><!><p>The migration of cells (A172, U87, and U251) was assessed using a standard in vitro wound-healing assay. The cells were grown in normal growth media to 70% confluence in six-well tissue culture plates. Next, the cells were scraped with a 200 μL pipette tip, washed with PBS, and incubated in serum-free media containing anlotinib (0, 2, and 4 µM) at 37 °C for 0 and 24 h. In combination drug studies, U87 and U251 cells were cultured in anlotinib (2 μM) with or without TMZ (100 μM) for 48 h. The changes in wounded areas were observed and imaged using a light microscope (Carl Zeiss Meditec AG, Jena, Germany). The wounded areas from four random fields of view were subsequently measured using ImageJ software (National Institutes of Health, Bethesda, MD, USA) and the percent healing was determined with the following formula: wound healing (%) = (initial scratch area—final scratch area)/initial scratch area × 100%. The results were analyzed using GraphPad Prism 8 software (version 8.0.2; GraphPad Software Inc., La Jolla, CA, USA).</p><!><p>Transwell assays (with or without Matrigel) were used to evaluate the motile and invasive capacities of A172, U87, and U251 cells treated with anlotinib. Transwell assays were performed using an Invasion Chamber (Corning Inc., NY, USA) following the manufacturer's instructions. Briefly, for the migration assay, cells (2 × 105) in 200 µL serum-free DMEM were added to the upper chamber of 6.5 mm Transwells (8.0 µm pore; polycarbonate membrane inserts; Corning Inc.). For the invasion assay, the upper chambers were coated with a matrix of Matrigel (Corning Inc.). With both experimental protocols, the lower chambers contained DMEM with 10% FBS. After an incubation at 37 °C for 16 h, the cells in upper chamber that did not penetrate the membrane were removed. Subsequently, the chambers were fixed with paraformaldehyde for 15 min and stained with 0.1% crystal violet for 10 min. Cells were counted in five random fields of view/insert using a light microscope.</p><!><p>For cell cycle analysis, A172, U87, and U251 cells were cultured and harvested after treatment, then fixed with 70% ethanol. After propidium iodide (PI; 500 µL) staining, nuclei were analyzed using a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA, USA).</p><p>For apoptosis analysis, cells were harvested and suspended in 300 µL of binding buffer containing 5 µL of annexin V-FITC (AV; KGA108, KeyGEN, China) and 5 µL of PI (BD Biosciences). After an additional 200 µL of binding buffer was added, the apoptotic cells were analyzed using a FACSCalibur flow cytometer (BD Biosciences).</p><!><p>Western blot assays were performed as previously described [18]. In brief, A172, U87, and U251 cells were treated with anlotinib (2 μM) and/or S3I-201 (100 µM) for 24 h. In a separate experiment, U87 and U251 cells were cultured in media containing anlotinib (2 μM) with or without TMZ (100 µM) for 24 h. Cells were harvested, and protein concentrations were determined using the bicinchoninic acid Protein Assay Kit (Beyotime). Equal amounts of protein were subjected to sodium dodecyl sulfate–polyacrylamide gel electrophoresis on 8–12% gels and then transferred onto a polyvinylidene fluoride membrane (EMD Millipore, Billerica, MA, USA). After blocking with 5% non-fat milk for 2 h at room temperature, the membranes were incubated at 4 °C overnight with the appropriate primary antibodies. After washing with tris-buffered saline with Tween 20, membranes were incubated with the corresponding secondary HRP-conjugated antibodies. Finally, protein bands were visualized using enhanced chemiluminescence detection reagents (EMD Millipore) and a chemiluminescence imaging system (Tanon, Shanghai, China).</p><!><p>VEGFA concentrations in the supernatants from U87 cells were determined using human VEGFA ELISA kits (Jianglaibio, Shanghai, China) according to the manufacturer's instructions.</p><p>To visualize the micro-vessels, HUVECs were cultured in tumor cell supernatant (without FBS) and seeded onto a 96-well plate (3 × 104 cells/well) coated with 50 μL Matrigel (Corning Incorporated, USA). Then, cells were incubated at 37 °C in 5% CO2. Six hours after seeding, tubules were photographed using light microscopy and evaluated by Image Pro Plus software.</p><!><p>U87 and U251 cells were seeded onto glass cover slips and allowed to adhere for 12 h. After treatment with anlotinib (4 µM) and an inhibitor of autophagy (3-MA; 5 mM) for 24 h, the cells were fixed with 4% paraformaldehyde for 15 min, then permeabilized with 0.3% Triton X-100 for 10 min. Coverslips were then incubated with the primary antibody against LC3B at 4 °C overnight, and the CY3-conjugated secondary antibody for 1 h at room temperature. The nuclei were stained using 4',6-diamidino-2-phenylindole (DAPI; Sigma-Aldrich) for 10 min. All images were taken using a ZEISS immunofluorescence microscope.</p><!><p>All experimental procedures and animal care protocols were approved by the Animal Care Committee of Southeast University. Athymic nude mice (4-week-old, male) were used to establish an orthotopic GBM model. Mice were randomly divided into three groups (n = 4/group) and treated with different concentrations of anlotinib (0, 3, and 6 mg/kg). Transfected U87MG-Luc cells (500,000 cells in 3 µL Hanks/mouse) were implanted stereo-tactically, anterior (1.0 mm) and lateral (2.5 mm) to the bregma and at depth of 3.5 mm from the skull surface [19]. Luciferin (150 mg/kg) was injected into mice intraperitoneally, and the Caliper IVIS Spectrum was used for in vivo bioluminescence imaging. Nude mice were killed after 28 days, and tumor tissues were prepared for western blotting and IHC. IHC staining was conducted according to methods previously described [20].</p><!><p>The SPSS version 25.0 (IBM Corporation, Armonk, NY, USA) software was used to analyze all data. Data were expressed as mean ± standard error of the mean (SEM) and the differences between control and treatment groups were evaluated by Student's t-test. Statistical comparisons among three or more groups were performed using an analysis of variance (ANOVA) with Tukey's post hoc test. A p value < 0.05 was considered statistically significant.</p><!><p>Anlotinib inhibits the proliferation of glioblastoma cells. a–c Anlotinib suppressed the growth of human glioblastoma cell lines (A172, U87, and U251) in both a dose- and time-dependent manner. d Representative images of the colony-formation assay. Cells were incubated for 14 days with increasing concentrations of anlotinib and colony formations were reduced in all tested human glioblastoma cell lines. e Quantification of the colony-formation ability. The values are expressed as the mean ± SEM from three independent experiments. *p < 0.05, **p < 0.01, and ***p < 0.001 versus the control</p><!><p>The colony-formation assay was used to test long-term effects of anlotinib on cell proliferation. As shown in Fig. 1d, e, the size of independent colonies was much smaller in the anlotinib-treated group than the vehicle-treated group, and the number of colonies was significantly reduced in the anlotinib-treated group. These results suggested that anlotinib inhibited the proliferation of glioblastoma cells in a dose-dependent manner.</p><!><p>Anlotinib suppresses the migration and invasion capacity of glioblastoma cells in vitro. a A172, U251 and U87 cells were treated with vehicle or anlotinib for 24 h. Cells that migrated into the wounded areas were observed and imaged. b Quantification of the wound-healing ability. c, e The migration and invasion of glioblastoma cells in Transwell migration and Matrigel invasion assays were inhibited. d, f Quantification of the number of migrated and invasive cells was analyzed from five independent fields of view. The wound-healing ability of the vehicle-treated group was adjusted to the value of 100. Values are expressed as the mean ± SEM from three independent experiments. *p < 0.05, **p < 0.01, and ***p < 0.001 versus the control</p><p>Anlotinib induces G2/M phase cell cycle arrest, induces apoptosis, mediates expression of apoptosis-related proteins, and triggers autophagy in glioblastoma cells. a, b U87 cells were tested in after anlotinib treatment for 24 h by flow cytometry and arrested at the G2/M phases. c, d Anlotinib enhanced the ratio of apoptotic cells in a dose-dependent manner. e, f Anlotinib upregulated the levels of pro-apoptotic proteins (BAX and cleaved caspase-3). In addition, anlotinib downregulated the level of the anti-apoptotic protein Bcl-2. The cells were pretreated with anlotinib for 24 h. g, h Anlotinib reduced the expression levels of Beclin-1 and LC3B as detected by western blotting. i Immunofluorescence staining of LC3B showed that anlotinib increased autophagosome formation, and this process was suppressed by an inhibitor of autophagy (3-MA). Data are represented as mean ± SEM of four independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001 vs control group</p><!><p>Previous studies indicated that arresting the cell cycle initiates an apoptotic program [21, 22]. However, whether anlotinib has a pro-apoptotic effect is unknown. As such, the effect of anlotinib (0, 2, and 4 µM) treatment on apoptosis was examined. The percentage of apoptotic cells was elevated in three human glioblastoma cell lines (A172, U87, and U251) treated with anlotinib. The examination indicated that anlotinib was able to induce apoptosis when compared with the control group (Fig. 3c, d). Subsequently, western blotting was performed on apoptosis-related proteins (Bcl-2, BAX and caspase-3) to determine the mechanism of anlotinib-induced apoptosis. The results indicated that Bcl-2 was markedly upregulated, whereas the levels of cleaved-caspase-3 and BAX decreased with anlotinib compared to vehicle-treated cells (Fig. 3e, f).</p><p>It has been reported that excessive autophagy may serve as a cell death pathway [23]. Importantly, anlotinib was also observed to induce the expression of autophagy-related proteins (Beclin-1 and LC3B) according to western blotting (Fig. 3g, h). Further exploration using immunofluorescence showed that 3-MA could inhibit the formation of autophagosomes induced by anlotinib during the initial stages of autophagy (Fig. 3i).</p><p>Taken together, these results indicated that anlotinib initiated both apoptotic and autophagic programs in glioblastoma cell lines.</p><!><p>The JAK2/STAT3 signaling pathway plays a crucial role in angiogenesis [16, 17]. In addition, anlotinib has been shown to target VEGFR [11]. VEGFA is a downstream target gene of JAK2/STAT3 signaling and promotes angiogenesis [24, 25].</p><!><p>Anlotinib inhibits vascularization through the JAK2/STAT3/VEGFA pathway. a Representative images of tubular formation assay. HUVECs were treated with corresponding tumor supernatant and subjected to a tubular formation assay. b Quantification of the number of vessels was analyzed using data from three independent tests. c The levels of VEGFA in the tumor supernatant from U87 cells were measured by ELISA. d, e, f Western blotting showed that decreased expression of p-JAK2, STAT3, p-STAT3, and VEGFA after anlotinib treatment. In addition, the anlotinib-effect on STAT3, p-STAT3, and VEGFA was enhanced by S3I-201. g, h The decreased expression of cell cycle phase-related proteins (cyclin A2 and cyclin D1) and cell motility-related proteins (HMGB1 and MMP2) by anlotinib were potentiated by S3I-201. The relative protein levels in control cells were adjusted to the value of 1. Data are represented as mean ± SEM of four independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001 and ****p < 0.0001 vs control group, #p < 0.05, ##p < 0.01 vs anlotinib group</p><!><p>Collectively, the above findings demonstrated that the anti-angiogenic and anti-glioblastoma effects of anlotinib may be due to its influence on the JAK2/STAT3/VEGFA signaling pathway.</p><!><p>The combination of anlotinib and TMZ enhances the effect of anti-glioblastoma cells. a The combination of anlotinib and TMZ enhanced the effect of suppressing growth of human glioblastoma cell lines (U87 and U251), compared with single drug treatments. b, c Anlotinib combined with TMZ greatly suppresses the migration capacity of glioblastoma cells. d, e The combination treatment enhanced the cytotoxic effects in human glioblastoma cell lines. f, g The suppressive effect on the JAK2/STAT3/VEGFA pathway was enhanced with the combination of drugs. The relative protein levels in control cells were adjusted to the value of 1. Data are represented as mean ± SEM of three independent experiments. *p < 0.05, **p < 0.01, and ***p < 0.001 vs control group, #p < 0.05, ##p < 0.01, and ###p < 0.001 vs anlotinib group</p><!><p>A wound-healing assay was used to access the migratory ability of glioma cells treated with anlotinib or TMZ alone, or in combination. Figure 5b, c revealed that the combination of the drugs greatly increased the inhibition of cell migration compared to each drug used alone.</p><p>To investigate whether the enhanced cytotoxicity was due to cellular apoptosis, the pro-apoptotic effects of the combination treatment was assessed by flow cytometry in all three cell lines treated with anlotinib and/or TMZ. The data revealed that there were significant differences between anlotinib or TMZ single treatment groups and the combination group. Anlotinib or TMZ treatment alone increased apoptosis compared to the control, but the drugs in combination increased apoptosis more effectively than either drug alone (Fig. 5d, e).</p><p>To explore whether anlotinib and TMZ have a cooperative anti-angiogenic effect, the changes to components of the JAK2/STAT3/VEGFA signaling pathway were assessed following single treatments or a combination treatment. It was found that the combination of the drugs was more effective than a single dose of either agent to suppress JAK2/STAT3/VEGFA signaling (Fig. 5f, g).</p><p>Taken together, these results suggested that anlotinib and TMZ had a cooperative anti-glioblastoma effect.</p><!><p>Anlotinib restraints GBM growth in vivo. a Representative bioluminescent images showed tumor volumes in orthotopic GBM model at 7, 14 and 28 days. b Quantification of tumor volumes in the different treatment arms. c Representative images of IHC staining of Ki-67. d Tumor tissues from two different nude mice in each treatment group were analyzed by western blotting. The relative tumor volumes of the control group were adjusted to the value of 1. Data were represented as means ± SEM. *p < 0.05, **p < 0.01, and ***p < 0.001 vs control group</p><!><p>GBM are fatal brain tumors characterized by highly invasive cells with extremely strong vascular proliferation capabilities among solid tumors. Angiogenesis is a hallmark feature of GBM and the role of anti-angiogenic agents in GBM treatment has received increased attention. Bevacizumab (Bev), an anti-VEGF monoclonal antibody, was confirmed to suppress GBM growth in vivo [27] as well as the angiogenesis-promoting effects of glioma cells [28]. However, patients treated with Bev suffered from adverse effects that ultimately reduced their quality of life. Due to other treatment options lacking efficacy, Bev has been classified as a second-line drug for newly diagnosed GBM patients [29]. Therefore, novel and effective anticancer drugs with minimal adverse effects are urgently required to help these patients.</p><p>Anlotinib, a novel multi-targeted tyrosine kinase inhibitor, has been shown to inhibit VEGFR and has antitumor effects in many types of cancer. Anlotinib suppressed hepatocellular carcinoma via ERK and Akt signaling [13], and the dual blockade of VEGFR2 and mesenchymal–epithelial transition factor (MET) played an important role in the anlotinib-mediated inhibition of osteosarcomas [14]. With anlotinib treatment, intrahepatic cholangiocarcinoma was inhibited by blocking the VEGFR2/phosphoinositide 3-kinase (PI3K)/Akt cascade. Other cancers shown to be inhibited by anlotinib have included soft tissue sarcoma [30], esophageal squamous cell carcinoma [31], and gastric cancer [32]. Interestingly, the mechanism of anlotinib appears to be different compared to more commonly used anti-angiogenesis drugs. It not only acts on endothelial cells, perivascular cells, and smooth muscle cells by targeting VEGFRs, fibroblast growth factor receptors and platelet-derived growth factor receptors, but anlotinib can also act directly on tumor cells by targeting c-kit [33]. In clinical applications, anlotinib had been administered in a phase II clinical trial for non-small cell lung cancer patients to evaluate its therapeutic efficacy and safety [34]. Anlotinib is also being assessed in a recent single-center, single-arm, phase II trial that encompasses many cancer types including osteosarcoma, prostate cancer, chondrosarcoma, kidney cancer, gastrointestinal stromal tumor, pulmonary sarcomatoid carcinoma as well as 20 other types of cancer [35]. Therefore, the current study aimed to demonstrate whether (and how) anlotinib could be beneficial to treat glioblastomas.</p><p>In this study, the anti-glioblastoma effect of anlotinib in vitro was supported by results from three glioblastoma cell lines. Compared with canonical anti-glioma drugs, anlotinib was administrated at a lower dose and showed a more pronounced effect. In vitro, anlotinib inhibited the migratory and invasive capacities of glioblastoma cells, and arrested the cell cycle in the G2/M phase, which ultimately lead to cytotoxic effects on the glioma cell lines in a dose-dependent manner. The upregulation of BAX and downregulation of Bcl-2 were involved in caspase-3 activation following anlotinib treatment, resulting in increased rates of apoptosis. Although the difference in the proportion of apoptotic rates was statistically significant, the apoptotic rate obtained by flow cytometry was not as pronounced as the increased expression of pro-apoptotic proteins. There are three possible reasons for this slight discrepancy. First, exorbitant autophagy can promote cell death (type 2 cell death), which differs from apoptosis (type 1 cell death) according to the morphological status [36]. In this study, anlotinib also increased the expression of LC3B, which lead to excessive autophagy. Thus, anlotinib possibly activate type 2 cell death rather than apoptosis. Second, in regulated cell death, pyroptosis has gained increasing attention, and crosstalk between pyroptosis and apoptosis has been reported [37–39]. It is possible that the elevation of caspase-3 promoted pyroptosis rather than apoptosis. Third, autophagy can protect malignant cells against harsh microenvironmental conditions to enhance tumor progression [36, 40]. However, the ultimate goal of apoptosis is cellular death. Accordingly, with protection from autophagy, the final proportion of apoptosis may not appear as high as expected, despite the drastic changes in the levels of apoptosis-related proteins.</p><p>Although TMZ is a first-line chemotherapy agent against GBM in the clinic, it comes with a multitude of challenges. The response to TMZ is variable among patients [41], and resistance can occur rapidly after TMZ treatment [42]. The presence of TMZ resistance contributes to the poor prognosis and has researchers and clinicians concerned [41]. Thus, combination treatment methods have been given consideration. Gossypol was used in combination with TMZ for the inhibition of glioma cells in vitro and in female BALB/c nu/nu mice [43]. In the current study, it was also found that anlotinib can mediate the JAK2/STAT3/VEGFA signaling pathway in glioma cells to decrease levels of secretory VEGFA and angiogenesis, and in combination with TMZ, the anti-angiogenesis and cytotoxic effects of anlotinib are improved. Furthermore, it was shown that anlotinib also reduced the growth rate of glioma cells and suppressed the JAK2/STAT3/VEGFA signaling pathway in vivo.</p><p>In summary, the current findings suggested that anlotinib can suppress the proliferation, migration, invasion, and angiogenesis ability of glioblastoma cells in a dose-dependent manner, and the cooperative effect of anlotinib with TMZ contributes to further enhanced cytotoxicity and anti-angiogenesis in human glioblastoma cells. This strong evidence proves that anlotinib is a promising therapeutic agent for the treatment of glioblastoma.</p><!><p>Publisher's Note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p><!><p>PX performed the study and wrote the paper; HW and HP designed the study and provided the funding. JC and CD revised the paper.</p><!><p>This work was supported by Grants from The Science Foundation of Jiangsu Province, China: Grant numbers ZDXKB2016023 (HD Wang).</p><!><p>The authors report no conflicts of interest in this work.</p><!><p>The study was approved by the animal ethical committee of Southeast University (Jiangsu, China).</p>

PubMed Open Access

Synthesis and Biological Evaluation of Dantrolene‐Like Hydrazide and Hydrazone Analogues as Multitarget Agents for Neurodegenerative Diseases

AbstractDantrolene, a drug used for the management of malignant hyperthermia, had been recently evaluated for prospective repurposing as multitarget agent for neurodegenerative syndromes, including Alzheimer's disease (AD). Herein, twenty‐one dantrolene‐like hydrazide and hydrazone analogues were synthesized with the aim of exploring structure‐activity relationships (SARs) for the inhibition of human monoamine oxidases (MAOs) and acetylcholinesterase (AChE), two well‐established target enzymes for anti‐AD drugs. With few exceptions, the newly synthesized compounds exhibited selectivity toward MAO B over either MAO A or AChE, with the secondary aldimine 9 and phenylhydrazone 20 attaining IC50 values of 0.68 and 0.81 μM, respectively. While no general SAR trend was observed with lipophilicity descriptors, a molecular simplification strategy allowed the main pharmacophore features to be identified, which are responsible for the inhibitory activity toward MAO B. Finally, further in vitro investigations revealed cell protection from oxidative insult and activation of carnitine/acylcarnitine carrier as concomitant biological activities responsible for neuroprotection by hits 9 and 20 and other promising compounds in the examined series.

synthesis_and_biological_evaluation_of_dantrolene‐like_hydrazide_and_hydrazone_analogues_as_multitar

<!>Introduction<!><!>Introduction<!><!>Chemistry<!><!>Inhibition of MAOs and AChE<!><!>Inhibition of MAOs and AChE<!><!>Inhibition of MAOs and AChE<!><!>Inhibition of MAOs and AChE<!>Cell‐based assay of neuroprotection<!><!>Hydrolytic stability in buffered solution<!><!>Activation of carnitine/acylcarnitine carrier (CAC) transport<!><!>Activation of carnitine/acylcarnitine carrier (CAC) transport<!><!>Conclusion<!>Chemistry<!>Synthesis of compounds 1–12<!>Synthesis of compound 13<!>Synthesis of compounds 14–21<!>Chromatographic measures<!>Enzyme inhibition<!>Cell cultures<!>Measurement of reactive oxygen species levels: DCF‐DA assay<!>Transport measurement<!>Conflict of interest<!>

<p>I. Bolognino, N. Giangregorio, A. Tonazzi, A. L. Martínez, C. D. Altomare, M. I. Loza, S. Sablone, S. Cellamare, M. Catto, ChemMedChem 2021, 16, 2807.</p><!><p>Dantrolene (DAN; Figure 1) is a drug specifically used in the management of malignant hyperthermia, a life‐threatening pathology with fatal course. In a recent work, we disclosed new biological activities exerted by DAN, namely inhibition of monoamine oxidase (MAO) B human enzyme with K i value in the low micromolar range, acetylcholinesterase (AChE), and aggregation of beta amyloid‐40 and hexapeptide tau protein sequence PHF6, i. e. two probes of amyloid aggregation in Alzheimer's disease (AD) brain. [1] It is well known the crucial role of MAO isoforms A and B as metabolizing enzymes in modulating the concentration of neurotransmitters, mostly in some severe and chronic neurodegenerative pathologies. This established reputation is strictly related to the substrate and tissue specificity of both isoforms: MAO A selective inhibitors are clinically administered as antidepressants, [2] while MAO B selective inhibition is commonly used for the treatment of the early symptoms of Parkinson's disease. [3] A new outcome of that study was the discovery of the activation by DAN of the carnitine/acylcarnitine carrier (CAC), with EC50 of 9.3 μM for the purified recombinant wild type (WT) protein. This transporter acts through reductive activation and is involved in trafficking of acyl groups into the mitochondria, carried by l‐carnitine. Treated with DAN, this transport system facilitates, under oxidative stress (OS) conditions, the restoring of ATP production and thus cell vitality, but also the export of endogenous acetyl‐l‐carnitine from mitochondria, with consequent neuroprotective effects.</p><!><p>General strategy for the synthesis of hydrazide/hydrazone derivatives.</p><!><p>The above promising results prompted us to synthesize a number of novel DAN analogues, with the aim of optimizing the inhibitory activity against MAO B and AChE, ultimately improving their pleiotropic pharmacological potential in the treatment of AD and related neurodegenerative syndromes. In this work we investigated in particular: i) the bioisosteric replacement of the NO2 group, which may be toxicophore and precursor for the production of reactive oxygen species (ROS), with CN group; ii) the improvement of the aqueous solubility of DAN by replacing the hydantoin moiety with other (hetero)cyclic moieties bearing protonatable nitrogen(s); iii) the effect of molecular simplification of the three‐ring scaffold in DAN, for detecting the minimal pharmacophoric features responsible for the dual activity on MAO A/B and CAC (Figure 1). SARs were investigated as thoroughly as possible, even considering the effect of lipophilicity on the enzymes' inhibition potency.</p><p>Some of the prepared compounds retained the molecular motif of hydantoin, present in DAN and, as thiohydantoin, in the known hypoglycemic drugs rosiglitazone and pioglitazone (Figure 2), which also behave as moderate MAO inhibitors. In turn, the molecular pruning gave simple hydrazone and hydrazide derivatives (2‐rings series, compounds 14–21) whose structural pattern could be related to that of isocarboxazide (Figure 2), an early irreversible MAO inhibitor.</p><!><p>MAO inhibitors structurally related to dantrolene.</p><!><p>The synthetic pathways chosen for the preparation of the designed compounds are those explored by Snyder and coworkers with slight modifications. [4] The chemical scaffolds were selected to investigate a range of molecular diversity around the structure of DAN, in terms of variation of stereo‐electronic and hydrophobic properties. The general strategy of structural modifications is shown in Figure 1, whereas the syntheses of compounds are shown in Schemes 1–3. Condensations from suitable aldehydes and amino/hydrazide derivatives were performed in DMF/water or acetone/water mixtures, with acidic catalysis and agitation at room temperature. Final compounds were obtained in moderate (20–50 %) to good (70 %) yields, following a simple workup including filtration and purification through either crystallization or column chromatography.</p><!><p>Reagents and conditions: (i) HCl, 0 °C, NaNO2, rt, 30 min; (ii) 2‐furaldehyde, CuCl2, acetone, rt; (iii) amine or hydrazine or hydrazide, DMF/water, HCl (cat.), rt, 24 h.</p><p>Reagents and conditions: (i) HCl, 0 °C, NaNO2, rt, 30 min; (ii) 3‐methoxybenzaldehyde, CuCl2, acetone, rt; (iii) 2‐thiophenecarboxylic acid hydrazide, DMF/water, HCl (cat.), rt, 24 h.</p><p>Reagents and conditions: (i) hydrazine or hydrazide, acetone/water, HCl (cat.), rt, 24 h.</p><!><p>The results of in vitro inhibition tests on human MAOs and AChE of the newly synthesized DAN analogues are summarized in Tables 1 and 2, along with the inhibition data of pargyline and galantamine used as positive controls for MAO (B‐selective) and AChE, respectively. Inhibition assays were also performed on human butyrylcholinesterase (BChE), where all compounds resulted inactive or poorly active (data not shown). IC50 values were calculated for compounds displaying >60 % inhibition in one‐point (10 μM) concentration assay.</p><!><p>Inhibition of MAOs and AChE (compounds 1–13).</p><p></p><p></p><p></p><p>Entry</p><p>R</p><p>R'</p><p>IC50 [μM] or % inhibition at 10  μM</p><p>Clog P[a]</p><p>log k'[b]</p><p>hMAO A</p><p>hMAO B</p><p>hAChE</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>DAN</p><p>NO2</p><p></p><p>14.0±1.0c</p><p>2.69±0.44c</p><p>4.19±0.73c</p><p>1.63</p><p>0.115</p><p>7</p><p>CN</p><p>40 % ±5</p><p>50 % ±3</p><p>28 %±4</p><p>1.32</p><p>–</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>1</p><p>NO2</p><p></p><p>33 %±2</p><p>3.67±0.92</p><p>40 %±4</p><p>4.18</p><p>0.947</p><p>4</p><p>CN</p><p>1.46±0.21</p><p>2.63±0.42</p><p>51 %±3</p><p>3.12</p><p>–</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>2</p><p>NO2</p><p></p><p>7.89±1.10</p><p>3.56±0.36</p><p>30 %±1</p><p>2.63</p><p>0.522</p><p>5</p><p>CN</p><p>6.62±0.71</p><p>12.6±0.9</p><p>27 %±2</p><p>2.32</p><p>0.312</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>3</p><p>NO2</p><p></p><p>5.61±1.11</p><p>3.15±0.03</p><p>44 %±2</p><p>2.58</p><p>0.752</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>6</p><p>CN</p><p></p><p>4.25±0.45</p><p>2.65±0.11</p><p>38 %±4</p><p>1.88</p><p>0.236</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>8</p><p>CN</p><p></p><p>5.51±0.54</p><p>3.61±0.04</p><p>16 %±1</p><p>3.43</p><p>0.803</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>9</p><p>CN</p><p></p><p>3.46±0.25</p><p>0.68±0.05</p><p>30 %±0.4</p><p>3.95</p><p>0.782</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>10</p><p>CN</p><p></p><p>47 %±4</p><p>29 %±4</p><p>55±1</p><p>4.14</p><p>–</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>11</p><p>CN</p><p></p><p>11 %±4</p><p>28 %±3</p><p>39 %±4</p><p>3.15</p><p>–</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>12</p><p>CN</p><p></p><p>10.0±1.9</p><p>28 %±4.0</p><p>1.67±0.19</p><p>2.58</p><p>0.466</p><p></p><p></p><p></p><p></p><p></p><p></p><p>13</p><p>29 %±4</p><p>2.32±0.43</p><p>35 %±5</p><p>3.19</p><p>0.549</p><p>Pargyline</p><p>10.9±0.6</p><p>2.69±0.48</p><p>–</p><p>–</p><p>–</p><p>Galantamine</p><p>–</p><p>–</p><p>0.72±0.15</p><p>–</p><p>–</p><p>[a] ChemDraw software 15.0. [b] Logarithm of the capacity factor k' (defined as (tR‐t0)/t0, where tR is the retention time and t0 the dead time) measured by RP‐HPLC using MeOH/phosphate buffer pH 7.4 gradient from 80 : 20 to 60 : 40 v/v. [c] Data taken from Ref. [1].</p><p>Inhibition of MAOs and AChE (compounds 14–21).</p><p></p><p></p><p></p><p>Entry</p><p>R</p><p>IC50 [μM] or % inhibition at 10  μM</p><p>Clog P[a]</p><p>log k'[b]</p><p>hMAO A</p><p>hMAO B</p><p>hAChE</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>14</p><p></p><p>11 %±3</p><p>no inhibition</p><p>9.06±0.45</p><p>−0.21</p><p>−1.018</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>15</p><p></p><p>16 %±4</p><p>13 %±3</p><p>7.18±0.07</p><p>1.59</p><p>−0.010</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>16</p><p></p><p>18 %±3</p><p>13 %±4</p><p>21 %±5</p><p>1.27</p><p>–</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>17</p><p></p><p>22 %±5</p><p>22 %±4</p><p>52 %±4</p><p>1.89</p><p>–</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>18</p><p></p><p>25 %±5</p><p>21 %±3</p><p>27 %±5</p><p>1.03</p><p>–</p><p></p><p></p><p></p><p>19</p><p></p><p>19 %±5</p><p>12.2±1.5</p><p>11.2±1.6</p><p>1.69</p><p>0.129</p><p></p><p></p><p></p><p></p><p></p><p></p><p></p><p>20</p><p></p><p>42 %±2</p><p>0.81±0.04</p><p>10.2±1.6</p><p>2.09</p><p>0.307</p><p></p><p></p><p></p><p></p><p></p><p></p><p>21</p><p>8 %±2</p><p>18 %±5</p><p>28 %±4</p><p>−0.08</p><p>–</p><p>[a], [b] see Footnotes of Table 1.</p><!><p>Compared with previously obtained results of DAN, [1] its CN congener 7 showed a significant loss of inhibition potency toward all three enzymes (approximately a four‐fold decrease for MAO B). On the contrary, the thiophene hydrazides 1 and 4 proved to be equipotent with DAN for MAO B inhibition, with a noteworthy increase of MAO A activity and loss of MAO B/A selectivity for the CN congener 4. The same modification in compounds 2 and 5 resulted in almost overlapping activities, even with a decrease of MAO B potency.</p><p>Compound 3, which along with 1 and 2 maintains the 4‐nitrophenyl substituent, was prepared with the aim of introducing a strong basic moiety likely able to improve the affinity to cholinesterases. Unfortunately, it resulted a poor AChE inhibitor, while retaining fair MAO inhibition, although unselective, in the low micromolar range. The same activity profile was featured by the hydrazide 6 and 8, where the structural simplification of the hydantoin ring of the close analogue 7 to acethydrazide (6) and phenylacethydrazide (8) allowed the restoration of MAO inhibitory activity.</p><p>The introduction of terminal moieties with larger structural diversity, as in case of compounds 9–13, produced contrasting results. Concerning MAO B inhibition, we obtained an interesting submicromolar value of IC50 for phenol derivative 9, which turned out as the most potent MAO B inhibitor of this series, also displaying 5‐fold selectivity over MAO A.</p><p>Inhibition kinetics assessed for 9 a competitive mechanism, with K i equal to 0.50±0.06 μM (Figure 3). Taking into account the possible hydrolytic degradation of imine (see stability studies below), inhibition kinetics were determined without preincubation with substrate, as usually done for MAO inhibition experiments.</p><!><p>Michaelis‐Menten plot (A) and Lineweaver‐Burk linearization (B) of inhibition kinetics of hMAO B with compound 9. Image is representative of a single experiment.</p><!><p>The derivatization of furaldehyde bridge as 4‐substituted arylhydrazones (compounds 10–12) resulted in a decrease of activity towards MAO isoforms. Nevertheless, sulfonamide derivative 12 scored an unexpectedly remarkable inhibitory activity towards AChE with an IC50 value of 1.67 μM.</p><p>While compound 4 was the most active inhibitor of MAO A (IC50 1.46 μM), the replacement of the central furan ring with a larger and sterically hindered ring such as methoxybenzene in 13, resulted in a strong decrease of this inhibitory activity, while retaining a similar low value of IC50 for MAO B. This potency reversal represents an interesting example of isoform selectivity, but seems also contrasting with previous results, [5] assessing a preferential MAO A affinity for molecules bearing bulky bridging substituents.</p><p>A number of structurally simpler derivatives, based on two‐ring scaffolds, were also synthesized with the aim of gaining information on the minimal pharmacophore features [6] of the compounds under examination. The effects of such a molecular pruning on target interactions are shown in Table 2. Removal of nitrophenyl group (compare 14 vs. DAN and 7, 15 vs. 1 and 4, 16 vs. 3, 17 vs. 8, 18 vs. 12) resulted in a marked loss of activity towards MAOs, while only in few cases AChE inhibition was sparingly retained, particularly in the case of isonicotinic acid derivative 19, analogue of 2 and 5. It is worthy of note that sulfonamide 18 lost the appreciable AChE inhibitory activity of its analogue 12, likely because of the lack of favorable hydrophobic/aromatic interactions by the nitrophenyl moiety in the enzyme binding site. This hypothesis is strengthened by the result of compound 20, which can be considered as a superior homologue of 18. The increase of lipophilicity, along with the introduction of an electron‐donating substituent, through the replacement of furan with the methoxybenzene ring determined not only the restoring of the activity towards hAChE but also, in line with expectations, the restoring of the affinity towards MAO targets. Particularly in MAO B inhibition (IC50=0.81 μM), sulfonamide 20 resulted as a potent and B/A selective candidate within the entire molecular set herein presented.</p><p>Lastly the introduction of a sterically hindered ring such as 3,4,5‐trimetoxybenzene (21) caused a loss of activity (8–28 % inhibition) towards both MAOs and AChE at the highest concentration tested (10 μM).</p><p>To investigate a possible correlation between MAO inhibitory potency and lipophilicity, [7] we calculated log P with three different programs (ChemDraw 15.0; ALOG PS 2.1; ChemSketch 2017, see Table S1 in Supporting Information) and compared the calculated values with experimental lipophilicity indexes as assessed by reversed‐phase (RP) HPLC in isocratic conditions for the majority of compounds. The log of capacity factors (log k') measured by RP‐HPLC using a mixture of methanol/PBS (60 : 40, v/v) as the mobile phase are reported in Tables 1 and 2, along with Clog P values calculated with ChemDraw. These calculated lipophilicity descriptors correlated with the experimental log k' values (n=13, r 2=0.901) better than the other log Ps calculated by ALOG PS and ChemSketch computational tools (r 2 equal 0.705 and 0.568, respectively). As shown by the scatter plots in Figure 4 and Figure S1 in Supporting Information, there is no evident correlation trend between MAO A/B inhibition data and lipophilicity calculated by the expert system implemented in ChemDraw for compounds achieving finite IC50 values.</p><!><p>Plots of pIC50 values determined toward MAO A (A) and B (B) versus calculated Clog P values (ChemDraw); only compounds with finite IC50 values are shown.</p><!><p>While the graphical analysis proved the absence of a general correlation trend, the experimental log k' values (Tables 1 and 2), albeit limited to just over half of the compounds studied, suggest a certain effect of lipophilicity on the inhibition potency. Indeed, within the physicochemical property space explored, the strongest MAO A/B inhibitors possess higher lipophilicity (i. e., with values comprised in the 0.0–1.0 range), whereas the most active AChE inhibitors scored log k' values close to or lower than 0.</p><!><p>In order to get further information about the potential neuroprotective effects exerted by the most active compound of the molecular series (phenol derivative 9) toward hMAO B, we tested it in a 2′,7′‐dichlorofluorescein diacetate (DCF‐DA) fluorescence‐based assay measuring the production of ROS induced by dopamine in cultured SH‐SY5Y cells.</p><p>The immortalized neuroblastoma cells are a widely used model for neuroprotection assays, while dopamine at a concentration of 10 nM acts as an inducer of oxidative stress,[ 8 , 9 ] being metabolized by MAOs to form hydrogen peroxide. Once hydrolyzed and oxidized, DCF acts as the fluorescing probe of the oxidative stress (OS) state of cells. In the presence of an antioxidant, or even of a MAO inhibitor, ROS burden is lowered and DCF fluorescence decreased. Figure 5 shows that 9 was effective in reducing ROS oxidation of DCF. Its activity is superimposable to that of phenelzine, a nonselective MAO inhibitor used as a positive control in this test. [10] The same experiment performed on dantrolene in our previous work gave similar results. [1]</p><!><p>Neuroprotection of SH‐SY5Y cells from oxidative insult; DCF‐DA assay. Green line, control cells; purple line, 10 nM dopamine; blue line, 10 nM dopamine+10 nM phenelzine; black line, 10 nM dopamine+10 nM 9. The data represent mean±SD of three independent experiments.</p><!><p>The hydrolytic stability of some representative imino/hydrazone/hydrazide derivatives was determined in buffered aqueous media. The stability studies were carried out on compounds 3, 4 and 9, the most active MAO B inhibitors of the 3‐rings scaffold series, at a single concentration of 20 μM in 10 mM phosphate buffered saline (PBS) at physiological pH of 7.4, at 37 °C and for 6 h incubation time. The degradation profiles in Figure 6A confirmed a substantial stability for 3 and 4, while the imine 9 resulted, at the end of the 6 h of incubation, in a degradation percentage of 76 %. This result is in line with the nature of the functional group of this molecule: in fact, 9 is the only Schiff base within the synthesized series and therefore by itself less stable than the other hydrazone analogues. The hydrolytic degradation of 9 in its starting reagents was confirmed by the comparison of the chromatograms of 9 and 2‐chloro‐4‐hydroxyaniline, obtained in the same chromatographic conditions (Figure 6B).</p><!><p>(A) time‐resolved stability of compounds 3, 4 and 9 at the concentration of 20 μM in PBS at 37 °C. Data are representative of three independent experiments and values expressed as mean. (B) overlapping chromatographic peaks of 9 at t 0 and t 4 h and chromatogram of 2‐Cl‐4‐OH aniline.</p><!><p>CAC (SLC25 A20) is essential for the transport into mitochondria of acyl moieties as acylcarnitines, where they are processed by β‐oxidation pathway. The protein contains six cysteine residues, but two of them, namely C136 and C155, based on the redox state of the protein, are crucial for the regular function of the carrier.[ 11 , 12 ] In fact, the transporter is active when the two cysteines are in reduced form, while it is inhibited when a C136‐C155 disulfide bridge is formed in conditions of OS. One or both cysteines represent also specific targets for various chemical and physiological thiol reducing agents,[ 13 , 14 , 15 , 16 , 17 ] allowing to modulate the transport activity of the carrier. We demonstrated that DAN led to a significant recovery of the CAC transport activity of the oxidized protein. [1] Herein, we also investigated whether some newly synthesized derivatives, namely the most active MAO B inhibitors 9 and 20, the DAN homologue 14, and the dual MAO B/AChE inhibitor 19, are effective in activating CAC. To calculate the EC50 values from dose‐response curves, that is, the concentration which increases the transport activity of the carrier by 50 % compared to the control, a wide concentration range (1–100 μM) was tested (Figure 7). The EC50 values measured after 30 min of incubation were 8.2±2.8 μM (comp. 9), 8.4±1.6 μM (14), 8.2±0.57 μM (19), 13±1.8 μM (20), whereas the whole activation of the WT protein was observed at concentrations close to 100 μM for 8, 19 and 20, and 50 μM for 14.</p><!><p>Dose‐response curves of activation of CAC (purified recombinant WT protein). The antiport rate was measured by adding 0.1 mM [3H]‐carnitine to proteoliposomes containing 15 mM internal carnitine and stopped after 30 min by the specific inhibitor N‐ethylmaleimide (NEM). Compounds at increasing concentrations were added 2 min before the transport assay. Values are mean±SD from three independent experiments.</p><!><p>The tested molecules were able to improve the transport activity of CAC compared to the control and at least three of them (9, 14 and 19) showed EC50 lower than that previously calculated for DAN (9.3 μM) after the same exposure duration (30 min), highlighting similar pharmacological effect. On the contrary, the efficacy of these compounds, i. e., the power of the molecules to achieve maximum effect, is about 5 times lower than DAN. [1]</p><p>To demonstrate that the action of DAN analogues was exerted on the cysteine residues of the CAC, 1 or 50 mM dithioerythritol (DTE), a strong reducing agent, was added to the reconstitution mixture (see Experimental section) in order to mimic the protein at different states of oxidation. The bar plot in Figure 8 shows that the tested molecules enabled the protein to recover a significant transport activity, compared to the control, when the protein is more oxidized, i. e., in the presence of 1 mM DTE.</p><!><p>Effects of DAN analogues on the recombinant WT CAC protein. The proteoliposomes were prepared in two different reducing conditions, adding to the reconstitution mixture 1 or 50 mM DTE. Thus, the antiport rate was measured incubating the reconstituted protein with test molecules at 10 μM final concentration together with 0.1 mM [3H]‐carnitine and then stopping the transport activity after 30 min by NEM. The values are means±SD from three independent experiments, significantly different from the controls, as calculated from Student's t‐test analysis (* p<0.01).</p><!><p>From our previous investigation of the multitarget activity exerted by DAN, [1] we evidenced the potential of repurposing of this orphan drug toward AD‐related targets, but also its intrinsic limitations, particularly its low aqueous solubility, that may discourage further pharmacological evaluation. The DAN‐like molecules herein reported were designed and synthesized with the aim of extending the knowledge of the SARs and improving the pharmaceutical potential of this class of compounds. In particular, our efforts were focused on modifying the structure of DAN for increasing the aqueous solubility and replacing the potentially toxicophore nitro group, as well as following an approach of molecular simplification. The in vitro screening proved that some of the newly investigated analogues improved the MAO inhibitory potency, mostly for the 3‐ring series (compounds 1–13), although with low isoenzyme selectivity. The phenol derivative 9 emerged as an outstanding, reversible MAO B inhibitor (K i 0.50 μM) with fair B/A selectivity. The drop of MAO A activity of compound 13, compared to that of its close congener 4, is a matter of evidence that would deserve further investigations, considering the high B/A selectivity obtained with this homologation. Among the 2‐ring series, only the sulfonamide hydrazine 20 resulted in a strong and selective MAO B inhibitor (IC50 0.81 μM). As far as the AChE inhibition is concerned, appreciable inhibition values were obtained only sparsely, in line with results recently published for a related class of DAN analogues. [18] While only sulfonamide 12 resulted in good AChE inhibition, the best selectivity was achieved with compounds 14 and 15 resulting from the molecular simplification study. The limited molecular size of both 2‐ring and 3‐ring scaffold hampered a significant inhibition of BChE.</p><p>The new compounds confirmed a good stability in buffered conditions, with the obvious exception of imine 9, and a safe cellular activity in contrasting ROS cytotoxicity from oxidative degradation of dopamine. Finally, some tested compounds confirmed the activation of the mitochondrial carnitine trafficking mediated by CAC, thus giving further evidence to the multitarget profile of this class of molecules. The evaluation of possible activity on ryanodine receptors will be a major concern to be faced in the near future, in order to achieve a more complete activity profile of these DAN analogues.</p><!><p>Chemicals, solvents and reagents used for the syntheses were purchased from Sigma‐Aldrich (Milan, Italy) or Alfa Aesar (Haverhill, Massachusetts, USA) and used without any further purification. The purity of all intermediates, checked by 1H NMR and HPLC, was always higher than >95 %. Column chromatography was performed using Merck silica gel 60 (0.063–0.200 mm, 70–230 mesh). All reactions were routinely checked by TLC using Merck Kieselgel 60 F254 aluminum plates and visualized by UV light. Nuclear magnetic resonance spectra were recorded on a Varian Mercury 300 instrument (at 300 MHz) or on Agilent Technologies 500 apparatus (at 500 MHz) at ambient temperature in the specified deuterated solvent. Chemical shifts (δ) are quoted in parts per million (ppm) and are referenced to the residual solvent peak. The coupling constants J are given in Hertz (Hz). The following abbreviations were used: s (singlet), d (doublet), dd (doublet of doublet), t (triplet), q (quadruplet), qn (quintuplet), m (multiplet), br s (broad signal); signals due to OH and NH protons were located by deuterium exchange with D2O. High resolution mass spectrometry experiments were performed with a dual electrospray interface (ESI) and a quadrupole time‐of‐flight mass spectrometer (Q‐TOF, Agilent 6530 Series Accurate‐Mass Quadrupole Time‐of‐Flight LC/MS, Agilent Technologies Italia S.p.A., Cernusco sul Naviglio, Italy). Full‐scan mass spectra were recorded in the mass/charge (m/z) range 50–3000 Da. Melting points (MP) for solid final compounds were determined by the capillary method on a Stuart Scientific SMP3 electrothermal apparatus and are uncorrected. RP‐HPLC analyses were performed on a system equipped with automatic injector and a Waters Breeze 1525 pump coupled with a Waters 2489 UV detector (Waters SpA, Sesto San Giovanni, Italy). The UV detection was measured at λ 254 and 370 nm. Clog P values of the data set were computed by using ChemDraw version 15.0 (PerkinElmer, Milan, Italy), ALOGPS 2.1 (VCCLAB, Virtual Computational Chemistry Laboratory, http://www.vcclab.org) and ChemSketch 2017 version 2.1 (ACD/ChemSketch, Advanced Chemistry Development, Inc., Toronto, ON, Canada, www.acdlabs.com).</p><p>All compounds were synthesized following Snyder's procedures [4] with slight modifications. Compounds 2, [19] 14, [20] 15 [21] and 19 [22] have already been described; their analytical data agreed with those reported in quoted references.</p><!><p>A suspension of 4‐cyano or 4‐nitroaniline (2 mmol) in 10 mL 6 N HCl was heated until the solid is solubilized, then the mixture cooled to 0 °C. A solution of NaNO2 (0.14 g, 2 mmol) in 1 mL of water was added and the mixture left under stirring for 30 min. In the order, solutions of 2‐furaldehyde (0.19 g, 2 mmol) in 2 mL of acetone and CuCl2 (0.04 g, 0.3 mmol) in 1 mL of water were added and the mixture was kept under stirring for 5 h. The precipitate formed was filtered and washed with distilled water. This intermediate compound was then solubilized in DMF (2 mL) and slowly added to an aqueous solution of the appropriate amine/hydrazine/hydrazide derivative (1.8 mmol). A catalytic amount of 4 N HCl was added and the solution was left under stirring at room temperature for 24 h. The mixture was extracted with CHCl3 (3×15 mL), the organic phase abundantly washed with H2O to remove the DMF and dried with Na2SO4. The solvent was evaporated under reduced pressure to give the crude product that was purified by column chromatography with hexane/ethyl acetate: 6/4 or 7/3 v/v as the mobile phase.</p><p>N ′‐((5‐(4‐nitrophenyl)furan‐2‐yl)methylene)thiophene‐2‐carbohydrazide  (1). Yellow crystals; yield: 25 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 7.14 (d, J=3.5 Hz, 1H, furan), 7.23 (t, J=3.5 Hz, 1H, thiophene), 7.47 (d, J=3.5, 1H, furan), 7.89–8.40 (m, 7H arom.), 12.20 (brs, 1H, NH). ESI‐MS (C16H10N3O4S, [M−H]−) calcd. m/z=340.0390, found: 340.0392. MP 241–243 °C.</p><p>N ‐(4‐methylpiperazin‐1‐yl)‐1‐(5‐(4‐nitrophenyl)furan‐2‐yl)methanimine  (3). Red crystals; yield: 50 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 2.21 (s, 3H, CH3), 2.41–2.50 (m, 4H, piperazine), 3.13 (t, J=5.2 Hz, 4H, piperazine), 6.70 (d, J=4.1 Hz, 1H, furan) 7.35 (d, J=4.1 Hz, 1H, furan), 7.54 (s, 1H, aldimine), 7.91 (d, J=8.5 Hz, 2H, ArNO2), 8.26 (d, J=8.5 Hz, 2H, ArNO2). ESI‐MS (C16H19N4O3, [M+H]+) calcd. m/z=315.1453, found 315.1456. MP 122–124 °C.</p><p>N ′‐((5‐(4‐cyanophenyl)furan‐2‐yl)methylene)thiophene‐2‐carbohydrazide  (4). Yellow crystals; yield: 20 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 7.11 (d, J=3.5 Hz, 1H, furan), 7.23 (t, J=4.7 Hz, 1H, thiophene), 7.40 (d, J=3.5 Hz, 1H, furan), 7.80–8.05 (m, 6H, arom.), 8.37 (s, 1H, aldimine), 11.86 (brs, 1H, NH). ESI‐MS (C17H12N3O2, [M+H]+) calcd. m/z=322.0648, found 322.0643. MP 245 °C (dec).</p><p>N ′‐((5‐(4‐cyanophenyl)furan‐yl)methylene)isonicotinohydrazide  (5). Yellow crystals; yield: 30 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 7.14 (d, J=3.5 Hz, 1H, furan), 7.40 (d, J=3.5 Hz, 1H, furan), 7.80 (d, J=5.8 Hz, 2H, pyridine), 7.91 (d, J=8.5 Hz, 2H, ArCN), 7.96 (d, J=8.5 Hz, 2H, ArCN), 8.03 (brs, 1H, NH), 8.40 (s, 1H, aldimine), 8.75 (d, J=5.8 Hz, 2H, pyridine). ESI‐MS (C18H11N4O2, [M−H]−) calcd. m/z=315.0880, found 315.0879. MP 240 °C (dec).</p><p>N ′‐((5‐(4‐cyanophenyl)furan‐2‐yl)methylene)acetohydrazide  (6). Orange crystal; yield: 35 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 2.18 (s, 3H, CH3), 7.00 (d, J=3.6 Hz, 1H, furan), 7.35 (d, J=3.6 Hz, 1H, furan), 7.87–7.94 (m, 4H, arom.), 8.07 (s, 1H, aldimine), 11.33 (brs, 1H, NH). ESI‐MS (C14H11N3O2, [M+Na]+) calcd. m/z=276.0747, found 276.0743. MP 190 °C (dec).</p><p>N ′‐((5‐(4‐cyanophenyl)furan‐2‐yl)methylene)‐2‐phenyl‐acetohydrazide  (8). Orange crystals; yield: 35 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 3.99 (s, 2H, CH2), 7.05 (d, J=3.5 Hz, 1H, furan), 7.29–7.40 (m, 6H, arom.), 7.88–7.97 (m, 4H, arom.), 8.15 (s, 1H, aldimine), 11.45 (brs, 1H, NH). ESI‐MS (C20H16N3O2, [M+H]+) calcd. m/z=330.1239, found 330.1236. MP 197 °C (dec).</p><p>(4‐(5‐(((2‐chloro‐4‐hydroxyphenyl)imino)methyl)furan‐2‐yl)benzonitrile  (9). Yellow crystals; yield: 25 %. 1H NMR (500 MHz, DMSO‐d6 ) δ 6.76 (dd, J=8.5 Hz, 1H, arom.), 6.90 (d, J=2.9 Hz, 1H, arom.), 7.22 (d. J=8.8 Hz, 1H, arom.), 7.28 (d, J=3.6 Hz, 1H, furan), 7.45 (d, J=3.6 Hz, 1H, furan), 7.93 (d, J=8.5 Hz, 2H, arom.), 7.99 (d, J=8.5 Hz, 2H, arom.), 8.41 (s, 1H, aldimine), 9.95 (brs, 1H, OH). ESI‐MS (C18H10ClN2O2, [M−H]−) calcd. m/z=321.0429, found 321.0432. MP 196–198 °C.</p><p>4‐((5‐(2‐(4‐methoxyphenyl)hydrazin‐1‐ylidene)methyl)furan‐2‐yl))benzonitrile  (10). Orange crystals; yield: 40 %; 1H NMR (300 MHz, DMSO‐d6 ) δ 3.68 (s. 3H, OCH3), 6.76 (d, J=4.1 Hz, 1H, furan), 6.84 (d, J=9.9 Hz, 2H, arom.), 7.00 (d, J=9.9 Hz, 2H, arom.), 7.30 (d, J=3.5 Hz, 1H, furan), 7.72 (s, 1H, aldimine) 7.84–7.89 (m, 4H, arom.), 10.36 (brs, 1H, NH). ESI‐MS (C19H14N3O2, [M−H]−) calcd. m/z=316.1083, found 316.1099. MP 138–140 °C.</p><p>4‐(5‐((2‐(4‐(methylsulfonyl)phenyl)hydrazono)methyl)furan‐2‐yl)benzonitrile (11). Dark‐orange crystals; yield: 25 %; 1H NMR (300 MHz, DMSO‐d6 ) δ 3.10 (s. 3H, CH3), 6.95 (d, J=4.1 Hz, 1H, furan), 7.19 (d, J=8.7 Hz, 2H, arom.), 7.35 (d, J=3.5 Hz, 1H, furan), 7.73 (d, J=8.7 Hz, 2H, arom.), 7.72 (s, 1H, aldimine), 7.87–7.94 (m, 4H, arom.), 11.12 (brs, 1H, NH). ESI‐MS (C19H16N3O3S, [M+H]+) calcd. m/z=366.0909, found 366.0906. MP 175 °C (dec).</p><p>((5‐(4‐cyanophenyl)furan‐2‐yl))methylidene)hydrazin‐1‐yl)benzene‐1‐sulfonamide  (12). Dark‐orange crystals; yield: 32 %; 1H NMR (300 MHz, DMSO‐d6 ) δ 6.92 (d, J=3.5 Hz, 1H, furan), 7.08 (brs, 2H, NH2), 7.13 (d, J=8.2 Hz, 2H, arom.), 7.35 (d, J=3.5 Hz, 1H, furan), 7.67 (d, J=8.7 Hz, 2H, arom.), 7.84–7.96 (m, 5H, arom., aldimine), 10.91 (brs, 1H, NH). ESI‐MS (C18H13N4O3S, [M−H]−) calcd. m/z=365.0706, found 365.0699. MP 217–219 °C.</p><!><p>The procedure was the same as for compounds 1–12, using 3‐methoxybenzaldehyde (0.27 g, 2.0 mmol) instead of 2‐furaldehyde, and 2‐thiophenecarboxylic acid hydrazide (0.43 g, 3.0 mmol). After evaporation of organic extract, the crude product obtained was purified by crystallization from absolute ethanol.</p><p>N ′‐[(4′‐cyano‐2‐methoxy[1,1′‐biphenyl]‐4‐yl)methylidene]thiophene‐2‐carbohydrazide  (13). White ivory crystals; yield: 24 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 3.82 (s. 3H, OCH3), 7.01 (d, J=7.2 Hz, 1H, arom.), 7.19 (t, J=3.5 Hz, 1H, thiophene), 7.30–8.20 (m, 8H, arom.), 8.39 (s, 1H, aldimine), 11.86 (brs, 1H, NH). ESI‐MS (C20H16N3O2S, [M+H]+) calcd. m/z=362.0690, found 362.0699. MP 255 °C (dec).</p><!><p>2.0 mmol of aldehyde (2‐furaldehyde for 14–18; 3‐methoxybenzaldehyde for 19 and 20; 3,4,5‐trimethoxybenzaldehyde for 21) were solubilized in 5 mL of acetone and slowly added to the aqueous solution of the appropriate amine/hydrazine/hydrazide derivative, with a catalytic amount of HCl 4 N. The mixture was stirred at room temperature for 24 h, then extracted with ethyl acetate (3×15 mL) and the organic layer dried over anhydrous Na2SO4. Compound 21 was filtered after precipitation from the acetone/water mixture. The solvent was evaporated under reduced pressure to give the crude product that was purified by crystallization from absolute ethanol.</p><p>1‐(Furan‐2‐yl)‐N‐(4‐methylpiperazin‐1‐yl)methanimine  (16). Brown oil; yield: 38 %; 1H NMR (300 MHz, DMSO‐d6 ) δ 2.39 (s, 3H, CH3), 2.66 (t, J=3.1 Hz, 4H, 2xCH2), 3.24 (t, J=3.1 Hz, 4H, 2xCH2), 6.41 (t, J=1.5 Hz, 1H, furan), 6.45 (dd, J=1.5 Hz, 1H, furan), 7.26 (s, 1H, aldimine), 7.41 (d, J=2.0 Hz, 1H, furan). ESI‐MS (C10H16N3O, [M+H]+) calcd. m/z=194.1290, found 194.1286.</p><p>N ′‐((furan‐2‐yl)methylidene)‐2‐phenylacetohydrazide  (17). White ivory crystals; yield: 46 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 3.50 (s, 2H, CH2), 6.50 (t, J=2.1 Hz, 1H, furan), 6.86 (d, J=2.0 Hz, 1H, furan), 7.18–7.30 (m, 5H, arom.), 7.80 (d, J=2.1 Hz, 1H, furan), 7.88 (s, 1H, aldimine), 11.30 (brs, 1H, NH). ESI‐MS (C13H13N2O2, [M+H]+) calcd. m/z=229.0974, found 229.0980. MP 156–160 °C.</p><p>4‐(‐2‐((furan‐2‐yl)methylidene)hydrazinyl)benzene‐1‐sulfonamide  (18). Orange crystals; yield: 47 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 6.57 (t, J=1.6 Hz, 1H, furan), 6.72 (d, J=1.6 Hz, 1H, furan), 7.04 (brs, 2H, NH2), 7.05 (d, J=5.3 Hz, 2H, arom.), 7.63 (d, J=5.2 Hz, 2H, arom.), 7.71 (s, 1H, aldimine), 7.81 (d, J=1.6 Hz, 1H, furan), 10.72 (brs, 1H, NH). ESI‐MS (C11H12N3O3S, [M+H]+) calcd. m/z=266.0597, found 266.0593. MP 161–165 °C.</p><p>4‐(2‐((3‐methoxyphenyl)methylidene)hydrazinyl)benzene‐1‐sulfonamide  (20). Orange crystals; yield: 25 %; 1H NMR (300 MHz, DMSO‐d6 ) δ 3.79 (s, 3H), 6.89 (d, J=4.1 Hz, 1H, arom.), 7.07 (brs, 2H, NH2), 7.14 (d, J=8.8 Hz, 2H, arom.), 7.21–7.34 (m, 3H, arom.), 7.65 (d, J=8.9 Hz, 2H, arom.), 7.90 (s, 1H, aldimine), 10.79 (brs, 1H, NH). ESI‐MS (C14H14N3O3S, [M−H]−) calcd. m/z=304.0753, found 304.0756. MP 214–218 °C.</p><p>1‐(((3,4,5‐trimethoxyphenyl)methylidene)amino)imidazolidine‐2,4‐dione (21). White solid; yield: 70 %. 1H NMR (300 MHz, DMSO‐d6 ) δ 3.68 (s, 3H, OCH3), 3.80 (s, 6H, 2xOCH3), 4.31 (s, 2H, CH2), 7.01 (s, 2H, arom.), 7.73 (s, 1H, aldimine), 11.17 (brs, 1H, NH). ESI‐MSv(C13H16N3O5, [M+H]+) calcd. m/z=294.1086, found 294.1083. MP 270 °C (dec.).</p><!><p>Stability studies in buffered solution were performed following an already described procedure, [23] on a Phenomenex C18 column (150×4.6 mm i.d., 3 μm particle size; Phenomenex, Castel Maggiore, Italy) using a mobile phase consisting of a mixture of methanol‐water (75 : 25 v/v, with aqueous formic acid 0.1 %). The used flow rate was 0.500 mL/min while the injection volume was 20 μL. Wavelength of UV‐Vis detector was adjusted at 254 nm. The chemical stability was evaluated in a phosphate buffer solution pH 7.4 (10 mM HPO4 2−/H2PO4 −; 100 mM NaCl) at 37 °C. Five different concentrations from 0.5 μM to 20 μM were studied in a 2 h time range (data not shown). Each concentration (0.5, 1, 5, 10 and 20 μM) was tested in triplicate starting from 3 different stocks solution (1 mM) prepared separately. The time range was extended to 6 h only for the samples at 20 μM concentration (Figure 6a).</p><p>Log k' values (k'=(tr‐t0)/t0) and purity determinations were carried out using a Phenomenex Gemini C18 4.6×150 mm, with 3 μm size particles, built on a Waters double pump HPLC system in isocratic conditions. Injection volumes were 10 μL, flow rate was 0.5 mL/min, and detection was performed with UV (λ=254 and 370 nm). Samples were prepared by dissolving 0.1 mg/mL of the solute in 10 % v/v DMSO and 90 % v/v methanol. Retention times (tr) were measured at least from three separate injections, and dead time (t0) was the retention time of deuterated methanol. The mobile phase was filtered through a Supelco Nylon‐66 membrane 0.45 μm (Merck Life Science Srl, Milan, Italy) before use. For each reference compound, the average tr of three consecutive injections of 10 μL of sample was used to calculate the log k' values. The eluent consisted of five different mixtures of methanol and PBS buffer 10 mM at pH 7.4, with methanol/buffer ratios ranging from 80 : 20 to 60 : 40 v/v.</p><!><p>Inhibition assays of hChEs and hMAOs (all from Sigma Aldrich) were performed by using already published protocols. [24] All compounds were assayed at 10 μM concentration and, for those showing inhibition >60 %, IC50 values was calculated by testing seven concentrations in the range 30–0.01 μM. Briefly, the classical spectrophotometric Ellman's test (for ChEs) and the fluorimetric detection of 4‐hydroxyquinoline (for MAOs) were adapted to a plate reader procedure with 96‐well microtiter plates (Greiner Bio‐One GmbH, Frickenhausen, Germany). Readings were made with Infinite M1000 Pro plate reader (Tecan, Cernusco s.N., Italy) and statistical regressions with Prism software (GraphPad Prism version 5.00 for Windows, GraphPad Software, San Diego, CA, USA). Kinetics of MAO inhibition for compound 9 were calculated with four concentrations of inhibitor (0, 0.5, 0.8, 1.5 μM) and seven concentrations of kynuramine (from 10 to 250 μM), and data analysed by means of the "Enzyme kinetics" module of Prism.</p><!><p>Reagents for cell cultures were purchased from Life Technologies (ThermoFisher Scientific, Waltham, MA, USA) unless otherwise stated. The human tumour cell lines of neuroblastoma SH‐SY5Y were obtained from the National Cancer Institute, Biological Testing Branch (Frederick, MD, USA) and were maintained in the logarithmic phase at 37 °C in a 5 % CO2 humidified air in RPMI 1640+Glutamax medium supplemented with 10 % fetal bovine serum, 1 % penicillin and streptomycin and 50 μg/mL gentamicin.</p><!><p>ROS production in SH‐SY5Y cell line was detected using Cellular Reactive Oxygen Species Detection Assay Kit ab186027 (Abcam, Cambridge, UK), as previously described. [1] Briefly, cells were seeded into 384‐well flat bottom transparent polystyrene microtiter plates (Greiner) at a plating density of 12000 cells per well. After seeding, microtiter plates was incubated overnight at 37 °C, then added with phenelzine sulfate (positive control) or test compounds, and dopamine HCl (10 nM) as ROS inductor. After incubation and washing, DCF‐DA was added, the plate was incubated, washed again with PBS, and the fluorescence read every 15 min in a 60 min time interval at 535 nm (excitation at 485 nm) using the Tecan Infinite M1000 Pro plate reader.</p><!><p>An already reported protocol, [1] based on the inhibitor‐stop method, [25] was used. The recombinant WT CAC protein was reconstituted into liposomes as described previously.[ 1 , 26 ] Briefly, transport was started by adding [3H]‐carnitine to proteoliposomes and stopped by the addition of N‐ethylmaleimide. After removal of the external substrate, intraliposomal radioactivity was measured by a liquid scintillation counter (Perkin Elmer, Milan, Italy). EC50 values were calculated using AATBioquest EC50 calculator. [27] Statistical analysis was performed by Student's t‐test, as indicated in figure legends. Values of p<0.05 were considered statistically significant. Data points were derived from the mean of three different experiments, as specified in the figure legends.</p><!><p>The authors declare no conflict of interest.</p><!><p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p><p>Supporting Information</p><p>Click here for additional data file.</p>

PubMed Open Access

Structure of the competence pilus major pilin ComGC in Streptococcus pneumoniae

Type IV pili are important virulence factors on the surface of many pathogenic bacteria and have been implicated in a wide range of diverse functions, including attachment, twitching motility, biofilm formation, and horizontal gene transfer. The respiratory pathogen Streptococcus pneumoniae deploys type IV pili to take up DNA during transformation. These “competence pili” are composed of the major pilin protein ComGC and exclusively assembled during bacterial competence, but their biogenesis remains unclear. Here, we report the high resolution NMR structure of N-terminal truncated ComGC revealing a highly flexible and structurally divergent type IV pilin. It consists of only three α-helical segments forming a well-defined electronegative cavity and confined electronegative and hydrophobic patches. The structure is particularly flexible between the first and second α-helix with the first helical part exhibiting slightly slower dynamics than the rest of the pilin, suggesting that the first helix is involved in forming the pilus structure core and that parts of helices two and three are primarily surface-exposed. Taken together, our results provide the first structure of a type IV pilin protein involved in the formation of competence-induced pili in Gram-positive bacteria and corroborate the remarkable structural diversity among type IV pilin proteins.

structure_of_the_competence_pilus_major_pilin_comgc_in_streptococcus_pneumoniae

Introduction<!>ComGC is the major pilin in S. pneumoniae competence-induced pili<!><!>ComGC is the major pilin in S. pneumoniae competence-induced pili<!>Structural features of pneumococcal ComGC filaments<!><!>ComGC processing and dimerization in the membrane<!><!>ComGC processing and dimerization in the membrane<!>Structure of soluble ComGC<!><!>ComGCs dynamics on different time scales might be important for pilus assembly<!><!>Sequence variation in ComGC<!><!>Discussion<!>Bacterial strains and growth conditions<!>Transmission electron microscopy and immunogold labeling to visualize competence pili<!>Analysis of competence pili<!>Preparation of pili, two-dimensional PAGE, and immunoblotting to assess ComGC assembly<!>Transformation frequency assay<!>In vitro ComGC processing<!>BACTH<!>Chemical cross-linking<!>Expression and purification of labeled ComGC for NMR<!>NMR data collection<!>Sequential assignment<!>Structural determination<!>Dynamics<!>Statistical analysis<!>Author contributions<!>

<p>Type IV pili are important virulence factors on the surface of many pathogenic bacteria. These extracellular appendages can be several microns long and are involved in various functions, including adherence (1, 2), twitching motility (3, 4), biofilm formation (5, 6), and DNA uptake (7–9). Type IV pili are composed of thousands of copies of major pilin protein that are tightly packed in a helical arrangement (10, 11). Pilins are synthesized as prepilins containing a conserved N-terminal prepilin cleavage motif. Once synthesized, prepilins are processed by a membrane-bound prepilin peptidase, often called PilD, which removes the signal peptide. Based on the length of the signal peptide and the length of mature pilin, two subclasses, namely type IVa and type IVb pilins, have been distinguished (12).</p><p>A number of pilin structures are available for both subclasses mainly for Gram-negative bacteria (13). They suggest an overall conserved architecture, with each pilin having an extended N-terminal domain (α1-N and α1-C) and a C-terminal globular head domain. α1-N is primarily hydrophobic and retains the pilin subunits in the inner membrane until assembly, whereas the α1-C is tightly packed against the head domain composed of several β-strands. The α/β loop connects the N-terminal helix to the β-sheet and is important for interactions between individual pilin subunits (10). Upon pilus assembly, α1-N forms the core of the assembled pilus, and α1-C is buried in the C-terminal head domain that forms the pilus surface. Characteristic for most pilins is also a disulfide-bonded loop (D-region) in the C-terminal domain, which is essential for pilus assembly (10). Most of the structural diversity among different pilins lies in the α/β loop, and the number and topology of β-strands are in the C-terminal domain. Notably, many of the available pilin structures are lacking the highly hydrophobic N-terminal domain (α1-N) making the truncated protein more soluble and easier to purify for later structural characterization.</p><p>Type IV pili are also produced by Gram-positive bacteria, including several Clostridium species (14), Ruminococcus albus (15), and Streptococcus species (9, 16, 17), but many molecular and structural aspects of pilus biogenesis in Gram-positive species remain unclear. Recently, DNA uptake in Streptococcus pneumoniae was shown to rely on the formation of a type IV pilus that is able to directly bind to DNA (9). This transformation pilus is assembled on the surface of competent bacteria and composed of the major pilin ComGC. Pneumococcal comGC is encoded in the comG operon that also encodes a putative ATPase (ComGA), which powers pilus assembly (9), a membrane-spanning protein (ComGB), and four minor pilins (ComGD, -E, -F, and -G) whose functions remain elusive.</p><p>Herein, we characterize the pneumococcal major pilin ComGC and its ability to assemble into type IV pili. We also present the NMR structure of N-terminally truncated ComGC, which exclusively consists of α-helical segments and a variable C-terminal domain with no sequence similarity to previously characterized type IV pilin proteins.</p><!><p>Previously it was reported that S. pneumoniae produces type IV pili composed of ComGC in S. pneumoniae strain R6 and the clinical isolates G54 and CP strains (9). To detect competence-induced pili in the S. pneumoniae TIGR4 (T4) background, we have used the un-encapsulated T4 strain (T4R) deficient in the rlrA operon (T4RΔrrgA-srtD). The rlrA operon encodes an adhesive pneumococcal pilus that is assembled by pilus-associated sortases (18, 19). By using this mutant strain, we were able to rule out other pilus structures expressed on the bacteria. We then looked at the formation of type IV pili in T4RΔrrgA-srtD cultures induced with the competence-stimulating peptide (CSP)3 and control cultures without CSP addition. As shown in Fig. 1A, a type IV pilus could be visualized by transmission electron microscopy in negatively stained S. pneumoniae T4RΔrrgA-srtD. When we compared electron micrographs of negatively stained competent T4RΔrrgA-srtD to R6, pili were less frequently observed in the T4R background, which likely provides an explanation as to why the transformation frequency is almost three orders of magnitude lower in T4R than in R6 (Fig. 1B).</p><!><p>S. pneumoniae assembles competence type IV pili composed of ComGC. A, electron micrograph of negatively stained competent S. pneumoniae T4RΔrrgA-srtD induced with CSP. Black arrows indicate the pilus. B, transformation frequency of S. pneumoniae T4R and R6 strain. The error bars represent standard deviation (S.D.) of a minimum of three independent experiments. C and D, immunogold electron microscopy to visualize pili on competent S. pneumoniae R6 using primary antibody specific to ComGC and secondary antibody conjugated to 6-nm gold particles. D, enlargement of the immunogold-labeled pilus. Black arrows indicate the pilus. E, electron micrograph of a competence pilus in strain R6 stained with anti-ComGC antibody and protein A coupled to 10-nm gold particles. F, two-dimensional PAGE to assess multimerization of mature ComGC. A pilus preparation of T4 WT or ΔC strain was run on a 12% native gel (1D, first dimension). A piece of gel corresponding to one lane of the gel was cut and placed horizontally on top of a second SDS-PAGE (2D, second dimension). After migration, gels were immunoblotted with anti-ComGC antibody. Arrows indicate ComGC and protein multimers.</p><!><p>For that reason, we decided to do immunogold labeling of ComGC in competent R6 bacteria and used primary polyclonal ComGC antibodies, raised against the purified protein or an anti-peptide antibody, and secondary antibody labeled with 6-nm gold particles. We frequently found gold particles labeling the entire type IV pilus suggesting that ComGC is the major pilin protein (Fig. 1, C and D). We also stained competent R6 bacteria with primary polyclonal ComGC antibody followed by incubation with protein A coupled to 10-nm gold particles. In this way the pilus is less frequently labeled with gold particles; however, the underlying pilus filament is clearly visible (Fig. 1E).</p><p>To further study pilus polymerization also in an encapsulated T4 background, we analyzed pili preparations by two-dimensional (2D) PAGE. First, pili preparations of wild-type T4 (WT) or a comGC knock-out mutant (ΔC) were run on a 12% native gel, which resulted in a local concentration of ComGC on the top of the gel. One lane of each sample was then cut and placed horizontally on SDS-PAGE. After migration, the gel was immunoblotted and probed with ComGC antibodies. When entering the SDS-containing gel, high-molecular-weight structures will be denatured, which is why we observe monomeric ComGC (x1); when only partially denatured, distinct ComGC building blocks (x2 and x3) can be detected (Fig. 1F) suggesting that ComGC also forms the pilus backbone in S. pneumoniae T4.</p><!><p>To further assess the structural features of native competence pili, micrographs of uranyl acetate-stained samples of S. pneumoniae strain R6 were inspected. The filaments showed a pronounced degree of flexibility and only short straight regions were observed (Fig. 2A). A suitable amount of straight filament regions were identified by inspecting a large number of micrographs and were used for analysis of potential helical symmetry in the filaments. No helical diffraction pattern was evident from raw micrographs, but after averaging filament segments layer lines became visible in the power spectra. Based on a class average power spectrum the first prominent layer line was observed at a distance of 0.0252 Å−1 from the equator corresponding to a helical pitch of ∼40 Å (Fig. 2B). This was in accordance with a helix normal profile plot in real space showing similar distances between peaks along the helical axis (Fig. 2C). The average diameter of the filaments was derived from helix width profiles of 16 class averages and found to be 64 ± 1.6 Å (Fig. 2D). A representative class average can be seen in Fig. 2E.</p><!><p>Structural features of ComGC filaments. A, representative electron micrograph of a competence pilus in strain R6 used for class averages. Scale bar, 50 nm. B, averaged power spectrum of a representative class average based on straight pilus regions. Predominant layer lines at 0.0252 Å−1 from the equator are visible corresponding to a helical pitch of ∼40 Å. C, helix normal profile along the helical axis showing a distance between peaks corresponding to the pitch derived from the power spectrum. D, helix width profile of class averages showing a width of 64 Å. The mean diameter of 16 class averages was 63 ± 1.6Å. E, representative 2D class average of the competence pilus.</p><!><p>One characteristic of proteins belonging to the type IV pilin family is the presence of a well-conserved prepilin cleavage motif Gly-Phe-Xaa-Xaa-Xaa-Glu (20). Pneumococcal ComGC is synthesized with a 15-residue leader sequence and shares a highly conserved PilD cleavage site with other known major pilins (Fig. 3A). It can also be processed in vitro by co-expressing full-length ComGC and PilD (Fig. 3B).</p><!><p>Pneumococcal ComGC is processed by PilD and can interact with itself. A, partial sequence alignment of the N-terminal domains of the major pilin proteins in K. oxytoca (PulG), N. meningitidis (PilE), S. pneumoniae (ComGCSp), and B. subtilis (ComGCBs). The characteristic prepilin cleavage site recognized by the prepilin peptidase PilD and the invariant Glu residues at position 5 (E5) after the cleavage site are indicated by an arrow. Conserved residues are shaded, and identical residues are shown in bold. B, in vitro ComGC cleavage analyzed by Western blotting with antibodies specific to ComGC. ComGC is partially processed when co-expressed with PilD in E. coli. C, quantification of ComGC–ComGC interaction identified by bacterial two-hybrid assay. The graph shows mean values of β-galactosidase activity expressed in Miller units between the indicated hybrid proteins T25-ComGC/T18-ComGC. A strain expressing Zip-T18 and Zip-T25, in which the hybrid proteins interact through a leucine zipper motif, was used as positive control. K. oxytoca PulG, T25-PulG/T18-PulG was included as functional positive control. E. coli BTH101 co-transformed with pUT18C and pKT25 empty plasmid or a strain expressing T25-PulG/T18-ComGC was used as negative control. The error bars represent S.D. of a minimum of three independent experiments with three different clones. A one-way analysis of variance test followed by Dunnett's post-test to compare each interaction pair to the negative control (T25/T18) was used for statistical analysis: ***, p < 0.001; ns, no significant difference. D, paraformaldehyde cross-linking of E. coli BTH101 expressing T25-ComGC/T18-ComGC. Cell extracts were analyzed by immunoblotting with anti-ComGC antibody. An untreated sample was used as expression control (indicated as C, left lane). Hybrid proteins and dimerization are indicated on the right side of the panel.</p><!><p>To test whether two full-length membrane-embedded ComGC monomers can directly interact with each other, we used the bacterial adenylate cyclase two-hybrid (BACTH) system (21). Mature ComGC was fused to the C-terminal end of T25 and T18 fragments of Bordetella pertussis adenylate cyclase (CyaA), and lacZ expression was measured. Compared with the negative control (T25/T18), T25-comGC/T18-comGC showed a statistically significant increase in CyaA activity (Fig. 3C). Because the positive control, in which T25 and T18 are fused to the leucine zipper domain of GCN4 (21), showed much higher activity, we included another functional control protein, PulG. PulG is the major pilin protein of the type II secretion system in Klebsiella oxyctoca and is known to form type IV-like pili when overproduced (22). The level of CyaA activation in T25-PulG/T18-PulG was similar to T25-comGC/T18-comGC, indicating efficient dimerization of ComGC in the membrane (Fig. 3C). We also tested a strain expressing T25-PulG/T18-ComGC, which showed very low CyaA activity similar to the negative control (T25/T18), suggesting that these two functional major pilins cannot interact in the membrane. To validate our interaction between two ComGC monomers, we also performed chemical cross-linking of Escherichia coli BTH101 expressing T25-comGC/T18-comGC and were able to detect ComGC dimerization by immunoblotting with ComGC antiserum (Fig. 3D).</p><!><p>ComGC has very little sequence similarity to other pilins of which the three-dimensional structure has been solved. Specifically, ComGC has only few hydrophobic amino acid residues in the C terminus, which in other pilins form the β-strand-rich head domain. Indeed, secondary structure predictions using Jpred4 (23) and Agadir (24) show that the ComGC sequence has several segments with high α-helix propensity and no β-strand propensity (supplemental Fig. S1). This suggests that the three-dimensional structure of pneumococcal ComGC may differ significantly from known structures of type IV pilins. To determine the structure of ComGC, we prepared a truncated construct lacking the predicted N-terminal transmembrane helical domain (ComGCs, see Fig. 5A). It was previously shown for the major pilin PAK in Pseudomonas aeruginosa that deletion of α1-N does not perturb the structural fold, with full-length and truncated protein essentially being identical (25). To determine the ComGCs structure, we used NMR spectroscopy. ComGCs provided well-resolved spectra and remained largely homogeneous and stable at 10 °C (Fig. 4), which enabled us to solve the atomic resolution structure of ComGCs in solution (Fig. 5B). A summary of the structural statistics and constraints is provided in Table 1. ComGCs consists of three flexible helical segments: α1-C, involving residues 54–69; a shorter α2 helix involving residues 75–81; and finally, a C-terminal α3 spanning residues 86–99. The first 14 N-terminal and 10 C-terminal residues remain unfolded in our in-solution structure, and only few inter-residual NOEs are observed in this part of the molecule (supplemental Fig. S2). This observation is in good agreement with the secondary chemical shifts (supplemental Fig. S1A). α1-C seems to be only loosely attached to α2 and α3, and a general lack of long-range distance restraints between these two "domains" indicates that the structure is less constrained and rather flexible in this hinge. The relative orientation of the helices was restrained by measuring residual dipolar couplings (Fig. 5, B and C). The overall tertiary fold appears almost two-dimensional being ∼60 Å tall in the vertical plane, ∼50 Å wide in the horizontal plane, but only ∼10 Å broad in the profile plane (Fig. 5D), which essentially caused all three helices to be mostly solvent-exposed, providing a very large solvent-accessible surface (∼8000 Å2). Visualizing the electrostatic potential of the solvent-accessible surface revealed a well-defined electropositive cavity formed between the helices, and two highly electronegative areas (denoted δ−) in the top of α1-C and the opposite side of α2 (Fig. 5E). Similarly, visualizing the hydrophobicity of the surface also showed two well-defined patches. The first hydrophobic patch (φ1) is situated at the back of α1-C, opposite to the electropositive patch (φ1) and the other (φ2) in α2 (Fig. 5F).</p><!><p>Assigned 1H-15N HSQC of ComGC recorded at 283K. The HSQC spectrum displays signals from all the backbone and side chain N-H correlations. The 1H chemical shift is plotted along the x axis and the 15N chemical shifts along the y axis. The chemical shifts report on the local chemical environment, and thus very small changes in structure will cause changes in chemical shifts. We observed 65 well defined amide peaks in the ComGC HSQC of which we were able to assign 61 residue-specific resonances (black arrows). Unassigned resonances in the upper right corner are side-chain N-H correlations. Importantly, we do not see any clear indication of more than one conformational state as this would give rise to more chemical shifts in the spectrum.</p><p>NMR structure of soluble ComGC is composed of three flexible helical segments. A, schematic and secondary structure overview of the full-length ComGC protein. The leader peptide is colored in cyan; the membrane-spanning helix is in brown; soluble helices are in red, and flexible regions are in green. The ComGCs construct used for structural determination by NMR is indicated. In the protein sequence Glu-5 is marked by ■ and the helix-breaking residue Pro-22 by ●. B, alignment of the 20 lowest energy structures returned from the structure calculations. Ensemble alignments for all three helices (left), α1-C only (middle), and α2-α3 only (right) are shown. The structure is particularly flexible between α1-C and α2-α3, which is illustrated by alignment of the α1-C only and α2 and α3. Root mean square deviation values are listed in supplemental Table S1. C, schematic of the ComGCs NMR structure showing the three helical segments as well as the flexible regions. D, calculated solvent-accessible surface of ComGCs. E, APBS calculated electrostatics from ±2 kT/e display well defined electropositive (+) and electronegative (δ−) solvent-accessible patches. F, solvent-accessible hydrophobic patches φ1 and φ2 colored using the Eisenberg hydrophobicity scale ranging from −2.5 to 1.5.</p><p>NMR structural constraints and structure statistics for ComGCs</p><p>None of the structures exhibit distance violations of >0.3 Å or dihedral angle violations >4°.</p><p>a PROCHECK, structured regions 16–30, 36–42, and 47–60 are shown.</p><p>b Residues 16–30, 36–42, and 47–60 are shown. Large root mean square deviations can be assigned to the flexible hinge between H1 and H2.</p><!><p>The structural flexibility hypothesized above led us to study the dynamics in greater detail, and we therefore measured the longitudinal (R1) and the transverse (R2) 15N relaxation rates in both (relative to the external magnetic field) as well as heteronuclear 1H-15N-NOEs (hetNOEs), at two different field strengths (Fig. 6A). As expected, and in support of the ComGCs structure, the unstructured region 40–52 displayed generally longer R1 rates (>1.5 s−1), short R2 rates (<10 s−1), and relatively lower hetNOE values (<0.5), compared with the structured regions. Unlike R2, R1 rates are strongly field-dependent, and therefore the relative R1 difference is mostly visible at the higher field strength. The R2 rates are generally high (20.3 s−1 on average for residues 56–108) in all of the structured regions as would be expected. However, several residues in α1-C exhibit high R2 rates, which could suggest conformational exchange with one or more additional states (Fig. 6B). To gain insight into site-specific internal motion, we used the measured R1, R2, and hetNOE values to calculate the reduced spectral density functions, J(0), J(ωN) and J(0.87ωH), reporting on dynamics on three different time scales (Fig. 6B). J(0) represents protein mobility in the nano-second time scale, thus low J(0) values normally indicates higher flexibility as observed for residues 40–52, showing also higher internal motion in the J(ωh) pico-second time scale supporting that this region remains largely unstructured in solution. The more structured regions, and especially the flexible hinges between the helical segments, displayed much higher J(0) values indicating that these regions have mobility on the nano-second time scale. Interestingly, Asp-48 just before α1-C appeared highly dynamic from the hetNOE experiment; however, on a time scale (lower nano-second) different from all other residues. Also, the hydrophobic residues Leu-78 and the stretch from Ala-89 to Lys-93, located in the interface between α2 and α3 showed dynamics on a faster time scale than observed for other nearby residues.</p><!><p>ComGCs is dynamic on several different time scales. A, fitted 15N R1 rates (top), R2 rates (middle), and hetNOEs (bottom), at two different field strengths, 600 and 900 MHz, with respect to protons. The secondary structure of ComGCs is shown above. B, reduced spectral density functions J(0) (top), J(ωN) (middle), and J(0.87ωh) (bottom) calculated from the backbone relaxation data.</p><!><p>A total of 14 polymorphic sites differing in the number of variations from the reference sequence TIGR4 were identified in 23 publicly available S. pneumoniae genomes suggesting that ComGC is well conserved. A phylogenetic tree of strains clustered according to their ComGC sequence and the corresponding multiple sequence alignment are shown in supplemental Fig. S3. The most divergent strains exhibit a sequence identity of 91%. All strains can be grouped into two main clusters. The strains belonging to cluster 1 are identical with exception of strain NT11058 that carries one additional variation (N107Y) than the other strains present in this group. The second cluster, containing our reference sequence, is more diverse and can be sub-grouped into five sub-clusters. The virulent strain D39 and the avirulent, un-encapsulated laboratory strain R6, a derivative of D39, are closely related to TIGR4 with only one sequence variation (N96H). The majority of polymorphisms are localized to the interface between helices α2 and α3 and only 1 out of 14 is localized to the αC-1 helix (Fig. 7). This suggests that the hypothesized hydrophobic pilin–pilin interface involving the transmembrane α1-N and α1-C helical domains has been largely conserved throughout evolution and that the α2-α3 head group has undergone significantly larger changes primarily affecting the exposed electrostatic regions depicted in Fig. 5E.</p><!><p>Polymorphisms in ComGC. Model of soluble ComGC. Polymorphisms are plotted on the ComGC structure. Variable residues are shown in shades of red depending on their susceptibility to undergo mutations.</p><!><p>The pneumococcal competence pilus was first visualized recently (9). It is morphologically similar to other type IV pili described displaying filament diameters between 6–9 nm (11). Competence pili in S. pneumoniae have a mean diameter of 64 Å, which is comparable with the 60 Å diameter of type IV pili in Neisseria gonorrhoeae (26). They are helical assemblies, and the observed pitch of ∼40 Å is somewhat larger than the 37 Å pitch of N. gonorrhoeae pili, suggesting different assembly and stabilization strategies in ComGC competence pili. In comparison, the type IV pilus in Thermus thermophilus, ∼3 nm in diameter, shows a helical pitch of 49 Å forming a less compact pilus than type IV pili in N. gonorrhoeae (27). The observed differences in pilus diameter and helical pitch are likely explained by structural features of the major pilin subunit, which can vary considerably in sequence and size among bacteria expressing type IV pili.</p><p>Pneumococcal ComGC shares many features of canonical type IV pilins. Full-length ComGC has a well-defined conserved prepilin cleavage motif, an invariant Glu residue at position 5 after the cleavage site, and it is processed by PilD. The structure of soluble ComGC, provided here, is the first example of a type IV pilin protein involved in the formation of competence-induced pili in Gram-positive bacteria and reveals new structural features. Similar to previously described type IV pilins, ComGC has a predicted extended N-terminal α-helix but differs otherwise significantly as follows: 1) ComGC is exclusively α-helical; 2) the head group is much smaller; 3) the α1-C helix is separated from the transmembrane helix by a flexible linker that is largely unfolded in solution; and 4) ComGC contains no cysteines. Overall, ComGC is shorter than other type IV pilins and highly dynamic in solution, which may be an important feature for pilus assembly and function.</p><p>An important question raised by this structure regards the stabilization of ComGC. Most type IV pilins in Gram-negative bacteria and the major pilin ComGC in Bacillus subtilis have two cysteine residues in the C-terminal part of the protein that are important for protein stability and polymerization (13, 28), but there is no disulfide bond to stabilize ComGC. The major pilin, PilA1, in the Gram-positive bacterium Clostridium difficile also lacks cysteines (29). However, it is structurally much more compact in its C terminus than pneumococcal ComGC. In ComGC only two α-helices (α2 and α3) are forming the head domain, and the absence of other stabilizing structural elements might explain the observed flexibility in this region. In fact, PilA of Geobacter sulfurreducens (only 66 amino acids) is essentially lacking any globular head domain, and the NMR structure also showed a highly dynamic C-terminal region (30).</p><p>The assembly of pilin monomers into a model of the fully formed pilus has primarily been based on negative staining and electron cryo-micrographs, where individual monomers are fixed in a favorable multimeric organization and fitted into the obtained electron density (26, 31). These structural models serve as important frameworks for understanding pilus dimensions, appearance, and surface, but as a consequence of the low structural similarity of ComGC, primarily in the head group, we were not able to reliably predict ComGC assembly. Our data suggest that soluble monomeric ComGC will not adopt secondary or tertiary folds similar to other type IV pilins, but we cannot rule out that additional conformational states (i.e. helical rearrangements) will be favored during assembly or in the mature pilus structure.</p><p>The structure of ComGC itself provides initial information on the assembly and function of competence pili in S. pneumoniae. The electrostatic potential as well as the hydrophobicity of the accessible surface in ComGC reveals highly defined patches, which might restrict or guide pilus formation. Based on the hydrophobicity profile, we propose that α1-N and α1-C are involved in forming the core of the pilus structure, with parts of α2 and α3 being primarily surface-exposed. The residues Leu-78, Ile-84, and Tyr-92, involved in the hydrophobic patch, φ2, formed between α2 and α3 seem functionally distinct and may contribute to pilin flexibility during pilus assembly. Additionally, they could provide better resistance to shear forces in the environment by increasing the flexibility of the assembled pilus. It is also notable that the proposed α1-N and α1-C helices in ComGC seem to be separated by a larger stretch of residues, including the helix-breaking residue Pro-22, with no or less helical propensity. Interestingly, cryo-electron microscopy reconstruction of the Neisseria meningitidis type IV pilus recently revealed a similar non-helical portion in α1-N, between the residues Gly-14 and Pro-22, of the major pilin pilE (31). This stretch was proposed to function as a spring providing the filament additional flexibility in response to external forces, and it may have a similar purpose in pneumococcal competence pili.</p><p>Type IV pili have a conserved role during the process of transformation, and pilus-deficient strains of naturally transformable species have reduced DNA uptake potential (32–34). Interestingly, Neisseria species bind DNA, in a sequence-specific manner, through the minor pilin ComP exposed on the type IV pilus surface (35, 36). In many other competent bacteria, the exact mechanisms that govern pilus-DNA interactions remain elusive. It is generally believed that DNA binding is a function of the intact pilus through solvent-exposed surface residues that mediate interactions with the DNA backbone. Laurenceau et al. (9) have previously shown direct DNA binding to the pneumococcal pilus, but monomeric ComGC was unable to bind DNA (37) suggesting that elements in the competence pilus quaternary structure are required for DNA interactions. Visualizing the electrostatic potential of the solvent-accessible surface in ComGC revealed a well-defined electropositive cavity formed between the helices. Along with the flexible N-terminal part, this region displays several solvent-exposed Lys and Arg residues, which are residues that have been found to mediate DNA backbone interactions in other DNA-binding proteins (38). Once a competence pilus model is available, it will be interesting to explore whether and how this electropositive cavity contributes to DNA binding.</p><p>In conclusion, the structure of pneumococcal ComGC represents a unique member in the growing family of type IV pilins, and it provides initial structural insights into understanding how competence pili assemble and how DNA is taken up in natural transformation of S. pneumoniae.</p><!><p>All S. pneumoniae strains used in this study are described in supplemental Table S1. Bacteria were grown on blood agar plates at 37 °C and 5% CO2 overnight (O/N). For competence induction, plate-grown bacteria were used to inoculate C+Y medium, pH 7.9–8.0, at A620 = 0.05 and grown without agitation at 37 °C until A620 = 0.15. Competence was induced by addition of competence stimulating peptide (CSP-1 or 2 dependent on the strain used) at a final concentration of 100 ng/ml for 20 min, if not specified otherwise.</p><!><p>S. pneumoniae R6 or T4RΔrrgA-srtD, an unencapsulated strain lacking pili encoded by the rlrA islet, were grown at 37 °C in C+Y medium until A620 = 0.15 when competence was induced as described above. Twenty minutes post-induction the cells were centrifuged for 15 min at 5000 × g, 4 °C. The pellet was resuspended in 80 μl of phosphate-buffered saline (PBS). Drops of 10 μl were placed for 1 min on glow-discharged carbon-coated copper grids (Oxford Instruments, UK) for negative staining or carbon-coated gold grids (Aurion, Germany) for immunogold labeling. Negative staining was performed with 2% uranyl acetate in water. For immunogold labeling anti-ComGC antiserum, raised against a synthetic peptide corresponding to residues 95–108 of ComGC, was used. Grids were fixed with 10 μl of 0.2% glutaraldehyde for 2 min, and the reaction was stopped with 10 μl of 1% glycine for 15 min. The grids were then washed three times with PBS, 1% BSA, incubated with ComGC antibodies (1:100) for 1 h, washed three times with PBS, and incubated with secondary goat anti-rabbit antibody conjugated to 6-nm gold particles or protein A coupled to 10-nm gold particles diluted 1:250 for 45 min. Finally, the grids were washed six times with PBS and twice with distilled water before negatively staining with 2% uranyl acetate. Specimens were examined in a Tecnai 12 Spirit Bio TWIN transmission electron microscope (FEI Company, Eindhoven, Netherlands) operated at 100 kV. Digital images were recorded using a Veleta camera (Olympus Soft Imaging Solutions, GmbH, Münster, Germany).</p><!><p>Negative stain grids were prepared as described under immunogold labeling. Micrographs were collected manually at 120 kV using a Tecnai G2 Spirit TWIN electron microscope with a defocus value of 0.5–2.0 μm. Images were collected using a Tietz TemCam-F416 CMOS camera at a nominal magnification of ×67,000 and a pixel size of 1.57 Å employing the EM-Menu software (TVIPS GmbH). Data processing was done using the SPRING suite employing CTFFIND, CTFTILT, EMAN2, and SPARX (39–43). Straight regions of the pilus filaments were extracted, segmented, and averaged to determine outer dimensions and helical parameters. Averaged intensity width profiles were plotted, and the outer diameter was taken as the distance between the two outer minima in the intensity profile. Power spectra were calculated from the averages, and the most prominent layer lines were identified. The pitch was determined in real space from intensity normal profiles along the helical axis as well as from Fourier space based on layer line positions.</p><!><p>Competence pili preparations were obtained from S. pneumoniae grown in 500 ml of C+Y medium, and competence was induced as described above. Bacteria were pelleted at 4 °C by centrifugation for 15 min at 6000 × g. The supernatant containing detached/broken pili was filtered and pelleted by ultracentrifugation at 100,000 × g at 4 °C for 1 h. Pellets were resuspended in 100 μl of PBS. Multimerization of mature ComGC was assessed by two-dimensional PAGE, native gel (first dimension) and SDS-PAGE (second dimension). In brief, pili preparations of competent T4 WT and T4ΔcomGC were run on a 12% native gel. Then, one entire lane of each sample was cut and placed perpendicular on top of a second gel. After migration, electroblotting (Bio-Rad, Trans-Blot® TurboTM Midi PVDF Transfer Packs) and immunodetection with ComGC antibody were performed. Rabbit polyclonal ComGC antibody has been previously described (37). HRP-conjugated goat anti-rabbit antibody (GE Healthcare) and Amersham Biosciences ECL Prime Western blotting detection reagent (GE Healthcare) were used to visualize the blots.</p><!><p>Genomic DNA of S. pneumoniae carrying a streptomycin resistance mutation in the rpsL gene (44) was used to transform competent bacteria. In brief, S. pneumoniae was grown in C+Y medium at 37 °C until A620 = 0.15. Bacteria were then incubated at 30 °C for 15 min before CSP was added. After 15 min, 1 μg/ml DNA was added. Bacteria were then incubated for 30 min at 30 °C and another 60 min at 37 °C before plating in the presence and absence of streptomycin at 100 μg/ml final concentration. Blood plates were incubated O/N at 37 °C and 5% CO2 before being counted.</p><!><p>The plasmids pJWV25-PilD and pACYCDuet-1-flcomGC were constructed as follows. Full-length pilD and full-length comGC were amplified from S. pneumoniae TIGR4 genomic DNA using Phusion Flash High-Fidelity PCR Master Mix (Thermo Fisher Scientific) and suitable primers (supplemental Table S2). PCR products were digested with NotI (pilD) or NdeI and Xho (comGC) and subcloned into pJWV25 and pACYCDuet-1, respectively. The correct insertion was confirmed by PCR and sequencing (Eurofins MWG Operon). The resulting plasmids pJWV25-PilD and pACYCDuet-1-flcomGC (supplemental Table S3) were then co-transformed into competent T7 express Escherichia coli (New England Biolabs). Bacteria were grown in LB, pH 7.5, supplemented with 100 μg/ml ampicillin and 50 μg/ml chloramphenicol at 37 °C until A600 = 0.5, and induced with 1 mm isopropyl β-d-thiogalactopyranoside for 3 h. Bacteria were spun down, and 1× sample buffer was added to the pellet. Samples were incubated at 100 °C for 5 min before analysis by SDS-PAGE and immunoblotting with ComGC antibody as described above.</p><!><p>All plasmids used for BACTH are listed in supplemental Table S3. The gene encoding mature ComGC and mature PulG were PCR-amplified using suitable primers (supplemental Table S2) and cloned into pUT18C and pKT25. E. coli Top10 (Invitrogen) was used for all clonings. E. coli BTH101 (Euromedex) was co-transformed with respective BACTH plasmids (supplemental Table S3) and used for BACTH assay. The efficiency of the functional complementation between the recombinant plasmids encoding fusions to T18 (pUT18C) and T25 (pKT25) was quantified by measuring β-galactosidase activity in liquid culture as described previously with some modifications (21). Co-transformed BTH101 strains were grown in 5 ml of LB medium, supplemented with 100 μg/ml ampicillin, 50 μg/ml kanamycin, and 0.5 mm isopropyl β-d-thiogalactopyranoside, O/N at 30 °C. Three individual clones of each co-transformation were tested, and at least three independent cultures were performed. Subsequently, cultures were incubated for 20 min on ice and pelleted by centrifugation for 10 min at 4 °C. Next, cells were resuspended in the same volume of 1× Z buffer (90 mm Na2HPO4·2H2O, 40 mm NaH2PO4·H2O, 6 mm NaOH, 10 mm MgSO4·7H2O, 50 mm β-mercaptoethanol) and diluted until a final A600 nm = 0.3. Then, 1 ml of bacterial suspension was permeabilized by adding 100 μl of chloroform and 50 μl of 0.1% SDS. Tubes were then vortexed and incubated at 28 °C for 10 min before the enzymatic reaction was started by adding 200 μl of 0.4% o-nitrophenyl-β-d-galactopyranoside in phosphate buffer (90 mm Na2HPO4·2H2O, 40 mm NaH2PO4·H2O). The reaction was stopped by the addition of 500 μl of 1 m Na2CO3 when the samples became noticeably yellow, and the time of incubation with the substrate was recorded. The reaction mixtures were centrifuged for 5 min, and the supernatants were transferred into a cuvette. Then, the absorbance was recorded at 420 and 550 nm for each sample. The β-galactosidase activity was expressed in Miller units by using the following formula: 1000 × (A420 nm − 1.75 × A550 nm)/(incubation time (minutes) × volume (1 ml) × A600 nm).</p><!><p>In vitro cross-linking experiments were essentially performed as described previously (46). In brief, exponentially grown bacteria were pelleted by centrifugation, washed with 10 mm sodium phosphate buffer, pH 6.8, and incubated with 1% paraformaldehyde (Sigma) in 10 mm sodium phosphate buffer, pH 6.8, for 30 min. Cross-linking was stopped by addition of 3 m Tris, pH 8.8 (final concentration 300 mm Tris). Bacteria were washed, and pellets were resuspended in 1× NuPAGE sample buffer (Thermo Fisher Scientific) without reducing agent. Each sample was split into two tubes. One tube was kept at room temperature, and one tube was heated at 96 °C for 15 min before further analysis by SDS-PAGE and Western blotting with ComGC antibody.</p><!><p>The DNA sequence of ComGC lacking the signal peptide and codons for the N-terminal hydrophobic domain (ComGCΔ1–39) was cloned downstream of the His6 tag sequence into pet28a vector (Novagen). Constructs were confirmed by sequencing and transformed into E. coli Rosetta (DE3). Cells were grown O/N with shaking at 37 °C in M9 minimal media supplemented with [13C]glucose and [15N]ammonium sulfate containing 50 μg/ml kanamycin. The O/N culture was then diluted into fresh medium; cells were grown to A620 = 0.5 at 37 °C and induced with 1 mm isopropyl β-d-1 thiogalactopyranoside for 3.5 h. Cells were harvested by centrifugation at 7000 × g for 20 min at 4 °C, and pellets were stored at −20 °C. For affinity purification of ComGC, cell pellets were resuspended in buffer containing 50 mm Tris, 50 mm NaCl, pH 7.5, and protease inhibitor (Roche Applied Science) and lysed in a Stansted cell disrupter. Unbroken cells were pelleted by centrifugation at 35,000 × g, and supernatants were incubated with nickel-nitrilotriacetic acid (Ni-NTA, Qiagen)-agarose with rotation at 4 °C O/N. After washing the resin, protein was eluted with buffer containing 50 mm Tris, 50 mm NaCl, and 250 mm imidazole, pH 7.5. Imidazole was removed using PD-10 desalting columns (GE Healthcare). The N-terminal His6 tag was cleaved with thrombin (Sigma) for 2 h at room temperature and removed by incubation with Ni-NTA resin. ComGC was further purified by size-exclusion chromatography on a Superdex 75 gel filtration column.</p><!><p>The NMR samples contained ComGC at a concentration of 0.9 mm in a buffer containing 50 mm Tris, 50 mm NaCl, pH 7.5, and had a volume of 800 μl. Experiments were performed in 5-mm tubes at a temperature of 283 K on Bruker AVIII 600 spectrometer operating at 600 MHz (1H frequency). They were equipped with either a TXI cryoprobe or a TCI cryoprobe both equipped with a self-shielding z-gradient, and a Bruker AVII 900 spectrometer operating at 900 MHz (1H frequency), also at 283 K, and using a TCI cryoprobe equipped with a self-shielding z-gradient. Residual dipolar coupling (RDC) and HCCH-TOCSY spectra were recorded on an 800 MHz Agilent DD2 spectrometer with a room temperature probe.</p><!><p>ComGC backbone chemical shifts were sequentially assigned using 1H,15N-HSQC, 1H,13C-HSQC CBCANH, CBCA(CO)NH, HNCA, HN(CO)CA, HNCO, HN(CA)CO, HBHA(CO)NH CC(CO)NH, and HCC(CO)NH spectra. Side-chain chemical shifts were assigned by using a HCCH-TOCSY spectrum recorded with a mixing time of 20 ms, and 15N-TOCSY-HSQC and 13C-TOCSY-HSQC spectra recorded with mixing times of 80 ms. Chemical shifts are deposited in the BMRB with ID 34112.</p><!><p>Distance restraints were obtained from 15N NOESY-HSQC and 13C NOESY-HSQC experiments recorded using mixing times of 150 and 80 ms, respectively. Residual dipolar couplings were obtained from a sample aligned in PEG (C12E5)/hexanol (Sigma: 76437/H13303) liquid crystal medium with a final PEG concentration of 4%. The couplings were measured in in-phase/anti-phase 1H,15N HSQC spectra (47–49). Backbone dihedral angle restraints were calculated using DANGLE (50). Automated NOE assignment was performed using Cyana (51), and XPLOR-NIH (52) was subsequently used for including the RDC restraints and refining the structure. In total, 200 structures were calculated from which the 20 lowest energy structures were selected. Structures were aligned using Theseus (53) and visualized in PyMOL (DeLano Scientific). Electrostatics were calculated using APBS (54). Ramachandran plot statistics for the structural ensemble were calculated with PROCHECK (55). The coordinates are deposited in the Protein Data Bank with code 5NCA.</p><!><p>R1 and R2 relaxation rates were measured in using the 2D 1H,15N HSQC-based pulse sequences by Farrow et al. (56) using delays of 0.080*, 0.240, 0.400*, 0.640, 0.880*, 1.280, and 1.600 s for R1 experiments and 0.016*, 0.032, 0.048, 0.08*,0.112, 0.144*, and 0.2 s for R2 (starred values are recorded in duplicates). Heteronuclear 1H-15N NOE values were determined from peak ratios between saturated/steady-state and a reference spectrum (Iss/Iref) (57). Reduced spectral densities are calculated using Equations 1–4, (Eq. 1)J(0)=13d2+4c2(6R2−R1(3−185(γNγH)(NOE)−1)) (Eq. 2)J(ωN)=43d2+4c2(R1(1−75(γNγH)(NOE)−1)) (Eq. 3)J(0.87ωh)=45d2(R1(γNγH)(NOE−1)) (Eq. 4)d=(μ0hγNγH8π2)1rNH3,c=ωNΔσ3 where R1 and R2 and NOE are the fitted relaxation rates or intensity ratio; γN and γH are the gyromagnetic ratios of N and H; μ0 is the permeability of free space; h is Planck's constant; rNH is the bond length vector of the amide NH bond (set to 1.02 Å); ωN is the larmor frequency of N, and Δσ is the chemical shift anisotropy of N (set to −172 ppm) (45).</p><!><p>Data were statistically analyzed as indicated in the figure legends, using GraphPad Prism 5.04. If not stated otherwise, asterisks in the figures indicate groups of statistically different means (***, p < 0.001), determined by one-way analysis of variance with subsequent Dunnett's post hoc test.</p><!><p>S. M., U. A., and B. H. N. designed the study, and S. M., M. S. A., and V. O. performed the experiments. S. M. purified ComGC, and S. E., P. S., C. D. L., K. T., and U. A. determined the NMR structure and dynamics. T. B. performed class averages on pili. S. M., S. E., M. S. A., and B. H. N. wrote the paper. All authors reviewed the results and approved the final version of the manuscript.</p><!><p>This work was supported by grants from the Swedish Research Council, the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, the Swedish Foundation for Strategic Research (SSF), the Knut and Alice Wallenberg Foundation, the Carlsberg Foundation, and the Lundbeck Foundation. The authors declare that they have no conflicts of interest with the contents of this article.</p><p>This article contains Tables S1–S3 and Figs. S1–S3.</p><p>The atomic coordinates and structure factors (code 5NCA) have been deposited in the Protein Data Bank (http://wwpdb.org/).</p><p>competence stimulating peptide</p><p>bacterial adenylate cyclase two-hybrid</p><p>heteronuclear 1H-15N-NOE</p><p>overnight</p><p>residual dipolar coupling</p><p>nickel-nitrilotriacetic acid.</p>

PubMed Open Access

Phosphine Catalysis of Allenes with Electrophiles

Nucleophilic phosphine catalysis of allenes with electrophiles is one of the most powerful and straightforward synthetic strategies for the generation of highly functionalized carbocycle or heterocycle structural motifs, which are present in a wide range of bioactive natural products and medicinally important substances. The reaction topologies can be controlled through judicious choice of the phosphine catalyst and the structural variations of starting materials. This Tutorial Review presents selected examples of nucleophilic phosphine catalysis using allenes and electrophiles.

phosphine_catalysis_of_allenes_with_electrophiles

1. Introduction<!>2.1. [3+2] Annulation with electron-deficient olefins<!>2.2. [4+2] Annulation with electron-deficient olefins<!>2.3. [3+2] Annulation with imines<!>2.4. [4+2] Annulation with imines<!>2.5. [3+2]/[4+2] Annulation with ketones<!>2.6. Annulations with aldehydes<!>2.7. Miscellaneous<!>3. Enantioselective nucleophilic phosphine catalysis of allenes with electrophiles<!>3.1. Chiral phosphines without additional functionality<!>3.2. Chiral phosphines with hydrogen-bond donors<!>4. Conclusions

<p>Trivalent phosphines and their derivatives are used widely in organic synthesis. Traditionally, they are applied as stoichiometric reagents in several name reactions, including the Wittig, Staudinger, and Mitsunobu reactions.1 In modern organic chemistry, organophosphorus compounds are often employed as ligands for transition metal–catalyzed processes.2 Although the use of phosphines as catalysts for organic reactions can be traced back to the 1960s, reports of nucleophilic phosphines as organocatalysts are relatively rare in the second half of the last century. In 1963, Rauhut and Currier reported one of the first phosphine-catalyzed reactions: the dimerization of electron-deficient olefins.3 In 1966, Winterfeldt and Dillinger discovered triphenylphosphine-catalyzed annulation for the synthesis of γ-butenolides when using acetylenedicarboxylates and aldehydes as substrates.4 Two years later, Morita et al. described a reaction of an activated olefin and an aldehyde catalyzed by a phosphine.5 This phosphine-catalyzed transformation, together with the similar amine-catalyzed reaction discovered by Baylis and Hillman in 1972, is known as the Morita–Baylis–Hillman (MBH) reaction; it has become one of the most useful and popular methodologies in organic synthesis.</p><p>In recent years, recognition of the huge potential of and the determined scientific interest in Lewis base catalysis has led to nucleophilic phosphine catalysis receiving considerable attention.6 Because the catalytic behavior and unique properties of trivalent phosphines differ from those of amines, many novel annulations of electron-deficient alkynes, alkenes, and allenes have been discovered in laboratories worldwide, as described in several recent reviews.7–9 In general, the significant growth of nucleophilic phosphine catalysis can be attributed to several important features: (1) the reactions are highly atom-economical and usually do not produce any by-products; (2) the catalytic system is metal-free, allowing the reactions to performed readily on large scales—a feature that is especially attractive for pharmaceutical applications; and (3) the reaction topologies can be controlled through judicious choice of the phosphine catalyst (i.e., varying its substituents) as well as structural variations of the starting materials.</p><p>The main purpose of this Tutorial Review is to present key developments in nucleophilic phosphine catalysis between allenes and electrophiles for application in organic synthesis. Scheme 1 summarizes the diverse range of allenes and electrophiles that can be used in this catalytic reaction. Because of space limitations, this Tutorial Review emphasizes the different kinds of novel reaction types in nucleophilic phosphine catalysis of allenes with electrophiles, rather than providing a comprehensive list of examples. Nevertheless, for certain novel reactions, such as the [3+2] allene–olefin annulation, relatively detailed accounts are presented. Furthermore, some important modifications of the reactions are discussed and very recent progress is mentioned. Some important applications of these methodologies in the construction of combinatorial libraries and the total syntheses of natural products are also highlighted. The literature related to theoretical studies of nucleophilic phosphine catalysis is beyond the scope of this Tutorial Review.</p><!><p>In 1995, Lu discovered a novel phosphine-catalyzed [3+2] annulation of ethyl 2,3-butadienoate (1) with electron-deficient olefins 2 to form the cyclopentene derivatives 3 and 4 (Table 1).10 Although the regioselectivity governing the product distribution was not great, this transformation is the first example of phosphine-catalyzed annulation of an allene. Enlightened by Lu's pioneering work, the reaction has been investigated by over 20 different research groups, with applications in the syntheses of medicinally important agents and bioactive natural products, including the total syntheses of iridoid β-glucoside-(+)-geniposide and (–)-hinesol.11,12 In the mechanism proposed (Scheme 2), the catalytic cycle is initiated by nucleophilic addition of triphenylphosphine to ethyl 2,3-butadienoate (1), leading to the formation of the resonance-stabilized phosphonium dienolates 5↔6. The nucleophilic addition at the α-carbon atom in 5 to the electron-deficient olefin 2 forms the intermediate 7, which undergoes intramolecular cyclization, proton transfer, and phosphine elimination to yield the α-addition product 3. Alternatively, the γ-addition product 4 can be generated through the γ-addition pathway of 6 to 2. Ethyl 2,3-butadienoate readily serves as a three-carbon synthon in this transformation.</p><p>The first intramolecular allene–olefin [3+2] annulation was reported by Kwon in 2007 (Scheme 3).13 The reaction starting materials 14 were synthesized from salicylaldehydes through Wittig reactions to form 13, followed by esterification with 3-butynoic acid under the influence of Mukaiyama's reagent. The geometric constraint inherent in the substrates can control the reaction pathway so that only the α-addition product is obtained. In this reaction, 2-styrenyl allenoates featuring either electron-donating or -withdrawing substituents on the aromatic ring were readily converted into cyclopentene-fused dihydrocoumarins 15 in excellent to good yields with exclusive diastereoselectivity.</p><p>In 2009, Loh reported a highly regioselective synthesis of functionalized cyclopentenes 18 through phosphine-catalyzed [3+2] annulations between α-silyl-substituted allenones 16 and electron-deficient olefins 17 (Table 2).14 The steric bulk of the silyl substituent at the α-position leads to preferential addition at the γ-position, yielding the γ-addition product 18. This method works well with both phenyl and 2-furanyl allenones and a range of electron-deficient olefins, including chalcones, methyl acrylate, diethyl maleate, diethyl fumarate, and ethyl-4,4,4-trifluorocrotonoate. Notably, the trimethylsilyl group in the starting material is not retained in the final product.</p><p>Interestingly, a range of polyfunctionalized fused- and spiro-cyclopentenes can besynthesized through Lu's allene–olefin [3+2] annulation of some designed electron-deficient olefins. A very recent example was reported by the Marinetti group (Scheme 4).15 Several spiro(cyclopentene)oxindoles 21 with trisubstituted cyclopentene units were obtained by using arylideneoxindoles 19 as starting materials. In particular, this synthetic strategy is a straightforward means of synthesizing carbocyclic analogues (22) of an important series of anticancer agents inhibiting MDM2–p53 interactions.</p><!><p>Inspired by the robust Lu's [3+2] annulation for the synthesis of functionalized cyclopentenes, Kwon disclosed an unprecedented [4+2] annulation of α-substituted allenoates 23 and arylidenemalononitriles 24 (Table 3).16 In this case, the reaction regioselectivity is controlled by the electronic nature of the phosphine catalyst. When hexamethylphosphorous triamide (HMPT) was used as the catalyst, the reaction produced the cyclohexene 25. On the other hand, when a more electron-withdrawing triarylphosphine, such as tris(p-fluorophenyl)phosphine, was used as the catalyst, the reaction provided the alternative regioisomeric cyclohexene 26.</p><p>In the mechanism proposed (Scheme 5), the γ-addition reaction pathway begins with conjugate addition of the phosphonium dienolate intermediate 27 to the benzylidenemalononitrile 24a, producing the vinylphosphonium species 28, which undergoes two proton transfer steps to form the allylic phosphonium species 29. Intramolecular cyclization of the intermediate 29 followed by the release of the phosphine catalyst gives the final product 25a. Alternatively, the phosphonium dienolate 27 isomerizes into the vinylogous ylide intermediate 31, leading to the reaction producing the cyclohexene 26c through the β´-addition pathway. The α-substituted allenoate readily serves as a four-carbon synthon in this transformation.</p><p>Recently, Kumar expanded the allene–olefin [4+2] annulation to the stereoselective synthesis of common tricyclic benzopyrone compounds 36, which were then efficiently transformed into a diverse range of naturally occurring scaffolds and related compounds (Table 4).17 With n-Bu3P as the phosphine catalyst, the tricyclic benzopyrone derivatives can be prepared, in moderate to good yields and with good diastereoselectivities, from 3-formylchromones 35 and allenoates 23 through a cascade reaction sequence of [4+2] annulation followed by deformylation. Notably, the presence of the formyl group in the chromenone starting materials 35 activates the chromenone double bond and allows the reaction to take place smoothly.</p><!><p>In allene–alkene [3+2] annulations, allenoates react with a variety of electron-deficient olefinic electrophiles to form multiply substituted cyclopentenes. To expand the utility of the [3+2] annulation, Lu developed the phosphine-catalyzed allene–imine [3+2] annulation in 1997 (Table 5).18 They obtained excellent yields of 2-substituted pyrrolines 39 as single annulation products from reactions of methyl 2,3-butadienoate 37 with N-tosyl imines 38 when employing triphenylphosphine as the catalyst. Unlike the allene–alkene [3+2] annulation (Scheme 2), for most aryl imines this reaction proceeds mainly through the α-addition pathway to generate the α-adduct products 39. When 2-furylimine was used as the reaction partner, however, the γ-addition product, methyl 4,5-dihydro-5-furyl-1-tosyl-1H–pyrrole-2-carboxylate, was isolated in 15% yield as a minor product.</p><p>In 2005, Kwon described the highly diastereoselective syntheses of highly substituted pyrrolines 40 through use of Lu's allene–imine [3+2] annulation (Scheme 6).19 In this reaction, tributylphosphine was used as the nucleophilic catalyst to improve the reaction efficiency and diastereoselectivity. When γ-substituted allenoates 20a were used as the imine reaction partner, 2,5-cis-substituted pyrrolines 40 were produced exclusively in high yield. The reaction efficiency and selectivity can meet the high standards of diversity-oriented synthesis (DOS) for library construction. A DOS library containing a variety of fused heterocyclic compounds possessing distinctive frameworks was constructed through a sequence of phosphine-catalyzed imine annulation, Tebbe reaction, Diels–Alder reaction, and, in some cases, hydrolysis. From this library, several molecules were identified as antimigratory agents of human breast cancer cells.20</p><p>Since the first report of Lu's allene–imine [3+2] annulation, several research groups have applied the reaction in the syntheses of various aza-heterocycles possessing distinctive frameworks. In a very recent example, Wang reported the synthesis of benzo-fused cyclic sulfamidate heterocycles 43 through phosphine-catalyzed [3+2] annulation between the allenoate 42 and the cyclic aldimine/ketimines 41 (Scheme 7).21 This approach allows benzo-fused cyclic sulfamidate heterocycles 43 featuring a variety of substituents at various positions on the aromatic ring to be prepared readily with high isolated yields. Furthermore, these reactions can also be performed conveniently on the gram scale.</p><!><p>In the imine [3+2] annulation described above, unsubstituted or γ-substituted allenoates react readily with N-sulfonylimines in the presence of a phosphine to generate functionalized pyrrolines. With the vision of exploiting the potential of phosphine catalysis of allenes, in 2003 Kwon disclosed an unprecedented allene–imine [4+2] annulation to produce highly functionalized tetrahydropyridines 44 (Table 6).22 A variety of N-tosylimines 38 and α-substituted allenoates 23 are suitable for this reaction. When 2-benzyl-2,3-butadienoates 23 are used as starting materials, 2,6-diaryltetrahydropyridines 44 are obtained in excellent yields with good diastereoselectivities favoring the cis isomer. This robust allene–imine [4+2] annulation can be employed to generate tetrahydropyridines 44 on large scales.23 The application of this reaction to natural product syntheses, such as the formal syntheses of (±)-alstonerine and (±)-macroline (2005) and the total synthesis of (±)-hirsutine (2012), was reported by the same group (Scheme 8).24,25 Unlike the allene–alkene [4+2] annulation (Scheme 5), this reaction proceeds through the γ-addition pathway to generate γ-addition products 44 as single products. Surprisingly, no β´-addition products were isolated in this case.</p><p>Recently, Ye discovered the phosphine-catalyzed [4+2] annulation of α-substituted allenoate 23a and cyclic ketimines 45 (Table 7).26 This reaction can produce corresponding sultam-fused tetrahydropyridines 46 in good yields and with moderate to excellent regioselectivities. The use of triarylphosphines featuring electron-withdrawing groups, such as tris(4-fluorophenyl)phosphine and tris(4-chlorophenyl)phosphine, can increase the reaction efficiency. Interestingly, in contrast to the annulation with aldimines described above, the ketimine [4+2] annulation proceeds mainly through the β´-addition pathway to generate the β´-adducts 46a as major products.</p><p>One of the merits of the robust allene–imine [3+2]/[4+2] annulation is that the reaction is extremely compatible with reactions performed in the solid phase, thereby allowing efficient construction of aza-heterocyclic compound libraries for biological screening. In 2007, Kwon described the first solid phase phosphine catalysis of resin-bound allenoates with imines to generate dihydropyrrole and tetrahydropyrodine libraries (Scheme 9).27 The resin-bound allenoates 50 were prepared from SynPhase lanterns of Wang resin 48 and allenoic acid in the presence of Mukaiyama's reagent. A library of 4288 carboxylic acids 54 and 55 was obtained, with good to excellent yields and high diastereoselectivities, through phosphine-catalyzed [3+2]/[4+2] annulations of the resin-bound allenoates with the N-sulfonylimines and subsequent cleavage of the resins 52 and 53 using 2.5% trifluoroacetic acid in CH2Cl2. After biological screening of the 4288 analogues, two potent inhibitors of protein geranylgeranyltransferase type I with submicromolar IC50 values were identified. An octahydro-1,6-naphthyridin-4-one library was reported by the same group in 2011. The library was built through a sequence of phosphine- catalyzed imine [4+2] annulation, Tebbe reaction, Diels–Alder reaction, and hydrolysis, using the solid phase split-and-pool technique; this approach led to the identification of octahydro-1,6-naphthyridin-4-ones as activators of endothelium-driven immunity.28</p><!><p>Inspired by the robust allene–olefin/imine [3+2] and [4+2] annulations pioneered by Lu and Kwon, Ye reported the [3+2] and [4+2] annulations between allenoates and ketones in 2010 and 2011 (Tables 8 and 9).29,30 The use of trifluoromethyl ketones was key for the success of these transformations. Various dihydrofurans 58 were generated through phosphine-catalyzed [3+2] annulation of 2,3-butadienoates 56 and trifluoromethyl ketones 57 in good yields with excellent γ-regioselectivities (Table 8).29 Furthermore, hydrogenation of the dihydrofurans produced the corresponding 2,5,5-trisubstituted tetrahydrofurans in good yields and with exclusive cis-selectivities.</p><p>Moreover, when ethyl α-benzylallenoates 23 were used as the allene reaction partners, [4+2] annulation occurred through a γ-addition pathway, very similar to the catalytic cycle proposed by Kwon. This transformation provided a straightforward means for the highly diastereoselective synthesis of 6-trifluoromethyl-5,6-dihydropyrans 59, reduction of which with H2 gave the corresponding tetrahydropyrans in high yields and with exclusive diastereoselectivity (Table 9).30</p><!><p>In contrast to the successful transformations observed when using electron-deficient olefins, imines, and trifluoromethyl ketones as electrophiles, subjecting aldehydes to the reaction did not result in any corresponding [3+2] and [4+2] annulations, but rather in interesting alternative transformations. Indeed, the reaction topologies are controlled by the nature of the phosphine catalyst, the reaction conditions, as well as structural variations of the starting materials (Scheme 10).31–34 When a small tertiary phosphine (e.g., trimethylphosphine) was employed in the reaction, the dioxanes 65 were produced through the intermediate 60 having s-trans geometry, due to electrostatic association of the dienolate oxygen anion with the phosphonium cation. When a bulky tertiary phosphine or a hydrogen-bond donor was present, the pyrones (in presence of tricyclopentylphosphine) or dihydropyrones (in presence of MeOH) were generated through the s-cis-phosphonium dienolate intermediate 61. When γ-methyl allenoate was used as the reaction partner instead of an unsubstituted allenoate, the tetrahydrofurans 74 were obtained through the phosphorus ylide 70, which was generated from the phosphonium dienoate 62 by an overall 1,4-hydrogen shift.</p><p>In 2005, Kwon reported the first phosphine-catalyzed reaction of aldehydes 76 with allenoates 75 to generate 2,6-disubstituted-1,3-dioxan-4-ylidene-acetates 77 (Table 10).31 Pyridine aldehydes and benzaldehydes with electron-withdrawing groups both afforded the corresponding 1,3-dioxan-4-ylidenes 77 in excellent yields and with good stereoselectivities favoring the E isomers. Less-reactive benzaldehydes bearing electron-donating substituents, however, afforded their products in moderate yields. Furthermore, some ubiquitous δ-hydroxyl-β-ketoesters were synthesized from the 1,3-dioxan-4-ylidenes through acid-mediated hydrolysis of the acetal functionality.</p><p>On the other hand, when bulky tricyclopentylphosphine was used as the catalyst, the 2-pyrones 78 were isolated from the same starting materials (Table 11).32 Various aromatic aldehydes 76, including benzaldehyde, 2-naphthaldehyde, and 2-furaldehyde, gave the 6-aryl-2-pyrones 78 in good yields. Although the reaction yields were not satisfactory when using aliphatic aldehydes as reaction partners, the reaction afforded a valuable compound, 6-propyl-2-pyrone, which possesses a sweet, creamy, coumarin-like herbal flavor, in one step from a commercially available aldehyde.</p><p>In 2008, Kwon also described the alcohol-assisted phosphine-catalyzed reaction of aldehydes 76 and allenoates 37 to provide disubstituted dihydropyrones 79 in moderate to good yields (Table 12).33 They found that the addition of a base, such as n-BuLi, allowed generation of methoxide in situ and led to the promising formation of the dihydropyrones 79 in good yields, without any undesired products. Benzaldehydes possessing a variety of electron-withdrawing or -donating groups provided the desired dihydropyrones 79 in moderate to good yields.</p><p>Recently, He disclosed the phosphine-catalyzed [3+2] annulation of allenoates 80 with aldehydes 76 as a simple and efficient pathway for the synthesis of 2-arylidenetetrahydrofurans 81 (Table 13).34 The presence of the γ-methyl group on the allenoates 80 changed the regioselectivity of the addition of the aldehyde to the non-substituted allenoates and played a critical role in the occurrence of the [3+2] annulation with aldehydes. The reaction conditions (i.e., catalyst, solvent, and temperature) significantly influence the chemoselectivity and efficiency of the [3+2] annulations.</p><!><p>Since Lu's initial discovery of phosphine-catalyzed allene–alkene [3+2] annulation, many research groups have expanded the substrate scope of the electrophiles, increasing the molecular complexity and structural variety of the products. Currently, more than eight allenes (shown in Scheme 1) with different substituents are known to be suitable substrates for nucleophilic phosphine catalysis with various electrophiles containing carbon, oxygen, nitrogen, sulfur, phosphorus, and fluorine atoms (Scheme 1). Several unusual reaction types of allenes with electrophiles, such as [8+2], [4+3], [3+3], and [3+2+3] annulations, have also been discovered in this research area. Some of the most interesting examples are outlined below (for more details, see ref. 35 and references therein).</p><p>In 2000, Ishar reported phosphine-catalyzed [8+2] annulation of allenic esters/ketones 82 with tropone 83, leading to the 8-oxa-9-(ethoxycarbonyl/acylalkylidene)-bicylo[5.3.0]deca-1,3,5-trienes 85 (Table 14).36 Notably, the [8+2] cycloadducts 85 were obtained as the only products in excellent yields; the normal electron-deficient allene–olefin [3+2]/[4+2] annulation products were not observed. Mechanistically, γ-addition of the phosphonium dienolate at the C2 atom of tropone formed the intermediate 84; subsequent intramolecular cyclization and elimination of phosphine provided the desired product 85.</p><p>In the same year, Ishar also described the synthesis of novel N-aryl-2,3-dihydro-4-ethoxycarbonylchromano[2,3-b]azepine-6-ones 87 from 3-(N-arylimino-methyl)chromones 86 through phosphine-catalyzed [4+3] annulation followed by tandem rearrangement (Table 15).37 In the mechanism proposed (Scheme 11), α-addition of the phosphonium dienolate 5 to the chromon 86 forms the intermediate 88, which undergoes intramolecular cyclization and phosphine elimination to afford the [4+3] annulation product 90. Thermal opening of the chromone ring in compound 90 generates the intermediate 91; subsequent rotation around a C–C single bond, recyclization of the chromone ring, and a 1,5-H shift in 93 affords the final product 87.</p><p>In 2009, Kwon disclosed a novel [3+3] annulation of allenoates 95 with aziridines 94 to generate highly functionalized tetrahydropyridines 96 (Table 16).38 Aryl aziridines 94 featuring both electron-rich and -deficient substituents are suitable for this reaction, giving the desired products 96 in good to excellent yields. In the mechanism proposed (Scheme 12), β´-addition of the vinylogous ylide 98 to the phenyl aziridine 94 occurs to form the intermediate 99, which is converted to the phosphonium dienolate 100 through proton transfer. Intramolecular nucleophilic aromatic substitution and desulfonylation of 100 affords 101; subsequent intramolecular conjugate addition and phosphine elimination afford the final product 96. Although the reaction is catalytic, one equivalent of triphenylphosphine was used to expedite the reaction.</p><p>Recently, Guo and Kwon reported a phosphine-catalyzed [3+2+3] annulation of two molecules of an allenoate 1 and an azomethine imine 102, leading to the tetrahydropyrazolo-diazocinone products 103 and 104 (Table 17).35 Both electron-rich and -deficient aryl azomethine imines, as well as a polyaromatic azomethine imine, are compatible substrates. Mechanistically, the key event is the formation of the trimeric zwitterionic intermediate 106, which gives the intermediate 107 after addition to the azomethine imine 102 (Scheme 13). Intramolecular cyclization of 107 generates 108, which gives the final products 103 and 104 as a mixture of tautomers after proton transfer, phosphine elimination, and olefin isomerization.</p><!><p>Since Lu reported the first phosphine-catalyzed allene–alkene [3+2] annulation in 1995, the nucleophilic phosphine catalysis of allenes with electrophiles has become one of the most powerful and straightforward synthetic strategies for generation of the highly functionalized carbocyclic and heterocyclic structural motifs found widely in bioactive natural products and medicinally important substances. Despite the many very promising results that have been achieved in phosphine catalysis of allenes with electrophiles, enantioselective variants of these transformations has, however, remained relatively rare. A handful of chiral phosphine organocatalysts, which can be divided into two categories (chiral phosphines without additional functionalities and chiral phosphines with hydrogen bond donors), have been found to be effective for these reactions (Scheme 14). In this Section, we provide a brief overview of these enantioselective nucleophilic phosphine-catalyzed reactions of allenes with electrophiles and also point the reader to several comprehensive reviews for more details.9,39–41</p><!><p>In 1997, Zhang reported the first enantioselective phosphine-catalyzed [3+2] annulation of 2,3-butadienoates 56 with electron-deficient olefins 120, affording the cyclopentene products 121 and 122 with excellent regioselectivity and good enantioselectivity (Table 18).42 After initial screening of known and new chiral phosphines, they found that the newly designed bicyclic monodentate chiral phosphine 110 was most suitable for this reaction. Furthermore, using acrylates with bulky ester substituents (e.g., tert-butyl) improved the regio- and enantioselectivity.</p><p>Despite the great synthetic potential of the results described above, no further progress was made in enantioselective nucleophilic phosphine catalysis of allenes with electrophiles until 2005, when Fu demonstrated the asymmetric allene–imine [4+2] annulation to give the piperidine derivatives 123 when employing Gladiali's phosphine 111 as the catalyst (Table 19).43 Under the optimized conditions, they obtained a range of useful functionalized tetrahydropyridines 123 in high yields and enantioselectivities. This asymmetric [4+2] reaction is a novel and efficient means of access to a common framework found in several important natural products, including 6-oxoalstophyllal and 6-oxoalstophylline.</p><p>In 2008, Marinetti reported the enantioselective allene–alkene [3+2] annulation by using the phosphine 115, exhibiting planar chirality, as the catalyst (Table 20).44 When using the chalcones 124 as reaction partners, the γ-addition products 125 were afforded in moderate to good yields, with excellent enantioselectivities favoring the trans isomers. Very recently, the same group employed this chiral phosphine as the catalyst for the enantioselective syntheses of spirocyclic compounds.45</p><p>In 2012, Kwon demonstrated the first enantioselective total synthesis of the monoterpene indole alkaloid (+)-ibophyllidine 132, featuring an asymmetric phosphine-catalyzed allene–imine [3+2] annulation as the key reaction step (Scheme 15).46 Using their P-chiral [2.2.1]bicyclic phosphine 112 as the catalyst, they obtained the syn-pyrrolidine 129 as a synthetic intermediate from 4-ethyl-2,3-butadienoate and N-tosylbenzaldimine in 93% yield and with 99% ee. Hydrogenation of 129 afforded the stereochemically dense pyrrolidine ring compound 130 in excellent yield with exceptionally high degrees of both diastereo- and enantioselectivity. A subsequent 12-step sequence of chemical manipulations provided the target natural product (+)-ibophyllidine 132.</p><!><p>In contrast to chiral phosphines lacking additional functionality, which induce asymmetry through steric interactions, chiral phosphines with hydrogen-bonding donors instigate high enantioselectivity through hydrogen bonding. The first example of asymmetric allene–olefin [3+2] annulation employing the multifunctional chiral phosphine 116 as the catalyst was reported by Miller in 2007 (Table 21).47 When using benzyl 2,3-budienoate 42 as the reaction partner, they obtained various spirocyclic compounds 135 and 136 from corresponding electron-deficient olefins in good yields with good to moderate enantioselectivities. The presence of a heteroatom-substituted ring system in the starting material resulted in significantly lower yields and enantioselectivities.</p><p>Encouraged by Miller's pioneering work, Zhao and Lu independently developed their amino acid–derived bifunctional chiral phosphines in 2010 and 2011, respectively.48,49 Zhao reported the highly enantioselective [4+2] annulation of the allenoate 95 with the alkylidene cyanoacetate 137 catalyzed by his N-acyl aminophosphine 118 (Table 22);48 a range of highly functionalized cyclohexene derivatives 138, bearing three contiguous chiral centers, were synthesized with good to excellent diastereoselectivities and enantioselectivities. On the other hand, Lu described versatile enantioselective [3+2] annulations of imines and allenoates catalyzed by his dipeptide-based chiral phosphine 119 (Table 23).49 Notably, this reaction is the first example of aliphatic imines 139 being applied successfully in phosphine-catalyzed [3+2] annulation. Moreover, this transformation was applied as a key step in the concise formal synthesis of (+)-trachelanthamidine.</p><p>Another significant example of asymmetric allene–imine [3+2] annulation catalyzed by a chiral phosphine featuring a hydrogen-bonding donor was discovered by Jacobsen et al. in 2008 (Table 24).50 They developed a new family of chiral phosphinothiourea derivatives 117 for highly enantioselective syntheses of disubstituted dihydropyrroles 143. Notably, the use of diphenylphosphinoyl (DPP) imines 142 and the addition of 0.2 equiv of H2O and 0.05 equiv of Et3N improved the reaction efficiency.</p><!><p>The use of nucleophilic phosphines as Lewis base catalysts for organic reactions has grown over the last decade and is now an active area of organocatalysis. Ten modes of nucleophilic phosphine catalysis with allenes and electrophiles have been demonstrated in this Tutorial Review; these transformations take advantage of the unique and highly tunable properties of trivalent phosphine. A variety of unique carbo/heterocyclic frameworks, some of which are present in a wide range of bioactive natural products and medicinally important substances, can be obtained through these transformations. Some examples of asymmetric nucleophilic phosphine catalysis with high enantioselectivities have also been developed, with promising applications in the total synthesis of natural products. Future advances in phosphine catalysis are likely to occur along a number of lines, including the development of novel reaction modes and the synthesis of novel chiral phosphines that perform their catalytic functions with high efficiency. In addition, much work remains to develop asymmetric variants of several recently discovered transformations.</p>

PubMed Author Manuscript

Biochemistry, molecular biology, and pharmacology of fatty acid synthase, an emerging therapeutic target and diagnosis/prognosis marker

Human fatty acid synthase (FASN) is a 270-kDa cytosolic dimeric enzyme that is responsible for palmitate synthesis. FASN is slowly emerging and rediscovered as a marker for diagnosis and prognosis of human cancers. Recent studies showed that FASN is an oncogene and inhibition of FASN effectively and selectively kill cancer cells. With recent publications of the FASN crystal structure and the new development of FASN inhibitors, targeting FASN opens a new window of opportunity for metabolically combating cancers. In this article, we will review critically the recent progresses in understanding the structure, function, and the role of FASN in cancers and pharmacologically targeting FASN for human cancer treatment.

biochemistry,_molecular_biology,_and_pharmacology_of_fatty_acid_synthase,_an_emerging_therapeutic_ta

Introduction<!>Structure and function of mammalian FASN<!>Regulation of FASN expression<!>Role of FASN in tumorigenesis and cancer cell proliferation<!>Role of FASN in prognosis and drug resistance<!>Mechanism of FASN action in cancers<!>FASN inhibitors<!>Cerulenin<!>C75<!>Olistat<!>Polyphenols/flavonoids<!>Triclosan<!>Other inhibitors<!>Conclusion and future perspectives<!>

<p>Altered metabolism in human cancers has long been recognized. The first observation of increased anaerobic glycolysis in cancer cells was made by Otto Warburg, the so called "Warburg effect" [1]. The "Warburg effect" has now become a hallmark of the transformed phenotype of cancer cells, and is thought to provide growth advantages to these cells [2, 3]. One of the metabolic changes in cancer is the altered lipogenic pathway with increased de novo fatty acid synthesis [4].</p><p>Fatty acids serve as important substrates of metabolism for energy, essential building blocks of cellular membranes, intracellular second messengers, and anchorage for membrane proteins. Fatty acids exist either as components of triacylglycerol, phospholipids and cholesterol or in free forms. Free fatty acids include dietary ones and the ones derived from de novo synthesis catalyzed by fatty acid synthase (FASN) in lipogenic tissues such as liver, adipose tissue, lactating breast and cycling endometrium.</p><p>However, the altered lipogenic pathway in cancers did not become a focus of interest until 1994, when Kuhjada and colleagues identified the oncogenic antigen-519 (OA-519), a molecule found in tumor cells from breast cancer patients with markedly worsened prognosis, as fatty acid synthase (FASN) [5]. Human FASN is a 270-kDa cytosolic enzyme [6, 7]. It is also referred as the cytosolic type I FASN complex while type II fatty acid synthesis system exists in mammalian mitochondria, which resembles the prokaryotic type II FASN. It is believed that the type II system produces fatty acids that play important roles in the mitochondrial function [8]. The type I FASN has recently been shown to have oncogenic activity [9, 10] and its inhibition has been shown to effectively and selectively kill cancer cells, with minimal side effects to normal cells [11–17]. Thus, targeting type I FASN opens a new window of opportunity for metabolically combating cancers. In this review, we will focus on the cytosolic type I FASN protein and perform a critical review on the recent progresses in understanding the structure, function, and the role of FASN in cancers and pharmacological targeting FASN for human cancer treatment.</p><!><p>The de novo synthesis of fatty acids from glucose consists of the following key elements: 1) citrate lyase, which converts citrate to acetyl-CoA; 2) acetyl-CoA carboxylase, which carboxylates acetyl-CoA to malonyl-CoA and is the rate limiting enzyme for fatty acid synthesis; 3) nicotinamide adenine dinucleotide phosphate (NADPH) as a reducing equivalent and ATP as the energy source; and 4) FASN, the enzyme that condenses acetyl-CoA and malonyl-CoA to 16-carbon palmitate (Figure 1).</p><p>Mammalian FASN is a multifunctional polypeptide containing seven catalytic domains: β-ketoacyl synthase (KS), malonyl/acetyltransferase (MAT), dehydrogenase (DH), enoyl reductase (ER), β-ketoacyl reductase (KR), acyl carrier protein (ACP) and thioesterase (TE) [18] (see Figure 2A). In the conventional model of mammalian FASN, it was thought that FASN forms a fully extended head-to-tail homodimer (Figure 2A). However, results from mutant complementation [19, 20], chemical crosslinking [21] and subunit interaction [22] studies were incompatible with this model. Therefore, a revised model was proposed, in which FASN forms an intertwined, X-shaped, head-to-head homodimer [23] (Figure 2B).</p><p>In the new model, each subunit in the dimeric FASN adopts a coiled conformation that allows multiple intra- and inter-subunit interactions between the functional domains, with the KS domain located in the central portion of the structure. This model was further supported by the results from cryo-electron microscopy and crystal structure studies [23–26]. The 3.2 Å crystal structure of FASN containing the MAT, KS, DH, ER and KR domains demonstrates that FASN assembles as an intertwined "X"-shaped dimer (Figure 3). The whole structure can be divided into two portions: the condensing portion including KS and MAT domains and the β-carbon modifying portion including DH, ER, and KR domains. In addition, two nonenzymatic domains, "pseudo-methyltransferase" (ΦME) and "pseudo-ketoreductase" (ΦKR) are located at the periphery of the modifying portion. The two subunits associate with each other mainly through hydrophobic interactions between the KD, ER and DH domains of the two subunits and have a buried surface area of 5400 Å2.</p><p>The FASN-catalyzed synthesis of fatty acids involves three major steps: (1) initiation with the condensation of malonyl-CoA and acetyl-CoA catalyzed by MAT; (2) elongation, a repeating cycle of reduction and dehydration to add 2 carbons in each cycle to the elongating fatty acid chain catalyzed by KS, DH, ER, and KR; and (3) termination to release palmitate from ACP catalyzed by TE (Figure 4). Synthesis of one palmitate consumes 1 acetyl-CoA, 7 malonyl-CoA, 7 ATP, and 14 NADPH molecules.</p><!><p>In normal adults, FASN is primarily expressed in hormone-sensitive cells and cells with high lipid metabolisms [27]. FASN expression in normal liver and adipose tissues is controlled mainly by nutritional signals. In a well-nourished individual, normal cells preferentially use circulating free fatty acids from diet. Thus, the de novo fatty acid synthesis is rarely needed and the FASN protein level is low. Carbohydrate ingestion, thyroid hormone, insulin, and glucocorticoid coordinately up-regulate while unsaturated fatty acids, cyclic-AMP, and glucagon down-regulate FASN expression [28]. In cycling endometrium, FASN expression is high in the proliferative phase and decreases in the secretory differentiation phase. Proliferative gland and stroma cells have high levels of FASN, as well as high levels of estrogen and progesterone receptors and Ki-67, indicating that FASN expression may be under the control by hormone and associate with proliferation [29]. In lactating breast tissues, FASN expression is up-regulated to produce milk fat [30].</p><p>In cancer cells and pre-neoplastic lesions, the expression of FASN has been found to be up-regulated [29, 31–45]. Because of FASN up-regulation, over 90% of the triacylglycerol in cancer cells are synthesized de novo despite the presence of high levels of circulating free fatty acids. Cancer cells are so dependent on de novo fatty acid synthesis that inhibition of lipogenesis targeting FASN induces apoptosis selectively in human cancer cells both in vitro and in vivo [46–49], with minimal effect on normal cells [17, 50, 51].</p><p>FASN expression in cancer cells is no longer responsive to the nutritional signals and its expression is regulated at multiple steps including gene amplification, transcription, translation and post-translational modifications. The increased FASN gene copy number has been found in prostate cancer cell line PC-3 and LNCaP, as well as in prostate adenocarcinoma and metastatic cancers [52]. The increased FASN staining in tumor tissues correlates with a 25% increase in gene copy number, whereas in benign tissues, only 1% of the cells with high FASN staining showed increased gene copy number. Thus, gene amplification in cancer cells may partly contribute to the increased FASN expression in prostate cancers.</p><p>Transcriptional regulation of FASN expression has been well-studied and is considered the major contributor to the increased FASN expression in cancer cells. Growth factors, hormones and their receptors have been shown to be the main factors that cause up-regulation of FASN transcription in cancer cells. Epidermal growth factor (EGF) can stimulate FASN expression through EGF receptor ERBB1 and ERBB2 [53, 54]. In breast and prostate cancer cells that have functional hormone receptors, FASN expression has been shown to be up-regulated at transcriptional level upon hormone treatment [55–57].</p><p>The effect of growth factors or hormones and their receptors on FASN expression involves complicated downstream signaling and crosstalk between multiple signal transduction pathways. The two well-studied major pathways that are possibly involved in regulating FASN expression are the mitogen-activated protein kinase (MAPK) and PI3K/AKT pathways. In H-ras transformed and immortalized human mammary epithelial cell line MCF10A1, FASN expression was significantly elevated upon EGF treatment [58]. Treatment of this cell line with MEK-1 inhibitor, U0126, blocked ERK activation and subsequently decreased FASN expression, while transient transfection of MCF10A1 cells with constitutively activated MEK-1 increased FASN expression. Similarly, MAPK inhibitors also decreased FASN promoter activity and FASN protein level in MCF7 and HCT116 cancer cells [58]. In another study, EGF was found to up-regulate the promoter activity of FASN and its expression while MAPK inhibitor abolished the EGF-stimulated FASN expression [59]. These observations suggest that MAPK pathway plays an important role in regulating and mediating EGF-stimulated FASN expression.</p><p>Multiple studies have demonstrated the relationship between PI3K/Akt activity and FASN expression. In the first study by Van de Sande et al. [60], it was found that the PI3K/Akt pathway was involved in FASN expression in the PTEN-null prostate cancer cell line LNCaP. Treatment with PI3K-specific inhibitor, LY294002 and transfection with PTEN both significantly decreased FASN expression level as well as FASN transcriptional activity. Co-transfection of constitutively active Akt with PTEN reversed the inhibitory effect of PTEN on FASN expression and its promoter activity. In human prostate tumors, an inverse correlation between FASN and PTEN expression has also been observed [61]. In several later studies of different cell lines, it was confirmed that PI3K inhibitors could reduce FASN expression in various cancer cell lines [58, 61–64]. PI3K/Akt pathway has also been suggested to mediate the induction of FASN expression by heregulin [63] and diogenin [64]. Hypoxia, which causes the generation of reactive oxygen species, can also up-regulate FASN expression thorough activation of Akt. Addition of H2O2 in several breast cancer cell lines increased FASN expression, which is in good agreement with the amount of ROS generated in these cell lines under hypoxic condition [65].</p><p>The relationship between PI3K/Akt pathway and FASN expression has also been observed in clinical studies of human cancer tissues. Following the initial observation that PI3K/Akt may regulate FASN expression in LNCaP cells, van de Sande et al. investigated this relationship in prostate cancer tissues and found that the increased FASN expression correlates with activation and nuclear localization of Akt [66]. In another study of more than 400 papillary thyroid carcinoma tissues, a significant correlation was also observed between FASN expression and PI3K/Akt activation using immunohistochemistry [67]. Yet in a third study of more than 400 colorectal cancer tissues on a tissue array, a significant correlation between FASN expression and PI3K/Akt activation was also found [68]. Together, these observations suggest that PI3K/Akt pathway may play important roles in regulating FASN expression, not only in cultured cells but also in human cancer tissues. However, it is noteworthy that the findings of these correlation studies are also consistent with the possibility that FASN over-expression up-regulates PI3K/Akt activation (see discussion below).</p><p>The major transcription factor that is involved in regulating FASN transcription is sterol regulatory element binding protein 1 (SREBP-1). SREBP-1 is one of the two SREBP membrane bound transcription factors of the basic-helix-loop-helix-leucine zipper family that regulate fatty acid and cholesterol synthesis [69]. The membrane-bound SREBPs are activated and released from membranes by protease cleavage in response to fatty acid and cholesterol depletion. The active SREBPs then translocate into nucleus and activate gene transcription. It has been suggested that SREBP-1 is important in regulating fatty acid synthesis while SREBP-2 is for cholesterol synthesis [70, 71].</p><p>In the androgen responsive prostate cancer cell line LNCaP, it was reported that androgen increased mRNA and protein levels of SREBP precursors and the mature active SREBP as well as elevated FASN transcript and protein levels [72]. The increased FASN transcription appeared to depend on the presence of SREBP biding site in the FASN promoter sequence. Deletion of this site abrogated the transcriptional activation of FASN by androgen. It has also been shown that androgen not only increased expression and activation of SREBPs, but also the expression of SREBP-activating protein (SCAP), that helps transport SREBP from their synthesis site to the proteolytic activation site and, therefore, enhances the maturation of SREBP [73].</p><p>SREBP also appears to mediate the regulation of FASN expression by growth factors such as EGF [59]. Using LNCaP prostate cancer cell lines, it was found that EGF stimulated FASN expression and its promoter activity can be stimulated by EGF via its SREBP-binding site. Introduction of a dominant negative SREBP eliminated EGF-stimulated FASN expression. In another study, FASN, SREBP-1 and Ki-76 were found to co-localize in primary human colorectal carcinoma specimens [74]. Similarly, in human mammary epithelial cell line MCF-10A1 and cancer cell line MCF-7 as well as a panel of primary human breast cancer tissues, it was found that the coordinated elevation of FASN and SREBP-1 was under the control of EGF and its downstream PI3K/Akt and MAPK pathway [75].</p><p>A transcriptome analysis of Her2 (ERBB2) in breast cancer cells has revealed a molecular connection between FASN and Her2 through PI3K-Akt-dependent signaling [53]. In this study, the authors used DNA microarray to compare and identify genes induced by Her2 in mammary epithelial cell line with ectopic Her2 over-expression and breast cancer cell lines derived from patients with different level of Her2 expression. They found that Her2 over-expression activated FASN promoter and transcription as well as increased protein production and activity, while inhibitors of Her2, Herceptin and CI-1003, attenuated the effect of Her2 on FASN expression. PI3K activity was thought to be the mediator of the Her2 control on FASN expression because LY294002, a known PI3K inhibitor, abrogated Her2-induced FASN protein production in the Her2-over-expressing normal mammary epithelial and breast cancer cells. Thus, the transcription of FASN gene may be induced by Her2 via the PI3K pathway and possibly by the transcription factor, SREBP, as a downstream effector of Her2-PI3K pathway [53].</p><p>However, a later study by Yoon et al. showed that Her2 regulation of FASN expression might be at the step of translational control [76]. In this study, breast cancer cell lines SK-BR-3 and BT-474 with high expression of Her2 were compared with MCF7 and MDA-MB-231 that have low levels of Her2 expression and a correlation between the levels of FASN and Her2 was found. However, the total and the activated nuclear level of SREBP1 and SREBP2 did not correlate with FASN expression. Furthermore, ectopically over-expressing Her2 in MDA-MB-231 breast cancer cells induced an increase in the level of FASN protein but not the level of FASN mRNA. These findings indicate that Her2-induced FASN protein production in MDA-MB-231 cells is not at the transcriptional step via SREBP. Nevertheless, the PI3K inhibitor LY294002, blocked Her2-induced FASN expression, suggesting that the PI3K/Akt pathway is indeed involved in mediating Her2-induced FASN expression. It was further shown that the PI3K downstream target mTOR mediates the regulation of FASN expression by increasing the overall translation rates of FASN mRNA via activating eIF4E and S6 ribosomal protein and that both the 5′- and 3′- UTRs of FASN are involved in its translational regulation.</p><p>Both above studies clearly showed that Her2 induces FASN expression via the PI3K/Akt pathway. However, the difference resides in the step, transcription or translation, at which FASN expression is up-regulated by Her2. This discrepancy between these two studies may be due to the different cell lines used and suggests that both transcriptional and translational regulations may be involved in FASN expression. These findings clearly indicate that the regulation of FASN expression is complicated.</p><p>Regulation of FASN expression at its post-translational stability/degradation step has also been suggested. In prostate cancer cells, FASN protein stability has been shown to be regulated by an ubiquitin-specific protease, USP2a [77]. Knockdown of USP2a reduced FASN expression. Microarray analysis from human prostate cancers has revealed a significant association between the genes in fatty acid metabolism and high USP2a expression [78].</p><p>In drug-selected breast cancer cell lines, it was found that FASN expression was further up-regulated compared to its parental cancer cell line [17]. The mechanism for this further up-regulation of FASN remains unknown. However, it has been observed that treatment with topoisomerase inhibitors doxorubicin (Adriamycin) and etopside increased FASN promoter activity in SK-Br3 breast cancer cells [79]. This drug-induced transcriptional activation of FASN did not appear to be via SREBP-binding site in the FASN promoter sequence. In our recent studies, both mRNA and protein levels of FASN increased in the series of stepwise drug-selected MCF7/AdVp cell lines compared with drug sensitive MCF7 parental cells (Figure 5). However, there is an obvious discordance in the mRNA and protein expression level of FASN in these drug-selected cells lines. The mRNA level increased to the maximum level in the low resistant cell line MCF7/AdVp100 while FASN protein level increased to the maximum level only in the most resistant MCF7/AdVp3000 cells although both mRNA and protein levels dropped in the partially revertant MCF7/AdVpRev cells that have lost most of its drug resistance following extended growth of MCF7/AdVp3000 cells in the absence of selection pressure. Based on theses observations, it is reasonable to speculate that in drug resistant cell lines, FASN expression is controlled at multiple levels including transcriptional and post-transcriptional regulation.</p><!><p>Increased FASN expression level has been found in various human cancers of breast [31], colon [32], prostate [33], lung [34], bladder [35], ovary [36], stomach [37], endometrium [29], kidney [38], skin [39], pancreas [40], head and neck [41], tongue [42–44], and soft tissues [45]. In addition, increased FASN expression has been observed in ductal carcinoma in-situ (DCIS) [80] and lobular carcinoma in situ (LCIS) [81] of breast. Thus, FASN has been considered as a metabolic oncogene.</p><p>The first evidence that shows the oncogenic function of FASN was from in-vitro studies where transient over-expression of ectopic FASN increased the proliferation, survival, and anchorage-independent growth of an immortalized breast epithelial cell line HBL100 [10]. Immortalized human prostate epithelia cell lines (iPrECs) with ectopic FASN over-expression had an increased rate of proliferation and anchorage-independent growth in soft agar in vitro, similar as the breast epithelial cell line HBL100 [10]. Histological examination of the prostate section of FASN transgenic animals showed prostate lumens full of proliferating cells, indicating the prostate hyperplasia. Several older male mice showed enlarged prostate which blocks the bladder outflow. However, there were no invasive prostate carcinomas observed in these mice. The above findings suggest that FASN over-expression alone may not be sufficient to generate prostate tumors in vivo. Indeed, over-expression of androgen receptor together with FASN transformed iPrECs to form invasive tumors in immune deficient mice [9], suggesting that the oncogenic function of FASN in prostate epithelial cells may require the coordination of androgen receptors. It is also possible that the oncogenic function of FASN in mammary epithelial cells require estrogen receptor. Clearly, this possibility and the mechanism of coordination of FASN with hormones in tumorigenesis require further investigation.</p><p>In both the above studies, it was clearly demonstrated that ectopic over-expression of FASN caused significant increase in proliferation of the non-tumorigenic mammary and prostate epithelial cells. Inhibition of FASN by siRNA or chemical inhibitors also caused significant growth arrest of cancer cells [82–85]. It is, however, noteworthy that it has also been observed that altering the FASN level either by siRNA or ectopic over-expression did not affect the growth rate of MCF7 and MCF7-derivied drug resistant breast cancer cells [17]. Although the reason for the difference between these studies is not known, it is possible that the extent of FASN inhibition may be the culprit. Nevertheless, more studies are clearly needed to demonstrate the role of FASN in promoting cell proliferation.</p><p>The possible role of FASN in promoting cell proliferation may be via affecting cell cycle progression. It was observed that inhibiting FASN activity by C75 produced rapid and potent blockage of DNA replication and inhibits S phase progression [86]. In another study, it was found that inhibiting FASN expression or activity resulted in arrest in G1/S phase transition [83]. This arrest of G1/S phase transition was thought to be due to the effect of FASN on Rb pathway. Inhibiting FASN activity reduced phosphorylation of the Rb protein, a parameter that governs the interaction of this protein with E2F-1 and subsequent entry into S phase; up-regulated p27Kip1, which negatively regulates cyclin-dependent kinase activity; and down-regulated Skp2, a protein component of the E3 ubiquitin ligase that regulates degradation of p27Kip1 [83]. This observation was later confirmed by a genome-wide analysis of FASN knockdown using siRNA [87]. In the genome-wide analysis, several other genes such as p21 that regulate cell cycle progression were also found to be up-regulated by FASN knockdown. This observation is consistent with an earlier study that a biphasic stress response was found with a transient accumulation in S and G2 at 4 and 8 hrs and a marked reduction in cyclin A- and B1-associated kinase activities, and then growth arrest in G1 and G2 with accumulation of p53 and p21 proteins at 16 and 24 hrs following FANS inhibition [84]. However, it was found later that the cell cycle arrest induced by FASN inhibition was independent of p53 in hepatoma cell lines, but may involve the p38 MAPK pathway [82]. Thus, the role of p53 in mediating FASN-inhibition-induced cell cycle arrest is debatable and certainly needs further investigation.</p><p>Currently, it is not clear how FASN inhibition induces cell cycle arrest at G1/S checkpoint. However, it is possible that FASN inhibition significantly reduces the synthesis of phospholipids [88, 89], which are major components of cellular membranes, and phospholipids biosynthesis is highest in S phase in preparation for cell division [90]. Thus, shortage in phospholipids due to reduced FASN expression may cause arrest at G1/S checkpoint or inhibit S phase progression. Nevertheless, supplementation of palmitate, the end product of FASN, to culture did not appear to affect cell cycle distribution [91]. Ectopic over-expression of human FASN in MCF7 cells also did not appear to affect cell cycle distribution (Figure 6). Hence, whether FASN really plays any role in cell cycle regulation requires further detailed investigation.</p><!><p>As discussed above, FASN was initially identified as an independent prognostic molecule in breast cancer cells from patients with markedly worsened prognosis [5, 92]. Breast cancers with high level of FASN staining were 4 times more likely to recur and metastasize than the ones with no staining [92]. Further studies of breast cancer samples indicated that patients with high FASN expression showed significantly shorter disease free survival and overall survival, even in patients with very early stage of breast cancer [31, 93]. It is now clear that increased FASN expression associates with cancer progression, higher risk of recurrence and shorter survival in many other types of cancers including prostate cancer [94], ovarian neoplasms [36], squamous cell carcinoma of lung [34], melanoma [39], nephroblastoma [38], renal cell carcinoma [95], soft tissue sarcoma [45], endometrium carcinoma [96], head and neck squamous cell carcinoma [41], pancreatic carcinoma [40], squamous cell carcinoma of the tongue [44], and colorectal carcinoma [97].</p><p>In-vitro studies with cancer cell lines also showed that FASN over-expression may cause resistance of cancer cells to treatments and, thus, contribute to clinical poor prognosis. In a recent study, FASN was found to be over-expressed in Adriamycin-selected breast cancer cell line with multidrug resistance phenotype and its expression increases with the level of resistance [17]. FASN over-expression in the drug selected breast cancer cell line has been demonstrated to contribute to the multidrug resistance phenotype of this cell line possibly by over-producing palmitate. The observed gradual increase in FASN expression in the series of stepwise-selected drug resistant breast cancer cell lines suggests that tumor cells with elevated FASN expression in a clinical setting may be selected following anticancer drug treatment which in turn causes relapse of the disease and eventual failure of treatments.</p><p>In an earlier study, Menendez et al reported that inhibiting FASN activity synergistically enhanced the cytotoxicity of docetaxel, in the Her2-over-expressing breast cancer cell lines [98]. Inhibiting FASN expression or activity also sensitized cancer cells to vinorelbine [48], paclitaxel [99], 5-fluorouracil [100], Herceptin [101, 102], and TRAIL [103]. Because the Her2-over-expressing cancer cell lines were used in most of these studies, it was thought that Her2 may play an important role in the drug resistance observed. Indeed, inhibiting FASN expression and activity reduced Her2 expression [98]. Thus, it is possible that inhibiting FASN down-regulates Her2 which in turn causes sensitization of the cancer cells to the anticancer drugs tested in these studies. On the other hand, it was thought that the DNA damage-inducible transcript 4 (DDIT4), a stress-response gene that negatively regulates the mTOR pathway, may mediate the role of FASN in TRAIL-induced apoptosis [101]. It is also noteworthy that in the study of MCF7-derived cells by Liu et al. [17] it was found that FASN over-expression caused resistance only to DNA-damaging anticancer drugs but not to paclitaxel and vinca alkaloid vinblastine. Further studies are needed to resolve the differences between these studies.</p><p>Both in-vitro studies and clinical data indicated that elevated FASN expression confers cancer cell resistance to anti-cancer therapies, which may be the reason of shorter survival of patients with high FASN expression. Although the detailed mechanism of drug resistance induced by FASN over-expression is currently unknown, the findings from the past studies suggest that FASN may regulate survival, apoptosis, and DNA repair pathways (see discussion below).</p><!><p>As discussed above, several signal transduction pathways may mediate the function of FASN in tumorigenesis and resistance to drug treatments. Although the detailed mechanism of FASN action in signal transduction pathways remains to be determined, various hypotheses have been proposed.</p><p>Fatty acids synthesized by FASN in cancer cells are not only used for cellular membrane construction, but also involved in the production of lipid signaling molecules, anchorage of membrane proteins, and modulate cellular responses to anticancer drugs. It is possible that the increased de novo synthesis of palmitate by FASN over-expression plays an important role in mediating FASN effect on Her1/Her2 activation. Recently, it was shown that palmitoylation of Wnt-1 by enforced expression of ectopic FASN in immortalized human prostate epithelia cells (iPrECs) stabilized and activated β-catenin and resulted in increased oncogenicity of the iPrECs cells [104]. It has also been found that supplementation of palmitate to primary mouse embryonic fibroblast (MEF) and primary osteoblasts compromised the normal response of these cells to DNA damages, favoring the mutated cells to survive and leading to tumorigenesis [91]. Supplementation of palmitate to cancer cells also increased the ability of these cells to resist DNA damaging anticancer drugs Adriamycin and mitoxantrone [17].</p><p>Palmitoylation helps to locate the palmitoylated proteins to specific regions of plasma membranes, a detergent-resistant membrane micro domain (lipid raft) for their proper functions [105]. Many proteins involved in signal transduction, apoptosis, membrane transport, and cell adhesion are associated with lipid raft [106–108]. Her2 is one example of the signaling proteins that co-localize with lipid rafts [101]. It has been shown that FASN mainly affects the synthesis of phospholipids that incorporate into lipid raft, but has a less effect on the synthesis of non-raft associated lipids [88]. Elevated FASN expression may also contribute to the increased ratio of saturated to unsaturated fatty acids and, thus, affect the structure and function of membrane lipids [109]. Changes in lipid rafts and membrane structures due to FASN over-expression likely affect the signaling proteins residing in the raft to enhance cancer cell survival and progression.</p><p>Recently, it was found that knocking down FASN expression using siRNA induced apoptosis by activating caspase-8 in tumor cells and inhibition of FASN sensitized cancer cells to TRAIL treatment [103]. It was also found that over-expressing ectopic FASN blocked caspase-8 activation-induced by Adriamycin (unpublished observation). These findings suggest that FASN may function by regulating the apoptosis pathway upstream of caspase-8 activation. One important mediator may be ceramide lipid molecules. Inhibition of FASN in several breast cancer cell lines by siRNA treatment induced cancer cell apoptosis by up-regulating ceramide synthesis. The increased ceramide level is thought to be the result of malonyl-CoA accumulation due to FASN inhibition, which in turn inhibits carnitine palmitoyltransferase (CPT-1) [110]. It was also found that several proapoptotic genes including BNIP3, TRAIL and DAPK2 were induced following FASN inhibition and these genes may play a role in mediating FASN inhibition-induced apoptosis [110]. We recently found that FASN over-expression in MCF-7 breast cancer cells decreased ceramide generation-induced by Adriamycin and, thus, inhibited the drug-induced apoptosis (unpublished observation). However, a recent study showed that FASN over-expression in prostate epithelial cells protects these cells from camptothecin induced apoptosis by inhibiting caspase-9 activation, but did not protect cells from anti-Fas ligand-induced apoptosis which activates caspase-8 [9]. The reason for the difference between this and the other studies on the role of FASN in caspase activation is currently unknown. However, the normal prostate epithelial cells may differ from breast cancer cells in the mechanism of FASN regulation of apoptosis.</p><p>PI3K/Akt survival pathway is known to be important for cancer cell survival and resistance to chemo-and radiation therapy [111–113]. As discussed above, activation of the PI3K/Akt pathway can increase FASN expression in human cancers for cell survival both in vivo and in vitro. However, PI3K/Akt pathway may also play an important role in mediating FASN function in a feed forward loop. It has been found that inhibition of FASN activity caused a decrease in the level of phosphorylated-Akt, which preceded the induction of apoptosis both in vitro and in vivo [14, 15, 62, 99]. It has also been observed that inhibition of the PI3K/Akt pathway by LY294002 sensitized human ovarian and breast cancer cells to FASN inhibitor-induced apoptosis [62, 114], indicating that Akt could serve as a downstream mediator of FASN in cell survival and protects cancer cells against FASN inhibitor and other drug-induced apoptosis.</p><p>FASN has also been suggested to play an important role in regulating gene expression. A genomic profiling analysis of a breast cancer cell line MDA-MB-435 following FASN knockdown using siRNA showed that FASN likely regulates the expression of genes of a variety of biological processes including cell proliferation, DNA replication and transcription, as well as apoptosis [87]. Although the mechanism of this regulation is currently unknown, it is possible that several signal transduction pathways that are under FASN control may mediate the FASN regulation of gene expression. In addition to regulating genes at their transcriptional level, FASN also appears to play a role in regulating gene expression at translational level. It has been found recently that knocking down FASN expression or treatment with FASN inhibitor Orlistat inhibited phosphorylation of translation initiation factor, eIF4E, which regulates the synthesis of many growth-controlling proteins [103].</p><!><p>Cancer cells are so dependent on de novo fatty acid synthesis that inhibition of lipogenesis targeting FASN induces apoptosis selectively in human cancer cells both in vitro and in vivo [46–48, 98], with minimal effect on normal cells [17, 50, 51]. The differential expression of FASN, together with the different responses to FASN inhibition between cancer and normal cells, makes FASN a suitable target for cancer treatment with good therapeutic index. Indeed, pharmacological inhibitors of FASN have been identified and shown to block tumor cell proliferation, elicit tumor cell death, and prevent tumor growth in animal models. These studies confirmed the potential use of FASN inhibitors as novel antitumor therapeutics (Table 1). These pharmacological inhibitors are discussed in more detail below.</p><!><p>Cerulenin [(2R,3S), 2–3-epoxy-4-oxo-7,10-trans, transdodecadienamide], isolated from the culture filtrate of the fungus Cephalosporum caerulens, is the first known FASN inhibitor that inhibits the biosynthesis of fatty acids and steroids [115, 116]. Cerulenin is a potent non-competitive irreversible inhibitor [117–119] of all known types of FASN, from bacteria to yeast to mammal, and is originally used as an antifungal antibiotic. The crystal structure of a fungal FASN in complex with cerulenin revealed that it covalently binds to a cysteine residue in the active site of the KS domain and causes significant conformational changes [120]. Cerulenin treatment significantly decreased fatty acid synthesis in cancer cells [89] and induced selective cytotoxicity in various types of cancer cells [13, 121, 122], delayed the disease progression in an ovarian cancer xenograft model [11], as well as suppressed liver metastasis in a colon cancer xenograft model [123]. However, cerulenin has a limited clinical relevance because of its highly reactive epoxy group that may interact with other cellular processes besides FASN-catalyzed lipid synthesis, including palmitoylation, proteolysis, and antigen processing [124–126].</p><!><p>To increase the potential applicability of cerulenin, an analogue, C75 (trans-4-carboxy-5-octyl-3-methylenebutyrolactone), has been synthesized by eliminating the reactive epoxy group [127]. Different from cerulenin which acts as a non-competitive inhibitor of the KS domain only, C75 acts as a competitive irreversible inhibitor of FASN on the KS domain, as well as the ER and TE domains [128] although the reason for this difference is currently unknown. In addition, C75 appears to be easily inactivated by DTT in solutions [128], suggesting that its efficacy in vivo may be affected by endogenous thiols such as glutathione. Nevertheless, C75 has been shown to have significant antitumor effects on cancer cell lines of human breast [12], prostate [13], mesothelioma [129], and ovary [62], as well as renal carcinoma in xenograft animal model [95].</p><p>Although both cerulenin and C75 have apparent antitumor effect, they both also have a side-effect in inducing profound weight loss which is far from ideal for cancer patients undergoing chemotherapy. This side effect is apparently due to their activity in increasing fatty acid oxidation through direct activation of CPT-1 [130–136]. They also reduce food intake by blocking the production of hypothalamic neuropeptide-Y [135, 137, 138]. These side effects clearly hinder the further clinical development of cerulenin and C75. A newer generation of cerulenin derivative, C93, was rationally designed to have FASN inhibitory effect without parallel stimulation of fatty acid oxidation [139] and was shown to inhibit tumor growth in vivo in a preclinical model of lung cancer, without causing anorexia or weight loss [15, 140, 141]. C93 may prove to be an interesting lead for further development into a clinical useful FASN inhibitor.</p><!><p>Orlistat (tetrahydrolipstatin) is a reduced form of the natural product lipstatin and currently marketed as the first US Food and Drug Administration (FDA) approved over-the-counter anti-obesity medication. Orlistat works primarily on pancreatic and gastric lipase within the gastrointestinal (GI) tracts [142] by blocking hydrolysis of triglycerides and, thus, uptake of fatty acids from the diet [117, 143]. In 2004, Orlistat was found to also inhibit FASN in an activity-based screening for inhibitors of serine hydrolases in prostate cancer cells and it acts as a tight-binding irreversible inhibitor of the TE domain of FASN [16]. Several follow-up studies has shown that Orlistat exhibits antitumor effects toward melanoma, breast and prostate cancer cells in vitro and in vivo by inhibiting FASN activity, with no adverse effect on normal cells [16, 17, 50, 83, 102, 103, 144–146]. Orlistat could also sensitize drug resistant breast cancer cells to Adriamycin and mitoxantrone via inhibiting FASN [17], validating FASN as a chemosensitization target. Orlistat treatment also appears to induce endoplasmic reticulum stress and apoptosis of tumor cells [145] and inhibit endothelial cell proliferation and angiogenesis [50] although the detailed mechanisms of these actions are currently unknown. Nevertheless, because Orlistat has a very poor solubility and oral bioavailability, its potential in clinical application for systematic use in cancer chemotherapy is very limited.</p><p>One important aspect of Orlistat is that a co-crystal structure of Orlistat and the TE domain has been solved [147] which shows that Orlistat binds to the active sites of TE dimers in two forms: a covalent bounded acyl-enzyme intermediate and a hydrolyzed product (Figure 7). The intermediate is a Ser2308 adduct that interacts with the protein surface of the TE mainly by hydrophobic interactions (Figure 7A). The Orlistat-binding pocket in TE domain can be divided into three portions: a cavity that holds the N-formyl-L-leucine moiety of Orlistat, the specificity channel where the 16-carbon palmitate core binds and the short-chain pocket that fits in the hexanoyl tail. The electrostatic field presented by Glu2431 and Arg2428 and the constriction caused by Ala2363 and Tyr2424 could be the cause of the preference for 16-carbon-containing substrates. The oxyanion is stabilized by the main chain nitrogen atoms of Ile2250 and Tyr2309 and a hydrogen bond with Glu2251. The interaction between the hexanoyl tail and His2481 may help prevent the activation of a water molecule that would result in the immediate hydrolysis of the intermediate. The hydrolyzed product of Orlistat has the C1 atom shifted out of the oxyanion hole and the hexanoyl tail shifted out of the original short-chain pocket (Figure 7B). The palmitate core also shifted about two carbon units toward the distal chamber of the cavity. These findings together with a molecular docking study [148] provide useful information for structure-based drug design targeting FASN in finding better inhibitors targeting the TE activity of FASN.</p><!><p>Recently, many plant-derived natural compounds have been explored as FASN inhibitors. Green tea polyphenols and plant-derived flavonoids were mostly studied and shown to have promising antitumor effect related to their FASN inhibitory activity. Green tea polyphenols, epigal-locatechin gallate (EGCG) and epicatechin gallate (ECG), competitively inhibited the KR activity of FASN [149, 150]. EGCG can induce selective apoptosis in human breast and prostate cancer cells [151–153]. EGCG suppresses FASN expression through down-regulating EFG receptor and downstream PI3K/Akt pathway [63, 152]. The galloyl-moiety of the green tea polyphenol is critical for their effect on FASN inhibition, as ungallated polyphoenol showed no inhibitory effect on FASN [149]. EGCG had no stimulatory effect on fatty acid oxidation and does not induce weight loss in experimental animals as cerulenin and C75 [134]. Unfortunately, the potency of EGCG in inhibiting FASN is low with IC50 of 52 μM [154]. Recently, it was found that heating EGCG in acid could increase EGCG potency by 350 fold [155]. It was thought that EGCG underwent a series of reactions in acidic conditions that resulted in a smaller product of 211 Dalton which trimerizes to form a more active FASN inhibitor. Different from the original EGCG, this new trimeric product inhibits FASN in a competitive fashion at the MAT domain.</p><p>Consumption of food rich in flavonoids has been shown to decrease the incidence of various types of cancers. Flavonoids, such as luteoin, have been shown to inhibit FASN in-vitro and produce cytotoxic effects in breast, prostate and hepatocellular carcinoma cells [156]. The exact FASN domains inhibited by flavonoid are unknown. However, the structural similarity between flavonoids to EGCG suggests that they may also target the KR domain of FASN.</p><!><p>Triclosan (2,4,4-trichloro-2-hydroxydiphenyl ether) is a commonly used antibiotic in soaps, mouthwashes and oral dentifrices due to its ability to inhibit the type II enoyl-reductases in bacteria. This antibiotic has also been demonstrated to inhibit the enoyl-reductase activity of mammalian FASN and cause growth arrest and reduce cell viability in MCF-7 and SKBr-3 breast cancer cells in culture [157]. Triclosan showed little toxicity in experimental animals.</p><!><p>As discussed above, the FDA-approved anti-obesity drug, Orlistat, is poorly soluble with low bioavailability. To improve this drug, more β-lactone type FASN inhibitors have been synthesized based on the structure of Orlistat [158–160]. Some of these compounds showed improved potency in inhibiting FASN activity and inducing tumor cell death, and some showed improved solubility compared with Orlistat [159]. In addition, from a high throughput screening of 36,500 compounds, 18 compounds were identified to have a novel 5-(furan-2-ylmethylene) pyrimidine 2,4,6-trione pharmacophore [161]. This class of compounds competitively inhibited the TE activity of human FASN, de-novo fatty acid synthesis, and induced FASN-dependent death of MDA-MB-435 breast cancer cells. These inhibitors of TE activity of FASN may prove to be useful clinically in future studies.</p><p>Taken together, the known FASN inhibitors have distinct inhibition mechanisms and the active site of FASN being inhibited include the KS, KR, ER, and the TE domain. Apart from their different working mechanisms, these inhibitors were all proven to be effective at eliciting anti-tumor effects, suggesting that any one of the six catalytic domains of FASN may be a promising target for drug discovery to inhibit FASN for cancer chemotherapy. As discussed above, the type II FASN in mitochondria consists of several dissociated individual enzymes resembling the bacterial type II FASN [162–164]. Although the mitochondrial type II FASN accounts for only a few percentage of the overall cellular fatty acid production, it provides the octanoyl group for the endogenous synthesis of lipoic acid. Defective mitochondrial type II FASN has been shown to cause a lethal syndrome of metabolic acidosis and renal tubular acidosis in infant [165] and cell death of human embryonic kidney 203T cells in culture [166]. Thus, future studies in drug discovery targeting FASN may need consideration in avoiding the domains that have high resemblance to the type II FASN in mitochondria.</p><!><p>As a large protein with a complex structure and multiple catalytic domains, FASN is slowly emerging and re-discovered as an important metabolic enzyme and potentially a target in human cancers. Numerous clinical and basic studies have shown that FASN over-expression confers cancer cells distinct growth advantages and the function of FASN in normal cells is limited only to the lipid-producing organs. Elevated FASN expression appears to be an early event in the process of tumorigenesis, and in response to chemotherapy and it is under regulation by several signaling pathways. Elevated FASN in cancer cells also appears to modulate lipid raft domains and various biological processes which in turn promote cell survival and/or prevent apoptosis induced by chemotherapeutic agents. However, the detailed mechanism on how FASN regulates these various biological processes is currently unknown. One hypothesis is the overproduction of palmitate which functions as a secondary messenger that relays signals to various biological signal transduction pathways for cell survival. This hypothesis is waiting to be tested.</p><p>Although it is now known that FASN may be a proto-oncogene and its over-expression promotes tumorigenesis and survival, how FASN is up-regulated in the first place in normal or pre-neoplastic cells to prime tumorigenesis is currently unclear. Future studies directed to understanding what up-regulates FASN may help reveal the secret regarding this issue. Findings from studies using cancer cells may contribute to this endeavor. However, studies using normal cells may be more fruitful.</p><p>The differences in the FASN expression level between normal and cancer cells, together with the specific cytotoxicity of FASN inhibition in cancer cells, as well as the role of FASN in chemotherapeutic resistance led to the exploration of FASN as a therapeutic target for cancer treatment. With the available crystal structure of FASN as well as co-crystal structures of FASN with its known inhibitors, more inhibitors of FASN are expected to emerge and some of these inhibitors may get tested in clinical settings in the foreseeable future. However, caution should be taken when targeting various catalytic domains of FASN for drug discovery to eliminate their potential effect on the mitochondrial type II FASN.</p><p>One other important area to watch for is the development of FASN as a diagnostic marker. Elevated FASN levels have been detected in the blood of patients with breast, prostate, colon, and ovarian cancers compared with normal subjects using ELISA [167], suggesting that FASN may be used as a diagnosis marker for cancers. This line of research may offer an important approach for early diagnosis of human cancers.</p><!><p>De novo fatty acid synthesis. The de novo fatty acid synthesis pathway functions in both cancers and lipogenic tissues. In both cases, excess glucose goes through glycolysis and TCA cycle, and exits mitochondria as citrate which is then converted to acetyl-CoA by ATP citrate lyase. Carboxylation of acetyl-CoA to malonyl-CoA is catalyzed by acetyl-CoA carboxylase (ACC). FASN condenses one acetyl-CoA and seven malonyl-CoA into palmitate which can be then modified into various lipids such as phospholipids.</p><p>Models of domain organization of FASN. (A) Conventional dimeric model of FASN. In this model, the two subunits in the homo-dimeric FASN are arranged in a fully extended head-to-tail organization. (B) Revised model of domain organization. In this revise model, FASN adopts an X-shaped dimeric form with each monomer in coiled structure to allow multiple intra- and inter-subunit interactions. KS = ketoacyl synthase; MAT = malonyl/acetyltransferase; DH = dehydrogenase; ER = enoyl reductase; KR=ketoacyl reductase, ACP = acyl carrier protein; TE = thio-esterase.</p><p>Atomic structure of FASN. The overall structure of FASN dimer is X-shaped (viewed in perpendicular to its pseudo-2-fold axis). One subunit is colored by different shades of blue and green for different domains. The other subunit is in infrared colors ranging from magenta to orange. The two non-enzymatic domains, pseudo-ketoreductase (ΦKR) and pseudo-methyltransferase (ΦME), are colored in gray and black, respectively, for both subunits. This figure was created from FASN structure (PDF ID: 2VZ8)</p><p>FASN-catalyzed palmitate synthesis. FASN-catalyzed palmitate synthesis involves three steps: initiation, elongation, and termination. The initiation step involves condensation of acetyl-CoA and malonyl-CoA catalyzed by the MAT domain. The elongation step of condensation of additional malonyl-CoA is catalyzed by KS, KR, DH, and ER domains. The final step of termination is catalyzed by the TE domain to release palmitate from FASN.</p><p>FASN expression in MCF7 and the stepwise-selected drug resistant and revertant cell lines. (A). Western blot analyses. 20 mg proteins, each from MCF7, its stepwise-selected MCF7/AdVp10, MCF7/AdVp100, and MCF7/AdVp3000 cells as well as the revertant cell line MCF7/Rev, were separated by SDS-PAGE followed by western blot analyses using FASN antibody. GAPDH was used as a loading control. (B). Real time RT-PCR analyses. RNAs isolated from MCF7, its stepwise-selected MCF7/AdVp10, MCF7/AdVp100, and MCF7/AdVp3000 cells as well as the revertant cell line MCF7/Rev were subjected to real time RT-PCR analysis using SYBR green. The relative level of FASN mRNA calculated in the fold change (2ΔΔCt) relative to that in MCF7 cells after normalization by internal control, GAPDH.</p><p>Cell cycle analysis of FASN over-expressing MCF7 cells and vector transfected control MCF7 cells. 5×105 cells were harvested, labeled with propidium iodide and analyzed by flow cytometry analysis for stage of cell cycle, G0/G1, S, G2/M.</p><p>Binding mode of Orlistat in the TE domain of FASN. Only the molecular surface of the TE domain where Orlistat binds is shown. The binding of Orlistat in the TE domain exists as a serine adduct intermediate (pink ball and stick, panel A) and hydrolyzed product (gray ball and stick, panel B). The serine intermediate is also superimposed to show the shifts and changes in the hydrolyzed product in panel B. This figure was generated from data in PDB (ID: 2PX6).</p><p>FASN inhibitors and their acting sites in FASN</p>

PubMed Author Manuscript

Random Forest Refinement of the KECSA2 Knowledge-based Scoring Function for Protein Decoy Detection

Knowledge-based potentials generally perform better than physics-based scoring functions in detecting the native structure from a collection of decoy protein structures.Through the use of a reference state, the pure interactions between atom/residue pairs can be obtained through the removal of contributions from ideal-gas state potentials. However, it is a challenge for conventional knowledge-based potentials to assign different importance factors to different atom/residue pairs. In this work, via the use of the 'comparison' concept, Random Forest (RF) models were successfully generated using unbalanced data sets that assign different importance factors to atom pair potentials to enhance their ability to identify native proteins from decoy proteins. Individual and combined data sets consisting of twelve decoy sets were used to test the performance of the RF models. We find that RF models increase the recognition of native structures without affecting their ability to identify the best decoy structures. We also created models using scrambled atom types, which create physically unrealistic probability functions, in order to test the ability of the RF algorithm to create useful models based on inputted scrambled probability functions. From this test we find that we are unable to create models that are of similar quality relative to the unscrambled probability functions. Next we created uniform probability functions where the peak positions as the same as the original, but each interaction has the same peak height. Using these uniform potentials we were able to recover models as good as the ones using the full potentials suggesting all that is important in these models are the experimental peak positions.

random_forest_refinement_of_the_kecsa2_knowledge-based_scoring_function_for_protein_decoy_detection

Introduction<!>Building up the probability list for the proteins<!>Building up the ranking list for a decoy set<!>Decoy sets<!>Protein structure preparation<!>The KECSA2 potential<!>Machine learning and validation<!>(ii) Overall decoy sets training<!>Model accuracy (individual decoy set training)<!>Ranking of the native structure<!>RMSD and TMscore of the first selected decoy structure<!>Feature importance analysis for the overall decoy set<!>Comparison of overall RF model with traditional scoring functions<!>Importance of potential<!>Conclusion

<p>According to the "thermodynamic hypothesis". 1 the native protein in its preferred milieu should adopt a structure that has the lowest Gibbs free energy. Hence, accurate energy functions are needed to solve the protein folding, the protein structure prediction, and protein design problems. Extant scoring functions can be classified into three broad categories, physics-based, knowledge-based, and machine learning based scoring functions. Physicsbased scoring functions typically employ a classical force field that represents the protein at the atomic level through the use of energy terms that represent bond, angle, torsion, van der Waals, and electrostatics interactions using relatively simple terms. [3][4][5][6][7][8][9] Alternatively, knowledge-based scoring functions extract radial distributions of atom/residue pairs from a protein structure database and use different statistical analysis to gain "pure" interactions between atom/residue pairs. 2, Machine learning based scoring functions utilize different machine learning/deep learning algorithms and a large variety of information from protein structures. [49][50][51][52][53][54][55] For example, SVMQA combines different statistical potentials, secondary structure information, and surface area as the descriptors for protein structure prediction. 53 Currently, knowledge-based scoring functions have been more successful than physics-based potentials in protein structure prediction. 2 Knowledge-based scoring function can be classified into coarse-grained residue 17,[21][22][23][24][25][26][27][28][29][30][31] or atomic level 2,[32][33][34][35][36][37][38][39][40] potentials due to different descriptions of the interactions present. The main challenge of building up a knowledge-based potential is how to set up an appropriate reference state. In 1985, Miyazawa and Jernigan introduced the 'Random-mixing approximation', 26 which states that, in the reference state, amino acid and solvent molecules would be uniformly distributed throughout the volume due to the absence of interactions. Many different kinds of reference states have been constructed since then. For instance, the freely-jointed chain (FJQ) model 41,42 was applied to construct a random-walk reference state. 39 Knowledge-based potentials are very sensitive to the completeness of the structural database used to describe the potential and given the current status of available structural information the contribution or presence of each atom/residue pair combination is not equal for every interaction. Thus, different importance factors need to be applied to each pair wise interactions in a knowledge-based potential to reflect this deficiency. In principle, the reference state removes the contribution from an ideal-gas state potential, but the process of accurately assigning different importance factors to each atom/residue pair remains challenging.</p><p>In order to obtain an accurate potential, and estimate of the relative importance of each atom pair is needed. In this work, we focus on using the Random forest (RF) machine learning (ML) model to refine a knowledge-based potential by designating different importance factors to each atom pair in a given potential. Here, the knowledge-based and empirical combined potential, KECSA2, with 167 atom types, 2001 torsion potentials, and 14028 non-bonded atom pairs is used in the RF refinement. Our goal is to construct a ML model that can accurately differentiate the native structure from decoys using a potential refined by RF optimization. Firstly, a 'comparison' concept is used to change an unbalanced database to a balanced one for the construction of the RF refinement models. Secondly, the RF refinement models are applied both on individual and combined decoy sets from twelve commonly used decoy sets. As a result of this optimization all of the RF refined models recognize native structure more accurately than conventional potentials. The performance improvement realized by our RF refinement protocol can be applied to the refinement of potentials other than KECSA2. Finally, the importance of KECSA2 was examined through the use of scrambled and uniform probability functions. The comparison result suggests that only the peak positions are important in the construction of RF models, and the RF models can be used to optimize the peak heights for different atom pairs.</p><!><p>If all independent pair wise probabilities with different magnitudes in a n-body system are known, the probability of the whole n-particle system can be obtained as:</p><p>where pn is the probability of the n-particle system, cij is the scaling factor, which can be evaluated using the random forest model, of pair wise probability pij, i and j represent two different particles. Using a knowledge-based potential with pair wise independent interactions, the independent pair wise probabilities for the bond, angle, torsion, and nonbonding terms can be obtained. If the protein structure is treated as a n-particle system, the probability is:</p><p>pprotein is the protein structure probability, c and p represent the scaling factor and the probability of atom pair  and , the subscripts ij, kl, mn, and pq correspond to bond, angle, torsion, and non-bonded atom pairs, respectively. In this work, we make two further assumptions: (i) ∏ 𝑝 𝑏𝑜𝑛𝑑 𝑏𝑜𝑛𝑑 and ∏ 𝑝 𝑎𝑛𝑔𝑙𝑒 𝑎𝑛𝑔𝑙𝑒 are similar for native and all decoys and, hence, are treated as a constant C; (ii) the probabilities for the torsion and nonbond atom pairs are independent since a reference state is used to remove contributions from the ideal-gas state. With these assumptions, the probability of a n-atom protein can be written as:</p><p>Taking the logarithm on both sides of equation 3 we get:</p><p>where xmn and xpq are the logarithm of cmn and cpq, respectively. A detailed potential database, KECSA2, was utilized to obtain pmn and ppq. Below we use O-MET-CG-MET as an example for what is involved in calculating the pair wise probability of a given protein. From KECSA2, the probability versus distance function, shown as a red curve in Figure 1, can be found. If the distance between O-MET-CG-MET in the protein is 4.5 Å, we first obtain the corresponding probabilities for the distances from 4 Å to 5Å with an interval of 0.005 Å.</p><p>Next, we take the logarithm of the average of the 201 probabilities obtained in the previous step, and use it to represent the probability at distance 4.5 Å. Using equation 5, the probability for each atom pair present in the protein can be obtained; for the same atom pairs, the probabilities were summed yielding the final probability. In this way, the probability list for each protein examined can be generated. ). The descriptor sets are defined as the 'Descriptor vector' in Figure 2. Next, the descriptor vector of the native minus the vector of each decoy are classified as class '1', which means 'more stable than' since the native structure is always more stable than the decoys; the descriptor vector of each decoy minus the vector of the native is defined as class '0', which represents 'less stable than'. The resultant descriptors are described as the 'final descriptor vector' in Figure 2. In this way, equal members of class '0' and class '1' can be generated, which is an ideal situation for classification. Hence, a RF model can be obtained based on using those two classes. Through the use of this classification system a RF model can be generated where the relative probabilities of two proteins with the same sequence can be compared. A final descriptor vector can be generated using the descriptor vector of the first protein minus the second's. Then the RF model can be used to predict the class for that final descriptor vector. If the prediction from the RF model is '1', it means the first protein is 'more stable than' the second one, and if the prediction is '0', the first protein is 'less stable than' the second one.</p><!><p>Constructing a RF model that can accurately differentiate native and decoy structures is not enough. For a native recognition blind test, in order to identify the native structure, a ranking of all structures should be generated. Thus, the RF model needs to be used to obtain the ranking list for a decoy set.</p><p>Figure 3 gives the protocol used to obtain the ranking of a decoy set with n structures.</p><p>First, the probability descriptor of each protein structure can be built using the KECSA2 database. Second, a table for each structure was obtained from the probability descriptor of the individual protein structure minus the probability vectors of all the other structures. Then, the RF model is used to predict the class of each column in all tables; in other words, the RF model is used to 'compare' two structures. Finally, a row with length n-1 can be generated for each structure. The value of each column in the resultant row is either '0' or '1', which represents the comparison result of each structure with all other structures. The sum of the resultant row is defined as a 'score', which indicates if the corresponding structure is more stable than the "score" amount of decoys. In this way, the score of each structure can be generated, thereby, creating a ranking list.</p><!><p>The decoy sets we used include the multiple decoy sets from the Decoys 'R' Us collection (http://compbio.buffalo.edu/dd/download.shtml), which include the 4state_reduced, fisa, fisa_casp3, hg_structal, ig_structal, ig_structal_hires, lattice_ssfit, lmds, and lmds_v2 decoy sets. The MOULDER decoy set was downloaded from https://salilab.org/decoys/; the I-TASSER decoy set-II was obtained from https://zhanglab.ccmb.med.umich.edu/decoys/decoy2.html; and the ROSETTA all-atom decoy set from https://zenodo.org/record/48780#.WvtCA63MzLF.</p><p>Our RF model was compared to the following potentials designed for decoy detection: KECSA2, GOAP, 2 DFIRE, 40 dDFIRE, 37,43 and RWplus. 39 The programs for these methods were downloaded from the corresponding author's website.</p><!><p>All protein structures (including both native and decoys) were converted into their biological oligomerization state and prepared with the Protein Preparation Wizard, 44 which adds missing atoms, optimizes the H-bond network, and performs energy minimization to clean up the structures for subsequent calculations. The decoy sets can be found here https://github.com/JunPei000/protein_folding-decoy-set.</p><!><p>KECSA is a potential specifically designed for protein and protein/ligand systems that was developed in our group. 45 A detailed atom type definition was used in this potential; in other words, every atom type represents a specific atom in the twenty naturally occurring amino acids. For instance, 'CA_ALA' corresponds to the alpha carbon in alanine. A detailed description of out atom typing scheme can be found here https://github.com/JunPei000/protein_folding-decoy-set.</p><!><p>The sklearn.ensemble.RandomForestClassifier function from Scikit-learn was used to create the proposed classification model. 46 For each decoy set, ten iterations described above were run creating ten sets of hyperparameters. Hyperparameters with the highest frequency are shown in Table s1.</p><!><p>In order to avoid duplicate protein system that existed both in the training and test set, different decoy sets were combined based on different proteins. For instance, 2cro is a decoy set that is present in both the 4state_reduced and fisa decoy sets; herein, the two 2cro sets were combined together. In total, there were 235 different decoy sets.</p><p>In overall decoy set training, the top 100 to top 500 most important features were used instead of using all 16029 descriptor elements, based on an importance feature analysis generated from the combined decoy sets. In order to obtain the overall importance feature analysis, ten importance feature analyses on the decoy subsets were generated. Specifically, for each importance feature analysis on a decoy subset, a grid search was done on 20% of the data from the combined data set, then an importance feature analysis of the best parameter set was generated. This process was repeated ten times in order to cover the whole data set, and the ten importance feature analyses were combined to obtain the overall result.</p><p>Based on this analysis, the top 100, 200, 300, 400, and 500 most important features were selected for use in the RF model. Again ten iterations were run to find the best hyperparameter set for the combined data set.</p><p>Where AB represents the torsion atom pair, rAB is the distance between atom A and B, rmax_AB is the corresponding distance of the lowest potential/highest probability point for atom pair AB.</p><p>For nonbond interactions, equation 8 was used to generate the uniform probability function of different atom pairs based only on the rmax values from the KECSA2 nonbond interactions.</p><p>Where AB is a nonbond atom pair, rAB represents the distance between atom A and B, E1 and E2 are parameters for repulsion and attraction interactions, respectively. It is known that the probability function achieves a maximum at rmax_AB; hence, the derivative of equation 8 should be equal to 0. By setting the maximum value to a constant, the parameters E1 and E2 can be obtained using equations 9 and 10.</p><p>In this way, if the constant in equation 10 is the same for all nonbonded interactions, probability functions with the same heights but different peak positions can be constructed. In the end, descriptor vectors and final descriptor vectors can be generated based on these uniform probability functions.</p><!><p>The most important characteristic of the resultant scoring function is its ability to differentiate the native structure from decoys. Table 1 shows the accuracy for both the RF models and traditional scoring functions. Since ten cycles of independent training and testing were performed for each decoy set, the highest, lowest, and averaged accuracy were used to represent the general performance of RF models on that specific decoy set. In this way, the performance of the RF model can be better interpreted. In general, the RF model shows higher accuracies than all traditional methods for all of the decoy sets. For some decoy sets, like fisa, ig_structal, lmds_v2, and rosetta, RF models significantly improved the averaged accuracy to nearly 1.000, and the lowest accuracy values are still higher than the best accuracies of the other scoring functions. For the other decoy sets, such as 4state_reudeced, fisa_casp3, hg_structal, ig_structal_hires, I-TASSER, lattice_ssfit, lmds, and MOULDER, the averaged accuracies from the RF models are similar to the best accuracies of traditional scoring functions, while the lowest accuracies of the RF models are similar to the accuracies of other methods. Overall, the RF models show better performance.</p><!><p>Although the accuracies of RF models are higher than other methods, we still wanted to further validate their performance. Other than accuracy, another important criteria for judging a model/scoring function is whether the model/scoring function identifies the native structure as having the lowest rank. Hence, native structure ranking from the different methods were also compared. Table 2 shows the rankings of the native structures from several different models. The highest, lowest, and averaged rankings are shown to assess the performance of RF models. For the decoy sets fisa, ig_structal, lmds, lmds_v2, and ROSETTA, the RF models substantially improves native structure ranking over the other models. In the remain decoy sets, the averaged rankings of native structures are similar to the best performance of the other scoring functions. It can be concluded that, in general, the RF model shows a better performance in ranking the native structure over other methods we tested.</p><!><p>Although the ability to recognize the native structure as the most stable structure is a crucial characteristic of a good model/potential. For a model/potential to be useful for guiding conformation sampling, it should have a good correlation with structural quality. The RMSD and TM-score were used as two criteria for assessing the quality of each decoy structure.</p><p>RMSD is the root mean squared deviation of all C pairs of the decoy to the native structure.</p><p>TM-score 47 gives a large distance a small weight and makes the magnitude of TM-score more sensitive to the topology. Table 3 and Table 4 summarize the results of best model selection of different methods. a) RF models were trained on different decoy sets.</p><p>Table 3 shows the 1 st decoy's RMSD of RF models and against a range of available scoring functions. The RMSD values of available methods are generally within the range of lowest and highest RMSD values of the RF models for each decoy set. This means the performance of those traditional scoring functions are within the confident range of our RF models. Table 4 shows the 1 st decoy's TM-score for the RF model and against several models; these results are similar to what we observed for the RMSD analysis. In each decoy set, the 1 st decoy's TM-score is within the range of the lowest and the highest TM-score from the RF models. Considering that the independent training and testing process was done ten times, the range of lowest to highest RMSD/TM-score values show the confidence range of RF models for each decoy set. In general, the RMSD/TM-score performance of available models are within the confidence range of the RF models, and the averaged values are similar in RF models and models we tested against. In other words, the performance of the RF models against a range of models, when it comes to selecting the best decoy structure, were similar.</p><!><p>It is important to understand whether the better performances of RF models are due to overfitting because a large number of descriptors were used. To this end, a feature importance analysis was performed and is shown in Figure s1. Based on the analysis, new RF models using only the top 500 features were constructed using the previous procedure. Table 5 shows the comparison of the accuracies between using only the top 500 and all 16029 features. In general, the highest, lowest, and averaged accuracy values of the RF models using the top 500 features for each decoy set are similar to the corresponding values of the RF models using all features. Table s2 shows the comparison of the native structure's ranking between RF models with the top 500 and all features. The native rankings of RF models with 500 features are similar to those rankings for the RF models using the full feature set except for decoy set fisa_casp3. For fisa_casp3, the native ranking increases from 1.00 to 36.40 due to the loss of the remaining 15529 features. Among the 15529 features, they might contain important information to differentiate the native from decoys in that particular decoy set. But in general, the performance of RF models with 500 features for native structure ranking is still similar to the RF models with all features. Table s3 and Table s4 show the results of best decoy selection for RF models with the top 500 and whole feature set. Similar to comparisons of accuracies and native rankings, for the best decoy selection, the performance of the RF models using the top 500 features is still similar to the RF models with all features. Hence, we conclude that the better performance of RF models with all features is not simply due to overfitting and the current method is robust even in the face of potentially non-essential features.</p><!><p>Besides creating RF models for each individual decoy set, combined RF models using all decoy sets were also constructed. This examines the situation where in a study one might generate decoys using one method and then score them with another. There were 291 individual systems across the 12 decoy sets that were combined finally, yielding 235 different protein systems (several proteins overlapped amongst the decoy sets). In these studies, 80% of the combined data set was used as the training data to build the RF models instead of choosing several specific decoy sets (like 4state_redueced, fisa, etc.). This was done to insure that the training and testing data set covered the same feature space and had the same distributionthis is known as an independent and identical distribution (IID). 48 The feature space and distribution of decoys from different decoy sets are different because different models were used to generate those structures.</p><p>Table 6 shows the result of comparing the overall performance of RF models with a number of available potentials. Due to the large number of descriptors, it is impossible to obtain RF models using the entire 16029 feature set. Based on the importance analysis discussed previously, instead of using all features, top 100, 200, 300, 400, and 500 features were used to build up the overall RF models on the combined decoy sets. First, all RF models with different importance features provide higher averaged accuracy values than other traditional scoring functions. Clearly, the accuracies of the RF models outperform the other conventional methods. Second, the highest rankings of the native structure from RF models are smaller than the rankings of other methods, and all of the averaged rankings of the RF models were ~10 or less, which means the RF models can identify the native structure within the top ten structures. Hence, the RF models outperform other methods on this task.</p><!><p>Based on the previous discussion, it is clear that the RF models with KECSA2 perform the best in accuracy and ranking both on individual and overall decoy sets. This which means those two atoms are most stable when they form a hydrogen bond at that distance. However, after scrambling, the peak position might change to 4.51Å (peak position of CA-GLY and C-THR), which no longer represents a hydrogen bond. Thus, the scrambled probability function suggests that the atom pair O-PRO and N-ALA is most stable when they do not form a hydrogen bond. It is clear that the scrambled probability functions are unphysical. We expect that it would be unlikely that the RF model, as employed herein, could correct these deficiencies so, the performance of the scrambled probability function is expected to be worse than original KECSA2.</p><p>Second, the uniform probability functions (or potential functions) were built for the top 100 and 500 atom pairs to test if the KECSA2 probability peak heights (or well-depths) are important in RF models. The uniform probability functions have the same peak positions found in KECSA2, but with same heights. By doing so, the interaction strength 'bias' of different atom types from KECSA2 can be eliminated via use of uniform probability functions. If the KECSA2 probability peak heights (or interaction potentials) are significant, the performance of uniform potential should be worse than KECSA2.</p><p>The comparison of the result between the original KECSA2 potential, scrambled potential, and uniform potential are shown in Table 7. From the comparison between the original KECSA2 and the scrambled potentials, we find the accuracy of the models decreased ~0.15, which gives a clear signal that the full KECSA2 potential (well depth and energy minimum) plays a role in RF models. The comparison between the uniform and original KECSA2 potential gives an evidence of how important the rmax component of the KECSA2 potential is in building an effective model. For the RF models with the top 100 features, the averaged, highest, and lowest accuracies based on the original KECSA2 potential are slightly higher than the corresponding accuracies from the RF models based on uniform potentials.</p><p>However, if the number of features is increased to 500, the averaged, highest, and lowest accuracies from the RF models based on the original KECSA2 are similar to the uniform potentials. This provides strong evidence that only peak positions in the probability functions are critical in building up RF models for native protein structure detection. More importantly, the result also implies that RF models can be used to tune the height of peaks in probability functions (or the depth of potential functions) only with the information of peak positions in protein structures.</p><!><p>In this work, we utilized a 'comparison' concept to construct RF models on an unbalanced data set. With these RF models, the knowledge-based potential, KECSA2, was refined via assignment of different importance factors to different atom pairs present in the scoring function. The performance of the resultant RF models were assessed with individual and combined decoy sets and compared with the results from conventional models. We find that the RF models perform better in accuracy and native ranking and have similar performance in the RMSD and TM-score tests. In other words, the RF models improved the effectiveness of finding native structures from a set of decoys, without compromising their ability to find the best decoy structures. This RF model based refinement not only can be used to improve the performance of KECSA2, but it can also be applied to other atom/residue pair based potentials. More importantly, we find that only peak positions in probability functions play a significant role in constructing the RF models. This result implies that, with peak position information, RF models can be created to construct probability functions (or potential functions) by tuning the height of peaks in those functions based on native and decoy protein structures.</p>

ChemRxiv

11C=O Bonds Made Easily for Positron Emission Tomography Radiopharmaceuticals

The positron-emitting radionuclide carbon-11 (11C, t1/2 = 20.3 minutes) possesses the unique potential for radiolabeling of any biological, naturally occurring, or synthetic organic molecule for in vivo positron emission tomography (PET) imaging. Carbon-11 is most often incorporated into small molecules by methylation of alcohol, thiol, amine or carboxylic acid precursors using [11C]methyl iodide or [11C]methyl triflate (generated from [11C]CO2). Consequently, small molecules that lack an easily substituted 11C-methyl group are often considered to have non-obvious strategies for radiolabeling and require a more customized approach. [11C]Carbon dioxide, [11C]carbon monoxide, [11C]cyanide, and [11C]phosgene represent alternative carbon-11 reactants to enable 11C-carbonylation. Methodologies developed for preparation of 11C-carbonyl groups have had a tremendous impact on the development of novel PET radiopharmaceuticals and provided key tools for clinical research. 11C-Carbonyl radiopharmaceuticals based on labeled carboxylic acids, amides, carbamates, and ureas now account for a substantial number of important imaging agents that have seen translation to higher species and clinical research of previously inaccessible targets, which is a testament to the creativity, utility, and practicality of the underlying radiochemistry.

11c=o_bonds_made_easily_for_positron_emission_tomography_radiopharmaceuticals

1.1 Strategies for radiolabeling with carbon-11<!>1.2 Criteria for Practical Radiosynthesis with Carbon-11<!><!>1.2 Criteria for Practical Radiosynthesis with Carbon-11<!>2.1 Production and Handling of [11C]CO2<!>2.2 Methods for Radiotracer Synthesis<!>2.3 Impact<!>3. Radiochemistry with [11C]COCl2<!>3.1 Production and Handling of [11C]COCl2<!>3.2 Methods for Radiotracer Synthesis<!>3.3 Impact<!>4. [11C]CO Carbonylation<!>4.1 Production and Handling of [11C]CO<!>4.2 Methods for Radiotracer Synthesis<!>4.3 Impact<!>5. [11C]HCN Cyanation<!>5.1 Production and Handling of [11C]HCN<!>5.2 Methods for Radiotracer Synthesis<!>5.3 Impact<!>6. Conclusions and Outlook<!>

<p>The discovery and development of positron emission tomography (PET) radiopharmaceuticals demands an iterative approach that, even when informed by existing medicinal chemistry data and computational modeling, suffers from capricious trial-and-error based evaluation.1–4 While advances in radiochemical methods with carbon-11 (11C, t1/2 = 20.3 min) and fluorine-18 (18F, t1/2 = 109.7 min) have enabled the preparation of a greater array of radiolabeled small molecules, relatively fewer of these methods have been applied for PET radiotracer development or led directly to the discovery of novel radiopharmaceuticals. Methods that require the synthesis of specialized precursors or which are proven only on relatively simple molecules hold limited value for radiopharmaceutical development since they require significant synthetic effort to apply them to the goals of rapidly and reliably preparing series of radiotracer candidates and eventually reproducible routine production. For these reasons, many small molecule tracer development programs still rely on a very small number of radiolabeling methods, chief among them being 11C-methylation.5,6</p><p>The merits of 11C-methylation as a choice reaction for radiotracer development have been well-recognized.3,7,8 [11C]Methyl iodide and [11C]methyl triflate are nowadays readily prepared in many cyclotron-equipped radiochemistry facilities using commercial apparatus.9 The precursors for 11C-methylation are typically alcohols, amines, thiols, carboxylates, or amides, which can all be subjected to similar labeling conditions that seldom require significant optimization. The primary variables are the nature and stoichiometry of added base (if needed) and any deprotection and/or workup steps prior to purification. Contemporary methods even do away with a dedicated reaction vessel for this process, and conduct the radiolabeling inside of an injector loop, which is subsequently flushed onto an HPLC column using mobile phase to initiate purification ("loop method").10–12 Despite this technical simplification, 11C-methylation represents only one strategy for radiolabeling, and can be applied to prepare O-, N-, S-, or in some cases C-11C-methylated products,13,14 in the presence of compatible functional groups (Scheme 1A). By relying so heavily on a single synthetic strategy, radiotracer development has necessarily been biased towards certain classes of 11C-methylated products, at the expense of greater chemical diversity.</p><p>In this review, we will explore 11C-carbonylation as an alternative set of strategies that can serve as a complementary tool to 11C-methylation for radiotracer development. Carbonyl groups are found throughout bioactive molecules and are featured in a great number of functional groups utilized by medicinal chemists.15 An analysis of drug candidates from the AstraZeneca's central nervous system portfolio in January 2012 revealed that <35% of compounds could be radiolabeled by 11C-methylation alone, compared to >75% when including candidates for 11C-carbonylation.16 Likewise, [11C]carbon dioxide, [11C]carbon monoxide, [11C]cyanide, and [11C]phosgene represent a versatile set of alternative carbon-11 reactants to enable 11C-carbonylation when 11C-methylation is either not applicable for preparation of 11C-isotopologues or not desirable for metabolic reasons17 (Scheme 1B). The criteria which each 11C-radiolabeling methodology must satisfy to be useful for radiopharmaceutical development are outlined herein with a focus on methods for preparation of 11C-carbonyl groups. We will show that the toolbox available for 11C-radiotracer development includes viable methods for 11C-carbonylation (using [11C]CO2, [11C]COCl2, [11C]CO, and [11C]CN), and will identify remaining challenges for widespread adoption of these for routine application in radiosynthesis.</p><!><p>PET is an imaging modality used to study biochemical processes by reporting on molecular interactions of in vivo probes.6,18 A number of positron-emitting isotopes are available, including 11C, nitrogen-13, oxygen-15,19 18F,5,20 copper-64, gallium-68, and zirconium-89,21,22 and may be selected for a given imaging target based on desired half-lifes, and synthetic and biochemical compatibility. Isotopologue radiolabeling is attractive for well-characterized small molecules to take advantage of known properties, such as target affinity, selectivity, specificity, pharmacokinetics, and metabolism, which can be affected by structural modifications. The ubiquity of carbon atoms in organic compounds is complemented by highly versatile radiochemistry and the potential for multi-tracer studies in a single imaging session to establish 11C as a frequently selected isotope for tracer development.</p><!><p>commercial availability or facile syntheses of precursors</p><p>radiochemical purity</p><p>specific activity (SA)</p><p>radiochemical yield (RCY)</p><p>ease of automation and reproducibility</p><!><p>A major strength of 11C-methylation is widespread availability of precursors such as carboxylic acids, amines, alcohols, and thiols with which to prepare 11C-methylated derivatives. On the other hand, a method such as [11C]CO2-fixation using air-sensitive and reactive Grignard reagents faces major headwinds to expanding its utility beyond relatively simple radiopharmaceuticals such as [11C]acetate and [11C]palmitate or labeled intermediates for acylation of more complex products such as [11C]WAY-100635 and [11C](+)-PHNO (vide infra).23 Achieving high radiochemical purity of the radiotracer is essential for in vivo imaging studies. Radioactive impurities, even in trace amounts, can dramatically skew the interpretation of PET imaging or decay counting experiments, since the detected γ-photons do not indicate molecular identity.24,25 Reactions that produce multiple structurally similar radioactive products can pose obstacles to efficient purification by semi-preparative HPLC and/or solid-phase extraction.26–28</p><p>The "tracer principle" forms the basis of diagnostic nuclear imaging, and allows for probing of biological targets in vivo without inducing physiological effects. The specific activity (SA) of a radiotracer is defined as radioactivity relative to mass and depending on the biological target, high SA (generally considered as >1 Ci·μmol−1, >37 GBq·μmol−1) may or may not be required at the time-of-injection.29 Regardless, to be applicable to a variety of radiotracers and biological targets, a labeling method should be capable of delivering high SA products. For 11C, SA can be compromised by sources of non-radioactive intermediates, usually arising from atmospheric CO2. Similarly, the chemical purity of the product should be high to maintain a low total injected mass, especially if the impurities may have affinity to the target of interest, or pose a toxicity concern.30,31 Ideally, radiolabeling reactions proceed with high yields and selectivity, such that separation of the product radiotracer from other species by HPLC purification is trivial. Consequently, it is advantageous to deploy precursors that have substantially different chromatographic/polarity profiles from the products and at low precursor loadings (<0.5–5 mg).</p><p>The only firm requirement for a PET labeling method with respect to radiochemical yield (RCY) is that in vivo studies are possible using convenient amounts of starting radioactivity (0.5–2 Ci, 18.5–74 GBq). For practical purposes, rapid synthetic processes are preferred with short-lived radionuclides and RCY of the entire process from isotope delivery (for 11C, typically as [11C]CO2) to isolation of a sterile formulated product should be determined. Most radiopharmaceutical production is conducted within the constraints of a hot cell and automated synthesis module to ensure high levels of reproducibility and to take advantage of engineering controls to minimize radiation exposure to personnel. To validate a radiopharmaceutical production for human administration, it is typically repeated multiple times, according to a set protocol, to generate consistent RCY, SA, radiochemical and chemical purity, within a margin of variability, and passing several analytical tests to ensure doses are safe for injection.31,32</p><!><p>[11C]CO2 is a highly convenient reagent for use in radiolabeling, as it is nearly always the first carbon-11 product formed in a cyclotron target. [11C]CO2 is generated by proton bombardment of nitrogen gas (14N(p,α)11C) in the presence of small amounts of oxygen (typically 0.5%). [11C]CO2 can be used directly from the cyclotron, though trap-and-release purification and concentration steps are often included to remove excess oxygen and nitrous oxides that may interfere with chemical labeling reactions, and to control delivery flow rate and volume of the gaseous reagent. Two strategies exist for this process. Cryogenic purification involves condensing [11C]CO2 in a small volume vessel (often a steel tube) cooled by liquid nitrogen or argon and subsequent removal of condensable impurities by in-line chemical traps.33 The second approach is to immobilize [11C]CO2 on a solid support such as molecular sieves,34 with release for delivery into the reactor upon heating. The latter approach has recently been adapted for "on-cartridge" labeling and purification of fatty acids using Grignard precursors, for rapid production of [11C]palmitic acid.35 In all cases, it is prudent to equip delivery lines with terminal chemical traps for irreversible retention of [11C]CO2 (e.g., soda lime, ascarite, charcoal) to prevent release of radioactivity.</p><p>[11C]CO2 is sparingly soluble in polar organic solvents, and this solubility can be dramatically improved by the presence of base. In many methodologies, organic nitrogenous bases, such as BEMP or DBU (Scheme 2) are used to trap [11C]CO2 in solution. Both appear to be highly efficient at trapping [11C]CO2 in DMF. Sequestering [11C]CO2 in this way without forming unreactive covalent bonds is appealing compared to [11C]CO2-fixation using strongly basic organometallic reagents, such as Grignard and organolithium reagents, in which trapping is concomitant with C–11C bond formation. Not only do the milder methods facilitate preparation of highly functionalized labeled compounds, but they also allow transamidation to other amines in solution.</p><p>Apparatus used for [11C]CO2-fixation should be rigorously assembled to afford a system that is leak-proof, anhydrous, free of air and constructed with efficient handling and well-controlled flow rates. Unlike other carbon-11 gaseous reagents, [11C]CO2 can easily become contaminated with atmospheric CO2, which reduces the specific activity of the product. Fortunately, many [11C]CO2-fixation protocols are effective with relatively simple apparatus and carried out at room temperature and ambient pressure. High specific activity products are routinely achieved with good reproducibility. Radiochemical yields can also be very high with efficient incorporation levels, in part thanks to relatively rapid syntheses that do not require transformation of [11C]CO2 into other labeling intermediates. While many of the modern [11C]CO2-fixation reactions were developed using bespoke apparatus, commercially available and widely deployed synthesis apparatus (such as those for the preparation of [11C]CH3I) can be adapted for semi-automated catch-and-release of [11C]CO2.36 Applications for [11C]CO2 will very likely continue to develop and become more commonplace in radiochemistry laboratories in the near future.</p><!><p>Owing to the low mass and concentration of [11C]CO2 in cyclotron target and delivery gas, efficient trapping of [11C]carbon dioxide in the reaction mixture is crucial to obtaining high radiochemical yields of labeled products relative to starting radioactivity. Early examples of [11C]CO2-fixation were accomplished using highly reactive organometallic substrates (i.e., Grignard and organolithium reagents) that react directly with [11C]CO2 to form C–11C bonds. In terms of carbon–heteroatom bond formation, Chakraborty et al. reported the first synthesis of [11C]urea using lithium hexamethyldisilazide (LHMDS) to trap [11C]CO2 in a THF solution, followed by aqueous hydrolysis with ammonium chloride.37 Unfortunately, this method is only applicable to the preparation of simple [11C]urea, and derivatives such as [11C-carbonyl]uracil by multi-step syntheses. Silanamines represent an alternative fixating agent for 11CO2, and could be used to generate O-silyl carbamates, which could then be reduced to 11C-methylamines using lithium aluminum hydride.38</p><p>In order to prepare more structurally complex 11C-ureas, organic base-mediated [11C]CO2-fixation was pursued, inspired by mild, industrial-focused processes being developed contemporaneously.23,39 In the first iteration, triethylamine in dichloromethane was used to facilitate 11C-carboxylation of aniline and aliphatic amines, followed by dehydration with POCl3 to generate 11C-carbonyl-isocyanates.40 Under these conditions, 11C-isocyanates reacted immediately with the excess amine, to form symmetrical products including 11C-carbonyl-ureas and 11C-carbonyl-carbodiimides. While these results provided evidence for the desired reactivity using [11C]CO2, they also suggested that achieving selectivity for unsymmetrical ureas could be a practical challenge in this context. Whereas one could reasonably expect to saturate precursor amines using excess CO2 in non-radioactive synthesis, analogous stoichiometry using no-carrier-added [11C]CO2 would demand very precise measurements and high dilution. To overcome these challenges, radiochemists then deployed organic bases such as DBU41 and BEMP,42 which could efficiently trap [11C]CO2 at ambient temperature and pressure, and at practical gas delivery flow rates (Scheme 2A). With BEMP, selective radiosynthesis of unsymmetrical 11C-carbonyl-ureas was finally achieved. Formation of symmetrical products could be suppressed by using excess POCl3, but this strategy also stipulated an even larger excess of the second amine nucleophile, for attack on the 11C-isocyanate. Consequently, a high concentration reaction mixture would be formed, which presented a challenge for purification. Fortunately, reducing the concentration of the initial amine (typically aliphatic primary and cyclic secondary amines) was found to be compatible with fast reaction times (≤2 min) and high radiochemical yields.43</p><p>An alternative approach to isocyanates relied on phosphinimine precursors, prepared from azides or primary amines, for condensation with [11C]carbon dioxide.44 Phenyltriphenylphosphinimine could be used to prepare [11C-carbonyl]phenylisocyanate, and a variety of unsymmetrical 11C-ureas from aliphatic and aromatic amines (Scheme 2B).45 In this case, [11C]CO2 was trapped in a THF solution cooled to −60 °C during gas delivery, followed by heating to 60 °C to complete the reaction. Given the high trapping efficiency in the absence of base, it is likely that [11C]CO2 forms a complex with either the phosphinimine or amine precursor. Mitsunobu chemistry could also be employed to convert ionic carbamates into isocyanates using phosphines and azo compounds (Scheme 2B).46,47 In the presence of an additional amine, the isocyanate could be transformed in situ to a urea.48 To accommodate this reaction to radiolabeling conditions, the reaction temperature was carefully controlled at 50 °C to promote the reaction and prevent premature release of [11C]CO2.49 Aliphatic and aromatic amines could be drawn on for 11C-isocyanate formation, though secondary aliphatic amines were necessary for 11C-urea formation to achieve selectivity for unsymmetrical products.50</p><p>Carbamates, like ureas, are attractive functional groups for drug and radiotracer design due to their stability in vivo, role as a linker of ligand fragments, and for drug-target interactions through the carbamate itself.51 While 11C-carbamates were previously radiolabeled using [11C]phosgene or [11C]carbon monoxide,5 methods using [11C]CO2 are especially convenient for avoiding intermediate redox manipulation. Unlike 11C-ureas, O-alkyl carbamates may be prepared without intermediate dehydration to form 11C-isocyanates. Simply bubbling [11C]CO2 into a DMF solution of DBU or BEMP, an amine nucleophile, and a benzyl, allyl or methyl electrophile followed by heating produced high yields of O-alkyl [11C]carbamates.41,42 Excess or early addition of the methylating agent led to reduced yields of the desired compounds, suggesting the intermediacy of the carbamate ion.</p><p>In order to prepare O-substituted 11C-carbamates not readily accessible by alkylation of carbamate ions, alcohols and phenols can be used to quench 11C-isocyanates, as described above (Scheme 2A).43 A wide variety of alcohols, including hindered and electron-deficient ones such as tert-butanol, and hexafluoroisopropanol52 have been successfully incorporated into 11C-carbamates by this method. Using amino alcohol precursors for [11C]CO2-fixation, oxazolidinones are formed at ambient temperature after dehydration with POCl3.53</p><p>11C-Carboxylic acids have been produced from [11C]CO2, using organometallic precursors, such as methylmagnesium bromide for [11C]acetate and n-pentadecylmagnesium bromide for [11C]palmitate.54,55 This strategy is, however, limited to 11C-carboxylic acids for which a stable organometallic precursor can be prepared. More complex 11C-carboxylic acid derivatives can be prepared by multi-step syntheses wherein magnesium 11C-carboxylate intermediates are converted into acid chlorides and distilled prior to being used in amide bond formation.56 For example, [11C](+)-PHNO, a D3-preferring agonist radiotracer,57,58 was initially prepared in this manner from ethyl magnesium bromide.59,60 However, the synthetic apparatus needed for multi-step reactions using Grignard reagent precursors are challenging to maintain and operate, often leading to high failure rates of radiosynthesis (see, for example, the remarkable preparation of [11C]lapatinib61), and generate an strong impetus to develop alternative methods that are simpler to operate and provide greater reliability.62,63</p><p>In the interest of expanding the utility of CO2 as a feedstock for bulk and specialty chemicals, metal and organocatalytic approaches for CO2-fixation to generate carboxylic acids and their derivatives have been keenly pursued.64,65 Boronic esters have been shown to be amenable for [11C]CO2-fixation using a copper catalyst,36 overcoming the significant challenge of much lower concentrations of [11C]CO2 available in the reaction mixture compared to CO2 under non-radioactive conditions. As such, significant optimization was required, including shifting away from alkoxide bases in favor of N,N,N′,N′-tetramethylethylenediamine (TMEDA), which acts both as a trapping agent for [11C]CO2 and a ligand for the copper catalyst. A variety of functional groups were tolerated under the optimized conditions and the 11C-carboxylic acids could be converted to 11C-carbonyl-esters and -amides, such as the bioconjugation reagent N-succinimidyl [11C-carbonyl]4-fluorobenzoate ([11C]SFB).36</p><!><p>Recently developed methods for [11C]CO2-fixation have led to a number of novel and important radiotracers for fatty acid amide hydrolase (FAAH), a serine hydrolase that regulates signaling at cannabinoid receptors CB1 and CB2 through metabolism of anandamide.66 [11C]CURB was designed in analogy to the selective and irreversible FAAH inhibitor and drug candidate URB597.67 [11C]CURB is an O-aryl carbamate prepared by [11C]CO2-fixation in 8% uncorrected radiochemical yield (RCY), with high specific activity (2.5 Ci·μmol−1, 92.5 GBq·μmol−1) 27 minutes after end-of-bombardment (Scheme 4A).43 Having shown high brain penetration and target selectivity for FAAH in rats,68 [11C]CURB has now been translated for regional quantification of FAAH activity in the human brain, where it has revealed sensitivity to a functional single-nucleotide polymorphism (rs324420, C385A) that inactivates FAAH (Fig. 1).69–71 Pfizer's urea-based irreversible FAAH inhibitor was radiolabeled as its direct isotopologue [11C-carbonyl]PF-04457845 by [11C]CO2-fixation72 in order to conduct biodistribution studies and confirm target engagement and irreversibility of binding to the enzyme in rats (Scheme 4B). Clinical translation of this tracer is also underway.</p><p>The potential and versatility of [11C]CO2-fixation for radiotracer discovery was demonstrated by a combinatorial approach to survey structure-activity relationships of O-aryl carbamates based on the structures of URB597 and URB694 (Fig. 2). To begin, non-radioactive carbamates were prepared – from commercially available amines, bicyclic phenols, and phosgene – for in vitro FAAH assays and physicochemical evaluation.74 Eight FAAH inhibitors were then radiolabeled with carbon-11 using a standard [11C]CO2-fixation protocol to generate 11C-carbonyl-carbamate radiotracers for biodistribution studies. It was found that a linear N-alkyl substituent leads to increased potency over cyclic isomers and that the presence of a dihydrooxazole confers faster and greater brain uptake with lower nonspecific binding. These insights lead directly to the design of two fluorine-18 labeled FAAH radiotracers: [18F]DOPP75,76 and [18F]FCHC.77 Both show greater brain uptake in vivo and sensitivity to FAAH activity in vitro than [11C]CURB. A similar combinatorial approach was implemented in the hopes of developing a monoacylglycerol lipase (MAGL) radiotracer, but unfortunately the radiolabeled compounds failed to show high brain uptake in rodents.52 More recently, a sulfonamide-based MAGL inhibitor SAR127303 was labeled at the 11C-carbamate position using [11C]CO2-fixation and demonstrated irreversible brain uptake with measurable specificity and selectivity for MAGL in rats.78</p><p>Previously designed radiotracers have also been prepared by [11C]CO2-fixation to improve their syntheses or in vivo imaging properties. The reversible monoamine oxidase B (MAO-B) PET radiotracer SL25.1188 was developed using [11C]COCl2, but this method presents technical challenges for widespread use.79 In a bid to improve the accessibility and the isolated yield of [11C]SL25.1188, the amino alcohol precursor was deployed in [11C]CO2-fixation and enabled translation for human PET imaging in clinical research studies (Fig. 3).53,80 [11C]GR103545 is a methyl carbamate PET radiotracer for κ-opioid receptors that was originally radiolabeled using [11C-methyl]methyl chloroformate,81 and later using [11C]CH3I82 or [11C]CH3OTf83 for methylation of the precursor carbamate anion. [11C]CO2-fixation presented an operationally simple alternative to prepare [11C-carbonyl]GR103545 at room-temperature in high yield (13% RCY) in 23 minutes including synthesis and purification.42 To probe glycogen synthase kinase 3β (GSK-3β), a labeled urea [11C-carbonyl]AR-A014418 was prepared by [11C]CO2-fixation84 as an alternative to the original 11C-methylation procedure.85 Though AR-A014418 was found to have low brain uptake, [11C]CO2-fixation presents an opportunity for testing analogues of the same scaffold without mandating methyl ethers.</p><p>With hopes of imaging 5-HT1A receptors in the brain, the 11C-methyl isotopologue of WAY-100635 was prepared and evaluated in vivo (Fig. 4). However the major metabolic pathway, amide hydrolysis in the periphery, releases an amine (M1) that crosses the blood-brain barrier and engages in specific and nonspecific interactions. Quantitative imaging using [11C-methyl]WAY-100635 is therefore confounded by [11C]M1.86 Using a multi-step synthesis involving [11C]CO2-fixation with a Grignard reagent precursor, imaging with [11C-carbonyl]WAY-100635 leads to lower observed nonspecific uptake in the tissue of interest and superior kinetics for target quantification, as the major radiolabeled metabolite [11C]M2 is ionized and does not enter the brain (Fig. 4).87,88 In this case, the 11C-carbonyl radiopharmaceutical was made necessary by troublesome radiometabolites, and 11C-carbonyl labeling89,90 meant WAY-100635 could be rescued for clinical research imaging studies.</p><p>Numerous other drugs and pharmaceutical candidates have been radiolabeled by [11C]CO2-fixation for biodistribution and pharmacokinetic evaluation. These include a serotonin receptor antagonist, metergoline;41 the histone deacetylase (HDAC) inhibitor MS-275 (entinostat);91 and an anti-cancer therapeutic and carbamate analogue of camptothecin, irinotecan.92 In order to radiolabel irinotecan, both [11C]CO2-fixation and [11C]COCl2 were evaluated. Specific activities and time-of-synthesis were comparable, but the yield of [11C]irinotecan using [11C]CO2-fixation was nearly twice that of the 11C-phosgenation method.</p><p>Bexarotene, a synthetic retinoid X receptor (RXR) agonist, is currently in clinical trials for treatment of Alzheimer's disease, and a brain-penetrating, RXR-selective radiotracer could assist in ApoE-mediated management of brain amyloidosis.93 The 11C-carboxylic acid isotopologue has been synthesized by copper-mediated [11C]CO2-fixation and used for PET-MR imaging in non-human primate to demonstrate brain uptake.94 Further imaging studies with [11C]bexarotene are underway in our laboratories to assess specific binding and occupancy.</p><!><p>[11C]Phosgene has played a relatively modest but continuous and manifest role in the history of PET radiochemistry. First reported in the 1970s, [11C]COCl2 was proposed as a useful complement to the already existing one-carbon precursors [11C]CO2, [11C]CH3I, [11C]CH3OTf, H[11C]CHO, and H[11C]CN. While these latter carbon-11-labeled reagents were mainly used for the introduction of 11C-methyl or 11C-carboxylate groups, [11C]COCl2 allowed the insertion of a labeled carbonyl between two heteroatoms without the need for dehydration, redox operations, or transition metal catalysis. 11C-Carbonyl heterocycles are directly accessible using [11C]COCl2 and represent several key radiotracers including 11C-imidazolones (NMDA inhibitor and β-adrenoreceptor radioligands), 11C-oxazolidinones for each of MAO-A and MAO-B, and an 11C-oxazolidindione for in vivo intracellular pH sensing.95</p><!><p>Despite its advantageous reactivity, [11C]COCl2 has never become as generally available as [11C]CO2, [11C]CH3I, or, later, [11C]CH3OTf, because of its rather complicated production that requires intensive upkeep of specialized apparatus, including replacement of key components prior to each use. Still, improvements in methods for preparation of this reagent have maintained a constant presence in the PET chemistry literature throughout the years. Table 1 compiles the principle methods used up to now for producing [11C]COCl2. These methods are all two-step-based processes, starting from cyclotron-produced [11C]CO2 or [11C]CH4, the latter being also available by reduction of [11C]CO2 with hydrogen over a nickel catalyst.</p><p>The first two methods were developed in the late 1970s and rely on the intermediate preparation of [11C]CO, which was most often generated by reduction of [11C]CO2 on zinc at 400 °C. In the first case, [11C]CO was passed through a quartz tube coiled around a strong UV lamp while chlorine gas was mixed in to concentrations of 15–50%.96,97 [11C]COCl2 was produced in up to 90% radiochemical yields (decay-corrected) and easily separated from Cl2 by passing the mixture through antimony or amalgamated copper. The second method was a non-photochemical one, producing [11C]COCl2 in 30–50% RCY.98–102 For this, cryogenically concentrated [11C]CO was swept by a carrier gas through PtCl4 that was heated up to 430 °C at the last moment. Technical problems and a certain propensity to failure were often reported together with relatively low measured specific radioactivities.103,104</p><p>Beginning in the 1980s, [11C]CO was abandoned for producing [11C]COCl2 and four alternative methods were described using [11C]CCl4 as the common intermediate.105–112 Invariably, the first step consisted of mixing [11C]CH4 with a certain amount of Cl2 and passing the mixture through a heated glass or quartz tube filled with cupric chloride on pumice stone,105,106 empty109,110,112 or filled with glass beads.107 Using the latter, >90% RCY for the production [11C]CCl4 been reported,111 higher than the 60–65% with the catalyst.105 The second step consisted of on-line transformation of [11C]CCl4 into [11C]COCl2. For this, [11C]CCl4 was swept through a second heated tube normally containing iron filings105,106 or an iron oxide/iron mixture,109,110 but also an empty quartz tube at 750 °C is effective, as trace oxygen in the carrier gas or available at the hot glass or quartz surface were proven to be sufficient to produce [11C]COCl2.112 Finally, a commercially available tube originally designed for the measurement of trace amounts of CCl4 in air and containing an immobilized mixture of I2O5 and fuming H2SO4 (serving here as the oxygen source) effects the transformation at room temperature in the highest yield reported so far (80%).111 All methods use an antimony guard placed at the end of the flow system for trapping excess Cl2.</p><p>[11C]COCl2 is well soluble at trace levels in various organic solvents (CH3CN, toluene, CH2Cl2, CHCl3, Et2O), and is usually directly trapped at room temperature or below in a solution containing the labeling precursors. As it is the case for the use of other carbon-11-labeled gases (such as [11C]CO2), apparatus designed for the use of [11C]COCl2 needs to be rigorously leak-proof, and constructed with efficient handling and well-controlled flow rates. However, if properly produced, the use of [11C]COCl2 remains of interest for the reactivity and high specific radioactivity that can be achieved.</p><!><p>The reactivity of [11C]COCl2 is well-characterized as an activated 11C-carbonylating reagent. Among the earliest applications for [11C]COCl2 included treatment with aqueous ammonia to generate [11C]urea,113 which itself served as a precursor to labeled barbituric acids114 and nucleosides such as thymidine.107 Similarly, symmetric 11C-carbonates and 11C-ureas are readily prepared from [11C]COCl2,96 as well as the heterocycles hydantoins114 and imidazolones.99 Unsymmetrical acyclic carbamates or ureas present a greater challenge using [11C]COCl2 due to the highly imbalanced stoichiometry of the reactions; 11C-isocyanates are readily prepared by treatment of [11C]COCl2 with an alkyl amine, however these are highly susceptible to excess amine present to generate symmetrical products.115 This is particularly true with low molecular weight and gaseous amines, as well as amine salts which are difficult to accurately dispense at microscale levels.108 Overcoming this obstacle has been a major emphasis for researchers and led to the development of "masked" amines as precursors to 11C-isocyanates or 11C-carbamyl chlorides, which can then be used for acylation of other nucleophiles. One such precursor class is N-sulfinyl amines, which are converted to 11C-isocyanates by heating with [11C]COCl2 in anhydrous toluene (50–70% RCC, >1 Ci·μmol−1, 37 GBq·μmol−1) (Scheme 5).108 Symmetrical ureas could be used in a similar manner, albeit in lower yields, and surprisingly without diminished specific activity products.108 N,N-bis(trimethylsilyl)methylamine has been demonstrated to be an effective precursor to methyl [11C-carbonyl]isocyanate, proceeding in 55–60% RCC upon warming the cooled mixture to room temperature.115,116 Secondary amine precursors can be effectively "masked" as tertiary benzylamines, using a phosgene-promoted debenzylation protocol.117 In the presence of [11C]COCl2, 11C-carbamyl chlorides were generated, which could then be treated with amines, alkoxides, Grignard reagents or arylcuprates to produce 11C-ureas, -carbamates, or -amides, respectively.</p><p>Finally, the high reactivity of [11C]COCl2 can be tempered by using it for the formation of less reactive 11C-carbonate intermediates. To complete the synthesis of an O-aryl-11C-carbamate, [11C]MFTC, Zhang and co-workers first prepared the symmetrical diaryl 11C-carbonate, which could undergo transamidation directly into the desired labeled product by treatment with the requisite amine (Scheme 6).118 This represents a strategy for preparing 11C-carbamates from [11C]COCl2 using commonly available precursors, such as phenols and secondary amines.</p><!><p>In order to study the mechanism of action of the anticancer drug temozolomide, two isotopologues were prepared for human PET imaging studies from [11C]methylisocyanate ([11C]MIC). [11C-carbonyl]MIC was prepared from [11C]COCl2 using the "masked" amine approach and used in the synthesis of [11C-carbonyl]temozolomide (Fig. 5). In vivo, this isotopologue was converted to [11C]CO2 to a greater degree than the 11C-methyl labeled drug.116,119 These studies confirmed that the temozolomide undergoes decarboxylation in vivo to release a highly reactive methyldiazonium ion for DNA alkylation. Labeled hydantoins, such as [11C]phenytoin can be readily prepared from [11C]COCl2 by condensation with α-aminoamides.114 This straightforward synthesis is readily amenable to preparation of a wide variety of derivatives, and the biodistribution of [11C]phenytoin was evaluated in epilepsy patients.120</p><p>Befloxatone is an oxazolidinone-based selective and reversible inhibitor of monoamine oxidase A (MAO-A), and was first radiolabeled for PET using [11C]COCl2 in high yield and specific activity in a single step from the corresponding amino alcohol precursor.121,122 In preclinical imaging studies, [11C]befloxatone has been used for cardiac imaging after tobacco smoke inhalation,123 and also demonstrated highly specific uptake in the brain, reversibility and high selectivity for MAO-A over MAO-B, all properties that indicated a high chance of success for human imaging studies.124 Indeed, [11C-methyl]befloxatone is currently used in human imaging research.125 As discussed earlier, reversible oxazolidinone MAO-B radioligands [11C]SBox-13 and [11C]SL25.1188 were originally developed using [11C]COCl2,79,126,127 but improvements in the synthesis of the latter compound using [11C]CO2-fixation have enabled human translation (Fig. 3).53,80 An imidazolone ?β-adrenergic receptor antagonist (CGP-12177) was radiolabeled using [11C]COCl2 from the diamine precursor,106 and has shown utility for imaging this target in myocardium and pulmonary tissue.128 The synthesis was considered a major challenge to widespread use of this radiotracer, to the point where attempts were made to design simpler derivatives for radiolabeling.129 More recently, improvements in handling of [11C]COCl2 appear to have made this radiopharmaceutical available at some sites.110,130</p><p>Efforts to develop a selective radiotracer for NR2B-containing NMDA receptors have heavily relied on [11C]COCl2 for radiolabeling of antagonists, which typically contain a benzoxazolone or benzimidazolone pharmacophore.131–133 This approach has allowed for rapid and direct radiosynthesis of candidate ligands to be evaluated in vivo, although to date a successful radiotracer for this target has proven elusive. [11C]Phosgene continues to play a significant role in development of next-generation FAAH radiotracers. Iterative structural refinements of carbamate and urea-based 11C-ligands have produced [11C]MFTC, which shows unfavourable nonspecific uptake, and more recently [11C]DPFC, which suffers from slow brain uptake kinetics.118,134 A comprehensive survey of the [11C]COCl2 literature would identify several more applications of its use for synthesis of radiolabeled molecules, including urea, thymidine,107 and heterocyclic ligands for numerous targets. Ultimately, however, obstacles to the widespread routine use of [11C]COCl2 have curtailed its use, and instead directed efforts to more routine labeling strategies and alternative radiotracers, such as [18F]fluorothymidine ([18F]FLT).</p><!><p>[11C]Carbon monoxide has been used for carbonylation and preparation of myriad 11C-ketones, -amides, -ureas, -carboxylic acids, and -esters.135 This versatile reactivity is enabled by transition metal catalysts adept at coordination of CO and facilitating insertion and reductive elimination of C–C, C–N, and C–O bonds. The major obstacle to radiosynthesis with [11C]CO is its low solubility in organic solvents, which is exasperated by the trace amounts available. Similar to [11C]COCl2, many of the major advances in [11C]CO radiochemistry have addressed the technical challenges of making the reagent available for chemical transformations in solution.</p><!><p>Carbon monoxide is most commonly prepared in good yields with minimal processing time by passing cyclotron-produced [11C]CO2 in a stream of helium or nitrogen carrier gas through a heated quartz tube containing zinc (400 °C) or molybdenum (850 °C) (equation 1). Despite its ease of preparation, its utility in labeling reactions has only become more widespread over recent years after the development of methods to overcome the poor solubility of [11C]CO in organic solvents: repeated recirculation of carbon monoxide through the reaction solution; the use of high pressure autoclaves; and the development of carbon monoxide trap-and-release reagents.</p><p>Recirculation of [11C]CO through the reaction solvent results in a 4–10-fold increase in trapped radioactivity compared to single-pass trapping to achieve efficiencies in excess of 60%.136 A micro-autoclave system was designed with quantitative [11C]CO trapping efficiency and to facilitate radiolabeling at high pressure (35 MPa) and temperature (up to 200 °C).137 Using this approach [11C]CO was released into a small volume reactor (250 μL) containing reactants and catalyst that was pressurized with an HPLC pump and could be heated to carry out labeling reactions. A technically simpler system based on a commercially available HPLC injector has also been developed.138 Flow-through systems for aminocarbonylation have also been developed, including disposable microreactors loaded with immobilized silica-supported palladium catalysts as well as gas-liquid segmented microfluidic reactors.139,140 However, with the desire to achieve wide dissemination within the field, much subsequent activity has focused on the development of low pressure molecule-mediated CO trap-and-release agents for 11C-labeling applications.</p><p>The conversion of [11C]CO into solvent-soluble adducts was first reported using a solution of THF·BH3 leading to the 'on-line' formation of BH3·11CO (b.p. −64 °C), which could be trapped in organic solvents at ambient temperature and pressure with >95% efficiency for subsequent use in palladium-mediated reactions.141 Commercially available copper(I) tris(pyrazolyl)borate ligands (so-called 'scorpionate' ligands) were found to be effective trap-and-release agents, relying on the coordination of [11C]CO with the central copper(I) ion.142 These complexes are technically simple to produce, enable quantitative CO trapping, and are compatible with suitable catalysts and substrates for 11C-carbonylation in conventional batch reactions and in microfluidic syntheses.143 The high solubility of Xe(g) in organic solvents can be exploited to process [11C]CO with a technically simple procedure.144 Using Xe(g) to transfer pre-concentrated [11C]CO to a glass reaction vial containing a solution of an appropriate catalyst and substrates resulted in high trapping efficiency and radiochemical yields of labeled products upon heating. Pd complexes possessing high CO trapping efficiency, (e.g., Pd-xantphos) have been shown to trap [11C]CO from helium of nitrogen gas streams at ambient pressure producing 11C-carbonyl labeled products in excellent yield and without any need for high pressure infrastructure.145 Given the simplicity of accommodating these solutions into existing infrastructure for preparing and handling [11C]CO, Xe(g) as well as Pd-xantphos complexes and selenium-TBAF mixtures146 (vide infra) appear to be practical and effective solutions to the solubility problem, and are likely to see widespread future application.</p><p>Another recent advance that should enable easier access to [11C]CO in radiochemistry labs is its facile production from [11C]CO2 through [11C]silacarboxylic acid intermediates, which obviates the need for specialized equipment to achieve this reduction.147,148 [11C]CO2 is trapped in solution by lithium silane chloride complexes and [11C]CO is then rapidly released in a small volume and at practical flow rates upon addition of TBAF (Scheme 7). In comparison to metal catalyzed reduction methods, [11C]CO can be produced for 11C-aminocarbonylation with improvements in speed and efficiency of the process, without the need for specialized apparatus and infrastructure.</p><!><p>The chemistry of carbon monoxide gives access to a plethora of carbonyl compounds of biological interest. Initial carbonylation reactions using organoborane or organolithium reagents and yielding labeled aliphatic ketones,149 alcohols,150 or carboxylic amides151 demonstrated the potential for radiolabeling, but were not widely used in the preparation of PET radiopharmaceuticals due to poor trapping efficiency of [11C]CO in organic solvents, even at low temperatures. Over the last two decades, the versatility of transition metal-mediated carbonylation reactions has continued to be translated to use in 11C-radiochemistry. Though a variety of transition metals have been utilized, palladium catalysts have played a dominant role and of these, Pd(PPh3)4 has been by far the most commonly utilized catalyst for CO insertion reactions. Oxidative addition of aryl halides or their equivalents to Pd(0) is followed by CO-insertion, coordination of a suitable nucleophile to the Pd(II) centre and finally reductive elimination to release catalyst and product (Scheme 8). Of Pd(0) catalysts, Pd-xantphos was surfaced from a screening array for its superior catalytic activity at relatively lower temperatures giving excellent radiochemical yields in aminocarbonylation.152 Recently, Pd(II)-aryl precursors have been developed as isolable stoichiometric reagents for aminocarbonylation to directly prepare labeled amides rapidly and with high radiochemical purity from [11C]CO.153 In this case as well, Pd-xantphos complexes appeared to be among the most reactive precursors, though electron-deficient aryl precursors demanded Pd-P(t-Bu)3 to prevent arene scrambling with the with phosphine ligand. This approach appears to be very promising, though the need to balance each of [11C]CO trapping efficiency, Pd-aryl complex reactivity, and amine nucleophilicity, all of which are highly dependent on the precursor, suggests that significant optimization may be important for each substrate.</p><p>There is considerable potential in the use of non-palladium based catalysts, however the scope of these has only been explored to a limited extent.154 Rh(I) catalysts, for example, have been deployed to produce small collections of 11C-ureas by aminocarbonylation in the presence of aryl or sulfonyl azides, including VEGFR-2 ligands.155,156</p><p>Selenium mediated carbonylation has positioned [11C]CO as a possible replacement for [11C]COCl2 for synthesis of cyclic or acyclic 11C-ureas or carbamates from similar precursors.146 Indeed, the initial report developing this chemistry featured a labeled oxadiazolone, [11C]SBox-13, previously only prepared from [11C]COCl2. These reactions are suggested to proceed through [11C]carbonyl selenide that undergoes substitution with an amine to produce 11C-isocyanate intermediates that are susceptible to a second incoming nucleophile (Scheme 9). In order to improve the solubility of Se, tetrabutylammonium fluoride (TBAF) in DMSO was used as the reaction medium in a microautoclave. Under these conditions trapping efficiency often exceeded 90% with substrate dependent and typically good radiochemical conversions.</p><p>Alkyl radicals generated using UV light and photosensitizers have been used to perform carbonylation with [11C]CO to obtain 11C-labeled amides, esters and carboxylic acids using aliphatic iodides and nucleophiles.157–159 Detailed mechanistic studies suggest key roles for solvent in initiating radical sequences and facilitating formation of acyl iodide intermediates. Despite the apparently limited functional group tolerance, this method represents a novel and appealing approach for 11C-carbonyl labeling.</p><!><p>Despite the flexibility of its synthetic applications, the use of [11C]CO for PET radiopharmaceutical development has to date been quite limited. Very few radiotracers prepared from [11C]CO have advanced for human imaging studies, perhaps due to the low availability of this reagent worldwide and the bespoke apparatus that have typically been required for practical handling. One notable exception is [11C]zolmitriptan, an oxazolidinone 5-HT1B/1D receptor agonist prepared by Se-mediated 11C-carbonylation in an autoclave (Fig. 6).160,161 Zolmitriptan is indicated for acute treatment of migraines, and the 11C-isotopologue was used to study uptake kinetics and distribution in healthy volunteers.</p><p>A selective NPY Y5 receptor antagonist, [11C]MK-0233 is a lactone radiolabeled by palladium mediated carbonylation. This compound has been utilized for measuring drug occupancy of the target in the non-human primate brain, but does not appear to have seen further adoption in academic or clinical research. [11C]Benzyl acetate was proposed as a superior probe for glial acetate metabolism than [11C]acetate, due to its higher potential for brain uptake. Indeed, [11C]BnOAc, prepared from iodomethane, [11C]CO, and benzyl alcohol by palladium-catalyzed carbonylation, displays relatively high peak brain uptake in non-human primate and could find utility in imaging.162</p><p>A number of other labeled compounds have been prepared using [11C]CO, including [11C-carbonyl]raclopride (which shows similar imaging properties to the more common 11C-methyl isomer163), the RXR agonist [11C]Am80,164 and an H3 receptor antagonist.148 Several radiotracer development efforts have attempted to leverage the combinatorial potential of metal-catalyzed 11C-carbonylation for targets including TSPO, EGFR, VEGFR-2, VAChT, and TG2.155,165–168 It is hoped that recent advances in production and handling of [11C]CO will unlock this highly versatile reagent for greater use in novel radiotracer development efforts in the near future.</p><!><p>Carbon-11 carbonyl groups have long been prepared by substitution with [11C]HCN, followed by hydrolysis to give 11C-amides or -carboxylic acids. This strategy has most notably been applied for the radiosynthesis of 11C-carbonyl amino acids and derivatives. Recent examples include the preparation of [11C]glutamine for metabolic imaging of tumors, [11C]leucine for amino acid transport, and [11C]auxins for plant imaging. This route is also ideal for preparation of 11C-benzamide derivatives, whose applications include non-human primate imaging with tuberculosis therapeutics isoniazid and pyrazinamide and human imaging with the CNS penetrant κ-opioid receptor antagonist radiotracer [11C]LY2795050.169,170</p><!><p>The first practical method for producing carrier-free [11C]HCN was reported in 1973,171 and continues to form the basis of similar production processes in use today. [11C]CH4, produced in the cyclotron target or prepared by passing [11C]CO2 with hydrogen gas over a nickel catalyst at ca. 400 °C is converted in-line to [11C]HCN (or more accurately [11C]NH4CN) by introduction of ammonia gas and passing the gas mixture over a platinum catalyst at high temperature (ca. 900 °C) (equation 2).</p><p>Compared to other 11C labeling reagents discussed above, [11C]HCN is relatively easy to capture in a small volume of organic solvent (e.g., DMSO) at atmospheric pressure. A principal challenge is the exclusion of excess NH3 that may be incompatible with the precursor or other reaction components, but this can be partially improved upon using in-line P2O5 traps.</p><!><p>Cyanide is a highly polarized soft base that readily participates in nucleophilic substitution reactions with aliphatic halides or quaternary ammonium salts to furnish organic nitriles, which themselves can be transformed under mild conditions to amides, aldehydes, amines, or carboxylic acids.172 This versatility allows for facile functionalization and derivatization for development of 11C-carbonyl radiotracers. Among the earliest radiochemical applications of [11C]HCN was substitution of aldehyde–bisulfite adducts to prepare 11C-cyanohydrin intermediates en route to 11C-methyleneamines173 or 11C-hydroxycarboxylic acids (Scheme 10A).174 11C-Carbonyl-amino acids could be prepared by the same strategy using modified Bücherer-Strecker chemistry,175,176 (Scheme 10B) or by enzymatic methods.177–179 Multicomponent reactions using [11C]cyanide salts have proven fruitful for radiolabeling and radiotracer development, particularly in the case of hydantoins, accessed directly from [11C]cyanide salts using the Bücherer-Bergs reaction (Scheme 10C).180–182 Aziridines represent an alternative electrophile for radiolabeling with [11C]HCN. In a single report, ring-opening of aziridine-2-carboxylates was employed to prepare 11C-β-cyano-amino acids, which were transformed into [11C-carbonyl]asparagine and aspartic acid (Scheme 10D).183</p><p>Several useful labeled intermediates are available from [11C]cyanide. Conversion of [11C]HCN to [11C]urea184,185 provides a labeled precursor for heterocycles including hydantoins186 and nucleosides.187 Oxidation of K11CN with potassium permanganate produces the 11C-cyanate salt, which can be converted into hydroxyurea or isohydroxyurea (Scheme 11A).188 [11C]HCN can be converted into an electrophilic 11C-radiolabeling reagent, [11C]cyanogen bromide by treatment with bromine (Scheme 11B).189 This intermediate could be used to label a range of small molecules, including guanidines,190 and biomolecules such as polysaccharides191 and proteins.192</p><p>Cyanide coordinates extremely well with soft metals like Cu+, Pd2+, Pt2+, a property that assists metal catalyzed cyanation of aryl and vinyl halides (Scheme 12). The first report of 11C-cyanation of arenes using transition metals utilized aryl fluoride–chromium tricarbonyl complexes as precursors for nucleophilic aromatic substitution with [11C]HCN.193 These complexes are extremely air sensitive and the relatively harsh reaction conditions were tolerated by only a narrow substrate scope. Copper(I) [11C]cyanide was also developed as a radiolabeling reagent to prepare aryl [11C]nitriles from aryl halides by the Rosenmund-von Braun reaction.194 Following reports of Pd-catalyzed cyanation of aryl triflates,195 the extension of this methodology to PET radiochemistry to prepare aryl [11C]nitriles using [11C]HCN and Pd(PPh3)4 was demonstrated with a wide substrate scope including heterocycles, electronically diverse arenes, and protic functional groups using iodoarene precursors (72–99% RCY).196 Recently, a method was reported describing near instantaneous, room temperature coupling of [11C]HCN to arylpalladium precursor complexes formed in situ from aryl halides and triflates.197 A variety of arenes, heteroarenes, and drug molecules were radiolabeled using this method, which takes advantage of an optimized sterically hindered Pd(biarylphosphine) precursor complex and shows high tolerance for the presence of protic and basic additives. It may be anticipated that selective and mild direct 11C-cyanation of complex molecules will have a major impact on radiotracer synthesis and design going forward.</p><!><p>PET imaging with [11C]urea and substituted 11C-ureas were among the earliest applications of radiochemistry with [11C]HCN. Substituted ureas, including hydantoins such as the anticonvulsant [11C]phenytoin, underwent extensive preclinical evaluation to determine biodistribution and to evaluate their potential as radiotracers.180,181 It is now known that [11C]phenytoin is a weak P-glycoprotein substrate, and may have utility in reporting on the activity of this efflux pump.198</p><p>The greatest impact [11C]HCN radiolabeling has had on clinical research may be the development of numerous 11C-carbonyl-amino acids, primarily used for imaging amino acid transport in tumors.199 Both unnatural amino acids182 and natural ones have been prepared from [11C]HCN, including [11C-carbonyl]tyrosine200 and [11C-carbonyl]leucine (Fig. 7),177 both of which are useful tools for imaging l-type amino acid transporter 1 (LAT1), protein synthesis in the brain, and gliomas.201,202 l-[5-11C]Glutamine represents the endogenous parent isotopologue of a series of radiotracers designed to measure glutaminolysis through selective imaging of the amino acid transporters SNAT and ASCT2. This tracer was prepared and characterized in cells and rodent tumor models by PET, and indicated the need for a radiotracer with a longer half-life for in vivo imaging, resulting in a number of 18F-labeled analogues that have now been designed.203–205</p><p>Conversion of aryl 11C-nitriles to 11C-benzamides can be accomplished in a single step following radiolabeling and gives access to [11C]nicotinamide and similar compounds that were identified as inhibitors of and potential radiotracers for poly(ADP-ribose) synthetase.206 Unfortunately, these compounds showed low brain uptake and were not further explored. Other radiopharmaceutical development efforts have used Pd-mediated radiolabeling with [11C]HCN to install [11C-carbonyl]benzamides. The κ-opioid receptor (KOR) antagonist [11C]LY2795050 was evaluated in non-human primates to determine metabolism, distribution, target selectivity and specificity of radiotracer uptake.207,208 [11C]LY2795050 has since been translated to human KOR neuroimaging studies in normal169,170 and diseased states.209 Furthermore, this strategy and method for radiolabeling has proven useful in development of a second-generation KOR antagonist PET radiotracer with improved KOR selectivity and binding, [11C]LY2459989.210</p><p>A series of tuberculosis chemotherapeutics was radiolabeled with carbon-11, including using [11C]HCN, and studied in non-human primates.211 In addition to the rates and routes of metabolism, the rank order of brain penetration of the drugs was determined, which could in turn inform treatment of disseminated TB in the brain. [11C]Hyaluronan is a labeled polysaccharide prepared using [11C]cyanogen bromide (Scheme 11B) designed to report on hyaluronan kinetics and metabolism in different organs.191 Hyaluronan is found in high concentration in connective tissue and in joints, and is extracted from the bloodstream by the liver and kidneys. PET studies using [11C]hyaluronan were conducted in patients with liver diseases and showed significantly lower uptake kinetics than in healthy subjects.212 It is possible that this test could further be useful in identifying regional differences in liver function.</p><!><p>Radiolabeling of an organic molecule as its direct isotopologue with carbon-11 for PET imaging represents an appealing strategy for radiotracer development. Complementary to 11C-methylation, new methodologies for 11C-carbonylation using [11C]carbon dioxide, [11C]phosgene, [11C]carbon monoxide, and [11C]cyanide reagents have begun to satisfy the demand for practical and efficient PET radiolabeling of a wider variety of functional groups, including ureas, carbamates, carboxylic acids, esters, amides, and related heterocycles. Robust and convenient methods for radiolabeling these functional groups with carbon-11 have had a transformative impact on PET radiochemistry and contributed to the development of several novel 11C-carbonyl based radiopharmaceuticals for clinical research, including targets such as FAAH, LAT1, MAO-A and -B, as well as κ-opioid, D3, and 5-HT1A receptors.</p><p>Further advances and refinements in this space are needed to overcome remaining obstacles for widespread 11C-carbonyl radiopharmaceutical research. In addition to the challenges of selective and rapid isotope incorporation into small molecules, new basic chemistry and applied radiochemistry for preparation and use of these reagents suggests wider dissemination of these techniques for development of both labeling methodologies and novel 11C-carbonyl radiotracers. Indeed, novel reagents for 11C-carbonylation, 11C-cyanation, and radiolabeling of alternative functional groups may too be on the horizon, as suggested by recent forays using [11C]methyl azide,213 [11C]formaldehyde,214 and [11C]carbon disulfide.215 Continued advances to these and other methods will streamline in vivo evaluation of labeled compounds, facilitate access to compounds with greater structural diversity, and expand the library of radiopharmaceuticals for PET imaging.</p><!><p>Human neuroimaging of FAAH using [11C]CURB. Baseline (left) and with pretreatment with a FAAH inhibitor (right). Reproduced from reference 73 with permission from the Society of Nuclear Medicine and Molecular Imaging, copyright 2014.</p><p>Combinatorial [11C]CO2-fixation enabled the design of a fluorinated radiotracer for FAAH, [18F]DOPP.</p><p>Structure and human PET neuroimaging of [11C]SL25.1188 for MAO-B. Reproduced from reference 73 with permission from the Society of Nuclear Medicine and Molecular Imaging, copyright 2014.</p><p>Peripheral metabolism of the 5-HT1A receptor antagonist WAY-100635 produces a nonpolar (M1) and a polar (M2) metabolite. If the tracer is labeled at the methyl position (blue), M1 will be radioactive and confound imaging as it enters the brain and engages in specific and nonspecific interactions. If the tracer is labeled at the carbonyl position (red), the parent compound accounts for most of the PET signal in the brain, since the radioactive metabolite M2 is ionized at physiological pH and does not cross the blood-brain barrier.88</p><p>A selection of radiotracers prepared from [11C]COCl2 that have advanced for human PET imaging.</p><p>Relatively few radiotracers developed using [11C]CO have undergone translational imaging.</p><p>Several radiotracers based on biogenic compounds and synthetic drugs have been developed using 11C-cyanide. [11C]Hyaluronan labeling likely occurs at one of several hydroxyl groups and specific activity measurements suggest ~1:1 stoichiometry.</p><p>A. Radiolabeling by the 11C-methylation strategy. B. Radiolabeling by the 11C-carbonylation strategy.</p><p>Synthesis of 11C-ureas and -carbamates by [11C]CO2-fixation.</p><p>[11C]CO2-fixation for the synthesis of carboxylic acids and acid chlorides using A. Grignard reagents and B. organoboron precursors and copper mediated coupling.</p><p>A. Synthesis of [11C]CURB, a covalent, irreversible radiotracer for fatty acid amide hydrolase (FAAH). B. Structure of unsymmetrical urea [11C]PF-04457845, which inhibits FAAH by the same mechanism.</p><p>Preparation of isocyanates from [11C]COCl2 using "masked" amines.</p><p>Synthesis of [11C]MFTC by way of a symmetrical 11C-carbamate intermediate.</p><p>Preparation of [11C]CO from [11C]CO2 using lithium silane reagents.</p><p>A. General mechanism for Pd-mediated aminocarbonylation with [11C]CO. B. Commonly used Pd-complexes for 11C-aminocarbonylation, including isolated arylpalladium precursors.</p><p>Selenium-mediated preparation of 11C-isocyanates from [11C]CO</p><p>Conversion of [11C]cyanide to amino acids and hydroxyacids.</p><p>Reactions of [11C]cyanate and [11C]cyanogen bromide.</p><p>Synthesis of 11C-cyanoarenes.</p><p>[11C]COCl2: a compilation of selected practical methods for its production.</p><p>decay-corrected</p>

PubMed Author Manuscript

ShRNA-Mediated Gene Silencing of Lipoprotein Lipase Improves Insulin Sensitivity in L6 Skeletal Muscle Cells

In previous studies, we demonstrated that down-regulation of lipoprotein lipase in L6 muscle cells increased insulin-stimulated glucose uptake. In the current study, we used RNA interference technology to silence the LPL gene in L6 cells and generate a LPL-knock-down (LPL-KD) cell line. ShRNA transfected cells showed a 88% reduction in the level of LPL expression. The metabolic response to insulin was compared in wild-type (WT) and LPL-KD cells. Insulin-stimulated glycogen synthesis and glucose oxidation were respectively, 2.4-fold and 2.6-fold greater in LPL-KD cells compared to WT cells. Oxidation of oleic acid was reduced by 50% in LPL-KD cells compared to WT cells even in the absence of insulin. The contribution of LPL in regulating fuel metabolism was confirmed by adding back purified LPL to the culture media of LPL-KD cells. The presence of 10 \xc2\xb5g/mL LPL resulted in LPL-KD cells reverting back to lower glycogen synthesis and glucose oxidation and increased fatty acid oxidation. Thus, LPL depletion appeared to mimic the action of insulin. These finding suggests an inverse correlation between muscle LPL levels and insulin-stimulated fuel homeostasis.

shrna-mediated_gene_silencing_of_lipoprotein_lipase_improves_insulin_sensitivity_in_l6_skeletal_musc

INTRODUCTION<!>Cell Culture and Differentiation<!>Silencing the LPL Gene<!>RNA Isolation and RT-PCR<!>Metabolic Studies in Cell Culture<!>Glycogen Synthesis Assay<!>Glucose Oxidation Assay<!>Fatty Acid Oxidation Assay<!>RESULTS<!>DISCUSSION<!>

<p>Lipoprotein lipase (LPL) is a lipolytic enzyme, required for the hydrolysis of triglycerides to glycerol and free fatty acids (FFA) [1,2]. LPL plays a key role in regulating the entry FFA into muscle and adipose cells, both insulin-responsive tissues [2,3]. LPL synthesis is regulated by various metabolic and endocrine stimuli in a tissue-specific manner [3], consistent with the different purposes of LPL activity in different tissues. In adipose tissue, LPL's function is to facilitate the entry of lipoprotein triglycerides into adipocytes for storage. Thus, activity of adipose LPL is increased in conditions of calorie excess. In the muscle, LPL activity releases FFA, which are oxidized for energy; thus, muscle LPL is induced during activity [3</p><p>The skeletal muscle accounts for more than 75% of total insulin-stimulated glucose uptake. Accumulation of muscle fat is associated with reduced glucose utilization and insulin resistance. Since FFA contribute to insulin resistance, regulation of LPL expression and activity can effectively modulate insulin sensitivity. Muscle LPL levels appear to correlate with insulin resistance [4]. Previously, we have demonstrated that siRNA-mediated down-regulation of LPL in L6 muscle cells increases insulin-dependent glucose uptake into cells [5]. Down-regulation of muscle LPL may result in unavailability of FFA, which in turn, may force muscle cells to oxidize glucose for energy. Thus, LPL down-regulation appeared to mimic the action of insulin with regards to glucose uptake. Insulin is also known to increase glucose oxidation and glycogen synthesis, whereas it has an anti-lipolytic activity [6]. Thus the present study was to determine the effect of LPL down-regulation on glycogen synthesis, glucose oxidation and fatty acid oxidation in muscle cells. Our results demonstrate that silencing of muscle LPL improves glucose metabolism and insulin sensitivity.</p><!><p>Rat L6 skeletal muscle myoblasts were obtained from ATCC and maintained in growth media (DMEM supplemented with10% FBS (Atlanta Biologicals), 50units/mL penicillin, 50µg/mL streptomycin, 10mM HEPES, pH 7.4, and 2mM glutamine) at 37 °C and 5% CO2. Every 2–3 days the cells were 75–85% confluent and passaged at a sub-cultivation ratio of 1:10 using Trypsin-EDTA (0.05% trypsin, 0.53 mM EDTA). For experimentation, myoblasts were sub-cultured into 60x15mm petri dishes in the presence of DMEM +10% FBS. By day 2, cells were 80–90% confluent and differentiated to myotubes by reducing the FBS content of the media to 2% for 2 days and subsequently to 0% for 2–4 days till several areas of fused myotubes were evident.</p><!><p>RNA interference (RNAi) technology was used to generate a stable LPL knock-down (LPL-KD) L6 cell line. Lentivirus particles expressing rat LPL-specific short hairpin RNA (shRNA) were integrated into the host genome of L6 cells to silence the host's LPL gene. Cells were seeded into two T-25 cm2 tissue culture flasks in growth medium at a density of 1 × 105 cells/mL, and incubated overnight at 37°C and 5% CO2. The next day, when cells were approximately 50% confluent, spent media was aspirated and replaced with 4mL of a mixture of complete growth media supplemented with 5 μg/mL Polybrene. Cells were infected by adding 100μL of LPL shRNA (rat) Lentiviral Particles (Santa Cruz Biotechnology, 0.5 × 104 infectious units/μL), chilled on ice for 15 min, and transferred to a 37 °C incubator for 48 hrs. The control flask was handled identically with the omission of Lentivirus. After 48 hours, cells were washed, split from 1 to 3 flasks, and each flask was incubated in complete growth medium for 2 days. Cells stably transfected with the shLPL construct (designated as LPL-KD cells) were selected by treatment with 10 μg/mL puromycin dihydrochloride until all cells in the control flask were confirmed dead. The medium was replaced with fresh puromycin-containing medium every 2–3 days, until LPL silencing was confirmed by RT-PCR. For experiments, cells were differentiated to myotubes by culturing in serum-free medium for 4 days. Differentiation was confirmed by the presence of fused multinucleated long myotubes aligned lengthwise.</p><!><p>RNA was isolated from differentiated myotubes using TRI reagent (Sigma) and Directzol™ RNA miniprep kit (Zymo Research) according to the manufacturers' protocols. RNA was quantified by spectrophotometry at 260nm and 4μg of RNA was used to synthesize cDNA by reverse transcription using Moloney Murine Leukemia Virus Reverse Transcriptase (M-MLV RT), dNTPs, and oligodT primers (Promega).</p><p>End-point PCR was performed using cDNA and primer pairs shown (Table 1). The PCR amplicons were resolved by 2% agarose gel and the DNA bands were quantified by ImageJ (NIH) analysis. The cDNA was also subjected to real time quantitative PCR using a Smart cycler (Cepheid Inc), RealMasterMix (5PRIME), and primer pairs shown (Table 1). A melting temperature (Tm) of 85 °C or higher was obtained, confirming primer-specific amplification. β-actin was used as the house-keeping gene control for both conventional and quantitative PCR. The threshold cycle (CT) values were used to calculate fold change in transcript levels using the 2−ΔΔCT method [7] as follows: Fold change = 2 −(CT target-CT β-actin)siRNA – (CT target-CT β-actin)control</p><!><p>To investigate the effects of LPL down regulation on insulin sensitivity, metabolic assays including glucose oxidation, glycogen synthesis, and fatty-acid oxidation were performed. WT and LPL-KD L6 cells were differentiated as described above. The differentiated myotubes (already serum-starved for differentiation) were simultaneously loaded with radiolabeled substrate (see below) and treated with or without Insulin (0.004U/mL, Humulin R Lilly) for 2 hr or 20 hr prior to a metabolic assay. For 'LPL add-back' experiments, the cell culture medium was supplemented with 10 µg/mL of purified bovine LPL [8] during the incubation with insulin.</p><!><p>L6 myotubes in 12-well plates underwent 3 days of serum starvation for differentiation, following which they were incubated for 2 hr or 20 hr ( 20 hr for LPL add-back experiments) in DMEM (4.5 mM glucose) without or with insulin (0.4 U/µL) in medium containing 0.15μCi/mL of D-[U-14C]glucose. Cells were then quickly washed in icecold PBS and lysed in 0.2 ml of 1 M KOH. Cell lysates were subjected to overnight glycogen precipitation with ethanol. Precipitated glycogen was dissolved in water and transferred to scintillation vials for counting radioactivity. Disintegrations per minute (DPM) were converted to moles of glucose using the specific activity of D-[U-14C]glucose (300 Ci/mol) [9].</p><!><p>Following 3 days of serum starvation, L6 myotubes in 60 × 15 mm Petri dishes were incubated with DMEM (1mM glucose) medium containing for 0.15µCi/mL of D-[U–14C]glucose with or without Insulin (0.4 U/µL) for 2 hr or 20 hr (20 hr for LPL add-back experiments). Each Petri dish was sealed with parafilm after a piece of Whatman paper was attached to the inside of the lid. The Whatman paper was wet with 100 μL of phenylethylamine-methanol (1:1) to trap CO2 produced during the incubation period. After incubation, 200 μL of 4M H2SO4 was added to the plates, followed by further incubation for 1 h at 37°C. Finally, the Whatman paper were removed and transferred to scintillation vials for counting radioactivity [10].</p><!><p>The procedure for measuring fatty acid oxidation was similar to that for glucose oxidation [11], except that 0.15 µCi/mL of D-[1-14C] oleic acid was used instead of D-[U–14C]glucose and for all experiments incubations with radiolabel and insulin were done for 20 hr.</p><!><p>In order to study the role of LPL in metabolic functions of insulin, we used shRNA lentivirus to silence the LPL gene in rat L6 skeletal muscle cells. Figure 1 shows the complete absence of LPL mRNA in shRNA transfected L6 cells (designated as LPL-KD cells). Control cells were treated identically, but without the addition of shRNA lentivirus (WT), and showed abundant LPL message. There was no difference in the expression of mRNA for β-actin, demonstrating that the shRNA specifically targeted only the LPL message. The β-actin PCR also served as a control for RNA mass and gel loading.</p><p>The absence of LPL in LPL-KD cells was also confirmed by real-time quantitative PCR. Table 2 shows the CT values obtained for LPL and β-actin using a Cepheid SmartCycler. While the CT values for β-actin were relatively similar in WT and LPL-KD cells, the CT value for LPL was significantly higher in LPL-KD cells. Identical results were obtained after repeated experiments. The fold change was calculated using the using the 2−ΔΔC T method [7] as follows: Fold change = 2−(CT target-CT β-actin)siRNA – (CT target-CT β-actin)control This represented a 88% lower LPL message in shRNA transfected cells (LPL-KD) than in control (WT) cells.</p><p>One of the functions of insulin is to increase glucose utilization (glycolysis) and storage (glycogen synthesis) in muscle cells. We compared the insulin sensitivity of WT and LPL-KO cells by measuring the incorporation of 14C-glucose into glycogen, and its oxidation to CO2. Figure 2A demonstrates the modulation of glycogen synthesis by LPL. For this experiment, cells were grown in complete growth media supplemented with excess (4.5 mM) glucose. In the presence of excess glucose insulin should promote glycogen synthesis. When cells were incubated in the absence of insulin, there is a slight increase in glycogen synthesis in LPL-KO cells compared to WT cells. The presence of insulin marginally increases glycogen synthesis in WT cells but dramatically induces glycogen synthesis in LPL-KO cells to more than twice that in the absence of insulin. Thus, depleting LPL from skeletal muscle cells sensitizes them to insulin.</p><p>The negative relationship between LPL protein and insulin sensitivity was confirmed by 'LPL add-back' experiments. Since LPL is a secreted protein, purified LPL protein was added exogenously to culture media of muscle cells simultaneously with insulin and the radioisotope. As shown in Figure 2B, incubation of LPL-KO cells with 10 µg/mL purified bovine LPL reduced their ability to synthesize glycogen to a third of the level in the absence of LPL. Stimulation with insulin failed to enhance glycogen synthesis in these cells when LPL was present in the culture medium. As in Figure 2A, insulin stimulated glycogen synthesis in LPLKO cells in the absence of exogenous LPL. Thus, the presence of LPL brings about a resistance to insulin in these skeletal muscle cells.</p><p>To measure oxidation of glucose in muscle cells, their supply of glucose was restricted to 1 mM. This limited glycogen synthesis, instead routing the available glucose for harvesting energy via oxidation to CO2. Stimulation with insulin increases glucose oxidation, as confirmed by the results shown in Figure 3A. Insulin induced glucose oxidation in both WT and LPL-KO cells, by 64% and 84%, respectively. Interestingly, LPL silencing resulted in a 2.3 fold increase in glucose oxidation even in the absence of insulin stimulation. Thus, depletion of LPL mimicked the effect of insulin stimulation in muscle cells. Stimulation of LPL-KO cells with insulin further enhanced glucose oxidation to a level more than 4-fold higher than that in WT unstimulated cells.</p><p>The ability of LPL to suppress glucose oxidation was also demonstrated by replenishing LPL in LPL-KO cells by the addition of purified LPL to the culture media. The pattern of glucose oxidation in these cells reverted to that of WT cells. Glucose oxidation was lower in the presence of LPL and higher in the absence of LPL. Thus LPL-depletion appeared to have insulin-mimetic properties with the depletion of LPL and stimulation with insulin having synergistic effects.</p><p>Insulin has an anti-lipolytic effect. Thus insulin is expected to reduce fatty acid oxidation [6]. Depletion of LPL from muscle cells has a similar effect. As seen in Figure 4A, LPL-KO cells exhibited only 50% of the oxidation of oleic acid seen in WT cells expressing LPL. Stimulation with insulin lowered fatty acid oxidation in WT cells, but in unstimulated LPL-KO cells, the oxidation of oleic acid was already below the level of insulin-stimulated WT cells, thus insulin did not significantly lower fatty acid oxidation in LPL-KO cells.</p><p>As expected, adding back LPL to LPL-KO cells increased fatty acid oxidation both in the presence and absence of insulin. The increase in the absence of insulin was 43% whereas in the presence of insulin the increase due to LPL addition was only 15%. In this assay also, it was evident that cells depleted of LPL behave as though they have been stimulated with insulin. Thus, silencing the LPL gene 'insulin-sensitizes' the cells.</p><!><p>In previous studies, we have shown that activation of PPAR-γby Ciglitazone treatment of L6 muscle cells resulted in a down-regulation of LPL transcription and translation [5]. Thus, the thiazolidinedione-mediated improvement of muscle insulin sensitivity was shown to be mediated by LPL repression. Concomitantly, when LPL specific siRNA was used to silence LPL expression in rat skeletal muscle cells, there was a co-incident increase in glucose uptake. Thus, in this study, we investigated the wider scope of LPL's correlation to the metabolic actions of insulin. A role of LPL in regulating insulin action was demonstrated by two strategies, LPL deficiency and LPL abundance. A rat skeletal muscle cell line was made LPL-deficient by transducing a lentivirus expressing shRNA specific to the LPL gene. End-point PCR and realtime quantitative PCR demonstrated a 88% knock-down of the LPL gene in shRNA transduced (LPL-KO) cells. In another approach, the LPL-KO cells' culture media was replenished with excess purified bovine LPL. Since LPL is a secreted protein, this strategy was akin to LPL overexpression.</p><p>Our results clearly establish an inverse relationship between LPL levels and the metabolic actions on insulin. Glycogen synthesis and glucose oxidation in unstimulated LPL-KO cells was equal to or greater than the level in insulin-stimulated wild-type cells. LPL-KO cells stimulated with insulin showed even greater metabolic activity. On the contrary, silencing of the LPL gene reduces the oxidation of oleic acid mimicking the anti-lipolytic activity of insulin. Adding back LPL to the culture medium of LPL-KO cells reverses the metabolic patterns by reducing glycogen synthesis and glucose oxidation, but increasing fatty acid oxidation.</p><p>Our results are consistent with prior reports of studies in experimental animals [12–14]. Two studies with muscle-specific over-expression of LPL in transgenic mice showed impaired glucose tolerance and an increase in plasma glucose levels [12,13]. Kim et al also showed a decrease in insulin-stimulated glucose uptake, glycolysis, and glycogen synthesis in the skeletal muscle of these mice [12]. In a reverse study, Eckel's group generated mice with skeletal muscle-specific LPL knockout (SMLPL−/−) [14], and consistent with our data, these mice showed increased insulin sensitivity. While the studies in whole animals are informative, crosstalk between different tissues hinder a clear understanding of the molecular events at the cellular level. Thus, our data obtained in cultured cells are significant, unambiguous evidence of the effect of skeletal muscle LPL on muscle metabolic activity.</p><p>There is a direct correlation between the level of free fatty acids (FFA) stored in the muscle and muscle insulin resistance [6]. LPL functions to make FFA available to the muscle cell for energy, and muscle-specific LPL over-expression correlated with accumulation of triglycerides in the skeletal muscle of transgenic mice [12]. Conversely, skeletal muscle-specific deletion of LPL resulted in a reduction in muscle triglyceride content [14]. In our study, LPLKO muscle cells may improve their insulin sensitivity due to a repression of cellular FFA uptake. A depletion of available FFA in LPL-KO cells may force the uptake, oxidation and storage of glucose. The scarcity of fatty acids may also explain the decrease in fatty acid oxidation seen in the LPL-KO cells, consistent with insulin's antilipolytic activity.</p><p>LPL is not a traditional signaling molecule, however, ours and previous studies establish that modulation of LPL levels in skeletal muscle cells or tissue triggers events that affect the insulin signaling pathway. LPL overexpression in the skeletal muscle of transgenic mice correlated with a significant decrease in insulin-stimulated activation of insulin receptor substrate-1 (IRS-1) associated phosphatidylinositol 3-kinase activity (PI 3 Kinase). PI 3 Kinase is a key intermediate of the insulin signaling pathway, responsible for the metabolic functions of insulin in the muscle [12, 15]. Mice with muscle-specific deletion of LPL showed an increase in insulin-stimulated phosphorylation of Akt, a down-stream effector of PI 3 kinase; however the phosphorylation was independent of PI 3 Kinase activity, suggesting the involvement of another pathway [14]. Thus, in our studies, the down –regulation of LPL may trigger signaling events that may lead to metabolic perturbations described here. In future studies, it will be important to map the specific signaling pathway that connects the lack of skeletal muscle LPL to an 'insulinstimulated' metabolic state.</p><!><p>This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.</p>

PubMed Author Manuscript

CUL5-ARIH2 E3-E3 ubiquitin ligase structure reveals cullin-specific NEDD8 activation

An emerging mechanism of ubiquitylation involves partnering of two distinct E3 ligases. In the best-characterized E3-E3 pathways, ARIH-family RBR E3s ligate ubiquitin to substrates of neddylated cullin-RING E3s. The E3 ARIH2 has been implicated in ubiquitylation of substrates of neddylated CUL5-RBX2-based E3s, including APOBEC3-family substrates of the host E3 hijacked by HIV-1 Vif. However, the structural mechanisms remained elusive. Here, structural and biochemical analyses reveal distinctive ARIH2 autoinhibition, and activation upon assembly with neddylated CUL5-RBX2. Comparison to structures of E3-E3 assemblies comprising ARIH1 and neddylated CUL1-RBX1-based E3s shows cullin-specific regulation by NEDD8. Whereas CUL1-linked NEDD8 directly recruits ARIH1, CUL5-linked NEDD8 does not bind ARIH2. Instead, the data reveal an allosteric mechanism. NEDD8 uniquely contacts covalently-linked CUL5, and elicits structural rearrangements that unveil cryptic ARIH2-binding sites. The data reveal how a ubiquitin-like protein induces protein-protein interactions indirectly, through allostery. Allosteric specificity of ubiquitin-like protein modifications may offer opportunities for therapeutic targeting.

cul5-arih2_e3-e3_ubiquitin_ligase_structure_reveals_cullin-specific_nedd8_activation

Introduction<!>Crystal structure of autoinhibited ARIH2<!>Overall E3-E3 assembly between ARIH2 and neddylated CRL5s<!>NEDD8-dependent allosteric remodeling of CUL5-RBX2<!>ARIH2-CUL5-RBX2 E3-E3act superdomain<!>Remodeled CUL5 groove cradles ARIH2 N-terminus<!>CRL5 neddylation removes barriers blocking ARIH2<!>General and specific neddylated CRL-ARIH E3-E3 features<!>Discussion<!>Cloning, protein expression and purification<!>Peptide<!>In vitro ubiquitylation assays<!>In vitro neddylation assay<!>Crystallization of autoinhibited ARIH2<!>Crystallographic data collection and structure determination<!>Sample preparation<!>Data collection<!>Data processing<!>Model building and refinement<!>Analysis of published hydrogen-deuterium exchange-mass spectrometry data based on structures of autoinhibited ARIH2 and the ARIH2* complex with neddylated CUL5-RBX2<!>ARIH2 and neddylated CRL5 E3-E3 assembly and activity<!>Interactions of ARIH2 and ARIH2*<!>Cryo-EM image processing flowchart for neddylated CRL5Vif-CBF\xce\xb2-ARIH2*-A3C complex<!>Cryo-EM image processing flowchart for neddylated CRL5Vif-CBF\xce\xb2-ARIH2*-A3G complex<!>Cryo-EM model building<!>Comparison of NEDD8 interactions with CUL5 in cryo-EM structure of neddylated CUL5-RBX2-ARIH2* and crystal of neddylated CUL5-RBX1<!>Interactions between ARIH2 N-terminal region and remodeled CUL5 groove<!>Neddylated CUL5-RBX2-ARIH2 and neddylated CUL1-RBX1-ARIH1 specificity

<p>Ubiquitin (UB) and ubiquitin-like proteins (UBLs) are eukaryotic post-translational modifiers that determine the functions and fates of many proteins. Key facets of this regulation are: (1) E3 ligase-mediated linkage of the C-terminus of UB or UBL to a target protein; and (2) recognition of the modified protein by a specific UB- or UBL-binding partner1,2.</p><p>The UBL NEDD8 is nearly 60% identical to UB, but has distinct targets and functions3. The best-characterized regulation by NEDD8 involves its linkage to a conserved lysine in cullin proteins4. Cullins (CULs) partner with RBX RING-type proteins to form core scaffolds within multiprotein cullin-RING E3 UB ligases (CRLs). In mammalian cells, CUL1, CUL2, CUL3, and CUL4 form dedicated core complexes with RBX1, while CUL5 partners with RBX25–11. Cullin and RBX proteins interact via an intermolecular β-sheet involving the cullin α/β-domain and RBX N-terminal region5. These elements are thought to fold upon binding to each other5. We refer to the intermolecular domain as "C/R" due to its containing elements from both the cullin and the RBX protein. C/R domains are sufficiently homologous across the cullin and RBX families to allow recombinant generation of alternative combinations, for example CUL5-RBX1 and CUL1-RBX2. Such alternative CUL-RBX pairings have proven useful for mechanistic studies7,12, although it is unclear if they normally exist and function in vivo.</p><p>CRLs assemble and perform ubiquitylation when opposite ends of a CUL-RBX core scaffold associate with interchangeable substrate-bound receptors and catalytic UB-carrying enzymes4,13. Suites of substrate-binding receptors - often in complex with adaptor proteins - associate with cognate cullin N-terminal domains4. For example, ≈70 human F-box proteins have an F-box motif, which binds the adaptor protein SKP1, which in turn binds CUL1's N-terminal domain. Most F-box proteins also have distinct protein-protein interaction domains that recruit substrates to the CUL1-RBX1 core. Meanwhile, ≈40 substrate-binding BC-box proteins bind the Elongin B-Elongin C (ELOBC) complex, which is an adaptor for CUL5-RBX2. Individual CRLs are named based on cullin identity, with substrate receptor denoted in superscript. For example, CRL5ASB9 refers to a CUL5-RBX2 complex with the ELOBC adaptor and the BC-box substrate receptor ASB914,15.</p><p>Opposite to the substrate receptor-binding end of a CRL, the C-terminal domains of the cullin and RBX proteins mediate ubiquitylation. The cullin's C-terminus consists of a rod-like H29-helix that continues into the WHB domain containing the neddylation site3,5. The C-terminus of the RBX protein is the hallmark E3 ligase RING domain, which in the context of a neddylated CRL can bind various UB-carrying enzymes - E2s in the UBE2D, UBE2G, and UBE2R families, and ARIH-family RBR E3s - from which UB is transferred to a receptor-bound substrate9,13,16,17. Structures of RING E3-E2~UB conjugates ("~" here refers to thioester bond between UB's C-terminus and an enzyme catalytic cysteine) were defined nearly a decade ago18–20. Moreover, a recent cryo-EM structure showed how the RBX1 RING-bound UBE2D~UB active site is juxtaposed with substrates of neddylated CRL1β-TRCP 17. However, mechanisms underlying assembly between neddylated CRL E3s and ARIH-family RBR E3s are only beginning to emerge9,16,21–23.</p><p>ARIH-family E3s – like many RBR ligases – are autoinhibited on their own24–28. ARIH-family E3s are allosterically activated upon assembly with a neddylated CRL into an E3-E3 ligase9,16,21,23. These E3-E3 ligases promote a UB transfer cascade: UB is transferred from the E2 enzyme UBE2L3 to the catalytic cysteine of the neddylated CRL E3-bound ARIH E3, and then from the ARIH E3 to the CRL E3-bound substrate9,16.</p><p>E3-E3 ligase formation requires cullin neddylation, and is remarkably specific: RBX1-containing neddylated CRLs partner with ARIH1, whereas neddylated CRL5s partner with ARIH29,16,21,23. Cryo-EM structures have shown how neddylated CRL1s employ ARIH1 to ubiquitylate F-box protein-bound substrates23. However, several distinctive features suggested unique NEDD8 regulation of the CRL5 assembly with ARIH2. In cells, CUL5 is not neddylated by the enzymes that typically modify CULs1-47. Instead, CUL5 neddylation requires RBX2 and the metazoan-specific NEDD8 E2 UBE2F7. The importance of CUL5-RBX2-specific regulation is underscored by its pathological hijacking by HIV-1. HIV-1 replication depends on redirecting cellular ubiquitylation pathways to degrade host restriction factors29. HIV-1 virion infectivity factor (Vif) conscripts the host protein CBFβ to form a heterodimeric BC-box receptor, which assembles into a CRL5Vif-CBFβ E3 that ubiquitylates APOBEC3-family restriction factors30–32. Vif-mediated APOPEC3 degradation - and HIV-1 infectivity - require neddylation, UBE2F, CUL5, RBX2 and ARIH28,9. Similarly, the human CRL5ASB9 E3 employs ARIH2 and not ARIH1 to ubiquitylate its substrate creatine kinase B (CKB)9,22,33. From a structural perspective, the interactions between NEDD8 and CUL1's WHB domain observed in recent cryo-EM structures differ from those between NEDD8 and a CUL5 fragment in a prior crystal structure12,17,23. Moreover, hydrogen-deuterium exchange data for a neddylated CRL5-ARIH2 complex are incompatible with the structurally-characterized assemblies between neddylated CRL1s and ARIH123,33. Thus, we performed structural and biochemical studies to gain insights into the distinctive assembly between ARIH2 and neddylated CRL5s.</p><!><p>To understand how ARIH2 is regulated, we determined the 2.45 Å resolution crystal structure of a near full-length, autoinhibited version that lacks the N-terminal region predicted to be disordered21 (Fig. 1a-b, Supplementary Table 1). The two ARIH2 molecules in the asymmetric unit superimpose with 0.6 Å RMSD, hence only one is described. The canonical RBR E3 catalytic elements (RING1, RTI-helix, IBR, and Rcat domains) are interspersed with the ARIH-specific UBA-like (UBAL) and Ariadne domains in a two-part arrangement. One part is a platform containing the canonical RBR E2~UB binding surfaces (Fig. 1b). Studies representing other, active RBR E3s revealed that RING1 binds the E2, while UB is cradled in an adjacent bowl-shaped surface formed by RING1, RTI-helix, and IBR domains23,34,35. To show roles of these elements from ARIH2, a model was generated by overlaying the structure of an ARIH1-UBE2L3~UB complex (Fig. 1b)23. The arrangement of the RING1, RTI-helix, and IBR domains in autoinhibited ARIH2 resembles that in activated ARIH1 bound to UBE2L3~UB. ARIH2's UBAL domain stabilizes the E2~UB-binding platform on the opposite side, by intercalating between the RING1 and IBR domains, and packing against the RTI-helix.</p><p>The second part of the ARIH2 structure shows autoinhibition: the Ariadne domain binds the active site in the catalytic Rcat domain (Fig. 1b). The Ariadne domain is an elongated 4-helix bundle. A groove between the first and third helices of the Ariadne domain secures the catalytic cysteine loop from the Rcat domain. In particular, Ariadne domain residues Leu381, Glu382, and Glu455 respectively contact the beginning, middle and end of the Rcat domain catalytic cysteine loop. A triple Leu381Ala, Glu382Ala, Glu455Ala mutant, which we term ARIH2*, was relieved of autoinhibition as monitored by autoubiquitylation. ARIH2* maintained ability to ubiquitylate substrates of CRL5ASB9 and CRL5Vif-CBFβ (Extended Data Fig. 1). Importantly, ARIH2*-mediated ubiquitylation of a CRL5 substrate required CUL5-RBX2 (Extended Data Fig. 1e-f).</p><!><p>We sought cryo-EM data to visualize how neddylated CRL5s bind and activate ARIH2. However, complexes with wild-type ARIH2 were too heterogeneous to yield high-quality three-dimensional reconstructions. Assuming that ARIH2 adopts an activated conformation when bound to a neddylated CRL5, we hypothesized that mutationally relieving autoinhibition might improve complex formation. Indeed, the ARIH2* mutant showed enhanced copurification with substrate-bound neddylated CRL5Vif-CBFβ (Extended Data Fig. 2a).</p><p>We obtained cryo-EM maps for two ARIH2* complexes with neddylated CRL5Vif-CBFβ, one with the substrate APOBEC3C and the other with APOBEC3G (hereafter A3C and A3G, respectively) (Extended Data Figures 2-4, Supplementary Table 2). Because both complexes showed similar properties, only the higher resolution reconstructions with A3C are described. A 7.5 Å resolution low-pass filtered map allowed fitting with published atomic coordinates of A3C, Vif-CBFβ-ELOBC bound to CUL5's N-terminal domain, other domains of CUL5, NEDD8, and nearly all the ARIH2 crystal structure12,22,36–39 (Fig. 1c-d, Extended Data Fig. 5). However, lack of density unambiguously attributable to ARIH2*'s Rcat suggests that this domain is relatively mobile compared to the rest of the E3-E3 complex (Extended Data Fig. 2c).</p><p>The neddylated CRL5–ARIH2* E3-E3 assembly confirms several prior predictions5,9,16,23,33. First, the A3C (or A3G) substrate and ARIH2* are bound at opposite ends of the elongated neddylated CUL5-RBX2 and directed toward each other, presumably to promote catalytic encounter (Fig. 1d). Second, ARIH2*'s UBAL, RING1, RTI helix and IBR elements are configured as in the crystal structure of autoinhibited ARIH2, and superimpose with the corresponding E2~UB-binding platform of ARIH1 bound to a neddylated CRL123 (Extended Data Fig. 2c-d). Mutation of V141 in ARIH2's RING1 domain, paralogous to a key ARIH1 RING1 domain residue recruiting E2~UB, impaired ubiquitylation of a neddylated CRL5 substrate, confirming common ARIH-family RBR E3 enzymatic mechanisms (Extended Data Fig. 2e-f).</p><!><p>Focused refinement40 yielded a 3.4 Å resolution map allowing generation of atomic coordinates showing interactions between neddylated CUL5-RBX2 and ARIH2* (Fig. 2a, Extended Data Fig. 2b, Extended Data Figures 3-5). Unexpectedly, CUL5-linked NEDD8 does not approach ARIH2*. Their closest residues are separated by more than 30 Å (Fig. 2a). NEDD8's concave β-sheet embraces two domains from CUL5, resulting in a striking ≈110° rotation of CUL5's rod-like H29-helix and repositioning of the WHB domain compared to its position in unneddylated CUL512,22 (Fig. 2b-d).</p><p>NEDD8's Ile44-centered hydrophobic patch makes extensive noncovalent interactions with CUL5's WHB domain (Fig. 2c, Extended Data Fig. 6a). NEDD8's Ile44 and Val70 interact with Leu710 and Leu713 from the WHB domain portion of CUL5's H29-helix. To one side, NEDD8's Leu8 is inserted into a hydrophobic pocket between CUL5's H29- and H30-helices. On the other side, NEDD8's Leu73 and Arg74 intercalate between CUL5's Ile720, Trp759, Tyr765, Tyr778, CUL5's C terminus, and the isopeptide bond linking NEDD8 to CUL5's Lys724. Additionally, CUL5's Glu717 coordinates a network of electrostatic interactions with NEDD8 (Extended Data Fig. 6a). Notably, this NEDD8-CUL5 interface was already observed in the crystal of a neddylated CUL5 C-terminal region bound to RBX1 (reported prior to discovery of neddylation enzymes for CUL5-RBX2)12 (Extended Data Fig. 6b-c).</p><p>NEDD8 also binds the edge of CUL5 in the intermolecular C/R domain. NEDD8's Lys6 and His68 form a 3-way interface with Leu710 from CUL5's H29-helix and a stripe of Glu617, Leu621, and Glu624 side-chains from CUL5 in the C/R domain (Fig. 2d). Retrospective analysis revealed the same 3-way interactions in the prior crystal of neddylated CUL5's C-terminal region, albeit with a twist: in the crystal, rather than occurring within a single complex, these interactions mediate packing between the C/R domain from one molecule of CUL5 and NEDD8 and its linked WHB domain from an adjacent complex in the lattice12 (Extended Data Fig. 6b-c). Mutation of the key NEDD8 binding surfaces on CUL5's WHB and C/R domain impaired ARIH2-mediated ubiquitylation of neddylated CRL5 substrates (Fig. 2e).</p><!><p>Two surfaces from ARIH2* bind neddylated CUL5-RBX2. One interaction involves ARIH2*'s Ariadne domain binding CUL5 and RBX2 in an E3-E3act superdomain (Fig. 3a). The homologous E3-E3act superdomain formed by ARIH1 and neddylated CUL1-RBX1 was named for its amalgamation of the two distinct types of E3 and activating ubiquitylation23. Here, the loop between the first and second helices of ARIH2*'s Ariadne domain docks in a cleft from CUL5's CR3 and 4HB domains. The third and fourth helices, on other side of ARIH2*'s Ariadne domain, bind RBX2's RING domain and the junction with CUL5. Mutating ARIH2 Ariadne domain residues binding CUL5 and RBX2 impairs substrate ubiquitylation, confirming the importance of the E3-E3act superdomain (Fig. 3a, Extended Data Fig. 7a).</p><p>Both E3s undergo conformational changes to form the E3-E3act superdomain (Supplementary Video 1). Relative to its orientation in an unnedddylated CRL522, RBX2's RING undergoes a ≈100° rotation to bind the ARIH2* Ariadne domain (Fig. 3b). Also, comparing the Ariadne domain conformations in autoinhibited ARIH2 and ARIH2* bound to CUL5 shows reorientation of the helices (Fig. 3c). In particular, the first Ariadne domain helix, which we term "switch-helix", displays a central ≈15° kink when bound to CUL5. ARIH2 residues 380 and 381 (alanines in ARIH2*) at the center of the kink along with nearby side-chains are rotated outward. The switch-helix kink precludes autoinhibitory interactions with the Rcat domain's catalytic Cys (Fig. 3c). Thus, it seems that when ARIH2 is bound to neddylated CUL5-RBX2, kinking of the switch-helix would relieve autoinhibition. This rationalizes the prior finding that neddylated CUL5-RBX2 stimulates reactivity of ARIH2's catalytic Cys with the electrophilic UB probe, UB-VME21.</p><!><p>The second crucial portion of ARIH2 is its N-terminal region, which is not present in the crystal structure. In complex with a neddylated CRL5, ARIH2*'s N-terminus mediates interactions extending more than 50 Å across the structurally-remodeled CUL5 (Fig. 3d).</p><p>The central portion of ARIH2*'s N-terminal region (residues 35-46) forms a kinked amphipathic helix that docks in a CUL5 groove. One side of the groove is formed by CUL5's 4HB domain. The other side involves CUL5 elements from the C/R domain and the loop preceding its H29-helix, which we term "gate/groove-loop" (Fig. 3d). In an unneddylated CRL5 complex, the gate/groove-loop (CUL5 residues 691-695) restricts access to CUL5's 4HB. However, in neddylated CUL5 the H29-helix rotation is accompanied by gate/groove-loop remodeling, which generates the ARIH2-binding groove.</p><p>Ile35, Tyr38, Tyr39, Val42 and Val46 from ARIH2* form a stripe of hydrophobic knobs that fit into hydrophobic pockets between CUL5 4HB domain helices (Fig. 3e-f, Extended Data Fig. 7b-c). A pair of neddylated CUL5 arginines - Arg460 from the 4HB and Arg691 from the gate/groove-loop – seal ARIH2*'s Tyr39 in the groove. CUL5's Arg691 additionally interacts with the backbone carbonyl from ARIH2*'s Gly41 at the kink and Asp45 at the C terminus of the helix (Fig. 3f).</p><p>Density was poorly visible for the elements connected to ARIH2*'s N-terminal region. Residues 50-55 comprise a linker to the canonical RBR elements (Fig. 3d). At the opposite, extreme N-terminal end, additional density was visible only at low contour, in a basic groove from CUL5 (Extended Data Fig. 7b).</p><p>To interrogate roles of ARIH2's N-terminal region, we performed alanine scanning mutagenesis. Substituting residues individually, or three or four at a time, confirmed key roles of the region containing ARIH2's Tyr38 and Tyr39, and intermediate effects at the junction to the acidic stretch (Fig. 3g, Extended Data Fig. 7d). We also tested effects of deletions (Extended Data Fig. 7e). The most destructive effects arose from removing portions of ARIH2's N-terminal region - either residues 35-39 or 40-44 - that dock in the remodeled CUL5 groove. Deleting the N-terminal 20 residues, which were not observed by cryo-EM, did not overtly impair ubiquitylation. However, deletions within an ARIH2 acidic stretch (residues 25-29 or 30-34) impaired ubiquitylation of neddylated CRL5 substrates. We speculate that the ARIH2 acidic residues could contact basic residues at the entrance to the CUL5 groove. Notably, Ala substitution for either CUL5 Arg460 or Arg691, or for the four basic residues lining the exit of the CUL5 groove (Lys418, Lys423, Lys676, and Lys685) substantially impair ARIH2-mediated ubiquitylation of CRL5Vif-CBFβ substrates (Fig. 3h). None of the mutations impaired CUL5 neddylation, suggesting they did not affect protein folding (Extended Data Fig. 7f).</p><!><p>Although CUL5-linked NEDD8 does not directly bind ARIH2*, neddylation structurally activates the E3-E3 assembly in several ways. Gate/groove loop remodeling not only provides a binding site for ARIH2's N-terminal region, but also eliminates blockage of the groove (Fig. 4a). Also, when unneddylated, the WHB domain packs against CUL5's 4HB and RBX2's RING domains so as to block access of ARIH2's Ariadne domain (Fig. 4b). This unneddylated arrangement is also incompatible with noncovalent interactions between CUL5's WHB domain and NEDD8 (Fig. 4c)12,22. Considering that the neddylation reaction requires yet another distinct relative arrangement of RBX RING and cullin WHB domains41, we speculate that after NEDD8 linkage to CUL5, formation of the structurally-observed noncovalent interactions hinders these domains from adopting the orientations in unneddylated CRL5.</p><p>The structurally-observed conformational changes explain previously reported hydrogen-deuterium exchange (HDX) properties of an unneddylated and neddylated CRL5, ARIH2, and the neddylated CRL5-ARIH2 complex33. Deuterium incorporation was measured by mass spectrometry (MS) of peptides generated after HDX was quenched33. Peptides corresponding to several regions of neddylated CRL5 and ARIH2 most strikingly remodeled in the cryo-EM structure, for example NEDD8 and the regions of CUL5 it binds, were not detected by MS33. Nonetheless, the detectable regions that showed greatest HDX differences upon complex formation correlate with the conformational changes indicated by the cryo-EM structure (Supplementary Video 1). In particular, the HDX differences33 between unneddylated and neddylated CRL5 primarily map to CUL5 4HB and C/R domain regions exposed by the structurally-observed relocation of neddylated CUL5's WHB domain. Comparing HDX properties of ARIH2 alone versus bound to a neddylated CRL5 showed greatest differences in the Ariadne domain33. The regions showing increased HDX correspond to the switch- and subsequent Ariadne domain-helices that become exposed in the structural transition between autoinhibited ARIH2 and neddylated CRL5Vif-CBFβ-bound ARIH2*. Meanwhile, Ariadne domain regions that were protected from HDX in the complex33 correspond to ARIH2* elements that bind CUL5-RBX2. Likewise, the CUL5 regions whose HDX properties differ in the complex with ARIH233 correspond to those bound to ARIH2* in the cryo-EM structure.</p><p>The ultimate test of NEDD8's allosteric role would be to mutationally elicit such activation. Thus, we wondered if removing CUL5's WHB domain and/or the H29 helix, would be sufficient to activate ARIH2 ubiquitylation of a CRL5 substrate. Such deletion mutants would in principle remove the barrier blocking ARIH2's Ariadne domain, although they would preclude interactions that stabilize the remodeled the gate/groove loop. The deletions did increase ARIH2-mediated ubiquitylation of CKB compared to unneddylated CRL5ASB9, although not to the level observed with neddylation (Fig. 4d-e). We thus inspected the structures of unneddylated12 and neddylated CUL5 to identify residues potentially anchoring the inactive conformation, but whose mutation would not hinder relocation of the H29-helix. In unneddylated CUL5, four CUL5 H29-helix glutamates (Glu701, Glu702, Glu703, Glu705) either directly contact the C/R domain, or establish H29 helix-C/R domain electrostatic networks (Fig. 4f). A flanking glutamate (Glu697) also may contribute to the inactive conformation. All five of these H29-helix glutamates are solvent-exposed - their side-chains not visible in the maps – in neddylated CRL5 bound to ARIH2*. Thus, we hypothesized that charge-swap mutants could expunge unneddylated CUL5's H29-helix and WHB domain, while allowing the active conformation. Indeed, an "E-to-K" mutant version of unneddylated CRL5ASB9 with these CUL5 H29-helix glutamates replaced with lysines enabled ARIH2-dependent CKB ubiquitylation at a level similar to that achieved with neddylated CRL5ASB9 in our assay (Fig. 4e).</p><!><p>We confirmed and extended prior findings that CRL-ARIH pairing is strikingly specific. Neither ARIH1 nor ARIH2 was active with a noncognate neddylated CRL9,16,21, nor with alternative versions harboring mismatched CUL1-RBX2 or CUL5-RBX1 core scaffolds (Extended Data Fig. 8a-b).</p><p>To gain further insights into similarities and differences between E3-E3 ligases, we compared structures of ARIH2 and ARIH1, and their complexes with a neddylated CRL5 or CRL1, respectively (Fig. 5a-b). The comparison showed similar roles of the ARIH2 and ARIH1 Ariadne domains. The Ariadne-Rcat domain arrangements superimpose in autoinhibited ARIH2 and ARIH1 (0.8 Å RMSD, Extended Data Fig. 8c), and the E3-E3act domains also superimpose for both families (1.1 Å RMSD, Fig. 5c). Notably, the Ariadne domain switch-helix kink observed for ARIH2* is shared by both WT ARIH1 and the corresponding ARIH1* mutant when bound to the cognate neddylated CRL23.</p><p>However, the two E3-E3 pathways show substantial differences in interactions directly impacted by neddylation. In autoinhibited ARIH2, the RING1, RTI-helix, and IBR domains are arranged much like in activated, E2~UB-bound ARIH1 and other RBR E3s35,42–45 (Extended Data Fig. 8d-j). However, these E2~UB binding platform elements are misaligned in autoinhibited ARIH123,25,46,47. These elements are also misaligned in autoinhibited PARKIN26–28.</p><p>Activation of ARIH1 depends on Val123 and Phe150 in its UBAL domain binding the Ile44-centered hydrophobic patch in CUL1-linked NEDD816,21,23. However, despite sharing a common fold, the sequence of ARIH2's UBAL domain is strikingly divergent. Notably, Lys110 corresponding to ARIH1's Phe150 is incompatible with hydrophobic interactions (Fig. 5d, Extended Data Fig. 8k-l). Accordingly, ARIH2's UBAL domain does not bind NEDD8. Mutation of ARIH2 Val83 and Lys110 - corresponding to ARIH1's Val123 and Phe150 - did not impact ubiquitylation of neddylated CRL5 substrates (Fig. 5e).</p><p>NEDD8 also makes distinct noncovalent interactions with covalently-linked CUL5 and CUL1. NEDD8 allosterically activates a CRL5 through its Ile44-centered hydrophobic patch simultaneously packing against CUL5's H29-helix and C/R domain (Fig. 2, 5f). However, CUL1's H29-helix binds a different, Ile36-centered NEDD8 hydrophobic patch17,23 (Fig. 5g). The exposed Ile44-centered hydrophobic patch of CUL1-linked NEDD8 binds UB-carrying enzymes including ARIH117,23 (Fig. 5b). The different interactions with NEDD8 are rationalized by the cullin sequences (Extended Data Fig. 8m-n). CUL5's Leu710 and Glu717 that bind NEDD8's Ile44 patch would clash with NEDD8's Ile36 patch. Meanwhile, the corresponding CUL1 residues Asp and Ala, respectively, are conserved across CULs1-4 and incompatible with NEDD8's Ile44 patch, explaining the deleterious effects of their swapping into CUL5 (Fig. 2e).</p><!><p>Structures of ARIH2 alone and bound to neddylated CRL5Vif-CBFβ reveals the HIV-1 hijacked E3-E3 ligase assembly that overcomes host restriction and defines mechanisms by which NEDD8-linked CUL5-RBX2 activates ARIH2. Due to high sequence and functional homology, we anticipated that neddylated CRL5-ARIH2 and neddylated CRL1-ARIH1 would form superimposable but sequence-specific E3-E3 assemblies. Indeed, for both, CRL5s and CRL1s, the neddylated conformations remove barriers that mask ARIH E3-binding sites in their unneddylated counterparts. Moreover, for both ARIH2 and ARIH1, the Ariadne domains mediate homologous autoinhibitory interactions with the Rcat domains, and homologous interactions with their cognate CUL-RBX partners.</p><p>Unexpectedly, however, comparing structures of the homologous E3s – ARIH2 versus ARIH1, and a neddylated CRL5 versus CRL1 – individually or in E3-E3 complexes also revealed striking differences, most notably, cullin-specific regulation by NEDD8 (Fig. 6). Different surfaces of NEDD8 interact with covalently-linked CUL5 or CUL1 (Fig. 5f-g). CUL1-linked NEDD8 binds directly to ARIH1's UBAL domain and elicits its rearrangement in the activated conformation of the E2~UB binding platform, a configuration already largely observed in autoinhibited ARIH2 (Fig. 1b, 5a-b). Instead, it is the restructured conformation of the neddylated CRL5, rather than NEDD8 itself, that is recognized by ARIH2. NEDD8 allosterically generates ARIH2-binding surfaces not present in an unmodified CRL5 (Fig. 6).</p><p>Why might NEDD8 uniquely modulate the structure of CUL5-RBX2 and its interactions with ARIH2? Although answering this will require future studies, we speculate that additional regulation co-evolved with emergence of CUL5-RBX2 in metazoan lineages. For example, CUL5-RBX2 and/or ARIH2-specific metazoan-specific post-translational modifications or binding partners awaiting discovery may require a distinctive assembly from that formed by ARIH1 and neddylated CRL1s.</p><p>The indirect, allosteric mechanism by which NEDD8 stimulates binding to ARIH2 differs from most characterized interactions between UB and UBLs and their downstream recognition machineries. UB-, SUMO- and LC3-interacting motifs in different proteins often form structurally-superimposable complexes with their UB or UBL partners1,2. Moreover, to our knowledge, UBL (or UB)-driven protein-protein interactions mediated by conformational changes - without direct binding to the UB or UBL itself - have not been structurally defined before. However, SUMO and UB have been shown to induce conformational changes that inhibit interactions of their targets. For example, a SUMO-interacting motif in thymine DNA glycosylase (TDG) interacts with a linked SUMO to stabilize a conformation incompatible with DNA-binding48. Also, UB-binding domains the yeast transcription factor Met4 engage a K48-linked polyUB chain modification so as to counteract interactions required to activate transcriptional targets49. Such unique allosteric switches, as revealed by our structural analyses, may provide opportunities for therapeutic targeting specificity distinguishing otherwise homologous complexes. This may be particularly relevant for CRL5s and ARIH2, which regulate immune pathways, and are conscripted by several viruses to promote infection29–32,50.</p><!><p>For all expression constructs described in this study, standard molecular biology techniques were used for preparation and verification. Except for HIV-1 Vif (viral infectivity factor), coding sequences of the described proteins are of human origin. Mutant versions of ARIH2, CUL5 and UBE2L3 were generated using the Quikchange system (Agilent) and verified by sequencing.</p><p>Open reading frames encoding CUL5 (untagged), RBX2 (a GST fusion with an intervening TEV protease site, and encompassing RBX2 residues 5 through the C-terminus), UBA1 (a GST fusion with an intervening TEV protease site), APOBEC3C (a GST fusion with an intervening TEV protease site) and APOBEC3G (a GST fusion with an intervening TEV protease site) were subcloned into pLIB vectors for expression in Trichoplusia ni High-Five insect cells. CUL5 and RBX2 were co-expressed via baculoviral co-infection in a manner similar to that described previously for CUL1-RBX117,23. Briefly, CUL5-RBX2 and UBA1 were initially purified by GST-affinity chromatography, subjected to TEV protease cleavage of the fusions overnight at 4°C, and further purified by anion exchange chromatography using a HiTrap Q HP column (Cytiva Life Sciences) and then by size-exclusion chromatography. CUL5-RBX2 variants were purified using the same procedure, and are indicated by the residue numbers mutated and/or the ranges encompassed with the following exceptions: the CUL5 mutant "Δ29-helix" lacks residues 694-726; "K-to-D" is K418D K423D K676D K685D; "E-to-K" is E697K E701K E702K E703K E705K. APOBEC3C and APOBEC3G (hereafter referred to as A3C and A3G, respectively) were purified as previously described37. Neddylated CUL1-RBX1, SKP1-FBXW7 (the ΔD version lacking the dimerization domain), and ARIH1 were expressed and purified as previously described16,17,23. The buffer used for the final size exclusion chromatography purification of all these proteins and complexes was 25 mM HEPES pH 7.5, 150 mM NaCl and 1 mM DTT. Purity of all protein samples was verified by intact mass spectrometry provided by the Max Planck Institute of Biochemistry Core Facility.</p><p>Two base-versions of ARIH2 are used. A near full-length version lacking only the first 50 residues (encompassing residues 51 to the C-terminus) was used for obtaining the crystal structure of autoinhibited ARIH2. All biochemical assays and cryo-EM studies used full-length versions of either wild-type (WT) ARIH2 or the mutant versions of the full-length construct. ARIH2* refers to a mutant version of full-length ARIH2, relieved from autoinhibition through three residue substitutions: L381A E382A E455A. Deletion mutant versions of ARIH2 are indicated by "Δ" followed by residues excluded from the construct. All versions of ARIH2 were expressed using a common protocol. The constructs, in pRSF vector, contain an N-terminal His6-tag followed by MBP and a TEV protease cleavage site fused to the N-terminus of ARIH2 (or residue 51 in the version used in the crystal structure). The various versions of ARIH2 were expressed in in E. coli (Rosetta, DE3). Cultures were grown to OD 0.6-0.8 upon which expression was induced with 0.1 mM Isopropyl-β-D-thiogalactopyranoside (IPTG, Sigma) and 0.1 mM ZnCl2 (Sigma). The various versions of ARIH2 were initially purified by nickel-affinity chromatography, subjected to TEV protease cleavage of the fusions overnight at 4°C, and further purified by anion exchange chromatography using a HiTrap Q HP column (Cytiva Life Sciences) and then by size-exclusion chromatography in 25 mM HEPES pH 7.5, 150 mM NaCl and 1 mM DTT.</p><p>An ORF encoding HIV-1 Vif (UniProt sequence P12504), codon-optimized for expression in E. coli, was obtained from GeneArt/ThermoFisher. This and the gene encoding human CBFβ were subcloned into pRSF duet vector (MCS1 and MCS2, respectively). Vif was expressed with an N-terminal His6-tag followed by a TEV protease cleavage site. Full-length untagged Elongin B (ELOB) and Elongin C (ELOC) were sub-cloned into MCS1 and MCS2 of pACYCDuet-1 (Novagen), respectively. The Vif, CBFβ and ELOB and ELOC expression plasmids were co-transformed into E. coli (BL21 Gold, DE3) and the proteins co-expressed and purified as previously described37. The ASB9 complex with ELOBC was expressed similarly, except ASB9 was subcloned into the pET3a vector with an N-terminal His6-tag followed by a TEV protease cleavage site. These complexes were initially purified by nickel-affinity chromatography, subjected to TEV protease cleavage of the fusions overnight at 4°C, and further purified by ion exchange chromatography and then by size-exclusion chromatography in 25 mM HEPES pH 7.5, 150 mM NaCl and 1 mM DTT.</p><p>CKB was expressed as an N-terminal GST-fusion - with a TEV protease between GST and CKB - in E. coli (Rosetta, DE3) cells. Neddylation components NEDD8, UBE2F, UBE2M and APPBP1-UBA3 were expressed in either E. coli (Rosetta, DE3) or BL21 Gold, DE3) cells as GST-fusions with either thrombin or TEV as intervening protease cleavage sites. These proteins were expressed and purified as previously described16,41, with the exception of APPBP1-UBA3, where all fractions containing the neddylation E1 enzyme were pooled to maximize yield rather than purity. The CUL5-RBX2 complex was neddylated by mixing 12 μM CUL5-RBX2, 1 μM UBE2F, 0.2 μM APPBP1-UBA3, 25 μM NEDD8 in 25 mM HEPES pH 7.5, 150 mM NaCl, 10 mM MgCl2, and 1 mM ATP. NEDD8 was added at room temperature. Neddylation was quenched after 8 min by adding 10 mM DTT to suppress activity of APPBP1-UBA3 and UBE2F. After microcentrifugation at 13K rpm for 10 min, the NEDD8–CUL5-RBX2 was purified using a Superdex SD200 column, in 25 mM HEPES pH 7.5, 150 mM NaCl, 1 mM DTT (– refers to isopeptide linkage between NEDD8 or UB and a lysine on the target, here a cullin).</p><p>*UB refers to human ubiquitin expressed from pGEX-2TK, but with the N-terminal RRASV sequence replaced with RRACV, where the Cys serves as the site for fluorescent labeling with fluorescein-maleimide. *UB was expressed in E. coli (BL21 RIL, DE3), purified and fluorescently-labeled as previously described41.</p><!><p>The peptide used as substrate in ubiquitylation assays corresponds to phosphorylated Cyclin E (pCycE) and has sequence KAMLSEQNRASPLPSGLL(pT)PPQ(pS)GRRASY. The peptide was synthesized in the Max Planck Institute of Biochemistry Core Facility, and purified to greater than 95% purify by high-performance liquid chromatography (HPLC).</p><!><p>*UB transfer was monitored using a pulse-chase format. Briefly, the thioester-bonded UBE2L3~*UB intermediate (~ refers to thioester linkage between two proteins) was produced in the pulse reaction, and various proteins were added to initiate the chase reaction in which *UB is transferred from UBE2L3 through the ARIH2-dependent ubiquitylation cascade. Pulse-reaction conditions were optimized such that when examined by Coommassie-stained SDS-PAGE, all visibly detectable UBE2L3 was thioester-bonded to UB. The pulse reaction producing UBE2L3~*UB was carried out by incubating 15 μM UBE2L3, 0.3 μM UBA1 and 15 μM *UB in 25 mM HEPES pH 7.5, 100 mM NaCl, 2.5 mM MgCl2, 1 mM ATP at room temperature for 30 minutes. The reaction was quenched with 2 U/mL Apyrase and incubated on ice for at least 5 min. The quenched solution was further diluted to 5 μM with 25 mM HEPES pH 7.5, 100 mM NaCl.</p><p>The chase reaction was initiated by adding a pre-made mixture of various components to the pulse-reaction. Chase reaction mixes are described here by the mixture of components, but in final concentrations in the reactions, after addition to the pulse mix. To examine CRL5 activities, the concentration of UBE2L3~*UB generated in the pulse reaction was 0.4 μM. To examine CRL5 substrate ubiquitylation, the chase reaction mix consisted of 0.1 μM ARIH2, 4 μM substrate (A3G, A3C, or CKB as indicated), and a neddylated CRL5 assembled in the mix from two parts: 0.4 μM NEDD8–CUL5-RBX2, and either Vif-CBFβ- ELOBC or ASB9-ELOBC as indicated. To examine autoubiquitylation, the chase reaction mix contained 0.4 μM ARIH2 and 0.4 μM NEDD8–CUL5-RBX2 or CRL5. To examine CRL1 activities, the substrate was a phosphopepide derived from Cyclin E (pCycE; sequence provided above). The chase reaction mix consisted of 0.4 μM UBE2L3~*UB, 2 μM pCycE, and 0.5 μM each of ARIH1, NEDD8–CUL1-RBX1, and SKP1-FBXW7ΔD.</p><p>All reactions were carried out at room temperature and quenched at the indicated time points by adding 2x non-reducing SDS-PAGE sample buffer. SDS-PAGE was performed under non-reducing conditions. Gels were scanned using an Amersham Typhoon imager (GE Healthcare). Graphs shown in the main and extended data figures were generated from the 10 min timepoint. Band intensities for ubiquitylated products (*UB linked to A3G or CKB) were measured by ImageQuant TL v8.2.0.0 and normalized relative to intensities for products generated with WT CUL5 and ARIH2. For samples derived from the same experiment, gels were processed in parallel. Data was processed in Microsoft Excel v16.16.25 and data points plotted in GraphPad Prism v8.4.1 (GraphPad Software). All reactions were performed as technical duplicates. All proteins used in assays were ≈95% pure as judged by Coommassie-stained SDS-PAGE, and molecular weights confirmed by mass spectrometry. For fluorescent ubiquitin, and for ubiquitin-linked proteins, electrophoretic migration was determined by SDS PAGE and detection by Coommassie staining and fluorescence scanning of the same gel. On this basis, *UB, UBE2L3~*UB, A3G~*UB, CKB~*UB and ARIH2~*UB served as markers of molecular weights 8 kDa, 26 kDa, 54 kDa, 56 kDa, and 66 kDa, respectively. The Source Data files contain the uncropped gel images.</p><!><p>Neddylation of CUL5-RBX2 variants was monitored by using a previously-described pulse-chase format41, except with UBE2F as E2, RBX2 as E3 and CUL5 as substrate. For the chase reaction, the final concentration of UBE2F~*NEDD8 was 0.2 μM, and CUL5-RBX2 (or indicated variant) was 0.5 μM. Reactions were performed at room temperature in 25 mM HEPES, 100 mM NaCl pH 7.5. Samples were taken the indicated time points, quenched with non-reducing 2X SDS-PAGE sample buffer, run on SDS-PAGE, and scanned with an Amersham Typhoon imager (GE Healthcare).</p><!><p>The N-terminal 50 residues of ARIH2 are predicted to be disordered21 and were not included in the version used for crystallization. Crystals of ARIH2 (a version encompassing residues 51 to the C-terminus) were grown at 4°C by the sitting drop vapor diffusion method. 10 mg/ml protein was mixed in a 1:1 ratio with 0.2 M Sodium nitrate, 0.1 M Bis-Tris propane pH 8.5 and 20% PEG 3350 at 4°C. Crystals typically appeared within 5–10 days. Crystals were cryoprotected in the reservoir solution supplemented with 35% ethylene glycol and flash-frozen in liquid nitrogen.</p><!><p>Diffraction data were collected at the PXIII beamline Swiss Light Source (SLS, Switzerland), at -173 °C with a wavelength of 1.2783 Å. The crystal had a rod-like shape. With the goal of obtaining a strong anomalous signal arising from bound zinc atoms in the RING1, IBR, and Rcat domains, 360° of data were collected at three different translations across the length of the crystal. The three independent datasets from the single crystal (1080° of data total) were merged into a single reflection file using XSCALE. Data were indexed, integrated and scaled using XDS51. The structure was determined by single anomalous diffraction from zinc atoms, which were located using SHELXC/D/E52 followed by phase extension using PHENIX Autosol. The resultant map was used in Buccaneer53 for automatic chain tracing to build the initial model. Further iterative rounds of manual building and refinement were done using COOT54 and PHENIX55. Initially, waters were placed manually in unmodelled density observed in both the 2Fo-Fc map at 1σ and the Fo-Fc map at 3σ contour levels. Next, the 'Update waters' option in PHENIX was used to monitor, add and/or remove waters during the refinement. All waters in the final coordinate file were manually inspected to confirm density in the 2Fo-Fc map. In the final structure, the N-terminal residues of the construct (ARIH2 residues 51-57) and a loop connecting residues 128 and138 were not visible in the density and hence were not modeled. Pro267 is modeled with a cis peptide bond in both molecules in the asymmetric unit. For the final model, the Clashscore is 6.2, and the Ramachandran statistics are 96% favored, 4% allowed, and no outliers. Data collection and refinement statistics are listed in Supplementary Table 1.</p><!><p>Cryo-EM samples were generated by mixing 10 μM neddylated CUL5-RBX2, 12 μM Vif-CBFβ-ELOBC, 14 μM A3C or A3G and 10 μM ARIH2* (L381A E382A E455A). The mixture was incubated at 4°C for at least 30 minutes, and subjected to size-exclusion chromatography using a Superose™ 6 Increase column, in 25 mM HEPES, 100 mM NaCl, 1 mM DTT. 3 - 4 μl of freshly assembled protein complex at 0.5 mg/ml was applied to glow discharged (30 sec at medium intensity) Quantifoil holey carbon grids (R1.2/1.3 200 mesh) at 4 °C and 100 % humidity. Grids were immediately blotted with Whatman no.1 filter paper (blot time 3 sec, blot force 4) and vitrified by plunging into liquid ethane using Vitrobot Mark IV (Thermo Fisher Scientific).</p><!><p>Cryo-EM datasets were collected using SerialEM v3.8.0-b556 on a Titan Krios electron microscope at 300 kV with a Quantum-LS energy filter, using a K3 direct detector in counting mode. In total, 9,271 images were collected for the A3C complex and 7,830 images for the A3G complex at a pixel size of 0.8512 Å and 1.094 Å, respectively. The total exposure ranged from 75 to 90 e-/ Å2 and defocus values from -0.7 to -2.5 μm. The data collection statistics are listed in Supplementary Table 2.</p><!><p>The micrographs were imported into RELION 3.157, motion corrected and dose weighted using RELION's own implementation of MotionCorr258, followed by CTF estimation with Gctf v.1.0659.</p><p>For the reconstruction of A3C-bound neddylated CRL5Vif-CBFβ-ARIH2*, 5,030,529 particles were initially picked using Gautomatch v.056 (K. Zhang, MRC Laboratory of Molecular Biology), followed by 2D and 3D classification. Initially particles were binned by a factor of 5, resulting in Å/pixel of 4.26. Subsequent 2D and 3D classifications were done to remove particles belonging to poorly resolved classes. Cryo-EM data for both the A3C- and the A3G-bound neddylated CRL5Vif-CBFβ-ARIH2* assemblies refined to several similar but non-identical classes. Even during initial processing, it was apparent that density corresponding to Vif-CBFβ-A3C was relatively poorly resolved, presumably due to heterogeneous orientations of these subunits relative to CUL5. One class with 7689 particles showed features for the entire complex during 3D classification. This class refined to 6.8 Å resolution, and was low-pass filtered to 7.5 Å enable docking of subunits (Extended Data Fig. 3a).</p><p>Two masks were used for initial consensus refinement, both encompassing the visible density for the entire CRL5Vif-CBFβ-A3C-ARIH2* complex (Extended Data Fig. 3a). The narrower mask showed more density for the Vif-CBFβ-A3C subunits, resulting in a reconstruction with global resolution of 3.7 Å. The portion of the map corresponding to neddylated CUL5-RBX2-ARIH2* showed clear density with distinct features. Focused 3D classification using a mask covering only ARIH2* bound to neddylated CUL5 (C-terminal region)-RBX2 was used to further improve reconstruction. After iterative rounds of classification, a final set of 191,792 particles were used for final refinement with full pixel size, resulting in a 3.4 Å reconstruction with well-resolved interfaces between ARIH2* and neddylated CUL5-RBX2. The flow chart shown in Extended Data Fig. 3a shows the data processing schemes, including for maps with density for all proteins in the A3C-bound neddylated CRL5Vif-CBFβ-ARIH2* at 6.8 Å resolution (shown low-pass filtered to 7.5 Å resolution in Fig. 1d and Extended Data Fig. 5a), and for the ARIH2* assembly with a portion of neddylated CUL5 at RBX2 at 3.4 Å resolution. Reported resolution is based on the gold-standard Fourier Shell Correlation (FSC) using the 0.143 criterion (Extended Data Fig. 3b-c). Final maps were sharpened using RELION57 postprocessing or DeepEMhancer40. To facilitate model building by improved map quality by local sharpening and noise reduction, two half maps from the final refinement were provided without a mask as input to DeepEMhancer40. This resulted in reduced anisotropy and better overall map connectivity. The flow chart for A3G-bound complex processing is shown in Extended Data Fig. 4.</p><!><p>A number of maps were used as a guide for model building and refinement. Initially, coordinates from existing crystal structures were fit into the 6.8 Å resolution map (low-pass filtered to 7.5 Å resolution, EMD-12998), which showed density for all subunits as follows: A3C (PDB ID: 3VOW39); Vif-CBFβ-ELOBC and CUL5 N-terminal domain (chains l, m, n, o and p from PDB ID: 4N9F36), the crystal structure of ARIH2 from this study, and domains from neddylated CUL5 C-terminal domain-RBX1 (PDB ID: 3DQV) split into two units (the 4HB and C/R domain were fit together as one unit, NEDD8 and its linked CUL5 H29-helix and WHB domain were fit together as another unit)12.</p><p>The coordinates for a neddylated CUL5-RBX2-ARIH2* subcomplex of the A3C-bound neddylated CRL5Vif-CBFβ-ARIH2* E3-E3 were subjected to rebuilding, guided by the map processed with DeepEMhancer40, and refined using the 3.4 Å resolution postprocessed map arising from focused refinement (A3C E3-E3catalytic focused in Extended Data Fig. 3a, EMDB-12995). Initial regions of crystal structures were docked in the focus refined map using Chimera v1.1460 and they were allowed to move independently of each other in rigid body refinements using PHENIX55. ARIH2*'s UBAL, RING1, and RTI-helix region was visible at relatively lower resolution in all cryo-EM maps. Thus, this region of the model was only further subjected to rigid body refinement. The remainder of the structure was subjected to manual model building (including converting the original RBX1 model into the RBX2 protein in this complex) using COOT54. Real space refinements were performed in an iterative manner to improve the fit using Phenix.refine55. Other than ARIH2* Rcat domain (residues 283-351), most parts of the complex could be resolved except residues 1-34, 51-53, 128-133 and 492-493 of ARIH2*, 6-27 of RBX2 and 1-151, 170-173, 189-193, 386-400 and 675-679 of CUL5, which are not modeled in the final structure. Because the ARIH2* UBAL, RING1 and RTI-helix were less well-resolved in the maps, side-chains were maintained largely during refinement by restraining them using reference model restraints based on the crystal structures of autoinhibited ARIH2 reported in this study. The side-chain of CUL5 Glu717, which is not visible in the density but faces the center of the interface with NEDD8, was modeled based on the crystal structure showing the corresponding portion of neddylated CUL5 (PDB ID: 3DQV)12, but with zero occupancy. Structures and maps in the figures were rendered with PyMOL or ChimeraX v1.0.</p><!><p>A prior study compared hydrogen-deuterium exchange (HDX), quantified by mass spectrometry of tryptic peptides generated after HDX was quenched, for CUL5-RBX2-ELOBC, NEDD8–CUL5-RBX2-ELOBC, ARIH2, and ARIH2-NEDD8–CUL5-RBX2-ELOBC33. The authors compared HDX properties between CUL5-RBX2-ELOBC and NEDD8–CUL5-RBX2-ELOBC, between ARIH2 and ARIH2-NEDD8–CUL5-RBX2-ELOBC, and between NEDD8–CUL5-RBX2-ELOBC and ARIH2-NEDD8–CUL5-RBX2-ELOBC and determined peptides that after 0.25 min of HDX showed either statistically significant protection or deprotection upon complex formation33. Because HDX-MS data serve as an independent test of changes in protein conformation, the peptide sequences that show statistically significant protection or deprotection upon complex formation were color-coded on the structures of the individual CUL5-RBX222 and autoinhibited ARIH2 E3s, and the neddylated CRL5Vif-CBFβ-ARIH2* E3-E3 complex (deprotected red, protected-blue, no significant difference white and sequences not detected in the experiments black, Supplementary Video 1). Morphs showing potential trajectories between different conformations were generated using Chimera60, and movies were made using PyMOL (The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC).</p><!><p>a, Cartoon representing the core CRL5 assembly, highlighting relative locations of domains.</p><p>b, Cartoon representing structure of autoinhibited ARIH2 showing relative locations of domains.</p><p>c, Coomassie-stained SDS-PAGE gel of proteins used in this study.</p><p>d, Schematic of chase portion of pulse-chase assays of E3-E3 activity. The assays detect fluorescent UB (*UB) harboring an N-terminal tag wherein a cysteine is conjugated to fluorescein-5-maleimide. First, an E1 (UBA1)-catalyzed pulse reaction generates the reactive, thioester-linked UBE2L3~*UB intermediate. After the pulse reaction is quenched, the chase is initiated by adding ARIH2 and neddylated CRL5, which mediate *UB transfer from UBE2L3. ARIH2 is activated by binding a neddylated CRL5. When a CRL5 substrate is added, E3-E3 activity is monitored by transfer of *UB from UBE2L3 to the substrate via a fleeting thioester-linked ARIH2~*UB intermediate that is not readily detected. Without a CRL5 substrate, intrinsic E3-E3 activity is detected by ARIH2 autoubiquitylation. ~ refers to thioester linkage. – refers to isopeptide linkage.</p><p>e, Fluorescent scans of gels examining ARIH2 and CRL5Vif-CBFβ-dependent *UB transfer from UBE2L3 through E3-E3 cascade for ubiquitylating A3G substrate, following assay scheme shown in d. The assays test effects of NEDD8 and/or mutationally overcoming ARIH2 autoinhibition. The indicated E3-E3 components were added to UBE2L3~*UB. Components of CRL5Vif-CBFβ were added as two subcomplexes: either neddylated or unneddylated CUL5-RBX2, and Vif-CBFβ-ELOBC mixed with A3G substrate. Reactions use either WT ARIH2 or ARIH2* (*mut, with L381A E382A E455A mutations). Results are representative of N = 2 independent experiments. Assay results shown in the main figures are quantified from the 10-minute time point and normalized relative to activity with WT proteins (Source Data Extended Data Fig. 1).</p><p>f, Experiment performed as in e, except with CRL5ASB9 and substrate CKB.</p><p>g, Experiment performed as in e, except with substrate A3C.</p><!><p>a, Chromatograms (top) and Coomassie-stained SDS-PAGE gels of fractions (bottom) from size exclusion chromatography of neddylated CRL5Vif-CBFβ-A3C mixed with WT ARIH2 (blue) or ARIH2* (green, Source Data Extended Data Fig. 2). The experiment was performed twice.</p><p>b, Interactions between ARIH2* (violet) and neddylated CUL5-RBX2 seen in map from ARIH2*-neddylated CRL5Vif-CBFβ-A3C complex generated using DeepEMhancer40. Connections to the ARIH2* Rcat domain, not visible in the map, are indicated as dotted lines. Black arrow indicates the >30 Å distance between the ARIH2* UBAL domain and NEDD8.</p><p>c, Left, crystal structure of autoinhibited ARIH2, with domains colored as in Figure 1a, fit into the cryo-EM map (sharpened by DeepEMhancer40) of ARIH2* from complex with neddylated CRL5Vif-CBFβ-A3C. Right, crystal structure of autoinhibited ARIH2 with domains colored as in Figure 1a superimposed with structure of ARIH2* (in grey) from complex with neddylated CRL5Vif-CBFβ-A3C. The Rcat domain of ARIH2* is not clearly defined in the density and thus was not modeled. To generate the model for ARIH2*, the coordinates for the UBAL, RING1, RTI-helix, and UBAL domain from the ARIH2 crystal structure were wholesale docked into the cryo EM density, which is relatively lower resolution over this region of the complex. The ARIH2* IBR and Ariadne domains were rebuilt based on the high-quality density for these regions.</p><p>d, Structure of ARIH2* from complex with neddylated CRL5Vif-CBFβ-A3C, with domains colored as in Figure 1a. Structure of corresponding region of ARIH1 (light blue) from a complex with a neddylated CRL123 is shown superimposed. The latter complex represents UB transfer from UBE2L3 to neddylated CRL1-bound ARIH1, but for simplification, the Rcat domain of ARIH1 is not shown.</p><p>e, Structure of E2~UB-binding platform of autoinhibited ARIH2 is shown with domains colored as in Figure 1a. The corresponding region of the structure representing UB transfer from UBE2L3 to neddylated CRL1-bound ARIH123 was superimposed and is shown in light blue with its bound UBE2L3~UB (cyan and orange). Close-up (rotated 45° in x) shows interface between UBE2L3 and ARIH1 RING1, highlighting the central I188, and corresponding ARIH2* RING1 V141.</p><p>f, Fluorescent scan of gel showing neddylated CRL5Vif-CBFβ and ARIH2-dependent *UB transfer from UBE2L3 through E3-E3 cascade to A3G substrate, comparing WT ARIH2 and V141D mutant. (Source Data Extended Data Fig. 2). The data are representative of N = 2 independent experiments.</p><!><p>a, Cryo-EM image processing flowchart for the complex containing ARIH2*, neddylated CRL5Vif-CBFβ, and A3C. Masks are shown in transparent yellow surface superimposed with grey maps.</p><p>b, From left to right: two views showing local resolution colored on the A3C consensus map for the complex containing ARIH2*, neddylated CRL5Vif-CBFβ, and A3C; Fourier Shell Correlation (FSC) curve showing the overall resolution of 3.7 Å with the FSC=0.143 criterion; and angular orientation distribution of the final 3D reconstruction.</p><p>c, As in b, for the focused refined map (A3C E3-E3catalytic focused) over the catalytic assembly containing ARIH2* and a portion of neddylated CUL5 bound to RBX2.</p><!><p>a, Cryo-EM image processing flowchart for the complex containing ARIH2*, neddylated CRL5Vif-CBFβ, and A3G. The portion of the reconstructions corresponding to A3G-Vif-CBFβ-ELOBC is visible only at low contour. This subcomplex is presumably mobile relative to the assembly between ARIH2* and neddylated CUL5-RBX2. Masks are shown in transparent yellow surface superimposed with grey maps.</p><p>b, From top to bottom: two views showing local resolution colored on the A3G consensus map for the complex containing ARIH2*, neddylated CRL5Vif-CBFβ, and A3G; Fourier Shell Correlation (FSC) curve showing the overall resolution of 3.8 Å with the FSC=0.143 criterion; and angular orientation distribution of the final 3D reconstruction.</p><!><p>a, Cryo-EM map of ARIH2* complex with neddylated CRL5Vif-CBFβ-A3C, low-pass filtered to 7.5 Å resolution, and structures fit into the map12,22,36,39. Crystal structure of ARIH2 (PDB ID 7OD1) was determined in this study.</p><p>b, Close-up of interface between ARIH2* Ariadne domain and RBX2, shown in A3C E3-E3catalytic DeepEMhancer map.</p><p>c, Close-up of interface between ARIH2* Ariadne domain and CUL5, shown in A3C E3-E3catalytic DeepEMhancer map.</p><p>d, Close-up of interface between ARIH2* N-terminal region and CUL5 groove, shown in A3C E3-E3catalytic DeepEMhancer map.</p><p>e, Close-up of interface between NEDD8 and its linked CUL5 H29-helix shown in A3C E3-E3catalytic DeepEMhancer map.</p><p>f, Close-up of 3-way junction between NEDD8 and its linked CUL5 WHB domain, and C/R domain portion of CUL5, shown in A3C E3-E3catalytic DeepEMhancer map.</p><p>g, Domains from crystal structure of autoinhibited ARIH2 shown fit into A3C E3-E3catalytic focused map.</p><!><p>a, Close-up of the noncovalent interface between NEDD8 (yellow) and its linked CUL5 WHB domain (green), from the cryo-EM structure of neddylated CRL5Vif-CBFβ-A3C complex with ARIH2*. Side-chains mediating contacts, and CUL5 H29-, H30-, and H31-helices are indicated.</p><p>b, Portion of the cryo-EM structure corresponding to NEDD8, CUL5 C-terminal domain (encompassing the 4HB, C/R domain, and WHB domain), and the N-terminal strand of RBX2 contributing to the C/R domain.</p><p>c, Lattice packing in prior crystal structure of neddylated CUL5 C-terminal domain (CTD)-RBX1 complex12, highlighting CUL5's H29-helix and WHB domain in dark green, and its linked NEDD8 in yellow. Dotted line indicates the border between the two different neddylated CUL5 CTD-RBX1 complexes in the crystal lattice. NEDD8 and CUL5 interact similarly as in the cryo-EM structure, although contacts between NEDD8 and its linked CUL5 WHB domain are with the C/R domain of the adjacent complex in the crystal.</p><!><p>a, Neddylated CRL5Vif-CBFβ-dependent fluorescent UB (*UB) transfer to A3G in 10 minutes, catalyzed by WT ARIH2 or indicated Ariadne domain mutants. (Source Data Extended Data Fig. 3). N = 2 independent experiments. For samples from same experiment, gels were processed in parallel.</p><p>b, Close-up showing cryo-EM density at low contour, over ARIH2*'s N-terminal region (magenta) and neddylated CRL5 groove. Basic residues from neddylated CUL5 (K418, K423, K676 and K685) line the groove and are poised to contact the largely acidic ARIH2 N-terminal stretch (residues 22-34) not modeled in the structure.</p><p>c, Close-up of cryo-EM structure, showing complementarity between ARIH2* N-terminal region (magenta) and CUL5 groove shown as surface colored by electrostatic potential (red negative, white neutral, blue positive).</p><p>d, Fluorescent scans of gels showing neddylated CRL5Vif-CBFβ and ARIH2-dependent *UB transfer from UBE2L3 through E3-E3 cascade for ubiquitylating A3G substrate over time (Source Data Extended Data Fig. 3). The assay follows the scheme shown in Extended Data Figure 1d. The assays test effects of indicated multi-Ala mutants in ARIH2 N-terminal domain. Residues substituted with Ala are encompassed by the indicated region, for example 22-24A is 22A 23A 24A. The data are representative from N = 2 independent experiments.</p><p>e, Assay as b, except with indicated deletion-mutant versions of ARIH2 (Source Data Extended Data Fig. 3).</p><p>f, Chase assays monitoring neddylation of various CUL5-RBX2 mutants as quality control for proper folding. Assays were performed in pulse-chase format, and detect fluorescent *NEDD8. *NEDD8 harbors an N-terminal tag wherein a cysteine is conjugated to a fluorescein-5-maleimide. First, the reactive, thioester-linked UBE2F~*NEDD8 intermediate was generated in a pulse reaction catalyzed by the NEDD8-specific E1 enzyme (the APPBP1-UBA3 complex). After the pulse reaction was quenched, the chase reaction was initiated by adding either WT or indicated mutant versions of CUL5-RBX2, and *NEDD8 transfer from UBE2F to CUL5 was monitored over time. The deletion mutants of CUL5 all lack the neddylation site (K724) and are: ΔH29 lacking residues 693-725, 1-696 lacking residues 697-780, and 1-712 lacking residues 713-780. Shown are fluorescent scans of SDS-PAGE gels of reaction products (Source Data Extended Data Fig. 3). The data are representative from N = 2 independent experiments.</p><!><p>a, Fluorescent scan of gels showing neddylated CRL5Vif-CBFβ and ARIH-family RBR E3-dependent *UB transfer from UBE2L3 through E3-E3 cascade for ubiquitylating A3G substrate, testing roles of ARIH E3 identity (ARIH1 or ARIH2) and RBX identity in neddylated CRL5Vif-CBFβ generated from Vif-CBFβ-ELOBC and either neddylated CUL5-RBX2 or CUL5-RBX1 (Source Data Extended Data Fig. 4). The data are representative from N = 2 independent experiments.</p><p>b, Assays performed as in a, except with neddylated CRL1FBXW7ΔD and phosphopeptide derived from Cyclin E (pCycE) as substrate (Source Data Extended Data Fig. 4).</p><p>c, Superposition of Ariadne and Rcat domains in autoinhibited ARIH2 and ARIH1 (PDB ID: 4KBL25).</p><p>d, UBAL-RING1-RTI-helix-IBR domains (i.e., E2~UB-binding platform) of ARIH2 crystal structure.</p><p>e-j, RING1-RTI-helix-IBR domains (i.e., E2~UB-binding platform) of different RBRs (neddylated CRL1 bound ARIH1 PDB ID: 7B5L23, autoinhibited ARIH1 PDB ID: 4KBL25, HOIP PDB ID: 5EDV34, louse PARKIN PDB ID: 5CAW42, human PARKIN PDB ID: 5N2W43, autoinhibited human PARKIN PDB ID: 4BM926) aligned over their RING1 domains as in d.</p><p>k, Superposition of the UBAL domain of ARIH2 crystal structure with that of a neddylated CRL1-bound ARIH1 (PDB ID: 7B5L23).</p><p>l, Alignment of UBAL domain sequences of human ARIH2 and ARIH1. Secondary structures are indicated by rectangles for helices. Residues identical between the two are shaded in rose. ARIH1 F150 and ARIH2 K110 are shaded in yellow.</p><p>m, Alignment of WHB domain sequences for CUL5 from the indicated organisms. Secondary structures based on crystal structure of unneddylated CUL512 are indicated by rectangles for helices, arrows for β-strands. Degree of conservation is indicated by color-coded bars above. L710 and E717, which configure noncovalent interactions with covalently-linked NEDD8 are highlighted in red.</p><p>n, Alignment of WHB domain sequences from human CUL5, CUL1, CUL2, CUL3, CUL4A, and CUL4B. Degree of conservation is indicated by color-coded bars above. In CUL5 sequence, L710 and E717, which configure noncovalent interactions with covalently-linked NEDD8 are highlighted in red. The corresponding aspartate and alanine residues from CULs1-4 are highlighted black. CUL5 glutamates that are candidates for securing H29-helix in unneddylated CUL5 and that were mutated to lysines in E-to-K mutant are highlighted in cyan.</p>

PubMed Author Manuscript

Exacerbation of tobacco smoke mediated apoptosis by resveratrol: an unexpected consequence of its antioxidant action

Resveratrol, a polyphenolic compound rich in grapes and red wine, has been reported to protect cells against oxidative damage and cell death by increasing cellular antioxidant/detoxification capacity. Cigarette smoking is a major risk factor for respiratory diseases and oxidative damage is implicated in its pathogenesis. Here we investigated the enhancement of antioxidant capacity by resveratrol and its potential protection against cell death caused by cigarette smoke in human bronchial epithelial cells (HBE1). At concentrations that did not affect cell growth, resveratrol activated Nrf2 signaling and increased the expression of NAD(P)H:quinone reductase-1, heme oxygenase-1, and the catalytic subunit of glutamate cysteine ligase. Surprisingly, instead of protecting against cell death, resveratrol significantly enhanced cigarette smoke extract-induced apoptosis. To define the underlying mechanism, the effect of resveratrol on caspase activity was examined and it was found that resveratrol significantly enhanced cigarette smoke-stimulated caspase activity. In conclusion, results from this study suggest that although resveratrol increased antioxidant and detoxification capacity, it increased rather than protected against cigarette smoke-induced apoptosis.

exacerbation_of_tobacco_smoke_mediated_apoptosis_by_resveratrol:_an_unexpected_consequence_of_its_an

Introduction<!>Reagents<!>Cell culture and treatment<!>Preparation of cigarette smoke extracts (CSE)<!>Measurement of mRNA content<!>Western Blotting<!>Cell growth assay<!>Assay of caspase activity<!>Apoptosis assay<!>Statistical Analysis<!>Resveratrol increases expression of antioxidant genes<!>Resveratrol increased CSE-triggered apoptosis<!>Resveratrol mediated inhibition of cell growth<!>Resveratrol protected caspase activity<!>Caspase3 and 9 were reversibly oxidized during cigarette smoke exposure in the absence of resveratrol<!>Discussion<!>

<p>Resveratrol, a polyphenolic compound found in grapes, wine, berries, and herbal medicines, such as Polygonum cuspidatum, has been shown to exhibit various biochemical activities, such as regulation of the cell cycle (Hsieh and Wu, 1999), stimulation of endothelial nitric oxide synthase (Taubert and Berkels, 2003), and inhibition of platelet aggregation (Pace-Asciak et al., 1995). Recent studies have found that resveratrol increased antioxidant capability and protected against oxidative damage by enhancing the expression of antioxidant genes, such as heme oxygenase-1 (Chen et al., 2005; Das et al., 2006; Juan et al., 2005), thioredoxin reductase (Hu et al., 2007), and glutathione (GSH) (Savaskan et al., 2003; Vieira de Almeida et al., 2007).</p><p>Apoptosis or programmed cell death is a tightly regulated process that consists of complex biochemical cascades involving the activation of caspases (Zimmermann et al., 2001). Caspases are a class of cysteine proteases involved in the initiation and execution of apoptosis and are activated through either extrinsic or intrinsic apoptosis pathways. In the extrinsic pathway, activation of membrane death receptors such as Fas receptor results in the auto-activation of caspase 8 and the subsequent cleavage of procaspase 3 into its active form. The intrinsic pathway, on the other hand, is triggered by signals that cause the release of cytochrome c, Apaf-1, and other proteins from mitochondria. These proteins then form an apoptosome with procaspase 9, resulting in formation of caspase 9. Caspase 9 then cleaves procaspase 3, resulting in caspase 3, the major apoptosis executor (Zimmermann et al., 2001).</p><p>Cigarette smoke is the major environmental hazard causing pulmonary diseases such as chronic obstructive pulmonary disease (COPD) and lung cancers. Cigarette smoke is a mixture of more than 4000 chemicals that include significant amounts of free radicals, peroxides, and electrophiles (Pryor and Stone, 1993). Oxidative damage and cell death caused by these oxidants have been implicated in the pathogenesis of COPD and lung cancers (MacNee, 2000; Traber et al., 2000). Therefore, increasing antioxidant capacity has been proposed as a promising strategy to prevent cigarette smoke-induced lung diseases.</p><p>Considering its potential in inducing antioxidant defenses, we hypothesized that resveratrol would alleviate cigarette smoke-caused apoptosis. In this study, we tested this hypothesis and unexpectedly found that, although resveratrol increased the expression of some antioxidant genes, it actually enhanced apoptosis, which was apparently through protection of caspase activity.</p><!><p>Unless otherwise noted, all chemicals were from Sigma (St. Louis, MO). Antibodies and small interfering RNAs were from Santa Cruz (Santa Cruz, CA). Annexin V-FITC Apoptosis Detection kit, Acetyl-Asp-Glu-Val-Asp-7-amino-4-(trifluoromethyl)-coumarin (Ac-DEVD-AFC) and acetyl-Leu-Glu-His-Asp-7-amino-4-(trifluoromethyl)-coumarin (Ac-LEHD-AFC) were bought from EMD Biosciences (La Jolla, CA). TRIzol Reagent was from Life Technologies (Grand Island, NY). DNA-free reagent was from Ambion (Austin, TX). TaqMan Reverse Transcription Reagent and SYBR Green PCR Master Mix were from Applied Biosystems (Foster City, CA). FuGENE 6 transfection reagent was from Roche (Indianapolis, IN).</p><!><p>A human bronchial epithelial cell line (HBE1 cell) was cultured in collagen-coated dishes in 5% CO2 at 37°C as described by Harper et al. (Harper et al., 2001). The HBE1 cell line, which has been demonstrated to share many properties with primary human bronchial cells (Yankaskas et al., 1993), has been used to study the response of human bronchial epithelial cells to various insults including cigarette smoke. Indeed, Lee and coworkers have shown that cigarette smoke exposure caused similar injury in HBE1 cells as in primary human airway epithelium (Lee et al., 2008). Resveratrol was freshly dissolved in ethanol and the final concentration of ethanol in medium was 0.05%.</p><!><p>CSE was an extract of mainstream cigarette smoke. Briefly, the smoke from one filtered cigarette (Camel regular) containing 1.2 mg of nicotine and 18 mg of tar, according to the manufacturer's report, was drawn through an experimental apparatus with a constant airflow driven by vacuum. The smoke was bubbled through 25 ml of cell medium in 2 min and the solution was used as the stock (100%) for further dilutions. After adjusting the pH to 7.2, the obtained CSE was filtered through a 0.22-μm filter (Millipore, Bedford, MA) for sterilization and diluted for use in 20 min after the preparation.</p><!><p>The content of GCLC, NQO-1, and HO-1 mRNAs was determined with real-time PCR method using the protocol described previously (Zhang et al., 2005a). NQO-1 primers, sense 5'- TCTCGGCTCACTGCAACCTCT, antisense, 5'-GCACTTTGGGAGGCTGAGGTA; HO-1 sense 5'- TCTCTTGGCTGGCTTCCTTAC, antisense 5'- GGCTTTTGGAGGTTTGAGACA. GCL and GAPDH primers are same as described previously (Dickinson et al., 2004).</p><!><p>Western blotting was performed as described previously (Dickinson et al., 2002). Briefly, protein was extracted and 25 μg protein was heated for 15 min at 95°C in loading buffer containing SDS (Tris base, pH 6.5, glycerol, dithiothreitol (DTT), and pyronin Y), electrophoresed under denaturing conditions on a 10% Tris-glycine acrylamide gel (Invitrogen, Carlsbad, CA), and then electroblotted onto a polyvinylidene difluoride (PVDF) membrane (Immobilon P; Millipore, Bedford, MA). Membranes were blocked with 5% fat-free milk at room temperature for 1 h, and then incubated overnight at 4°C with appropriate primary antibody in 5% milk in Tris-buffered saline (TBS). After being washed with Tris-buffered saline containing 0.05% Tween 20 (TTBS), the membrane was incubated with appropriate secondary antibody at room temperature for 2 h. After TTBS washing, the membrane was treated with chemiluminescence reagent (ECL Plus; Amersham, Arlington Heights, IL) for 5 min. The target bands were then imaged on a Kodak Image Station 2000R.</p><!><p>Cell growth was assayed with direct cell counting. Briefly, cells at 60-70% confluence were treated with different concentrations of resveratrol for 24 hours. Cell numbers at 0h and 24h after treatment were counted with hemocytometer.</p><!><p>Activity of caspase 3 and 9 was determined by following the protocol described previously (Watanabe et al., 2002). Briefly cells in 6-well plate were collected and lysed in 200 μl of 0.1% Triton X-100/NaPi (0.1 M sodium phosphate buffer, pH 7.4) and centrifuged at 10,000 g for 10 min at 4°C to obtain the supernatant. Assays of caspase activity were carried out in 200 μl of reaction containing the following: cell lysate equivalent to the original 6 × 104 cells, 10 mM dithiothreitol, 0.05% (vol/vol) Triton X-100, and 50 μM of either Ac-DEVD-AFC (caspase 3 substrate) or Ac-LEHD-AFC (caspase 9 substrate) in NaPi. After incubation at 37°C for 1 h, the fluorescence intensity was measured in a fluorescence microplate reader (SpectraMax GeminiXS, Molecular Devices) with excitation and emission wavelengths of 400 and 500 nm, respectively. The values were converted to AFC concentrations using an external AFC standard.</p><!><p>Apoptosis was determined with a FITC-conjugated annexin V-propidium iodide (PI) kit in a Guava EasyCyte Mini System (Guava Technologies Inc., Hayward, CA). Briefly, cells in 12-well plate were collected with trypsin treatment and combined with cells in the medium. Cell pellet was rinsed with 1 X PBS for 2 times and incubated with annexin V-FITC in binding buffer for 15 min. After adding PI, samples were incubated in ice for 10 min and then analyzed in the Guava flow cytometer.</p><!><p>A comparative ΔΔCT method was used for the relative mRNA quantification as described before (Zhang et al., 2005b). All data were expressed as the mean ± standard error. Sigma Stat software was used for statistical analysis and statistical significance was accepted when p < 0.05. The one-way ANOVA and Tukey test were used for comparison of mRNA level and relative caspase activity.</p><!><p>Antioxidant enzymes, such as glutamate cysteine ligase (GCL), NAD(P)H quinone oxidoreductase-1 (NQO-1), and heme oxygenase-1 (HO-1), play crucial roles in the detoxification of oxidants and the maintenance of redox homeostasis. To examine the potential protective effects of resveratrol against oxidative stress, we first determined the effects of resveratrol on the expression of NQO-1, HO-1, and the catalytic unit of GCL (GCLC). As shown in Figure 1A, resveratrol (2 and 5 μM) significantly increased the mRNA levels of GCLC, NQO-1, and HO-1 in HBE1 cells. In addition, the nuclear content of Nrf2, a critical transcription factor involved in the induction of a variety of antioxidant/detoxifying genes, was also increased by resveratrol (Figure 1B). These data demonstrated that resveratrol increased the expression levels of a variety of antioxidant and detoxifying genes in HBE1 cells.</p><!><p>As shown in Figure 2A, resveratrol itself did not cause apoptosis. Even when cells were exposed to a concentration as high as 50 μM resveratrol, only 6.84% of the cells were apoptotic (Annexin V +/PI-), similar to vehicle control. These data suggest that resveratrol alone does not cause apoptosis in HBE1 cells at concentrations less than 50 μM. Since resveratrol increased antioxidant gene expression (Figure 1), we initially hypothesized that resveratrol would protect cells from cytoxicity caused by cigarette smoke. To test this, we investigated the protection of resveratrol against CSE-induced cell death. Exposure to CSE for 4 h caused apoptosis in a concentration-dependent manner (Figure 2B); pre-exposure to 2 and 5 μM of resveratrol for 24 h, contrary to our initial hypothesis, further increased CSE-induced apoptosis. Although 5% CSE did not induce apoptosis, with resveratrol pretreatment, it markedly increased early apoptotic cells indicated by higher percentages of Annexin+/PI- cells (represented by high green fluorescence and low red fluorescence). With 10% and 20% CSE, pretreatment with resveratrol caused a similar pattern of increased percentage of early apoptotic cells. With 20% CSE, we also observed a marked increase in late apoptosis in respect to increasing dose of resveratrol as indicated by the higher percentage of Annexin V+/PI+ cells (Figure 2B).</p><!><p>It was reported previously that resveratrol might sensitize cells to apoptosis by inhibiting cell growth (Ahmad et al., 2001; Ferry-Dumazet et al., 2002; Fulda and Debatin, 2004). To examine whether this effect was responsible for the enhancing effect of resveratrol on CSE-triggered apoptosis, we measured the effect of resveratrol on cell growth. As shown in Figure 3, when cells were exposed to less than 5 μM resveratrol, the cells proliferated at the same rate as that of vehicle control with the cell number increasing by 2 fold in 24h. When cells were exposed to 20 μM resveratrol however, cell number increased only by 14% in 24h. Thus, while 20 μM resveratrol could inhibit cell growth as previously reported, inhibition of cell growth was not involved in the increased CSE-triggered apoptosis by 5 μM resveratrol.</p><!><p>Caspase 9 and caspase 3 play critical roles in the initiation and execution of the apoptotic process. To elucidate how resveratrol increased CSE-induced apoptosis, we investigated the potential effect of resveratrol on caspase activity. CSE alone significantly increased the activities of both caspase 9 and 3 (Table 1). The activities of both caspases were further increased with the pretreatment of cells with 5 μM of resveratrol for 24 h, indicating that resveratrol increased caspase activity. However, resveratrol alone did not elevate the activity of caspase 9 and 3 (Table 1), suggesting that resveratrol enhanced CSE-activated caspase activity through mechanisms other than directly activating the caspases.</p><!><p>To support the hypothesis that a fraction of caspase activated by CSE was in an inactive state as a result of oxidation, we examined the post-exposure recovery of caspase inhibition with the dithiothreitol (DTT), a reductant frequently used in biochemical assays to maintain the reduced state of proteins. The caspase activity of cells exposed to CSE was determined with/without DTT (2 mM) in assay mixture. Compared with non-DTT condition, DTT incubation significantly increased activities of both caspase 9 and caspase 3, which are activated by CSE (Table 1), suggesting that reduction could increase caspase activity after CSE exposure.</p><!><p>The original purpose of this study was to examine the potential increase in antioxidant defense by resveratrol and its protection against cigarette smoke-induced cell death. To do this, we measured the expression levels of some antioxidant genes and examined the effect of resveratrol pre-treatment on CSE-caused apoptosis in human bronchial epithelial cells (HBE1 cells). The results suggest that although resveratrol increased antioxidant and detoxification capacity, it did not alleviate CSE-triggered apoptosis. Instead, resveratrol exacerbated CSE-induced apoptosis. Furthermore, we demonstrated that resveratrol appeared to potentiate apoptosis by protecting CSE-stimulated caspase activity rather than by activating caspases.</p><p>Resveratrol has been shown to exhibit antioxidant properties, particularly through the induction of antioxidant genes (Chen et al., 2005; Das et al., 2006; Hu et al., 2007; Juan et al., 2005; Savaskan et al., 2003; Vieira de Almeida et al., 2007) and the alleviation of oxidative damage (Ara et al., 2005; Cadenas and Barja, 1999; de Almeida et al., 2007; Kasdallah-Grissa et al., 2007; Mizutani et al., 2001). In agreement with this, we found that resveratrol increased the mRNA contents of NQO-1, HO-1, and GCLC, which are critical in defense against oxidative stress. The resveratrol-mediated activation of Nrf2, a key transcription factor involved in the induction of many antioxidant and detoxifying genes, provides one mechanism through which resveratrol increases cellular antioxidant and detoxification capacity.</p><p>Significant amounts of free radicals and oxidants are present in cigarette smoke and produce oxidative stress-related damage, such as cell death in the lung of a smoker, which eventually leads to cigarette smoke-induced lung disease (MacNee, 2000; Pryor and Stone, 1993; Traber et al., 2000). Antioxidant treatment is thus usually considered an effective strategy to reduce smoke-induced damage (Kinnula, 2005). This study however, showed that although resveratrol increased the antioxidant and detoxification capacity, it exacerbated rather than alleviated cigarette smoke-induced apoptosis. This unexpected result demonstrates that an increase in antioxidant capacity by resveratrol did not translate into an alleviation of cell death from oxidative stress. Similar phenomena with other phase II enzyme inducers have been reported previously. For example, D'Agostini et al. showed that N-acetylcysteine alone or in combination with oltipraz significantly decreased cigarette smoke-induced apoptosis, while phenylethyl isothiocyanate enhanced apoptosis caused by cigarette smoke (D'Agostini et al., 2001). Like resveratrol, phenylethyl isothiocyanate is a potent inducer of antioxidant genes and considered a chemopreventive agent (Hu et al., 2006; Xu et al., 2006). Martin et al. also found that resveratrol decreased oxidative damage but enhanced apoptosis caused by 2, 4, 6-trinitrobenzene sulfonic acid, an inducer of oxidative stress (Martin et al., 2004). Indeed, resveratrol has been reported to enhance the apoptosis caused by a diversity of apoptosis triggers including cytokines and chemotherapeutic agents (Duraj et al., 2006; Fulda and Debatin, 2004; Jazirehi and Bonavida, 2004; Shankar et al., 2007). The difference here is in the proposed mechanism. Previously, it was proposed that cell growth arrest by resveratrol might be involved in its apoptosis sensitization effect (Ahmad et al., 2001; Ferry-Dumazet et al., 2002; Fulda and Debatin, 2004). In the current study however, we did not see cell growth inhibition by resveratrol at the concentrations that enhanced apoptosis (Figure 3). Instead, we found that the CSE-induced caspase activity was protected (and thus further increased) by resveratrol, suggesting that increased caspase activity rather than cell growth inhibition was involved in the enhancement of cigarette smoke-induced apoptosis by resveratrol.</p><p>Caspases play critical roles in the apoptotic process and their activities are highly regulated. In this study we found that resveratrol apparently increased the activities of both caspases 3 and 9 that were induced by CSE although resveratrol itself did not activate caspases (Table 1). This suggests that the resveratrol treatment resulted in prevention of the loss of CSE-induced caspase activity and that this is responsible for at least part of the apoptosis exacerbating effect of resveratrol. Activation of caspase 9 is through the intrinsic apoptosis pathway or mitochondrial pathway and involves a balance between proapoptotic and antiapoptotic members of the Bcl-2 family. Previously, resveratrol was shown to increase caspase 9 activity by up regulating Bcl-2 family members (Benitez et al., 2007; Jazirehi and Bonavida, 2004; Jo et al., 2004). The increased caspase 9 activity would consequently activate more caspase 3. In addition, it was reported that resveratrol could cause redistribution of death receptor (CD95) and thus increase the caspase 3 activity (Delmas et al., 2004). In this study however, 5 μM resveratrol did not cause apoptosis (Figure 2A), nor did it increase caspase activity alone (Table 1), suggesting that resveratrol instead protected caspases that were activated by cigarette smoke.</p><p>Caspases are cysteine proteinases that are redox sensitive and could be inhibited upon oxidative modification (Borutaite and Brown, 2001; Hampton and Orrenius, 1997). For instance, Zech et al. found that the caspase 3 activity was inhibited by nitric oxide and peroxynitrite (Mohr et al., 1997). Little is known about the modification of caspases by cigarette smoke. A recent study by Stringer et al. demonstrated that caspase 3 was inhibited by CSE dose-dependently and the inhibited caspase activity could be restored with DTT incubation (Stringer et al., 2007). In the current study, DTT addition to cell extracts post exposure to CSE markedly increased the activities of both caspases 9 and 3 after activation by CSE (Table 1). DTT is a powerful reductant that would reduce the disulfide bonds in caspases and then recover the oxidative modification of caspases, if there were any. These data imply that a fraction of the caspases (caspase 9 or caspase 3) could be recovered from reversibly oxidized inactive form. Based on this, it may be inferred that caspase (3 and 9) activity was affected in two phases by cigarette smoke; caspases were initially activated by CSE and then a fraction of these active caspases were oxidatively inhibited by CSE. By increasing antioxidant levels, resveratrol apparently decreased oxidative modification of caspases and protected their activity.</p><p>In summary, results from this study showed that while resveratrol induced antioxidant/detoxifying genes expression, it did not protect cells from apoptosis caused by cigarette smoke but rather exacerbated it, partially through protection of the activities of caspase 9 and caspase 3. Excessive apoptosis is involved in the pathogenesis of lung diseases such as emphysema while dysregulated apoptosis is implicated in the development of lung cancer. Therefore, enhancement of apoptosis can be both beneficial and detrimental within the lung parenchyma depending on the pathogenic changes. Obviously, further studies are required to define the potential beneficial health effects of resveratrol.</p><!><p>Resveratrol increased antioxidant gene expression. (A) Resveratrol increased mRNA levels of GCLC, NQO-1, and HO-1. HBE1 cells were treated with 0, 2 and 5 μM of resveratrol for 12h and mRNA level of specific gene was determined using RT-real-time PCR assay. N=3, * P<0.05 compared with vehicle control. (B) Nuclear content of Nrf2 is increased by resveratrol. HBE1 cells were treated with 5 μM resveratrol for 1 h and the nucleus was extracted and then nuclear Nrf2 level was determined with Western blotting. Lamin B1 was used as internal control.</p><p>Resveratrol enhanced CSE-induced apoptosis. (A) Resveratrol did not induce apoptosis itself. (B) Pretreatment of resveratrol increased apoptosis induced by CSE. HBE1 cells were pretreated with or without 5 μM resveratrol for 24h before being exposed to CSE for 4h. Apoptosis was then determined with annexin V-FITC method. Experiments were performed 4 times and data from one experiment was shown. The number in low-left, low-right, up-left, up-right phase shows the percentage of cells in normal condition, in the early apoptotic stage, in necrotic stage, and in late apoptotic/necrotic stage, respectively.</p><p>Effect of resveratrol on cell growth. HBE1 cells were treated with different concentrations of resveratrol for 0 and 24 h and the cell number was counted. N=3, * P<0.05 compared with vehicle control.</p><p>Effects of resveratrol on CSE-stimulated caspase activity</p><p>HBE1 cells were pretreated with 5 μM resveratrol for 24 h before being treated with/without CSE for 4 and 24 h; and the caspase activity was measured as described in Methods. Values are mean ± SE of three experiments.</p><p>P<0.05 compared with vehicle control (ethanol) of 0% CSE treatment;</p><p>P<0.05 compared with vehicle control (ethanol) of same CSE exposure. Cas 3, caspase 3; cas 9, caspase 9; R, resveratrol; 0, vehicle control (ethanol).</p>

PubMed Author Manuscript

SEIRAS Study of Chloride-Mediated Polyether Adsorption on Cu

Surface-enhanced infrared absorption spectroscopy is used to examine the co-adsorption of a selection of polyethers with Cl\xe2\x88\x92 under conditions relevant to superconformal Cu electrodeposition in CuSO4\xe2\x80\x93H2SO4 electrolytes. In 0.1 mol/L H2SO4, a potential-dependent mixed SO42\xe2\x88\x92\xe2\x80\x93H3O+/H2O layer forms on weakly textured (111) Cu thin-film surfaces. With the addition of 1 mmol/L NaCl, the SO42\xe2\x88\x92\xe2\x80\x93H3O+/H2O adlayer is displaced and rapidly replaced by an ordered halide layer that disrupts the adjacent solvent network, leading to an increase in non-hydrogen-bonded water that makes the interface more hydrophobic. The altered wetting behavior facilitates co-adsorption of polyethers, such as poly(ethylene glycols), polyoxamers, or polyoxamines. Interfacial water is displaced by co-adsorption of the hydrophobic polymer segments on the Cl\xe2\x88\x92-terminated surface, while the hydrophilic ether oxygens are available for hydrogen bond formation with the solvent. The combined polyether\xe2\x80\x93Cl\xe2\x88\x92 layer serves as an effective suppressor of the Cu electrodeposition reaction by limiting access of Cuaq2+ to the underlying metal surface. This insight differs from previous work which suggested that polymer adsorption is mediated by Cu+\xe2\x80\x93ether binding.

seiras_study_of_chloride-mediated_polyether_adsorption_on_cu

INTRODUCTION<!>MATERIALS AND METHODS<!>RESULTS AND DISCUSSION<!>SO42\xe2\x88\x92 Adsorption on Cu in H2SO4.<!>SO42\xe2\x88\x92 Displacement by Cl\xe2\x88\x92.<!>PEG Adsorption on Cl\xe2\x88\x92-Terminated Cu.<!>Effect of Potential.<!>PEG Adsorption on Cu in the Absence of Cl\xe2\x88\x92.<!>Influence of Cl\xe2\x88\x92 Additions on PEG Adsorption.<!>Poloxamer and Poloxamine Adsorption on Cl\xe2\x88\x92-Covered Cu.<!>Poloxamer and Poloxamine Adsorption on Cu in the Absence of Cl\xe2\x88\x92.<!>Influence of Cl\xe2\x88\x92 Additions on Poloxamer and Poloxamine Adsorption.<!>Discussion.<!>CONCLUSIONS<!>

<p>Cu electrodeposition is a key process used in the fabrication of microelectronic circuitry ranging from deep submicrometer logic and memory interconnects to micron-scale through-silicon vias (TSV) for three-dimensional chip stacking. The success of the process stems from surfactant additives that enable void- and seam-free, bottom-up "superfilling" of recessed surface features, such as trenches and vias. 1,2 For submicrometer features, superconformal growth involves competitive adsorption between polyethers (e.g., poly(ethylene glycol) (PEG) and/or its derivatives) that suppress metal deposition and sulfonate-terminated alkyl disulfides and/or related thiols that accelerate Cu deposition.3,4 For larger-scale features, such as TSV, extreme bottom-up filling can occur due to disruption of the polymer suppressor layer by positive feedback with the metal deposition reaction itself.5–8</p><p>In prototypical acidic CuSO4 electrolytes, Cl− is an essential additive influencing the co-adsorption and operation of both polyether inhibitors and sulfonate-terminated alkyl disulfide accelerator species.3–20 In situ scanning tunneling microscopy (STM) and surface X-ray scattering (SXS) measurements have revealed a great deal about the structure and step dynamics associated with potential-dependent phase transitions of the chemisorbed anions, SO42− and Cl−, on low-index Cu surfaces.21–31 At technically relevant concentrations, Cl− displaces SO42− from the Cu surface and facilitates an increase in the rate of the Cu2+/Cu+ inner sphere electron-transfer reaction.32,33 The addition of PEG (Mw = 3400 g/mol) to the electrolyte suppresses the Cu deposition rate by 2 orders of magnitude relative to the H2SO4–CuSO4–Cl− solution.3–17 However, in the absence of halide, negligible inhibition of metal deposition is observed, demonstrating that Cl− is required for the polyether suppressor to function.9–17</p><p>A variety of in situ measurements have been used to examine the relative roles of Cl− and Cu+ in the formation and function of polyether suppressor layers. Ellipsometry measurements of the PEG–Cl− adlayer, in the absence of metal deposition, indicate that a thin (≈0.6 nm) PEG layer is formed on top of the Cl− adlayer while no polymer adsorption is evident in the absence of Cl−.34 An electrochemical quartz crystal micro-balance (EQCM) study indicates that neither Cu+ nor Cu2+ is required to form the suppressor layer.35 In contrast, other experimental studies have invoked Cu+ as the binding agent between the polymer ether oxygen and the halide-covered surface.10,36,37 Among these, a surface-enhanced Raman spectroscopy study ascribed a vibrational feature at 670 cm−1 to Cu+ mediating or binding the polyether oxygen to the Cl−-covered surface in analogy to crown ether complexes and related solid-state poly(ethylene oxide) (PEO)–cation complexation.10,36 The proposed crown ether conformation was used to explain the influence of PEG molecular weight on suppression and feature filling.10,38 However, other Raman studies are at odds with the preceeding result, with only weak and/or transient signals observed, which were most likely related to morphological instabilities that are known to hinder quantitative SERS.39,40</p><p>Imaging the suppressor layer by scanning tunneling microscopy (STM) and atomic force microscopy has proven challenging as tip scanning forces tend to disrupt the polymer due to its modest monomeric binding energy; however, three recent STM studies provide evidence of the formation of two-dimensional (2D) PEG adlayers.41–43 For small PEG oligomers, such as a 5-mer, an ordered (4 × 4) arrangement was imaged on top of Clads/Cuupd/Pt(111) surfaces with a nearest-neighbor modulation of the electron density of 1.1 nm. Increasing the tunneling current to bring the tip closer to the surface revealed the underlying √3 × √3 R30° Cl− adlayer on top of the Cuupd layer.42 Attempts to image higher-molecular-weight polymers (PEG with Mw = 400, 600, and 4000) yielded irreproducible results, which was attributed to the interference between the polymer and the imaging tip. The difficulty in imaging is congruent with the collapsed sphere model derived from an EQCM study of PEG–Cl− adsorption on Cu as well as the loop-train-tail picture of polymer adsorption and more recent observation of the substantial adsorption–desorption dynamics of PEG at hydrophobic solid–liquid interfaces in the dilute coverage limit.11,44 In contrast, a subsequent study of PEG (Mw = 6000) adsorption on negatively charged Au in pH 3 sulfate electrolyte revealed a 2D monomolecular film exhibiting linear, possibly nematic, features within the surface plane consistent with individual PEG chains.43 The planar nature of the arrangement indicates a significant polymer–surface interaction energy compared to the solvation energy of the polymer.45,46 Unlike with Cu, STM and voltammetry indicate that halide adsorption is not necessarily required for PEG adsorption on Au, although EQCM and ellipsometry reveal conditions where halide is required.11,34,41,43 The seemingly divergent observations suggest that a more complete understanding of PEG adsorption should consider both the state of charge and hydration of the respective surfaces.</p><p>Despite these prior efforts, molecular insight into the polymer–halide binding interaction and suppressor function is still lacking. The role of fluxional adsorption–desorption polymer dynamics in determining the leakage currents and breakdown events associated with the passivating layer is unknown. It is unclear if the suppressor layer operates by site blocking, i.e., simply limiting access of Cu2+ to the surface or is directly involved in the metal deposition reaction itself through interactions with the Cu+ reaction intermediate. Likewise, it is not clear whether Cu+ plays a role in binding the polymer to the halide adlayer. Studies of polyether adsorption in other, chemically distinct, systems suggest other possibilities. Among these, multisite noncovalent interactions with molecular solvation and interfacial water structure being perturbed by anion or cation co-adsorption is of particular relevance.47–49</p><p>For example, PEG adsorption on negatively charged mica surfaces is thought to be mediated by differences in the hydration shells associated with co-adsorbing alkali–metal cations.47 Similarly, reports of the assembly and mobility of PEG at hydrophobic solid–liquid interfaces point to the importance of wetting forces in understanding polyether adsorption.44,50,51</p><p>In situ vibrational spectroscopy techniques, such as sum frequency generation (SFG) and surface-enhanced infrared absorption spectroscopy (SEIRAS), enable direct probing of the molecular nature of interface hydration and its potential dependence.50–55 Specifically, enhancement effects associated with nanostructured ultrathin-film electrodes enable SEIRAS to be combined with potential step and titration schemes to study the adsorption dynamics of ionic and molecular species at electrode surfaces. Herein, SEIRAS is used to examine co-adsorption of prototypical polyether–Cl− additives that provide suppression during Cu electroplating.</p><!><p>SEIRAS measurements were performed using a Cu thin-film electrode supported on an optically polished Si prism (PIKE Technologies, Inc.a) in the Kretschmann attenuated total reflection (ATR) configuration. The prism was positioned within the spectrometer using a modified commercial attachment (VeeMAX II, PIKE Technologies, Inc. with an in-house-modified base plate to support the prism) with the incident and exit angles set to 60°. The Nicolet Magna-IR860 Fourier transform infrared spectrometer was equipped with a liquid N2-cooled HgCdTe detector. Spectra were typically recorded at 4 cm−1 resolution with 100 interferometer scans co-added for an acquisition time of ca. 60 s. Measurements were conducted with unpolarized IR radiation, and the optical path of the spectrometer was purged with dry air from a gas generator or evaporated cryogenic N2 for at least 30 min prior to initiating the electrochemical experiments. The spectral region below 900 cm−1 was not accessible due to absorption in the Si prism as evident in the single-beam spectrum for the Si/air and Si/Cu/air interface shown in Figure S1a. The 20 nm Cu film was deposited on the prism surface by physical vapor deposition (PVD) via electron beam evaporation. As shown in Figure S1b, the Cu film is just past the onset of island coalescence, to take advantage of the percolation threshold being associated with the strongest enhancement of vibrational signals.56 In a subset of experiments, a thin Ti adhesion layer was examined to improve the adhesion between Cu and SiO2; however, this resulted in an inverted spectral response that will be reported elsewhere. For electrochemical measurements, a cylindrical Kel-F chlorotrifluoroethylene cell was mounted on top of the horizontal working surface of the Cu-coated Si prism. Electrical contact to the perimeter of the film was provided by a thin annular Cu foil that was mechanically pressed against it by a Teflon-coated O-ring defining the outer diameter of the cell. A Pt coil counter electrode and a Hg/Hg2SO4/K2SO4(sat'd) (saturated sulfate electrode (SSE)) reference electrode were used. All solutions were made with 18 MΩ cm water (Barnstead EasyPure UV). Commercially available chemicals were used for all experiments: analytical-grade H2SO4 (Aldrich) and NaCl (Aldrich), poly(ethylene glycol), PEG77 (Mw avg ∼ 3400, Aldrich), deuterated poly(ethylene oxide), dPEG (Mn avg ∼ 3450 max., 3200 min., Mw/Mn 1.08, Polymer Source), a poloxamer, poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol) PEO2–PPO31–PEO2 (Mn avg ∼ 2000, Pluronic L-61, Aldrich), and a poloxamine, ethylenediamine tetrakis(propoxylate-block-ethoxylate)tetrol (PEO4PPO12)2ED(PPO12PEO4)2 (Mn avg ∼ 3600, Tetronic 701, Aldrich). Schematic drawings of the respective polyethers are shown in Figure 1a.</p><p>A fresh Cu surface was prepared for each experimental run. Preparation involved the following sequence of steps: mechanical polishing of the Si prism with 0.3 μm and then 0.05 μm diamond paste, sonication in Caro's (piranha) solution (75 vol % H2SO4 + 25 vol % H2O2), and drying in flowing N2 or Ar. The prepared crystal was placed in an electron beam evaporator and pumped overnight to a pressure ≤2.7 × 10−5 Pa (2 × 10−7 Torr). Additional Si wafer fragments were placed besides the Si prism to serve as reference and control specimens for X-ray photoelectron spectroscopy examination and voltammetric analysis. In a subset of experiments, the vacuum was further scrubbed prior to film deposition by evaporating Ti while the Si prism was protected by a shield. Metal deposition was initiated by turning the shielded Si prism, with its native oxide-coated surface, toward the Cu source. The rate of film growth was controlled and the final thickness was determined by quartz crystal monitors located in proximity to the prism substrate. The results presented in this paper focus on Cu films deposited at fixed rates of 0.1, 0.05, 0.01, or 0.006 nm/s. No distinctive SEIRAS features, nor trends, were associated with the deposition rate or vacuum conditions.</p><p>SEIRAS experiments were initiated with the addition of Ar-sparged 0.1 mol/L H2SO4 electrolyte to the electrochemical cell. The Cu thin film and adjacent Hg/Hg2SO4/K2SO4(sat'd) (SSE) reference electrode were sequentially covered with the electrolyte, and potential control was established when the counter electrode subsequently made contact, which usually occurred within 1 s. Potential step and additive titration experiments were then performed. Typically, multiple spectra were collected for given electrochemical conditions to establish and verify time stability as a precondition for interpreting subsequent potential difference or titration experiments. Difference spectra are presented as absorbance A, defined as A = −log(I1/I0), where I1 is the intensity of the reflected beam at the potential or concentration of interest and I0 corresponds to that at the specified reference condition. Positive bands correspond to increased adsorption cross section, indicating increased coverage and/or transition moment dipole due to altered orientation of the adsorbing species. Negative bands correspond to the opposite. Changes in the magnitude and shape of the absorption bands were quantified by peak deconvolution using the Voigt or Gaussian peak shape within the Origin 2016 analysis and graphing program.</p><!><p>Voltammetry for Cu deposition from a 0.24 mol/L CuSO4 + 1.8 mol/L H2SO4 electrolyte is shown in Figure 1b. The addition of Cl− and polyethers results in significant suppression of the deposition process due to the formation of a passivating polyether–Cl− layer that blocks access of Cu2+ to the Cu surface. SEIRAS was used to examine adsorption of the individual components and their interactions to gain insight into the structure, dynamics, and function of the overlayer.</p><!><p>A cyclic voltammogram for a 20 nm PVD Cu film in 0.1 mol/L H2SO4 is shown in Figure 2. Metal dissolution occurs at potentials positive of −0.5 VSSE, while proton reduction is evident at more negative potentials. For SEIRAS measurements, the potential was held at, or below, −0.55 VSSE to avoid film dissolution, while the limited adhesion strength of Cu to the oxide-covered Si prism hindered exploration in the hydrogen evolution region. Despite these limitations, the potential window examined (gray bar, inset) overlaps that used for superconformal deposition of Cu interconnects. The reduction wave at −1.050 VSSE and the anodic wave centered near −0.670 VSSE correspond to similar, albeit more well-defined, voltammetric waves previously reported for freshly prepared Cu(111) in a variety of electrolytes.25–27</p><p>Physical vapor deposition of face-centered cubic (fcc) metals on amorphous SiOx surfaces usually results in a (111) out-of-plane film texture. Accordingly, a brief review of prior STM and infrared reflection absorption spectroscopy (IRRAS) studies of Cu(111) in 5 mmol/L H2SO4 is warranted.26,57,58 At potentials >−0.8 VSSE, in the double-layer region, SO42− adsorption occurs rapidly, followed by a much slower reconstruction and expansion of the top Cu surface to form an ordered √3 × √7 R19° mixed SO42− + H5O2+ adlayer.26 Kinetic limitations on the interlayer Cu mass exchange needed to form the SO42−-covered reconstructed surface account for the slow ordering dynamics. At potentials <−0.9 VSSE, SO42− desorption occurs accompanied by rapid relaxation to a 1 × 1 Cu(111) metal surface. Repetitive rearrangements with potential cycling result in significant roughening of the interface. The surface structure is highly sensitive to processing history with the formation of large ordered domains favored by slow potentiodynamic scan rates, or small potential steps, whereas poorly ordered layers are formed during more rapid SO42− adsorption, as evidenced by in situ STM studies.26 IRRAS measurements on Cu(111) revealed a potential-dependent SO42− band, whose intensity increased in a monotonic, but nonlinear, fashion with potential.57,58 At the same time, a linear Stark shift of 55 cm−1 V−1, from 1205 to 1225 cm−1, was observed based on the reference spectra collected at a potential negative of the reduction wave that marks the lower limit of the "double layer" regime. The potential dependence of the SO42− intensity, and thereby coverage, was hysteretic while the Stark shift was completely reversible.58 Despite the kinetic constraint, the saturation IRRAS intensity and its vibrational energy were largely independent of adlayer ordering. There are no firm reports of ordered SO42− layers on other low-index Cu surfaces in acidic media.</p><p>SEIRAS experiments on the thin PVD Cu films were initiated upon the addition of 0.1 mol/L H2SO4 with the electrode poised at −0.65 VSSE. Individual spectra include substantial contributions from electrolyte species that lie beyond the double-layer region.53,56 However, by taking the difference between sequential spectra collected at different potentials, or before and after titration of a dilute species, the contributions associated with bulk electrolyte species are effectively nulled and the sensitivity of SEIRAS to changes in interface species are revealed. For example, Figure S2 shows spectra referenced to a spectrum collected at −0.65 VSSE. The bands near 1234 cm−1 capture increased SO42− coverage at −0.55 VSSE versus a net loss at −0.8 VSSE. Changes in the water-bending mode, δ(HOH), near 1650 cm−1 and stretching modes, ν(OH), between 3200 and 3600 cm−1 are also evident. The potential-dependent trends for adsorbed SO42− were reproducible with potential cycling, as well as between independent experiments, while the water modes continued to evolve with cycling.</p><p>To determine the potential dependence of anion coverage, reference spectra are ideally taken at potentials that correspond to an "adsorbate-free" surface. The negative point of zero charge (pzc) of Cu, i.e., −0.98 to −1.36 VSSE, combined with the tendency of the Cu films to delaminate from the Si prism at such negative potentials made this difficult to implement.59 As a result, difference spectra were referenced to the most negative value reliably examined, namely, −0.85 VSSE. Data collection was initiated immediately after stepping to the specified potential, and once acquisition was complete, typically within a minute, the potential was stepped in the positive direction, typically in 0.05 V increments, and the process repeated. As shown in Figure 3a, a monotonic increase in the intensity of the major SO42− band at ≈1225 cm−1, accompanied by a monotonic decrease in the smaller neighboring peak at 1114 cm−1, occurs between −0.80 and −0.55 VSSE. The complete spectra with the corresponding water-bending modes δ(HOH), near 1650 cm−1, and stretching modes ν(OH), above 3000 cm−1, are shown in Figure S3a. The bipolar characteristic associated with the dominant ∼1225 cm−1 band is related to the choice of reference potential, whereby the negative portion of the spectra reflects the Stark shift of species previously adsorbed at the reference potential. The spectra were fit to three peaks, as shown in Figure 3b, with the peak wavenumber and intensity of the components summarized in Figure 3c,d, respectively. Among the spectral components, only the 1205–1230 cm−1 band (SEIRAS band 1) exhibits a Stark shift (≈33–35 cm−1 V−1). Arbitrary normalization of the potential difference spectra to that at −0.85 VSSE, combined with the absence of an obvious indication of saturated band intensity at the most positive potential, hinders determination of the absolute SO42− coverage. Damage to the Cu film by faradaic reactions such as metal dissolution or hydrogen evolution precluded the use of an expanded potential range that might reveal saturation.</p><p>Potential difference spectra highlight changes in the intensity and frequency of the vibrational bands but obscure modes that have minimal potential dependence. Displacement reactions offer an alternative means to determine the SO42− coverage. For Cu surfaces, halides are suitable candidates as they adsorb more strongly than SO42−.21–27,60 Addition of 1 mmol/L Cl− to the electrolyte results in complete displacement of SO42− at −0.65 VSSE, as revealed by the four negative titration bands in Figure 3e. In addition to the strong band centered at 1215 cm−1, a second peak near 1180 cm−1 was necessary to fit the spectra, along with the smaller adjacent band near 1115 cm−1 and the solitary band at 968 cm−1, close to the Si prism spectral cutoff. The combined integrated intensity of the 1215 and 1180 cm−1 desorption peaks (band 1 + band 2) in Figure 3e exceeds by a factor of 4–5, that seen in the potential difference spectra in Figure 3a. This indicates that a significant SO42− coverage is present at the reference potential (−0.85 VSSE) used to generate the difference spectra shown in Figure 3a. The potential difference spectra of Figure 3a are offset by the intensity loss spectrum (Figure 3e) for the titration displacement experiment at −0.65 VSSE to account for this nonzero coverage. The potential dependence of the combined 1215 and 1180 cm−1 bands derived from this procedure is scaled to the value at −0.55 VSSE and compared to the similarly scaled integrated intensity of the ≈1215 cm−1 band from the IRRAS study of Cu(111), as summarized in Figure 3f.58 We note that the published Cu(111) spectra were also asymmetric and could be modeled by two correlated symmetric Voigt functions. As the respective SEIRAS and IRRAS measurements were performed in electrolytes with different H2SO4 concentrations and reference electrodes, the potential axis for the Cu(111) literature data was offset, taking −0.680 VSSE to correspond to 0.0 VRHE, for comparison of the coverage evolution with the present results. The black arrows in Figure 3f indicate the hysteresis observed between the adsorption and desorption processes for the Cu(111) IRRAS measurements.58 The favorable overlap of the normalized intensity of the Cu thin-film data (sum of the 1221–1229 cm−1 (band 1) and 1186 cm−1 (band 2) components) with that for SO42− adsorption on Cu(111) (1200–1225 cm−1) is noteworthy. The steep increase in the 1215 cm−1 band intensity near −0.9 VSSE marks the onset of SO42− adsorption, followed by the more gradual approach to saturation at more positive potential.</p><p>The ca. 30–38 cm−1 V−1 Stark shift of the dominant ≈1225 cm−1 peak in the Cu thin-film SEIRAS measurements, summarized in Figure 3c, differs from the 60–55 cm−1 V−1 reported for Cu(111).57,58 The peak band energy for SO42− displaced by Cl− at −0.65 VSSE (Figure 3e) is 1215 cm−1, shifted slightly (−10 cm−1) from the peak position observed in the potential difference spectra referenced to −0.85 VSSE. The respective experimental values at −0.65 VSSE, shown in Figure 3c, bracket those reported for Cu(111) while the anticorrelated nature of the 1221–1229 cm−1 (band 1) and 1186 cm−1 (band 2) components reflects convolution of coverage changes and Stark shift captured in the difference spectra. Contributions associated with structural dispersion of adsorption sites on the (111) textured, but nonetheless polycrystalline, Cu thin film, relative to Cu(111), may also contribute to the difference in the observed Stark shift. Previous transient measurements on Cu(111) show that the SO42− coverage and associated Stark shift are established quickly relative to the formation of the √3 × √7 R19° mixed SO42−–H3O+/H2O adlayer, indicating that extended in-plane ordering is a second-order effect relative to SO42− binding to (111) surface segments.26,57,58 An additional source of dispersion between the experiments is the pH, 0.1 mol/L H2SO4 (SEIRAS) versus 0.005 mol/L H2SO4 (IRRAS), which may alter the degree of protonation in the adsorbed sulfate layer, i.e., SO42−/HSO4−. To explore this question, the SEIRAS experiment was repeated using deuterated reagents, and the potential-dependent spectra from one of two experiments are summarized in Figure S3b. As shown in Figure S4, the Stark shift (≈44 ± 3.3 cm−1 V−1) over the 0.25 V window was slightly altered and the nominal peak positions shifted ≈6 cm−1; however, after correcting for the different reference state, −0.8 versus −0.85 VSSE for the deuterated versus conventional experiment, the difference falls within the 4 cm−1 measurement uncertainty, indicating that the SO42−, not HSO4−, accounts for the dominant 1220–1240 cm−1 band.</p><p>In contrast to the ≈1215 cm−1 band, no Stark shift was evident for the weaker 1114 cm−1 band (band 3, Figure 3c). Repetition of the potential difference study of Figure 3 performed with 88 μmol/L PEG in the electrolyte revealed a negligible impact on SO42− spectra (Figure S4). Possible overlap exists between the C–O–C PEG backbone modes and the SO42− band; however, the complete set of measurements, vide infra, indicate either minimal interaction between solvated PEG and adsorbed SO42− or at least negligible potential dependence for whatever limited amount of PEG is co-adsorbed.</p><p>SEIRAS and IRRAS are sensitive to vibrational modes that have a significant transition dipole component aligned with the local surface normal, with the intensity proportional to surface coverage and the square of the transition dipole moment. In principle, adsorption of SO42− or HSO4− may occur via one, two, or three of the oxygen atoms, with the energy and intensity of the vibrational modes of the respective adsorbed species being perturbed by the different symmetries. Table S1 provides a summary of spectral assignments for solvated sulfate species derived from ATR measurements of various electrolytes performed using the Si prism covered with its native oxide (Figures S5–S9). The results are in good agreement with literature results obtained in a transmission geometry.61 For 0.1 mol/L H2SO4, dissociation of the diprotic acid (pKa = 1.9) is incomplete and the electrolyte contains 0.11 mol/L H3O+, 0.09 mol/L HSO4−, and 0.01 mol/L SO42−. Accordingly, HSO4 might be expected to be the dominant adsorbed anion. However, in situ SERS studies of Cu in 1 mol/L H2SO4 indicate that SO42− is the adsorbed species, evident by a large shift and substantial broadening of the totally symmetric (Raman-active, IR-forbidden) SO42− vibrational frequency from 982 cm−1 for the dissolved species to 967 cm−1 for the anion adsorbed on the roughened Cu surface.62,63 The tetrahedral (Td) symmetry of free SO42− is lowered by adsorption to either C3v or C2v with three or four active bands, respectively.57,58,61 The nominally IR-forbidden 967 cm−1 band is also evident in the SEIRAS sulfate displacement spectra in Figure 3e congruent with the decreased symmetry accompanying its adsorption. As with the ≈1215 cm−1 SEIRAS band (Figure 3b), the 967 cm−1 Raman peak was insensitive to isotope H2O–D2O exchange, again pointing to adsorbed SO42−.62 Deconvolution of STM images of SO42− adsorption on Cu(111) obtained at high tunneling conductance was used to infer a C2v configuration with bridging coordination via two oxygen atoms.26,57,58 However, more recent work on √3 × √7 R19° mixed SO42−–H3O+/H2O adlayers formed on other close packed (111) fcc surfaces, namely, Pt, Ir, Pd, Rh, Au, as well as (0001) hexagonal close-packed Ru, favors the C3v assignment.64–66 Common to these isostructural anion–water adlayers on close packed metal surfaces is an intense IRRAS band between 1150 and 1310 cm−1 and a weaker band near 950 cm−1. Density functional theory (DFT) calculations for Pt(111) in sulfuric acid provide an explanation for the energy, intensity, and positive Stark shift of the strong 1200–1250 cm−1 band consistent with adsorbed SO42−.67,68 The intense band is ascribed to the large dynamic dipole moment and favorable alignment of the uncoordinated ν(S–O) stretching mode of SO42− bound to the surface by the other three oxygen atoms.67–69 The weaker band near 950 cm−1 corresponds to the infrared-inactive symmetric ν(S–O) stretching mode of SO42− that becomes active due to symmetry reduction that accompanies adsorption. The spectral range for the 950 cm−1 band was only sampled in a subset of measurements, although the band is clearly present in the SO42− displacement spectra (i.e., Figure 3e). The weaker 1114 cm−1 band that decreases with potential in Figure 3a is attributed to the loss, or conversion, of physisorbed SO42−. The feature is also evident in the complementary deuterated experiment shown in Figure S3b consistent with the triply degenerate ν(S–O) stretching mode for solvated SO42− (Table S1).</p><!><p>The halides Cl−, Br−, and I− adsorb strongly on group IB metal surfaces and, depending upon the potential, form high-coverage ordered phases on low-index surfaces, as revealed by STM and surface X-ray diffraction.21–31 As shown in Figure 4, the addition of 1 mmol/L Cl− to 0.1 mol/L H2SO4 results in rapid displacement of SO42− from the Cu surface held at −0.65 VSSE, as evident by the negative bands centered at 1215 and 1115 cm−1 (and 965 cm−1, as shown in Figure 3e). Displacement of SO42− by Cl− was also reported in prior Raman studies.36,60 Importantly, the SEIRAS images reveal that the change in adsorbed anion is accompanied by significant time-dependent perturbation and rearrangement of the interfacial water structure, as shown by the distinct changes in the δ(HOH) bending (≈1600 cm−1) and ν(OH) stretching modes (3000–3600 cm−1). As seen in Figure 4 following initial halide injection (+0 min), negative ν(OH) peaks, including subtle changes in the hydronium modes, are associated with the displaced SO42−–H5O2+ adlayer, while positive peaks reflect the restructured hydration layer that develops adjacent to the adsorbed halide. Specifically, the increase at 1625 cm−1 suggests enhanced alignment of the δ(HOH) water mode adjacent to the halide layer, while the decrease at 1663 cm−1 is due to disruption of the H3O+ species that accompanies desorption of the SO42−–H5O2+ adlayer.70–72 At the same time, the slight rise in the broad background intensity near 1750 cm−1 is congruent with a slight increase of hydronium (Figures S7–S9) that may serve to screen the negative halide charge. At higher wavenumber, the ν(OH) decrease between 2750 and 3500 cm−1 manifests the displacement and desorption of the water associated with the SO42− adlayer along with changes in the hydronium continuum, while the more distinct and narrow increase at 3605 cm−1 is ascribed to the formation of non-hydrogen-bonded water.52,54,55,73,74 Two additional subtle bands, the minor decrease at 1430 cm−1 and an increase near 1518 cm−1, are common to the difference spectra collected immediately after Cl− titration. The inflections overlap those seen in difference spectra between acids and water (Figures S7–S9) and, according to recent theory, are ascribed to proton shuttling that involves a close coupling between bending and stretching modes.74,75 The changes convolve the loss of hydronium associated with the displaced SO42− + H5O2+ adlayer with the evolution of screening charge adjacent to the adsorbed Cl− adlayer.</p><p>In the first approximation, disruption of the hydrogen-bonded network by halide adsorption is analogous to that associated with the solvation shell of free Cl−.76 ATR measurements of concentrated NaCl–water electrolytes clearly reveal disruptions of the hydrogen bond network of water, as shown in Figure S10. Due to surface enhancement effects, the 3600 cm−1 mode for the Cl− adlayer on Cu in Figure 4 greatly exceeds the bulk signal associated with the additional 1 mmol/L NaCl. Polarization provided by surface-bound Cl− might be expected to draw dangling hydrogen of the free OH, although an alternative conformation might have the water molecules straddling the halide or aligned with nearest-neighbor halide species such that the H2O quadrupole is aligned to the surface normal. The first non-hydrogen-bonded configuration can be compared to dangling ν(OH) stretch associated with the broken symmetry of the air–water interface.52,54,55 The red shift to lower vibrational energy, from 3700 cm−1 for simple ν(OH) to 3600 cm−1, reflects the nature of the charge–dipole interaction between ν(OH) and Cl−. Importantly, a recent low-energy electron diffraction (LEED)-IV and DFT study of H2O adsorption on Cu(100) c(2 × 2)Cl− indicates the formation of a weakly bound water bilayer with 50% of the first water layer H facing the Cl− adlayer congruent with the present results.77 In the case of another coinage metal surface, that of Au, a similarly narrow ≈50 cm−1full width at half-maximum peak located between 3610 and 3582 cm−1 has been reported to accompany halide adsorption from 1 mmol/L KX (X = Cl−, Br−, or I−) electrolyte.78 A slight dependence on the cation, Li+ versus K+ was observed, while in the present experiments, electrolyte screening of negative halide charge is provided by H3O+. More recently, an SFG study of water–Au interactions in 1 mol/L HClO4 has revealed a free ν(OH) band at 3680 cm−1, whose intensity reaches a maximum near the pzc.79 As the static dipole moment bisects the HOH molecule, it was argued that as the negative charge on Au increases further, neither OH bond will be perpendicular to the metal surface; rather, a balance between orientation and density effects will ensue. In a related vein, beyond the strong 3669 cm−1 band of free OH band, SFG studies of the immiscible water/CCl4 interface reveal an additional small peak at 3600 cm−1, which was assigned to weakly bound monomeric water with both H facing the CCl4 phase.54,73 Summarizing, the increase in non-hydrogen-bonded water indicates the development of a more hydrophobic interface congruent with disruption of the water structure that underlies the distinction between hydrophobic versus hydrophilic interfaces.52,54,55,80–82</p><p>Sequential SEIRAS spectra collected following Cl− titration reveal a significant time dependence of the water modes as shown in Figure 4 (and Figure S11). Following halide addition, the ordered ("icelike" or tetrahedral water) ν(OH) modes around 3200 cm−1 and disordered ("liquid" or lower coordination water) ν(OH) modes at 3400 cm−1 increase on a time scale of minutes. Recent literature exploring the structural specificity of such ν(OH) assignments ascribes the blue shift to weakening of the hydrogen-bonding network as captured by coupling between stretching and bending overtones,83 Furthermore, beyond neutral water, the ν(OH) bands also incorporate the Eigen (≈2800 cm−1) and Zundel (≈3200 cm−1) stretching modes of hydronium evident in Figure 4 (and Figure S11).73–75,83 In the present work, the slow evolution of the 3000–3500 cm−1 spectral band, over 8 min, following Cl− addition is most likely correlated to coarsening of the freshly formed, ordered Cl− domains and mesoscopic step structure that impact long-range ordering in the adjacent hydration layer.21–24,28–30 Similar time-dependent microstructural effects on SEIRAS water spectra have been noted for sulfate adsorption on Au.72,84</p><p>The properties of bulk water are strongly influenced by hydrogen bonding between neighboring molecules, while solutes and interfaces disrupt the network to some extent.85,86 At neat water–air interfaces, non-hydrogen-bonded, free OH groups protrude into the atmosphere.54,55 The hydration shell around nonpolar molecular solutes is similarly characterized by the formation of dangling OH bonds, but with the vibrational energy red-shifted relative to that at the water–air interface due to the local electric field.80 For example, the narrow, high-frequency ν(OH) band at 3700 cm−1 observed at the water–air interface downshifts to 3674 cm−1 at the water–oil interface while for neopentanol and related alkane groups in water, the peak shifts to 3661 ± 2 cm−1 and for H–π aromatic ring interactions shifts to 3600 cm−1 have been reported.80,81,87 Accordingly, the band at 3600 cm−1 in Figure 4 is assigned to an increase in non-hydrogen-bonded water, ν(OH), either as the dipole or quadrupole, induced by the negative charge of the Cl−-saturated surface. The increase in non-hydrogen-bonded water at 3600 cm−1 is accompanied by a similar increase in the δ(HOH) scissoring mode at 1625 cm−1, and perhaps a slight increase in the hydronium continuum. With electrode aging, the envelope of hydrogen-bonded water reforms and strengthens as the domain size of the templating ordered Cl− adlayer coarsens. The SO42− displacement experiments were repeated multiple times, e.g., Figure S11, with fresh electrodes to verify that Cl− titration and adsorption yield an increase in the 3600 cm−1 non-hydrogen ν(OH) stretch and the 1625 cm−1 δ(HOH) bending mode. Similar effects were also noted for Cl− displacement of SO42− + D5O2+ in deuterated electrolyte, as shown in Figure S11b. The ν(OH) peak at 2659 cm−1 is ascribed to non-hydrogen-bonded water, while the overlaps between the increase in δ(DOD) with the loss of SO42− is evident. Most importantly, the development of non-hydrogen-bonded water and its association with hydrophobic interfaces have important implications for the co-adsorption of molecular species on halide-covered surfaces.</p><p>Recently, LEED and X-ray surface scattering have been applied to examine Cl− adlayers on (111) and (100) Cu surfaces.28–31,77 Modeling scattering from a Cu(100) c(2 × 2) Cl− surface indicates the halide adlayer templates lateral ordering of the adjacent water and hydronium species.28,30,77 For acid solutions, hydronium is thought to preferentially occupy hollow sites in the anionic layer, while the inner (anionic, Cl−) and outer (cationic, H3O+) components of the Helmholtz layer compete for water to form their respective solvation shells.28 Accordingly, the potential-dependent order–disorder phase transitions associated with halide adlayers provides a useful avenue to probe the connection between adsorbed anions and the neighboring water structure. As shown in Figure 5, SEIRAS images following a potential step from −0.65 to −0.8 VSSE reveal a decrease in the δ(HOH) and non-hydrogen-bonded ν(OH) water bands due to a combination of partial desorption and disordering of the Cl− adlayer. The absence of any sign of sulfate adsorption indicates that the coverage of the disordered Cl− layer is still significant enough to prevent sulfate adsorption despite the latter being 100-fold greater in concentration. A similar result was seen in a SERS and surface X-ray diffraction study.30,60 When the potential is stepped to a more positive value of −0.55 VSSE the free OH and other water vibrational modes are intensified relative to the values observed at −0.65 VSSE. The potential dependence of the 3000–3500 cm−1 ν(OH) hydrogen-bonded water envelope tracks that of the non-hydrogen-bonded water near 3612 cm−1 congruent with templating between a compact ordered halide adlayer and neighboring water structure. The minor changes at 1238 and 1440 cm−1 are ascribed to changes in the hydronium shuttling and umbrella modes.75</p><!><p>PEG adsorption was examined both in the presence and absence of Cl−. Accordingly, following the SO42− adsorption experiments, 1 mmol/L Cl− was added to the 0.1 mol/L H2SO4 electrolyte and displacement of the SO42−–H30+/H20 adlayer and the development of the narrow δ(HOH) and ν(OH) water modes due to Cl− adsorption at −0.65 VSSE was verified, as shown by the spectrum in Figure 6. This was followed by the addition of 88 μmol/L PEG (Mw = 3400 g/mol) to the cell, and the difference spectrum reveals PEG adsorption with multiple peaks for the different polymer modes. The large multicomponent peak with a maximum intensity near 1100 cm−1 and the narrow adjacent peak at 1030 cm−1 are ascribed to combinations of C–O and C–C polyether backbone vibrations and CH2 rocking modes. Four smaller peaks between 1200 and 1500 cm−1 are associated with the CH2 twist, CH2 wag, and CH2 scissor modes, while the CH2 stretches are evident between 2850 and 3000 cm−1.88–90 PEG adsorption is accompanied by a marked decrease in the water modes, including the narrow non-hydrogen-bonded ν(OH) stretch at 3600 cm−1 and the δ(HOH) bending mode at 1620 cm−1, both formerly associated with the saturated Cl− layer, and the broad loss of intensity between 3000 and 3500 cm−1 for hydrogen-bonded ν(OH) water modes. The negative δ(HOH) peak has a notable shoulder at higher wavenumber, near 1660 cm−1, which in combination with the sloping background beneath the CH2 stretching modes, 2850–3000 cm−1, is attributed to a decrease or rearrangement of hydronium at the interface. In brief, PEG adsorption disrupts and displaces the hydration layer adjacent to the halide adlayer as its hydrophobic character favors polyether adsorption over non-hydrogen-bonded water. The hydrophobic –CH2–CH2– segments are drawn to the Cl− adlayer, while the lone pair electrons of the intervening ether –O– contribute to the formation of the hydrogen bond network with the adjacent solvent such that the free energy of the Cu–Cl−–PEG layered interface is minimized.</p><p>Further insight into the structure of the adsorbed polyether layer is obtained by comparison to spectra for the dissolved and crystalline forms. Spectra for crystalline PEG powder were collected using a KBr mull in transmission mode, while a series of PEG–water and PEG–0.1 mol/L H2SO4 solutions were examined by ATR using the Si prism with its native oxide film. Representative results for crystalline and solvated PEG (Mw = 3400) along with the deuterated variants are shown in Figures S12–S17. Peak assignments are based on prior literature that include an assessment of the dichroic nature of textured samples, as summarized in Tables S2 and S3.88,89,91–93</p><p>The concentration dependence of the spectral features of solvated PEG was used to quantify the surface enhancement associated with spectra for PEG adsorption on the Cl−-covered Cu films. The difference spectra for PEG dissolved in water are shown in Figure S12, and the magnitude of selected peaks are summarized in Figure S13. Without surface enhancement from the Cu film, solvated PEG does not contribute significantly to the ATR spectra for the 88 μmol/L PEG solution. The enhanced signal associated with chemisorption on the Cl−-covered Cu surface ranges from a 150-fold increase in absorbance for the 1093 cm−1 C–C–O modes to a 450-fold increase for the 2885 cm−1 methylene stretch modes, as evident in Figure S13. The variation between individual bands reflects the conformation of the adsorbed versus solvated polymer, as detailed below. The spectra in Figure S12 also reveal the impact of solvated PEG on the water structure itself. Specifically, for additions of up to 16 mmol/L PEG, a decrease in the non-hydrogen-bonded ν(OH) water is evident due to the hydrogen-bonding sites provided by the polyether.</p><p>Examination of the C–C–O– backbone and CH2 modes of the adsorbed PEG–Cl− suppressor layer reveals several important differences relative to solvated PEG. The intensity ratio of the –C–C–O– envelope, 1000–1200 cm−1 in Figure 7a (and Figure S18a), to the methylene bands, 2700–3100 cm−1 in Figure 7b (and Figure S18b), decreases from 4.75 for the solvated polymer to 2.5 for the adsorbed layer. The anisotropy reflects the structure and orientation of the adsorbed PEG layer convolved with the IR selection rules, SEIRAS only being sensitive to components of dipole transitions that are perpendicular to the local surface normal. The change in the ratio of the C–C–O envelope to the CH2 modes implies a net preferential arrangement of the CH2 modes along the local surface normal and/or preferential arrangement of the C–C–O within the surface plane. Other spectral features of interest are the increased intensity of the 1030 cm−1 band, changes in the component contributions to the ≈1095 cm−1 –C–C–O– and methylene envelope, and variations in the other CH2 modes as indicated in Figure 7c.</p><p>A close inspection of the multicomponent peak envelope centered near 1100 cm−1 in Figure 7a (the deconvolved components shown in Figure S18a and listed in Table S4) reveals that the ratio of 1100/1067 cm−1 and 1100/1134 cm−1 components for the adsorbed polymer are significantly reduced compared to solvated PEG, while the opposite is true for the adjacent band at 1030 cm−1. Previous polarized infrared spectra for highly oriented crystalline PEG specimens (summarized in Table S3) provide insight into these differences;92,93 when the main helical axis of PEG lies within the surface plane, the modes exhibiting perpendicular dichroism are favored while the opposite is true for parallel dichroism. Accordingly, with reference to spectra for oriented crystalline PEG and isotropic solvated PEG, the perpendicular modes ν(C–O–C) + r(CH2) at 1060 cm−1, ν(C–C) + ν(C–O–C) at 1147 cm−1, and ν(C–O–C) at 1116 cm−1 of the adsorbed PEG layer are favored over the parallel ν(C–O–C) mode at 1103 cm−1. Likewise, as shown in Figure 7b (the deconvolved components shown in Figure S18b and listed in Table S4), the intensities of the components of the methylene envelope, also affected by dichroism, show an increase in the perpendicular component of the antisymmetric stretch at 2950 cm−1 congruent with the assumption that PEG lies in the plane of the Cl−-covered Cu surface. The same arguments apply to the relative intensity of the rock, twist, wag, and scissor modes, as detailed below.</p><p>In the solid state, crystalline PEG/PEO adopts a helical form with rotation about the C–C bond in the O–C–C–O sequence in the gauche (G) (±60° about the C–C backbone bond axis) conformation, while the C–O–C bond maintains a trans (T) (180° rotation) configuration.89,92,93 The trans–gauche–trans (T–G–T) O–C–C–O helical form has the hydrogen in CH2 pointing outward, while the ether oxygen points inward toward the helical axis. When dissolved in water, hydration interactions between the polar ether, nonpolar alkyl groups, and surrounding water stabilize the T–G–T conformation with hydrogen bonding between ether O and water.88–91 The situation is optimal when the C–C bond is G such that the 0.29 nm spacing between neighboring ether O atoms is close to the 0.285 nm O–O distance in liquid water. Defects and variations in the water-stabilized helical conformations are conferred by ±G rotation about the C–C bond, while deviations from the T conformation about the C–O axis provide important structural flexibility. Interestingly, for higher PEG concentrations in water, chain interactions are dominated by hydration forces, and the formation of flexible plates one molecule in thickness has been suggested.91 Adsorption is associated with additional interactions due to the double-layer electric field and wetting forces that can influence polymer assembly on the Cl−-covered Cu surface. In principle, this can include configurations that deviate substantially from the helical conformation that, among other variants, could include arrangements where the polar ether and nonpolar alkyl groups are biased to opposite sides of the molecule, whereby the amphiphilic character is expressed and stabilized by the metal–electrolyte interface.90 Indeed, the use of electrode polarization to induce conformation bias has been recently demonstrated for crown ether moieties adsorbed on graphene surfaces.94 In a similar fashion, the impact of co-adsorption of cationic species has also been explored.47,49,94</p><p>The CH2 modes evident in Figure 7c include the antisymmetric CH2 twist at 1256 cm−1, the symmetric CH2 twist at 1292–1307 cm−1, the antisymmetric CH2 wag at 1333–1350 cm−1, and the CH2 scissor at 1446–1474 cm−1. The CH2 twist and wag modes are diagnostic of the G/T conformation around the C–O and C–C bonds, respectively.88,89 The CH2 twist modes at 1292 and 1307 cm−1 correspond to T and G conformations about the C–O bond, while CH2 wag modes at 1325 and 1350 cm−1 correspond to the T and G states about the alkyl C–C bond, respectively. The spectra in Figure 7c show that the G form of the asymmetric CH2 wag at 1350 cm−1 dominates the T band at 1325 cm−1 for both the PEG–Cl− layer and the solvated polymer. This is in good agreement with literature results for short- (Mw = 600 g/mol) and long-chain (Mw = 2000 g/mol) PEG dissolved in water, indicating that the water-stabilized G conformation about the C–C bond of fully solvated species is maintained in the adsorbed PEG–Cl− layer.88 In contrast, the conformation about the C–O bond is substantially altered by adsorption on the Cl−-covered surface. For dissolved PEG, the 1305 cm−1 (G) to 1288 cm−1 (T) peak height ratio for the CH2 twist band is close to unity, consistent with prior literature results (see Figure 10 in ref 88). However, for PEG adsorbed on the Cl−-covered surface, the 1307 cm−1 G band is substantially greater than the 1292 cm−1 T peak, indicating a substantial increase in the G conformation about the C–O bonds.</p><p>In addition to the increased G conformation about the C–O bonds, a survey of the literature indicates that the prominent narrow band at 1030 cm−1, ascribed to a combination of C–O and C–C polyether backbone and CH2 rocking modes, is not widely observed and may be taken as another important marker of PEG conformation change upon adsorption on the Cl−-covered Cu surface. A normal coordinate analysis of the hybridized coupling between various –C–C–O– backbone modes of CH3(OCH2CH2)nOCH3 oligomers with n = 2, 3, and 6 suggests that the 1030 cm−1 band is associated with either the xTG-TGx or xGG-GGx sequence (among the 72 different conformations of CH3O–CH2–CH2–O–CH2–CH2–OCH3 examined), with the caveat that neither hydrogen bonding nor related chain–chain or chain–surface interactions were considered in the analysis.89 A recent STM study of PEG adsorption on negatively charged Au revealed a monolayer film with extended winding, linear features (Figure 2f of ref 43) congruent with individual polymer chains. The surface-confined packing and meandering nature of individual PEG chains is consistent with the measured increase in G conformation about the C–O bond. The strength of the 1030 cm−1 band, relative to that for the solvated state, indicates disruption of PEG's helical structure congruent with additional G conformation about the C–O bonds. The above features, combined with quenching of the non-hydrogen-bonded water modes associated the Cl−-terminated surface, suggest a structural bias with CH2 groups facing the halide-covered metal, while the ethereal O forms hydrogen bonds with the adjacent solvent. Further support for this interpretation is provided by an electrospray mass spectrometry study that indicates an association between Cl− and short-chain polyethers.95 Accompanying molecular dynamics simulations suggest that the halide is coordinated with –CH2– groups of the polymer to form quasi-cyclic structures, analogous to crown ether cationic complexes but with the polarity inverted.</p><p>Performing the same SEIRAS experiment in the absence of halide (Figures 7a,b and S16–S18 and Table S4) results in a much smaller PEG signal; the intensity of the 1000–1200 cm−1 –C–C–O– backbone and 2750–3050 cm−1 CH stretch envelope being 0.38 and 0.29, respectively, of that for the PEG–Cl− suppressor layer. Furthermore the shape of the –C–O–C– backbone and CH2 modes have features in common with solvated species, indicating weak physisorption of the polymer.</p><p>PEG co-adsorption with Cl− was also examined using the deuterated polymer, dPEG, as summarized in Figure S17. Consistent with PEG, there is a relative attenuation of C–C–O modes polarized along the chain axis, reflecting the anisotropy associated with dPEG adsorption as a surface-confined train on the Cl−-covered Cu electrode. In the absence of Cl−, only a very weak spectrum is observed for dPEG congruent with the results for PEG alone.</p><!><p>As PEG adsorption is facilitated by the effect of Cl− on interfacial water structure, the perturbation of the underlying halide layer by its potential-dependent order–disorder phase transition was used to further probe the nature of polyether co-adsorption. Prior work on Cu(100) (and related unpublished work on Cu(110)) reveals that the Cl− order–disorder transition on the respective crystal surfaces in 1 mmol/L NaCl + 0.1 mol/L H2SO4 is shifted −50 mV by the addition of PEG, indicating stabilization of the ordered Cl− phase by polyether co-adsorption.19,25,29 Difference spectra following a potential step to values more positive and negative of −0.65 VSSE are shown in Figure 8 and suggest disruption of the PEG–Cl− layer at negative potentials. At more positive potentials, −0.55 VSSE, an additional increment of PEG adsorption is manifest as a slight increase of the –C–O–C– backbone band (1110 cm−1) and CH2 stretch region (2800 cm−1) accompanied by a decrease in the non-hydrogen-bonded water ν(OH) near 3600 cm−1 and the δ(HOH) at 1625 cm−1. In contrast, stepping to −0.80 VSSE leads to a loss of intensity of the PEG backbone mode at 1029 cm−1, –C–O–C– and CH twist (G) modes near 1311 cm−1, scissor mode at 1443 cm−1, and C–H stretch modes between 2872 and 2954 cm−1. The paradoxical increase in the 1110 cm−1 band may reflect reorientation and partial solvation of the polymer backbone segments related to the loss of the 1029 cm−1 mode. Partial desorption and/or rearrangement of the polymer is accompanied by an increase in the δ(HOH) at 1625 cm−1 and the non-hydrogen-bonded ν(OH) water stretch near 3600 cm−1, along with a weaker increase in the broad envelope for hydrogen-bonded water. The changes reflect strengthening of non-hydrogen-bonded water modes on surface regions where PEG is lost from the interface. The disruption of the PEG layer at negative potential is congruent with and underlies the increase of the metal deposition rate at negative potentials evident in Figure 1 and in numerous other studies.3,5,8–17 It is notable that the potential induced alterations of the water mode are only 10–20% the size of, and anticorrelated with, those observed when the experiment is performed in the presence of Cl− alone (i.e., Figure 5), which reflects the cooperative and competitive interactions between PEG, Cl− and water during co-adsorption.</p><!><p>The importance of halide adsorption to polyether co-adsorption was also examined by reversing the order of additive addition, namely, PEG followed by Cl−. As in Figure 7a, Figure 9a shows detailed difference spectra collected at −0.65 VSSE after the addition of 88 μmol/L PEG to 0.1 mol/L H2SO4 revealing a small increment of PEG adsorption. The vibrational bands are significantly smaller than those obtained from the PEG layer formed in the presence of Cl−. The intensity of the 1100 cm−1 multicomponent peak for the backbone C–O–C modes of PEG on Cu is 38% that observed for the PEG–Cl− layer on Cu. PEG adsorption is accompanied by a measurable but small loss of sulfate intensity near 1216 cm−1. The PEG layer formed in the absence of Cl− clearly adopts a different structure as reflected by the absence of the associated signature mode at 1030 cm−1. Similarly, the 1307 cm−1 symmetric twist is greatly diminished, its intensity of similar order to the 1290 cm−1 peak, indicating that the proportion of gauche C–O bonds for adsorbed PEG is significantly less than that for the PEG–Cl− layer. In fact, the 1290/1307 cm−1 peak ratio is close to unity, like that reported for the fully solvated polymer.88</p><!><p>The addition of Cl− to electrolyte already containing PEG induces significant changes, as shown in the difference spectra in Figure 9a. Displacement of the SO42− species by Cl− adsorption is evident from the negative peaks centered at 1217, 1117, and 969 cm−1, similar to its displacement observed in the absence of PEG. In the presence of PEG, subsequent Cl− adsorption is accompanied by the development of the signature peak at 1030 cm−1 and an increase in the intensity at 1307 cm−1 for the CH2 twist, 1350 cm−1 for the CH2 wag, and 1447 and 1470 cm−1 for the CH2 scissor. The 1030 and 1307 cm−1 bands reflect a significant increase in the population of C–O bonds in the gauche conformation. The increased PEG coverage associated with Cl− introduction and adsorption is also reflected in the increased intensity of the CH2 stretch spectrum shown in Figure 9b and relative strengthening of the 2878 and 2954 cm−1 CH2 modes. Summing the methylene stretch spectra for the sequential addition of PEG and Cl− gives a favorable agreement with that obtained for the inverse order, namely, PEG adsorption on the Cl−-covered Cu surface. The related increase in the polyether backbone modes centered near 1095 cm−1 in Figure 9a is partly obscured by the loss of SO42− that accompanies the halide addition. Nonetheless, the Cl−-induced increase in polyether coverage inferred from the methylene stretch band 2878–2954 cm−1 for PEG and PEG–Cl− compares favorably to the increase in the other CH2 polymer modes. Examination of the complete spectral window reveals the loss of hydronium and water with the displacement of SO42− and co-adsorption of Cl− and formation of the PEG–Cl− layer (Figure S19). Within the variation observed between multiple experiments, the shape and magnitude of the linear combination of the PEG and Cl− spectra in Figure 9a compare favorably to those of the PEG–Cl− spectra. The demonstration that the final suppressor layer is essentially independent of the order of additive addition is consistent with ellipsometry measurements, which indicated that the optical thickness of the PEG–Cl− layer is independent of the order of additive addition.34</p><p>Numerous electrodeposition studies have demonstrated that Cl− is required to form an effective polyether suppressor layer for inhibiting Cu deposition reactions.3–17 Comparing the PEG–Cl− layer to PEG adsorbed in the absence of Cl− indicates that the conformation(s) associated with increased intensity of the 1030 and 1307 cm−1 band is associated with the formation of an effective blocking layer. The increased band intensity for co-adsorbed PEG–Cl−, versus PEG alone, reflects additional mass density and thereby a more compact overlayer. Effective packing of the nominally linear molecule on the hydrophobic Cl−-covered surface will involve kinks and in-plane loops that necessarily involve deviations from the polymer's native helical form that manifest in the increase in G conformations about the C–O bonds in the polymer backbone. At the same time, the dominant G arrangement of the C–C bonds supports effective coupling of ethereal oxygen to the hydrogen bond network in the adjacent electrolyte.</p><!><p>The aspect ratio of recessed features that can be filled by superconformal copper deposition is dependent on the dynamic range available between suppressed and actively growing surfaces.3–20 The search for more effective suppressors has largely focused on more complex polyethers ranging from block copolymers to star-shaped block copolymers as well as exploration of the role of fixed charges.5,15,96–102 Herein, two different classes of polyethers, poloxamer and poloxamine, have been selected to examine the role of oligomer chemistry and secondary structure in the adsorption process (see Figure 1).103–106 Poly(propylene oxide) (PPO) is the largest component in both molecules. The methyl side group introduces additional hindrance to hydration that sharply increases the hydrophobic character relative to poly(ethylene oxide) (PEO). For higher-molecular-weight triblock PEO–PPO–PEO poloxamers, variations in hydration often result in the formation of a polymer brush conformation, where the central PPO segment is segregated to surfaces while the PEO termini are solvated within the aqueous phase.104 Compared to PEG, hydration forces are expected to favor a more spherical conformation for the PPO core of the poloxamer of interest, PEO2PPO31PEO2. For the poloxamine, (PEO4PPO13)2N(CH2)2N(PPO13PEO4)2, the ethylenediamine core provides additional steric constraint, while protonation of the diamine core gives rise to a fixed charge.105,106 In the present work, the PEO blocks that facilitate solvation of the poloxamer and poloxamine are quite short, a 2-mer and ≈4-mer, respectively, while the hydrophobic PPO core is expected to increase the strength of polymer adsorption at hydrophobic surfaces.</p><p>For typical polymer and Cl− concentrations used for superconformal electrodeposition, inhibition of Cu deposition increases with the development of secondary structural motifs, as shown in Figure 1. SEIRAS experiments probing the co-adsorption of these polymers with Cl− reveal trends similar to that observed with PEG. As shown in Figures 10 and 11, the addition of halide at −0.65 VSSE displaces the SO42−–H3O+/H2O layer and results in the development of significant non-hydrogen-bonded interfacial water (≈3600 cm−1). The subsequent addition of the poloxamer (Figure 10) or poloxamine (Figure 11) results in polyether adsorption on the hydrophobic Cl−-covered surface accompanied by a substantial decrease in both non-hydrogen-bonded and hydrogen-bonded water. For both polymers, the large multicomponent peaks at 1084 and 1088 cm−1, along with the small narrow bands at 1012 and 1014 cm−1, correspond chiefly to C–O–C backbone modes. The 1088 cm−1 poloxamine peak (Figure 11) also includes contributions from the aliphatic ethylenediamine core.</p><p>For reference purposes, spectra for the as-received neat liquid poloxamer (Figure S20a) and poloxamine (Figure S20b) were examined and found to be quite similar. Subtraction of the two spectra reveals contributions between 1020 and 1190 cm−1 that are at least partly attributed to poloxamine C–N modes (Figure S20). For the suppressor layers, the peak energy of the multicomponent C–O–C peak envelope found at 1095 cm−1 for adsorbed PEG–Cl− (Figure 9) shifts to 1088 cm−1 for poloxamine–Cl− and 1084 cm−1 for poloxamer–Cl−. The trend is opposite to that reported for solvated triblock PEO and PPO polymers, presumably due to the interaction with the halide adlayer.107 The CH2 stretch modes between 2800 and 3000 cm−1 are similar for the two polymers with the additional peak at 2976 cm−1 for the antisymmetric stretch of the methyl groups in the PPO segments. Likewise, the symmetric CH3 umbrella mode of the PPO block is evident at 1379–1380 cm−1. Compared to more concentrated solution of larger poloxamers, the CH3 and CH2 band energies suggest that the adsorbed polymer has more in common with isolated chains than micelles.107</p><p>Curve fitting and area measurements of the C–O–C backbone and CH2/CH3 stretch region of the respective polyether–Cl− suppressor layers as well as the neat references are summarized in Figures S21 and S22 and Tables S5 and S6. The ratio of the area of the large multicomponent C–O–C peak to that of the methylene stretch region for the adsorbed polyether–Cl− adlayer is 2.47 for the poloxamer and 3.67 for the poloxamine. The former is similar to the 2.5 for the PEG–Cl− adlayer (Table S4). In both cases, the ratio for the adsorbed layer is smaller than the 4.35 value of the neat, isotropic, liquid polymers. As with PEG, the decrease reflects the anisotropy introduced by adsorption of the respective polymers on the Cl−-covered surface. The weaker change for the poloxamine is attributed to more limited molecular rearrangement during its adsorption due to constraints that arise from branching at the ethylenediamine core that give the polymer a more spherical motif. Compared to the respective neat forms, a relative decrease of the ∼2866 cm−1 and increase of the ∼2932 cm−1 CH2 stretch modes is evident in Figures S21 and S22 for the block polyethers adsorbed on the Cl−-covered surface. The anisotropy associated with polyether co-adsorption is also evident in the red shift of the C–O–C peak envelope of the respective polymers. Comparison to the solvated versions of the respective polyethers would be useful, but this awaits future investigation.</p><!><p>The importance of anion adsorption in the co-adsorption of poloxamer and poloxamine was examined by reversing the order of additive addition at −0.65 VSSE. As shown in Figure 12a,b, the addition of 82 μmol/L poloxamer to 0.1 mol/L H2SO4 leads to weak adsorption similar to PEG, as evident by the small multicomponent peak near 1084 cm−1, the CH3 mode at 1379 cm−1, the scissor modes near 1450 cm−1, and the CH2 stretches between 2850 and 3000 cm−1. On the basis of the size of the latter two bands, the poloxamer coverage is ≈34% that observed for the poloxamer–Cl− surface. The small dip near 1217 cm−1 in the poloxamer-only spectrum suggests that adsorption is accompanied by slight displacement of the SO42− species. The potential dependence of SO42− adsorption was thus examined and, as shown in Figure S23, a potential step to −0.55 VSSE led to an increase in SO42− coverage, followed by a decrease upon stepping to −0.8 VSSE. The changes are almost identical to those observed for the polymer-free electrolyte. The slight difference in the SO42− absorbance, ≈2.5 × 10−4 in Figure S23, is of the same order of magnitude as the decreased sulfate band, ≈4 × 10−4, in the −0.65 VSSE polymer titration spectrum in Figure 12a. Compared to the polymer-free spectrum in Figure S23, the small decrease near 1100 and 1450 cm−1 at −0.8 VSSE is due to a minor loss of the –C–C–O– backbone and CH2 scissor modes upon rearrangement and desorption of a small amount of poloxamer.</p><p>In contrast to PEG and poloxamer, a larger increment of poloxamine adsorption occurs with its addition to 0.1 mol/L H2SO4, as shown in Figure 13a,b. The multicomponent polyether backbone mode at 1088 cm−1 for C–O–C also includes C–N+ contributions from the ethylenediamine core while the CH2 wag at 1347 cm−1, CH3 mode at 1379 cm−1, CH2 scissor modes at 1453 and 1467 cm−1, and the CH stretch region between 2878 and 2976 cm−1 are all resolved. The negative peak near 1225 cm−1 marks the decrease in SO42− coverage that accompanies poloxamine adsorption. Examination of the SO42− potential dependence upon stepping from −0.65 to −0.8 or −0.55 VSSE reveals a notably smaller change compared to the polymer-free system as shown in Figure S24. The adsorbed polymer results in a decrease in the SO42− coverage available for reversible adsorption/desorption. The interaction between SO42− and the protonated ethylenediamine C–N+ core of the poloxamine is also evident in the change in the shape and position of the SO42− band. However, no other changes in the polymer modes were resolved for the potential range examined.</p><!><p>As with PEG, the addition of Cl− to the poloxamer solutions results in significant changes in the difference spectra, as shown in Figure 12 (and Figure S25). Complete displacement of the SO42− species by Cl− adsorption occurs as indicated by the negative peaks centered at 1217, 1117, and 969 cm−1 similar to the spectra for SO42− displacement by Cl− in the polymer-free electrolyte. Halide adsorption is accompanied by an increased intensity for the 1012 and 1084 cm−1 bands associated with the –C–C–O– backbone modes although the latter is somewhat obscured by overlap with the SO42− desorption peak. Likewise, an increase in the CH2 twist at 1291 cm−1, the CH2 wag near 1347 cm−1, the CH3 mode at 1379 cm−1, and the scissor bands at 1451 and 1467 cm−1 are evident along with the substantial increase in the CH2 stretch modes between 2850 and 3000 cm−1. The Cl−-stimulated desorption of SO42− and co-adsorption of the poloxamer are accompanied by displacement of hydronium and the water modes, both hydrogen-bonded and non-hydrogen-bonded, as shown in Figure S25.</p><p>Similar trends are evident with the addition of Cl− to the poloxamine-containing electrolyte, as shown in Figure 13. Compared to PEG and poloxamer, the increment of polymer adsorption is smaller due to the higher initial polymer coverage. Nonetheless, with the Cl− addition, the remaining SO42− is displaced and the poloxamine multicomponent polyether backbone band increases along with the CH2 wag near 1347 cm−1, CH3 mode at 1379 cm−1, and the scissor bands at 1453 and 1467 cm−1. As with the lower-wavenumber spectra, the intensities of the CH2 and CH3 stretch band increase with the addition of Cl−, almost doubling the poloxamine coverage consistent with the related loss of SO42− bands with sequential poloxamine and Cl− addition. Linear combination of the poloxamine spectra with that following Cl− addition matches the intensity associated with the inverse order of additions. Thus, the final poloxamine–Cl− layer is not dependent on the history of additive addition. As with the other polyethers, displacement SO42−–H3O+/H2O by halide addition is accompanied by significant loss in the hydronium and water modes coincident with the formation of the saturated poloxamine–Cl− layer, as shown in Figure S26.</p><!><p>Water-soluble polymers play a major role in many aspects of surface science and surfactant technology. Solvation of polyethers is intimately associated with hydrogen bond formation with ethereal oxygen, while their surfactant activity is related to interfacial water structure that is responsive to different surfaces and related chemistry.50,51 For Cu electrodeposition, the present experiments indicate an important role of anion-mediated changes in interface hydrophobicity in polyether co-adsorption. This insight stands in contrast to prior efforts that focused on Cu+–ether-mediated binding to Cu surfaces.10,36,37</p><p>SEIRAS measurements reveal the profound effect of anion adsorption on the water structure at Cu surfaces. At −0.65 VSSE in 0.1 mol/L H2SO4, a mixed SO42−–H3O+/H2O adlayer forms on Cu(111) that when ordered is isosymmetric with that reported for other fcc (111) surfaces.57,58,64–68 For the Cu thin films studied herein, the potential-dependent coverage of the sulfate adlayer is similar to that reported for Cu(111).57,58 The differences that remain are presumably associated with finite terrace size and dispersion of orientations associated with the PVD films. When halide is added to the electrolyte, the co-adsorbed SO42−–H3O+/H2O is displaced as Cl− rapidly forms a compact ordered adlayer on the low-index surface segments. Previous STM studies reveal that this is accompanied by significant step faceting and coarsening with time.21–27 The ordered halide adlayer on the Cu thin film gives rise to a narrow vibrational band near 3600 cm−1 congruent with significant non-hydrogen-bonded water with the net positive dipole of O–H being oriented toward the Cl−-covered Cu surface. The −100 cm−1 red shift to 3600 cm−1 compared to that of free OH− species observed at the water–air interface (3700 cm−1) may be associated with the halide charge.52,54,55,80,81,87 In addition to free OH, "labile" H2O (with neither H involved in hydrogen bonding) with its net molecular dipole oriented close to the surface normal has also been reported near 3600 cm−1.54,73 In either case, the halide adlayer clearly serves to stabilize non-hydrogen water at the interface. Following halide titration, the non-hydrogen-bonded water mode rises rapidly, followed by a much slower evolution of the hydrogen-bonded water over a time scale of minutes. The latter maybe related to further templating of the water structure as the domain size of the ordered halide layer increases with slow coarsening of the mesoscale surface features. Similar reports of the sensitivity of water modes to reorganization of surface structure exist for Au surfaces.72,84 Most importantly, several vibrational spectroscopy studies of water–air and water–solvent interfaces suggest an association between the development of non-hydrogen-bonded, dangling "free" OH and hydrophobic behavior.52,54,55,80–82 It follows that the high surface tension of water is intimately related to disruption of its hydrogen bond network. The amphiphilic nature of PEG is such that the disrupted water structure associated with the halide-covered Cu surface can be effectively dissipated by polyether segregation to the interface, whereby the hydrophobic CH2–CH2 components are biased toward the halide layer, while the ethereal oxygen sites are available for hydrogen bonding with the adjacent water network.</p><p>PEG co-adsorption on the Cl−-covered Cu surface, as reflected in the –C–C–O– backbone, CH2 twist, and CH2 wag modes, results in significant deviations from the water-stabilized T–G–T, –O–C–C–O– helical conformation associated with its solubility in water. Specifically, the increase in G (gauche) arrangement around the ethereal C–O–C bond, indicated by the backbone mode at 1030 cm−1 and the CH2 twist at 1307 cm−1, reflects the disruption of the helical backbone. Even in the absence of water, studies of energy funneling during melting of helical PEG point to C–O bond rotation as the more favored deformation path.108 In the present case, the hydrophobic nature of the Cl−-terminated surface induces restructuring of the polymer's secondary structure during adsorption. Specifically, the alkyl and ethereal groups of the adsorbed molecule are biased toward the inner and outer sides of the double layer to mediate the hydrophobic and hydrophilic interactions between the Cl−-covered metal and the electrolyte, respectively. Looking beyond PEG, the nonpolar PPO segments of the poloxamer and poloxamine provide further driving force for segregation and stabilization of the respective polymers to hydrophobic surfaces, thereby enhancing the polyether suppression of the Cu deposition reaction on halide-covered surfaces.</p><p>The above suggests an alternative approach to enhancing the suppressor action, namely, pretreating bare Cu surfaces with a hydrophobic methyl-terminated short alky chain thiol prior to electroplating in the presence of PEG. When this is done, significantly greater inhibition is observed due to the co-adsorption of PEG that blocks residual pin holes in the underlying hydrophobic monolayer systems.109 As detailed in the supplement (Figure S27), these hydrophobic methylated surfaces support PEG adsorption, although the conformation of the co-adsorbed polyether and resulting metal deposition processes are distinctly different from those associated with the halide-covered surface. More broadly, the impact of substrate hydrophilicity on the adsorption of PEG, PPG, and a triblock poloxamer on prototypical surfaces, such as hydrophilic silica and hydrophobic polystyrene, has been examined in detail.50,51 Specifically, SFG measurements of the CH3 and CH2 stretch region indicate no quantifiable change in the secondary structure of polyethers during weak adsorption on silica, while significant anisotropy accompanies polyether assembly on hydrophobic polystyrene.50 The measurements were congruent with the adsorbed polyethers having their hydrophobic components oriented toward the hydrophobic substrate surface. Further examination of polyether adsorption from methanol solutions indicated that the interaction of water with the hydrophobic surfaces was a key element in the anisotropic adsorption of the polyether. In a related fashion, a correlation between halide adsorption and hydrophobic character was previously inferred from the rapid assembly of ordered porphyrins and related 2D molecules on halide-covered Au(111) surfaces.110 The resulting adsorbate structures are analogous to those reported on other hydrophobic van der Waals solids.</p><p>The potential dependence of halide adsorption on Cu provides an excellent avenue for exploring polyether co-adsorption.21,25,29 At negative potentials, the Cl− adlayer formed on low-index Cu surfaces undergo order–disorder phase transitions with significant halide desorption. SEIRAS measurements reveal that this is accompanied by disruption of the neighboring non-hydrogen-bonding water. In the presence of polyethers, stepping to negative potentials results in some disruption of the polymer layer and corresponding alteration of the water modes. In the presence of both additives, the halide layer is somewhat stabilized by the polymer as the order–disorder phase transition is shifted, −50 mV, to more negative potentials, as revealed by voltammetric and SXS studies.19,29 From an application perspective, the link between the halide order–disorder phase transition, water structure, and polyether adsorption underlies the critical phenomena associated with breakdown of the polyether–Cl− suppressor layer that is central to bottom-up filling of Cu TSV.5,17,18,25 Presently, there are numerous efforts underway to develop physically robust models of the associated dynamics.5–7,17,18,25 What if any role cations, such as Cu2+ or, more importantly, its hydrated form, play in suppressor film formation and operation remains to be resolved. Recent studies of specific ion effects on polymer aggregation, i.e., Hofmeister series, indicate that divalent, but not monovalent ions, affect the micellization and aggregation of poloxamers at higher temperatures.111 Future work examining supporting electrolyte effects may be helpful in addressing this question.</p><p>Further insight into the nature of polyether adsorption has also been obtained by examining its displacement by competitive adsorption of hydrophilic sulfonate-terminated short alkyl chain disulfide (SPS) or thiol (MPS) molecules.3,4,15,19 SEIRAS experiments that explore the functional role of the accelerator will be detailed in a companion paper. Briefly, competitive adsorption of hydrophilic accelerator species results in a progressive disruption of the initially formed PEG–Cl− layer and the Cu deposition kinetics evolves toward that of an unsuppressed system.3,4,15,19 Accordingly, it is the competitive interaction between hydrophobic PEG–Cl− and hydrophilic SPS/MPS species that provides the chemical basis of the curvature-enhanced accelerator mechanism that underlies superconformal electrodeposition of Cu.</p><!><p>Superconformal electrodeposition is a key process in the fabrication of microelectronics interconnects from the nanoscale devices to printed circuit boards. The process depends on additives that suppress and accelerate the local growth rate while producing Cu deposits free of undue contamination. Co-adsorption of polyethers and Cl− on Cu provides suppression of the metal deposition process by hindering access of Cu2+ to the metal surface. The combination of potential difference and titration SEIRAS measurements provide new insights into the polyether–halide co-adsorption process. In 0.1 mol/L H2SO4, a potential-dependent mixed SO42−–H3O+/H2O layer forms on weakly textured (111) Cu thin-film surfaces. Limited polyether adsorption occurs on the hydrophilic oxyanion layer congruent with the absence of significant inhibition of metal deposition under such conditions. However, with the addition of Cl−, the SO42−–H3O+/H2O adlayer is displaced and an ordered halide layer rapidly forms. The halide layer exerts a profound effect on the adjacent solvent network, with the adsorbed halide giving rise to an increase in non-hydrogen-bonded water that makes the interface more hydrophobic. In the presence of the polyether, the altered wetting behavior induced by halide adsorption tips the balance in favor of polyether co-adsorption. Water is displaced from the interface as the hydrophobic portions of the polyether molecule assemble on the Cl−-covered surface while the lone pair electrons of the ethereal oxygen are available for forming hydrogen bonds with the solvent network in the electrolyte. The same trends are evident for polyethers with different tertiary structures, from linear PEG to the triblock copolymer polyoxamer PEO2PPO31PEO2 to the branched, block copolymer polyoxamine (PEO4PPO12)2N(CH2)2N(PPO12PEO4)2.</p><!><p>ASSOCIATED CONTENT</p><p>Supporting Information</p><p>The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcc.8b06644.</p><p>Single beam spectra; scanning electron micrograph; SEIRAS spectra; Stark tuning shifts; ATR difference spectra; absorbance vs SO42− concentration; SEIRAS difference spectra; intensity of a selected bands for solvated PEG; reference spectra; fingerprint region; peak deconvolution; potential difference spectra; SEIRAS titration spectra; (Figures S1–S27); spectral references for sulfate and bisulfate, solvated PEG and dPEG, PEG and dPEG powder; peak fit parameters (Tables S1–S6); PEG adsorption on propanethiol terminated Cu (PDF)</p><p>The authors declare no competing financial interest.</p><p>ADDITIONAL NOTE</p><p>Identification of commercial products in this paper is done to specify the experimental procedure. In no case does this imply endorsement or recommendation by the National Institute of Standards and Technology.</p><p>(a) Chemical structure of three polyether suppressors: PEG, poloxamer, and poloxamine. (b) Slow scan voltammetry (1 mV/s) of Cu deposition in the presence of the respective polymers and halide revealing the importance of co-adsorption and the chemistry and secondary structure of polyethers in the suppression of the Cu deposition (0.24 mol/L CuSO4 + 1.8 mol/L H2SO4 + 1 mmol/L NaCl + 80–90 μmol/L polymer).</p><p>Cyclic voltammetry of a 20 nm PVD Cu film supported on air-formed SiOx on Si reveals waves related to anion adsorption and reconstruction. The inset gray band corresponds to the potential window examined by SEIRAS.</p><p>(a) SEIRAS spectra, referenced to −0.85 VSSE, showing bands related to SO42− adsorption on the Cu film in 0.1 mol/L H2SO4. (b) Example of spectral deconvolution in 1000–1400 cm−1 region using three components. (c) The dominant SO42− peak exhibits a Stark shift of 33.1 cm−1 V−1 compared to 55–60 cm−1 V−1 from an IRRAS study of Cu(111).58 The red circle at −0.65 VSSE represents the peak position of the displacement band due to halide addition (vide infra). (d) The intensity of the respective SO42− spectral components, band 1 (1229 cm−1) and band 2 (1186 cm−1), are correlated and thus the sum (band 1 + band 2) is used for analysis. (e) SO42− displacement spectrum following the addition of 1 mmol/L NaCl at −0.65 VSSE. (f) Potential dependence of SEIRAS SO42− data (band 1 + band 2) compared to IRRAS data for Cu(111).58 The intensity of the potential difference data was offset by the SO42− displacement spectra (e).</p><p>SEIRAS titration spectra at −0.65 VSSE revealing displacement of SO42−–H3O+/H2O (negative peaks at 1115 and 1215 cm−1) by Cl− adsorption and rearrangement of the adjacent water structure (1600–1670 and 3000–3600 cm−1) in 1 mmol/L NaCl + 0.1 mol/L H2SO4. The narrow non-hydrogen-bonded water at the 3600 cm−1 band develops rapidly with the formation of the ordered Cl− adlayer, while the hydrogen-bonded water network evolves more slowly congruent with mesoscale coarsening of the halide-covered surface. The noise artifacts in the 4 and 8 min spectra are associated with atmospheric water contamination of the spectrometer's optical path.</p><p>SEIRAS images, referenced to −0.65 VSSE, show the impact of potential-dependent phase transitions in the Cl adlayer on the adjacent water layer in 1 mmol/L NaCl + 0.1 mol/L H2SO4.</p><p>SEIRAS difference spectra collected at −0.65 VSSE after Cl− titration (black) (1 mmol/L NaCl + 0.1 mol/L H2SO4), followed by the addition of PEG (red) (88 μmol/L PEG + 1 mmol/L NaCl + 0.1 mol/L H2SO4). The disruption of water modes by Cl− adsorption facilitates subsequent co-adsorption of PEG, wherein water is displaced by the hydrophobic segments while the ethereal oxygen sites are available for hydrogen bonding.</p><p>SEIRAS spectra for co-adsorbed PEG–Cl− (88 μmol/L PEG) and weakly adsorbed PEG (88 μmol/L PEG) compared to solvated PEG (20 mmol/L PEG). The shape and relative magnitude (see text) of the (a) –C–C–O– envelope and (b) CH2 stretch region reflect the anisotropy associated with PEG adsorption on the Cl−-covered Cu surface. (c) The PEG–Cl− layer exhibits increased intensity of the 1030 cm−1 –C–C–O–, CH2rock, and 1307 cm−1 CH2twist modes due to an increase in the percentage of gauche (G) C–O–C segments associated with deviation of the adsorbed molecules from the dominant helical arrangement of solvated PEG. Deconvolutions of the spectral envelope in (a) and (b) are provided in Figure S18.</p><p>SEIRAS experiments revealing the potential dependence of the PEG–Cl− suppressor layer. Upon stepping from −0.65 to −0.8 VSSE, disruption of the polymer occurs as evident in the negative polymer bands and the complimentary increase in water and non-hydrogen-bonded water modes. In contrast, stepping from −0.65 to −0.55 VSSE leads to a loss of water modes and increase in the polymer –C–C–O– and CH2 modes.</p><p>(a) C–C–O– backbone spectra based on the order of additive titration at −0.65 VSSE; PEG addition to NaCl + H2SO4 (red), PEG addition to H2SO4 (orange), NaCl addition to PEG + H2SO4 (blue), NaCl to H2SO4 (green). (b) Dependence of methylene spectra on the order of additive titration at −0.65 VSSE; PEG addition to NaCl + 0.1 mol/L H2SO4 (red), PEG addition to H2SO4 (orange), and NaCl addition to PEG + H2SO4 (blue). The final concentrations of the respective additives in 0.1 mol/L H2SO4 were 1 mmol/L NaCl and 88 μmol/L PEG.</p><p>SEIRAS difference spectra at −0.65 VSSE after Cl− titration (black) (1 mmol/L NaCl + 0.1 mol/L H2SO4), followed by the addition of poloxamer (red) (82 μmol/L PEO2PPO31PEO2 + 1 mmol/L NaCl + 0.1 mol/L H2SO4). Disruption of the water modes by Cl− adsorption (black) facilitates the subsequent co-adsorption of poloxamer (red) where water is displaced by the hydrophobic segments while the ethereal oxygen forms hydrogen bonds with the adjacent electrolyte.</p><p>SEIRAS difference spectra at −0.65 VSSE after Cl− titration (black) (1 mmol/L NaCl + 0.1 mol/L H2SO4) followed by the addition of poloxamine (red) (87 μmol/L poloxamine + 1 mmol/L NaCl + 0.1 mol/L H2SO4). The disruption of the water modes by Cl− adsorption (black) facilitates the subsequent co-adsorption of poloxamine (red) where water is displaced by the hydrophobic segments while the ethereal oxygen forms hydrogen bonds with the adjacent electrolyte.</p><p>(a) PEO2PPO31PEO2 backbone spectra based on the order of additive addition at −0.65 VSSE; PEO2PPO31PEO2 addition to NaCl + H2SO4 (red), PEO2PPO31PEO2 addition to H2SO4 (orange), NaCl addition to PEO2PPO31PEO2 + H2SO4 (blue), and NaCl to H2SO4 (green). (b) Dependence of the methyl and methylene spectra on the order of additive titration at −0.65 VSSE; PEO2PPO31PEO2 addition to NaCl + H2SO4 (red), PEO2PPO31PEO2 addition to H2SO4 (orange), and NaCl addition to PEO2PPO31PEO2 + H2SO4 (blue). The final concentration of the respective additives in 0.1 mol/L H2SO4 were 1 mmol/L NaCl and 82 μmol/L poloxamer.</p><p>(a) Poloxamine backbone spectra based on the order of additive addition at −0.65 VSSE; poloxamine addition to NaCl + H2SO4 (red), poloxamine addition to H2SO4 (orange), NaCl addition to poloxamine + H2SO4 (blue), and NaCl addition to H2SO4 (green). (b) Dependence of the methyl and methylene spectra on the order of additive titration at −0.65 VSSE; poloxamine addition to NaCl + H2SO4 (red), poloxamine addition to H2SO4 (orange), and NaCl addition to poloxamine + H2SO4 (blue). The final concentration of the respective additives in 0.1 mol/L H2SO4 were 1 mmol/L NaCl and 87 μmol/L poloxamine.</p>

PubMed Author Manuscript

Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field

BackgroundThere has been huge progress in the open cheminformatics field in both methods and software development. Unfortunately, there has been little effort to unite those methods and software into one package. We here describe the Open Drug Discovery Toolkit (ODDT), which aims to fulfill the need for comprehensive and open source drug discovery software.ResultsThe Open Drug Discovery Toolkit was developed as a free and open source tool for both computer aided drug discovery (CADD) developers and researchers. ODDT reimplements many state-of-the-art methods, such as machine learning scoring functions (RF-Score and NNScore) and wraps other external software to ease the process of developing CADD pipelines. ODDT is an out-of-the-box solution designed to be easily customizable and extensible. Therefore, users are strongly encouraged to extend it and develop new methods. We here present three use cases for ODDT in common tasks in computer-aided drug discovery.ConclusionOpen Drug Discovery Toolkit is released on a permissive 3-clause BSD license for both academic and industrial use. ODDT’s source code, additional examples and documentation are available on GitHub (https://github.com/oddt/oddt).Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0078-2) contains supplementary material, which is available to authorized users.

open_drug_discovery_toolkit_(oddt):_a_new_open-source_player_in_the_drug_discovery_field

Background<!>Implementation<!>Molecule formats<!>Interactions<!>Filtering<!>Docking<!>Scoring<!>Statistical methods<!>Results and discussions<!><!>Example 2: training and evaluating models for binding affinity datasets<!><!>Example 3: training classifiers to distinguish active from inactive compounds based on DUD-E<!><!>Conclusion<!>Availability and requirements<!><!>Availability and requirements<!>

<p>Over the past decades, in silico drug discovery has become an important element augmenting classical medicinal chemistry and high throughput screening. Many novel computational chemistry methods were developed to aid researchers in discovering promising drug candidates. In recent years, much progress has been made in areas such as scoring functions, similarity search methods and statistical approaches (for review see [1, 2]). By contrast to computational chemistry, cheminformatics remains a relatively young field that suffers from many "early age diseases", such as lack of standardization, particularly regarding data interchangeability and manipulation and reproducibility of results. To complicate the situation even more, format implementations usually have some additional, non-standard, software-oriented extensions (PDBQT is one prime example). Hardcoding a format into scientific software is also more common than using higher level toolkits, such as OpenBabel [3], RDKit [4], and OpenEye [5].</p><p>Some of the most popular and successful methods in drug discovery are structure-based. Structure-based methods are commonly employed to screen large small-molecule datasets, such as online databanks or smaller sets such as tailored combinatorial chemistry libraries. These techniques, from molecular docking to molecular mechanics to ensemble docking, employ scoring processes that are crucial for decision making. Empirical scoring functions use explicit equations based on physical properties of available ligand-receptor complexes. Knowledge-based scoring functions may additionally or exclusively use other types of interaction quantities that are parameterized using training set(s) to fit the data (for review see: [6, 7]). Currently, much effort is directed towards machine learning, which is most helpful in elucidating non-linear and non-trivial correlations in data. NNScore [8], Rfscore [9], and SFCscore [10] are among the most distinguished examples. However there are only a few freely accessible scoring functions and even fewer that are fully open source.</p><p>Analyzing output data, particularly when working with large scale virtual screening, can be a tedious and labor-demanding task that incorporates human error. Commercial software facilitate output data analysis to some extent, but there are also open source/free software solutions, such as VSDMIP [11] or DiSCuS [12], which are particularly designed for processing "big data". However, the field is still missing a coherent, open source solution that will guide the researcher in building a custom cheminformatics pipeline, tailored for specific project needs. Therefore, we sought to develop a comprehensive open source small-molecule discovery platform for both researchers designing their own pipelines or developing new drugs. To achieve this goal, we have reviewed state-of-the-art tools and algorithms and united them in one coherent toolkit. When the use of open-source tools was not possible, the algorithms were reimplemented using open source software. This approach will make the in silico discovery process more scalable, cost-effective and easier to customize. We believe, that making software open is especially important to ensure data reproducibility and to minimize technology costs. Open-source software model allows numerous individuals to contribute and collaborate, on creating opportunities for novel tools and algorithms to be developed.</p><!><p>The Open Drug Discovery Toolkit (ODDT) is provided as a Python library to the cheminformatics community. We have implemented many procedures for common and more sophisticated tasks, and below we review in more detail the most prominent. We would also like to emphasize that by making the code freely available through a BSD license, we encourage other researchers and software developers to implement more modules, functions and support of their own software.</p><!><p>Open Drug Discovery Toolkit is designed to support as many formats as possible by extending the use of Cinfony [13]. This common API unites different molecular toolkits, such as RDKit and OpenBabel, and makes interacting with them more Python-like. All atom information collected from underlying toolkits are stored as Numpy [14] arrays, which provide both speed and flexibility.</p><!><p>The toolkit implements the most popular protein-ligand interactions. Directional interactions, such as hydrogen bonds and salt bridges, have additional strict or crude terms that indicate whether the angle parameters are within cutoffs (strict) or only certain distance criteria are met (crude). The complete list of interactions implemented in ODDT consists of hydrogen bonds, salt bridges, hydrophobic contacts, halogen bonds, pi-stacking (face-to-face and edge-to-face), pi-cation, pi-metal and metal coordination. These interactions are detected using in-house functions and procedures utilizing Numpy vectorization for increased performance. Calculated interactions can be used as further (re)scoring terms. Molecular features (e.g., H-acceptors and aromatic rings) are stored as a uniform structure, which enables easy development of custom binding queries.</p><!><p>Filtering small molecules by properties is implemented in ODDT. Users can use predefined filters such as RO5 [15], RO3 [16] and PAINS [17]. It is also possible to apply project-specific criteria for MW, LOGP and other parameters listed in the toolkit documentation. See Example 1 in the "Results and discussion" section for more details on how to use filtering.</p><!><p>Merging free/open source docking programs into a pipeline can be a frustrating experience for many reasons. Some programs, like Autodock [18] and Autodock Vina [19], do not support multiple ligand inputs, where some other programs output scores to separate files (e.g., GOLD [20]) or even directly print to the console. Additional effort is required for re-scoring output ligand-receptor conformations in other software. Every in-silico discovery project is flooded with custom procedures and scripts to share data between programs. The docking stack within ODDT provides an easier path with the use of a common docking API. This API allows retrieving output conformations and their scores from various widely-used docking programs. The docking stack also supports multi-threading virtual screening tasks independently of underlying software, helping to utilize all available computational resources.</p><!><p>Open Drug Discovery Toolkit provides a Python re-implementation of two machine learning-based functions: NNscore (version 2) and RFscore. The training sets from its original publication were used for the RFscore function [9]. For NNScore, neither the training set nor the training procedure was made available by authors, other than a brief description [8]. To bring support for NNScore, we used ffnet  [21]. The training procedure for NNscore was reimplemented in ODDT and should closely reproduce the resulting ensemble of neural networks. The training data are stored as csv files, which are used to train scoring functions locally. After the initial training procedure, the scoring function objects are stored in pickle files for improved performance.</p><p>Machine learning scoring functions consist of four main building blocks: descriptors, model, training set and test set. ODDT provides a workflow for training new models, with additional support for custom descriptors and custom training and test sets. Such a design allows not only the use of the toolkit to reproduce scores (or reimplement scoring functions) but also enables the researcher to develop their own custom scoring procedures. Finally, if random seeds are defined, the scoring function results in ODDT are fully reproducible.</p><p>The ability to assess the predictive performance of scoring function (or scoring procedures) is of utmost importance. ODDT provides various ways to accomplish these tasks. One approach may use the area under receiver operating characteristics curve (ROC AUC and semi-log ROC AUC) and the enrichment factor (EF) at a defined percentage. These methods can be applied for every scoring function (and their combination) when training/test sets or active/inactive sets are supplied. Two other methods to test scoring function(s) performance include internal k-folds and leave one out / leave p out (LOO/LPO) cross-validation, both of which are particularly useful to detect model overfitting. These methods are available in ODDT through the sklearn python package [22].</p><!><p>Modeling the relationship between chemical structural descriptors and compound activities provides insight into SAR. Ultimately, such models may predict screening outcomes of novel compounds, guiding future discovery steps. Because some screening data are linear by their nature, simple regressors can be applied to find correlations (e.g., comparative molecular field analysis, CoMFA [23]). We implemented two straightforward regressions which that are widely used in cheminformatics, both in ligand and structure-based methods: multiple linear regression and partial least squares regression.</p><p>Nonlinear, more complex data are better assessed by machine learning models. Two forms of machine learning models are particularly important in drug discovery: (1) regressors for continuous data, such as IC50 values or inhibition rates, and (2) classifiers applied to multiple bit-wise features or ligands tagged as active/inactive (e.g., NNScore 1.0). ODDT employs sklearn as the main machine learning backend because it has a mature API and good performance. In some cases when neural networks are required, ODDT mimics the sklearn API and instead uses ffnet [21]. The current version of our toolkit provides machine learning models that are widely used in cheminformatics and drug discovery: (1) random forests, (2) support vector machines, and (3) artificial neural networks (single and multilayer). These models have been shown to provide great guidance when assessing protein-ligand complexes in the development and application of various scoring functions [8–10] and in SAR and QSAR (e.g., [24, 25]).</p><!><p>In this section, we provide examples of ODDT usage with code snippets. Our aim is to illustrate how one can utilize the toolkit for (a) preparing data for an in silico screening procedure, (b) score and rescore protein-ligand complexes, and (c) assess data quality and performance of different computational approaches for elucidating statistical correlations.</p><!><p>Code snippet illustrating ligand filtering, the docking procedure using the Autodock Vina engine, and rescoring with two machine learning functions: NNScore and RFscore.</p><!><p>In this example, the researcher is using a PDBbind dataset (ligand-receptor crystal structures along with experimentally-derived binding affinities (log Ki/Kd values) [26]. She wishes to train various prediction models on these data and then evaluate which model is the best predictor. (This workflow can also be used as a template to test and develop novel scoring functions and create custom, descriptor-based machine learning models).</p><p>In the first step, affinity values for both sets (training and test) are loaded from csv files. Then, all molecules and protein pockets (in sdf and pdb formats, accordingly) are read from the PDBbind 2007 directory (downloaded locally). Based on the csv files, these data are separated into training and test sets and close contact descriptors are generated (same as in RF-Score).</p><!><p>Workflow chart that illustrates how to select the best model for predicting compound activities based on the RF-Score descriptor. At each node there are methods/functions responsible for each calculation. Underlying code for this workflow is available in Additional file 1: (Snippet_2.ipnb).</p><p>2D plots presenting the predicted and target affinities produced by specific models.</p><!><p>This code snippet illustrates how to determine which fingerprint descriptor is the most suitable for describing active compounds for the AMPC protein by using DUD-E's subset of actives, inactives and decoys. The random forest classifier model is trained using various fingerprints implemented both in RDKit and OpenBabel.</p><p>Firstly, molecules for actives, inactives, decoys and marginal actives (treated as inactives for training) are read from SMILES files. Next, a wide range of fingerprints is built for all molecules: OpenBabel: fp1, fp2, MACCS; RDKit: rdkit (default), morgan, layered.</p><!><p>Workflow to assess the performance of using specific fingerprints for distinguishing actives from a library of substances. At each node there are methods/functions responsible for each calculation. The code for this workflow is available in Additional file 1: (Snippet_3.ipnb).</p><!><p>In this article, we introduce an out-of-the-box solution for building in-silico screening and data elucidation pipelines. The solution is flexible and provides a selection of useful tools, some of which are implemented for the first time. The three workflows illustrated in this paper demonstrate how one can use the toolkit to quickly prepare, filter, and screen data and apply various statistical methods to elucidate relationships.</p><!><p>ODDT (Open Drug Discovery Toolkit) is available at https://github.com/oddt/oddt</p><p>Operating system(s): platform independent</p><p>Programming language: Python</p><!><p>OpenBabel (2.3.2+),</p><p>RDKit (2012.03)</p><p>Python (2.7+)</p><p>Numpy (1.6.2+)</p><p>Scipy (0.10+)</p><p>Sklearn (0.11+)</p><p>ffnet (0.7.1+), only for neural network functionality.</p><!><p>License: 3-clause BSD,</p><p>Any restrictions to use by non-academics: none.</p><!><p>Snippets.zip—IPython notebooks containing the code for each example.</p><p>computer aided drug discovery</p><p>Open Drug Discovery Toolkit</p><p>enrichment factor</p><p>receiver operating characteristic</p><p>area under curve</p><p>leave one out</p><p>leave p out</p><p>ultra-fast shape recognition</p><p>structure-activity relationship</p>

PubMed Open Access

Formulating a new basis for the treatment against botulinum neurotoxin intoxication: 3,4-diaminopyridine prodrug design and characterization

Botulism is a disease characterized by neuromuscular paralysis and is produced from botulinum neurotoxins (BoNTs) found within the Gram positive bacterium Clostridium botulinum. This bacteria produces the most deadliest toxin known, with lethal doses as low as 1 ng/kg. Due to the relative ease of production and transport, the use of these agents as potential bioterrorist weapons has become of utmost concern. No small molecule therapies against BoNT intoxication have been approved to date. However, 3,4-diaminopyridine, (3,4-DAP), a potent reversible inhibitor of voltage-gated potassium channels, is an effective cholinergic agonist used in the treatment of neuromuscular degenerative disorders that require cholinergic enhancement. 3,4-DAP has also been shown to facilitate recovery of neuromuscular action potential post botulinum intoxication by blocking K+ channels. Unfortunately, 3,4-DAP displays toxicity largely due to blood-brain-barrier (BBB) penetration. As a dual-action prodrug approach to cholinergic enhancement we have designed carbamate and amide conjugates of 3,4-DAP. The carbamate prodrug is intended to be a slowly reversible inhibitor of acetylcholinesterase (AChE) along the lines of the stigmines thereby allowing increased persistence of released acetylcholine within the synaptic cleft. As a secondary activity, cleavage of the carbamate prodrug by AChE will afford the localized release of 3,4-DAP, which in turn, will enhance the pre-synaptic release of additional acetylcholine. Being a competitive inhibitor with respect to acetylcholine, the activity of the prodrug will be greatest at the synaptic junctions most depleted of acetylcholine. Here we report upon the synthesis and biochemical characterization of three new classes of prodrugs intended to limit previously reported stability and toxicity issues. Of the prodrugs examined, compound 32, demonstrated the most clinically relevant half-life of 2.76 h, while selectively inhibiting AChE over butyrylcholinesterase \xe2\x80\x93 a plasma-based high activity esterase. Future in vivo studies could provide validation of prodrug 32 as a potential treatment against BoNT intoxication as well as other neuromuscular disorders.

formulating_a_new_basis_for_the_treatment_against_botulinum_neurotoxin_intoxication:_3,4-diaminopyri

1. Introduction<!>2.1 Materials<!>2.2 Enzyme inhibition assays<!>2.3 Enzyme-specific drug release assays<!>2.4 Sera half-life assays<!>2.5 Statistical analysis<!>3.1 Design of Prodrugs<!>3.2 Synthesis of Class I prodrugs<!>3.3 Synthesis of Class II prodrugs<!>3.4 Synthesis of Class III prodrugs<!>3.5 Inhibition, release profile, and stability of prodrugs<!>4. Conclusion<!>

<p>Botulinum neurotoxins (BoNTs) produced from the Gram positive bacterium Clostridium botulinum are some of the deadliest toxins known to man1 with lethal doses as low as 1 ng per kg body weight being 10 million times more toxic than cyanide.2 Intoxication by BoNT produces generalized muscle weakness, and in severe cases flaccid paralysis leading to impaired respiration and autonomic function. In many cases rapid intubation and mechanical respiration are required to prevent greater risk and even death.3 BoNT intoxication is primarily caused by the consumption of poisoned canned food products; however, the use of these agents as potential bioterorrist weapons has become of concern. As such, the US Centers for Disease Control (CDC) have classified BoNTs as one of the six highest-risk agents for bioterrorism (Class A).</p><p>The induction of neuromuscular paralysis by BoNTs requires three biochemical steps. First, BoNT protein binds to gangliosides on the presynaptic cholinergic nerve terminal through interactions with the heavy chain. These interactions allow subsequent endocytosis into the neuron through several possible mechanisms involving synaptotagmins I and II (BoNT/B and BoNT/G) and SV2 (BoNT/A).4 The toxin is then translocated into the cytosol where its light chain (LC), a metalloprotease, binds to, and cleaves soluble N-ethylmaleimide-sensitive factor attachment protein receptor proteins (SNAREs).5 This action halts the release of acetylcholine (ACh) at the neuromuscular junction, leading to the cessation of neurotransmission.</p><p>Currently, the only approved therapies against BoNT intoxication include pre-exposure prophylaxis with a vaccine and post-exposure administration of sera containing anti-BoNT antibodies.6 Upon cellular intoxication, however, it is imperative to provide fast acting neuro-modulatory drugs to recover neurotransmission through ACh release, to at least restore partial muscle function. Thus, a potential small molecule pharmacological treatment could provide many benefits over these antibody-based approaches. Most small molecule research efforts have targeted the metallo-proteolytic properties of the BoNT LC protease, however, no small molecule therapeutics have been approved to date.7 Yet, clinically approved cholinergic enhancing drugs have been implemented to treat similar neurological disorders including Lambert-Eaton myasthenic syndrome (LEMS),8 multiple sclerosis (MS),9 and Alzheimer's disease.10</p><p>Of these classes of drugs, aminopyridines, in particular 3,4-diaminopyridine (3,4-DAP), has shown promise due to its agonistic effect on neurotransmitter release through Kv channel blockade.11 The aminopyridines, 3,4-DAP along with 4-aminopyridine (4-AP) facilitate recovery of neuromuscular action potential post botulism intoxication by reversibly blocking voltage-dependent K+ channels.12 This action promotes Ca2+ influx, driving signal transduction and ACh release at the synapse. The mechanism by which aminopyridines inactivate the Kv channel is unknown; however, using molecular modeling Caballero and colleagues hypothesized that two putative receptor sites found within the tetrameric channel are important in this overall process.13 It has also been hypothesized that once aminopyridines cross the membrane, the molecules become protonated intracellularly, thereby allowing the molecule to interact with receptors within the pore of the channel.</p><p>Recently, our laboratory initiated studies toward deciphering the pKa/hydrogen-bonding properties of 3,4-DAP in conjunction with the Kv channel.14 By synthesizing structural analogues, we hoped to discover more potent, yet, less toxic forms of the pharmacophore for treatment against BoNT intoxication. Previous reports indicate that 3,4-DAP and 4-AP, when administered at high doses, demonstrate toxicity issues such as seizures due to the molecules' ability to penetrate the blood-brain barrier (BBB). As such, the development of new compounds that alleviate BBB penetration without hampering the necessary molecular dynamics between the compound and the Kv channel would provide a path forward for treating BoNT/A intoxication. Exploring this possibility, a series of compounds were synthesized, and 3,4,5-triaminopyridine and 3,4-diamino-1-(prop-2-ynl)pyridinium were found to exhibit therapeutic potential, as characterized by paralysis reversal in mouse phrenic nerve-hemidiaphragm assays post BoNT/A induced paralysis. Yet, a shortcoming with these molecules is that they possessed modest plasma half-lives of 0.31 h and 1.2 h, respectively. Drug candidates with limited plasma lifetimes would require repeated dose regimen or a continuous iv infusion to systemically provide paralytic extinction.</p><p>While many research programs have focused on inhibition of the BoNT LC protease itself, therapies directed toward the inhibition of acetylcholinesterase (AChE) post BoNT intoxication remain sparse.15</p><p>The stigmines, a class of carbamate-based AChE inhibitors, provide effective treatment of multiple sclerosis,16 myasthenia gravis,17 and Alzheimer's disease.18 Mechanistically, carbamates produce reversible covalent inhibition via transesterification between the carbamoyl-moiety and the active site serine. Hydrolysis of the serine-carbamate intermediate is considerably slower (seconds to tens of minutes) than that of the acetyl-serine adduct formed during substrate hydrolysis. Clinically approved stigmines such as Rivastigmine (Exelon) are characterized as pseudo-substrate inhibitors of both AChE and serum-based butyrylcholinesterase (BChE), a highly active esterase with largely overlapping substrate specificity that must be avoided for therapeutic efficacy.19 Although obtaining selectivity for AChE over BChE is a challenging task, the success of the stigmines suggests that prodrug-type molecules could be similarly designed with sufficient selectivity towards AChE over BChE.</p><p>From the structure activity relationship found within the stigmines, carbamate conjugates of 3,4-DAP could act as potential pseudo-substrate inhibitors of AChE thereby providing the enhanced benefit of selectively unmasking 3,4-DAP proximal to its site of action. Also of note, carbamate inhibitors are competitive with respect to ACh meaning that inhibition of AChE and liberation of 3,4-DAP will occur in those synaptic junctions most depleted (and in need) of ACh. AChE is homeostatically occupied by ACh (Km = 0.4 mM) within the neuromuscular junction.20 Interestingly, studies by Smart and McCammon have found that the deactivation of AChE increases ACh lifetime in the synaptic cleft from 200 to 900 µs.21 Acetyl choline depletion could produce up to a 25-fold inhibition selectivity for AChE at BoNT/A intoxicated neuromuscular junctions over undamaged junctions. Therefore, there could be a therapeutically relevant directed inhibition of AChE and 3,4-DAP liberation in those synaptic clefts most depleted of ACh by BoNT intoxication.</p><p>Herein, we describe our studies regarding the design, synthesis and in vitro study of 3,4-DAP-based dual-acting prodrugs against BoNT intoxication.</p><!><p>Acetylthiocholine iodide (AChI), S-Butyrylthiocholine iodide (BChI), 5,5'-Dithiobis(2-nitrobenzoic acid) (DTNB), and sera from clotted mouse blood were purchased from Sigma Aldrich (St. Louis, MO). 100 mM stocks of AChI, BChI, and DTNB were prepared in 100 mM sodium phosphate pH 8.0. All other chemicals used were of analytical grade and highest chromatographic purity available. AChE purified from Electrophorus electricus (Electric eel) – Type V-S and BChE from equine serum were purchased from Sigma Aldrich and reconstituted in 1% gelatin/100 mM sodium phosphate pH 8.0 at 500 U/mL each.</p><!><p>The activities of class I, II, and III inhibitors were measured according to the method of Ellman et al.22 using AChI or BChI as the respective substrates for each enzyme. In brief, 100 µM AChI or BChI was added to 100 mM sodium phosphate pH 8.0 containing 360 µM DTNB and a range of prodrug concentrations from 500 µM to 2 µM. To initiate the reaction, 0.5 U of enzyme was added to each sample in a final volume of 200 µl per well in Costar 3904 96 well plates (Corning Inc., Corning, NY). Enzyme rates were measured at 37°C over the linear range using a Spectromax 250 spectrophotometer with 412 nm absorbance readings. (All reagent stocks were prepared in 100 mM sodium phosphate pH 8.0 unless stated otherwise).</p><p>In order to determine the kinetic mechanism of inhibition, inhibitors and substrate(s) were run in varying concentrations bracketing their Kis and Kms respectively.</p><!><p>To determine enzyme-mediated drug release, 500 µM of prodrug was incubated in 100 mM sodium phosphate pH 8.0 containing 1.0 U enzyme (100 µL total volume) for 3 h at 37°C. Post incubation, samples were quenched with 17.4 M glacial acetic acid and analyzed by analytical reverse-phase HPLC using a Vydac C18 218TP54 column (Western Analytical Products, Lake Elsinore, CA) monitored at 254 and 320 nm. A linear gradient of 0.5–50% (v/v) of solvent B (0.09% v/v TFA/acetonitrile) in solvent A (0.1% v/v TFA/water) from 5 to 15 min, then 50–90% (v/v) B over 5 min was used for all compounds. Peak area and linear dynamic range used to calculate 3,4-DAP was by use of authentic standards. Prodrugs demonstrating greater 3,4-DAP release by AChE over BChE were further analyzed for half-life in mouse sera.</p><!><p>15 µl of a 10 mM prodrug stock was added to 85 µL sera, pre-warmed to 37°C. Samples were then incubated at the following fixed time intervals 0, 5, 10, 20, 40, 60, and 120 min. Upon extraction with 300 µL 0 °C acetonitrile, precipitated proteins were removed by centrifugation (20,817 rcf) and the liquid phase was subsequently analyzed by analytical reverse-phase HPLC as described above. Stability of prodrug was determined based on presence of breakdown product 3,4-DAP. Half-life values were calculated using the 1-hour endpoint samples.</p><!><p>The prodrug concentration producing the 50% AChE and BChE activity inhibition (IC50), along with inhibition constant Ki values were calculated by non-linear regression analysis using GraphPad Prism v.5.0b software (GraphPad Software Inc., CA).</p><!><p>Based on previous reports of SAR and plasma stability, three prodrug models were designed with the hope of discovering dual action AChE inhibitors providing the selective release of 3,4-DAP at the site of intoxication. Class I molecules were designed from substrate specificity studies and modeled such that the anionic binding site of AChE would be occupied by 3,4-DAP while the active site would be occupied by an ester (Figure 1). Upon ester catalyzed hydrolysis, the prodrug would degrade to release 3,4-DAP into the synaptic cleft to act on nearby Kv channels (Figure 1). Class II prodrugs, on the other hand, were designed to contain a carbamoyl scissile linker like the stigmines. Lastly, class III prodrugs were designed to test whether non-specific esterases/peptidases in sera would allow the release of 3,4-DAP slowly over time.</p><!><p>The synthesis of Class I prodrugs followed one of two paths. Class Ia prodrugs (6a–i) began from 4-hydroxybenzaldehyde (1), which was treated with various alkyl acid chlorides affording compounds 2a-i, (Scheme 1). Subsequent reduction with NaBH4 resulted in benzyl alcohols 3a–i. Reaction of aryl azide 4,23 and subsequently its Curtius rearrangement; the resulting isocyanate was trapped by alcohols 3a–i to provide carbamates 5a-i. Finally, reduction of the nitro group with stannous chloride afforded DAP prodrugs 6a–i. Here yields ranged from 4% to 32% over four steps.</p><p>The general synthesis of Class Ib prodrugs followed a similar sequence. For compound 10, 1,2-phenylenedimethanol, (7), was treated with isobutyryl chloride affording 8, (Scheme 2a). Next, alcohol 8 underwent reaction with 4 providing carbamate 9. The nitro moiety was subsequently reduced yielding 10 in an overall yield of 9% over three steps.</p><p>On the other hand, the synthesis of carbamate 14 began from ethylene glycol (11), which was converted to ester 12 using isobutyryl chloride. Conversion to nitrocarbamate 13, vide supra, followed by its reduction, (Scheme 2b), afforded 14 in 12% yield over three steps.</p><!><p>The construction of the class II prodrugs began with the reaction of commercially available 3,4-DAP (15) and methyl chloroformate to provide carbamates 16 and 17 in one pot, (Scheme 3), which upon separation resulted in yields of 10% and 22% respectively. The 3,4-DAP prodrug 19, in which the carbamate is located at the 4-position, was prepared via palladium-catalyzed hydrogenation of the known precursor 18,24 with a yield of 36%.</p><!><p>The synthesis of class III prodrugs are depicted in Scheme 4 and Scheme 5. Amide 21 was obtained via palladium-catalyzed hydrogenation of the known aminopyridine 20,25 (Scheme 4), 68% yield. Diamide 22 was prepared in one step from 3,4-DAP (15) using acetyl chloride.</p><p>The synthesis of amides 25 and 27 proceeded from a common, commercially available starting material, 3-nitro-4-aminopyridine (23). In pursuit of 25, amide bond formation with benzoyl chloride yielded 24, followed by reduction of the nitro group to provide 25, with a yield of 18% over two steps. Synthesis of 27 began with the amide union between 23 and cyclopentanecarbonyl chloride, followed by reduction to provide 27 with a yield of 48% over two steps.</p><p>The final Class III prodrug, 32, started from commercially available succinic anhydride (28), which was treated with isopropyl alcohol to form the ester 29, followed by conversion to acyl chloride 30 (Scheme 5). The reaction of 30 with 23 in the presence of base provided 31, which in turn was reduced to the desired primary amine 32 via palladium-catalyzed hydrogenation. The overall yield over this four-step synthesis was 17%.</p><!><p>From screens of candidate compounds against AChE and BChE, only compounds 6b and 6d, of the substrate-like class I prodrugs, demonstrated moderate selectivity of AChE over BChE, as well as AChE-dependent release of 3,4-DAP (Tables 1 and 2). Both compounds bound to AChE 100-fold more tightly than Km for ACh. Progress curves of substrate consumption in the presence of the inhibitors were essentially linear indicating no significant buildup of acyl-enzyme intermediates (which would give time-dependent inhibition). While inhibition was relatively potent, turnover and release of 3,4-DAP was modest (Table 2). Incubation studies with AChE and BChE at saturating levels of 6b and 6d gave the expected zero order kinetics with apparent kcats that were approximately 10−4 slower than the natural substrates ACh and BCh. Given the higher concentration of 3,4-DAP release by AChE, these two prodrugs were further tested for their respective half-lives in mouse sera. Unfortunately compounds 6b and 6d were unstable to incubation in sera, with half-lives of just 1.2 and 1.9 min respectively. The extremely short half-lives of these molecules are due to unidentified esterases of the labile esters found within the prodrug molecules. The structural similarity of all class I substrate-like prodrugs meant that no other compounds from this class were likely to be stable in mouse sera.</p><p>The carbamates most representative of our intended dual action strategy, compounds 16, 17, and 19 from class II prodrugs all produced moderate to poor inhibition profiles (IC50s: 36– 660 µM) but failed as pseudosubstrates to generate 3,4-DAP enzymatically (Supporting Information Table S2). Simple methyl carbamates of 3,4-DAP are not recognized by the cholinergic esterases as stigmine-like substrates. As such, these carbamates were not analyzed for half-lives in sera.</p><p>Amide 21 from the class III prodrugs demonstrated competitive inhibition of AChE (32 µM Ki). Not surprisingly, the less labile amide bond did not undergo internal release upon incubation with AChE for 3 hours. Amide 32, while potently inhibiting AChE (3 µM Ki) also demonstrated negligible release of 3,4-DAP over the 3 h incubation period (Table 2). The greater stability of the amide-conjugated 3,4-DAP gave this prodrug an appreciable half-life of 2.8 h in mouse sera, providing a path forward for in vivo analysis, as well as elucidating the core functionality necessary in the design and synthesis of additional 3,4-DAP prodrugs.</p><!><p>The design and synthesis of small molecule inhibitors of BoNT have been of great interest over the past decade.26 While most compounds have focused on the direct inhibition of the BoNT protease, few have been designed to symptomatically relieve neuromuscular paralysis by blocking voltage-dependent potassium channels. This report took an alternative approach by investigating the possibility of dual action toward cholinergic enhancement at BoNT damaged synapses. We attempted to mask the Kv channel blocker 3,4-DAP as a carbamate or amide conjugated pseudo-substrate inhibitor of AChE thus allowing its directed delivery to afflicted synapses. The combined effect of the prodrug is to enhance the action potential for the neuron pre-synaptically as well as increase the lifetime of ACh post-synaptically. Although simple methylcarbamate conjugates to 3,4-DAP were not recognized by AChE as pseudo-substrates, the carbamoyl-linked 4-benzylalcohol-phenol esters 6b and 6d were. These compounds bound relatively tightly to AChE (low uM) but were sluggish in their turnover by AChE having only 10−4 the kcat of ACh. The esters within these compounds rendered them unstable to mouse sera.</p><p>Alternatively, amide conjugation of 3,4-DAP exemplified by 32, resulted in compounds that inhibited AChE selectively over BChE with good potency but did not liberate 3,4-DAP through the intended internal release mechanism. The greater stability of the amide bond gave 32 a reasonable half-life (2.8 hours) for the release of 3,4-DAP in mouse sera. Although such compounds lack the dual action originally intended, masking 3,4-DAP for controlled release holds therapeutic promise. On its own, 3,4-DAP generates muscle action potential and muscle contraction in vivo, yet its ability to cross the BBB and produce seizures has questioned the potential therapeutic relevance of this molecule.27 As such, the design of prodrugs of 3,4-DAP that limit toxicity would be pertinent as a means to effectively treat neuro-paralytic disorders including BoNT induced paralysis.</p><p>Three classes of prodrugs were designed, synthesized, and evaluated in vitro with the goal of elucidating structures that act as pseudosubstrates for AChE and release 3,4-DAP at affected neurons, via enzyme mediated catalysis. Localized 3,4-DAP would act to increase vesicular ACh release at intoxicated junctions, allowing the recovery of neuromuscular transmission while reduced acetylcholinesterase activity via AChE inhibition will allow the limited ACh present to persist. We anticipate that continual 3,4-DAP in circulation, released slowly overtime, would nullify the previous inefficacies of concentrated, repeated dosing, as well as BBB penetration.</p><p>Of the 19 compounds synthesized, two demonstrated inhibition and selectivity between enzyme classes, as well as a drug-release profile necessary for half-life determination in mouse sera (6b and 6d). Unfortunately, further testing revealed that these two class I prodrugs were unstable in sera limiting their usefulness in vivo. Prodrug 32 on the other hand, demonstrated inhibition and selectivity for AChE, but did not act as a pseudosubstrate for the enzyme. Regardless, 32 was tested for half-life in sera to determine if unidentified esterases/peptidases present could degrade the prodrug while in circulation, ultimately releasing 3,4-DAP over time. Prodrug 32 in fact had the best half-life of 2.76 h. The stability of 32 in sera may possibly be due to its amide bond, which would not be readily cleaved within the active site of AChE, but may be hydrolyzed by non-specific peptidases in sera. Modeling studies may help to clarify the chemical properties necessary for binding and release via AChE. Insum, 32 could be used as a lead structure to elucidate more potent inhibitors. However, future in vivo experiments will be necessary to validate prodrug 32 as an effective treatment for BoNT intoxication and other neuromuscular disorders.</p><!><p>This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.</p><p> Supplementary Material </p><p>Supplementary data associated with this article can be found, in the online version, at doi:.</p>

PubMed Author Manuscript

Hierarchical Porous Graphene–Iron Carbide Hybrid Derived From Functionalized Graphene-Based Metal–Organic Gel as Efficient Electrochemical Dopamine Sensor

A metal–organic gel (MOG) similar in constitution to MIL-100 (Fe) but containing a lower connectivity ligand (5-aminoisophthalate) was integrated with an isophthalate functionalized graphene (IG). The IG acted as a structure-directing templating agent, which also induced conductivity of the material. The MOG@IG was pyrolyzed at 600°C to obtain MGH-600, a hybrid of Fe/Fe3C/FeOx enveloped by graphene. MGH-600 shows a hierarchical pore structure, with micropores of 1.1 nm and a mesopore distribution between 2 and 6 nm, and Brunauer–Emmett–Teller surface area amounts to 216 m2/g. Furthermore, the MGH-600 composite displays magnetic properties, with bulk saturation magnetization value of 130 emu/g at room temperature. The material coated on glassy carbon electrode can distinguish between molecules with the same oxidation potential, such as dopamine in presence of ascorbic acid and revealed a satisfactory limit of detection and limit of quantification (4.39 × 10−7 and 1.33 × 10−6 M, respectively) for the neurotransmitter dopamine.

hierarchical_porous_graphene–iron_carbide_hybrid_derived_from_functionalized_graphene-based_metal–or

<!>Introduction<!>Reagents and Materials<!>Materials Synthesis<!>Materials Characterization<!>Magnetic Measurements<!>Sensing Measurements<!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!>Conclusions<!>Data Availability Statement<!>Author Contributions<!>Conflict of Interest

<p>Metal-organic gel integrated with an isophthalate functionalized graphene gives rise to a hierarchically porous hybrid Fe/Fe3C/FeOx enveloped by graphene, which enables the highly selective sensing of the neurotransmitter dopamine in presence of ascorbic acid in ratios similar to those of blood serum.</p><!><p>Metal–organic frameworks (MOFs) consisting of organic linkers bridging metal or metal–oxo clusters entail profound benefits when they are used in a variety of applications, such as separations, gas storage, chemical sensing, and catalysis (He et al., 2019; Chen et al., 2020; Huang et al., 2020; Roztocki et al., 2020). Nevertheless, their stability under certain environmental conditions and poor conductivity constitute limiting factors and pose a necessity for new strategies in MOF synthesis and design (Yuan et al., 2018). Toward this, gel-derived MOF synthesis remains a significantly unexplored path. This strategy meets the demand of stability by screening the inorganic metal ion and the organic struts both thermally and chemically inside the inert gel matrix. Crystallization takes place in a controlled way into the stable gel environment, and an in situ–formed MOF is released finally. Moreover, gel-to-crystal transformation provides a way for the construction of more multicomponent functional materials and preserves organization even in the case of incorporation of a nanomaterial, such as graphene that could improve the conductivity and modulate the architecture of the hybrid material (Aiyappa et al., 2015; Zhao et al., 2015).</p><p>Metal–organic frameworks can also constitute a sacrificial template toward the construction of metal–metal oxide or metal carbide nanoparticles via thermal treatment, for example, calcination or pyrolysis (Horike et al., 2009; Wu et al., 2014; Kornienko et al., 2015; Guan et al., 2016; Tian et al., 2017; Jayaramulu et al., 2019). Tailoring structures by tuning the microporosity and mesoporosity of the carbonaceous precursor material, for example, by integrating graphene into the metal–organic architecture, and size control of the produced nanoparticles are issues of critical importance for the properties of the final product and its specific applications (Bak et al., 2015; Zhu et al., 2017; Li et al., 2018a,b). The optimization of these two parameters is anticipated to adjust electron and mass transport, fundamental for application in biosensing (Urbanová et al., 2018; Wang et al., 2018).</p><p>The synergistic action of graphene combined with metal–metal carbide–metal oxide (M/M3C/MOx) nanoparticles provides simultaneously highly active catalytic sites and an excellent electron–transfer interface (Zhang et al., 2018). More specifically, metal-containing nanoparticles interact with the biological analytes, which can act as electron acceptors/donors, whereas the highly conductive graphene allows fast electron transfer kinetics that produces current and triggers fast response time (Gao et al., 2018; Ghanbari and Bonyadi, 2018). Moreover, chemical stability of graphene in acidic and alkaline environment, along with biocompatibility, non-toxicity, colloidal stability, and magnetic properties of metal–metal oxide nanoparticles, might open new perspectives for biomedical applications, such as magnetic resonance imaging (Thapa et al., 2019). In order to achieve such materials, the targeted pyrolysis of carbon precursors doped with metal precursors is a common method.</p><p>Biomarkers are molecules present in the human serum, and their levels in the blood can be indicative of health issues, making the development of new biosensors central aspects of biomedical materials synthesis. Two very common biomarkers of major importance in medical science are dopamine (DA) and ascorbic acid (AA). Recent biomedical advances endow AA as a part of anticancer combination therapy (McConnell and Herst, 2014) and as an antihypertensive agent (Wang et al., 2016) and relate its deficiency to muscle atrophy and deterioration in physical performance (Takisawa et al., 2019). Monitoring of AA and DA biomarkers appears highly appealing because it enables prompt prognosis, disease diagnosis, and treatment. Among various analytical methods (Bazel et al., 2018; Baenas et al., 2019; Ma et al., 2019), the electrochemical assay method provides an ideal platform for sensitive, selective, rapid, accurate, and simultaneous determination of these biomarkers, because they coexist in biological fluids, such as blood serum. A common hurdle to pass is the similar oxidation peak potentials of AA and DA at unmodified conventional electrodes, such as glassy carbon electrodes (GCEs), which results in a voltammetric overlap response (Guo et al., 2018a; Ji et al., 2018; Thirumalai et al., 2018). Besides this, the extremely low level of DA (<1 μM) compared to the concentration of AA (100–1,000 times higher than that of DA) needs to be considered (Ghanbari and Hajheidari, 2015; Edris et al., 2018). To address these issues, as well as the slow interfacial electron transfer, chemically modified electrodes (Anu Prathap et al., 2019) have been developed as sensing platforms based on conductive polymers (Xie et al., 2017; Li et al., 2019), MOFs (Fang et al., 2018), carbonaceous nanomaterials (Luo et al., 2016; Abellán-Llobregat et al., 2018), metal/metal oxide nanoparticles (Chen et al., 2018; Zhao et al., 2019a), and their composites (Grace et al., 2019; Lin et al., 2019; Zhao et al., 2019b).</p><p>Here in this work, we present the targeted synthesis of a metal–organic gel (MOG) consisting of Fe3Cl(H2O)2O clusters interconnected with 5-aminoisophthalic acid (NH2-ip) in the presence of isophthalate functionalized graphene (IG) (Vermisoglou et al., 2019). This ligand is an isomer of 2-aminoterephthalic acid (NH2-bdc), which is used for the preparation of NH2-MIL-101(Fe) (Fe3Cl(H2O)2O(NH2-bdc)3). It is anticipated that, by lowering the symmetry, intentional defects are created, leading to gel formation, with the IG also acting as a structure-directing agent (IG@MOG). This combination enhanced electronic conductivity and reinforced the structure. These iron–carboxylate MOGs served as precursors for the synthesis of carbon-encapsulated M/M3C/MOx nanoparticles on graphene via pyrolysis. The IG@MOG acted as a sacrificial template leading to iron-based derivatives of Fe/Fe3C/FeOx with conductive graphene nanosheets. It should be noted that, by changing pyrolysis temperature, the iron, carbon, oxygen, and nitrogen composition was altered. The resultant composites (after carbonization) showed significant surface area with hierarchical (micro/meso and meso/macro) pores, which is of major importance in electrochemical applications. The resultant metal-containing graphene hybrid MGH-600 (carbonized at 600°C) was investigated for DA sensing in presence of AA and revealed a satisfactory limit of detection. This significant electrochemical performance can be attributed to synergistic effects, where IG serves as a conducting matrix and provides hierarchical pores. MGH-600 exhibited remarkable stability as the electrochemical testing after ~15 months revealed.</p><!><p>Graphite fluoride (C: -F, 1:1.1), 5-aminoisophthalic acid (Niso) (94%), iron(III) chloride hexahydrate puriss p.a. (≥99%), L-AA, DA hydrochloride, and potassium hexacyanoferrate(III) were purchased from Sigma-Aldrich (Prague, Czech Republic). Ethanol (absolute), N, N-dimethylformamide (DMF), potassium chloride, and phosphate-buffered saline (PBS, pH 7.0) were purchased from Penta (Prague, Czech republic). All reagents were used as received without further purification. All stock solutions were prepared with ultrapure water (18 MΩ cm−1).</p><!><p>Isophthalate fluorographene (IG): see reference labeled as FG/Niso-24 h (Vermisoglou et al., 2019).</p><p>MOG: 1.0 g iron(III) chloride hexahydrate and 0.3 g 5-aminoisophthalic acid were dissolved separately in 11.5 mL DMF each. Then they were mixed and stirred for 30 min. The whole was transferred to a Teflon-lined autoclave reactor [Model 4744 General Purpose Acid Digestion Vessel, 45 mL; Parr Instrument Company (Illinois, United States)]. The reactor was placed inside a preheated oven (110°C) for 24 h (BINDER ED series oven drying; Sigma-Aldrich). After cooling down a red-brownish gel came out of the reactor.</p><p>MOG@IG: 1.0 g iron(III) chloride hexahydrate and 0.3 g 5-aminoisophthalic acid were dissolved separately in 11.5 mL DMF each. Then they were mixed, and 0.05 g IG was added under stirring for 30 min. The whole mixture was transferred to a Teflon-lined autoclave reactor (Model 4744 General Purpose Acid Digestion Vessel, 45 mL; Parr Instrument Company). The reactor was placed inside a preheated oven (110°C) for 24 h (BINDER ED series oven drying). After cooling down, a black gel was isolated.</p><p>MOG powder: MOG was dispersed in 80 mL ethanol and stirred for 1.5 h. Then it was centrifuged at a speed 10,000 for 10 min (Sigma 6–16 K Centrifuge), and the supernatant was removed. This washing procedure was repeated twice, and finally, the red-brownish solid was dried in an oven at 60°C for 48 h (BINDER ED series oven drying). The dried solid was ground in an agate mortar (Aldrich).</p><p>MOG@IG powder: MOG@IG was dispersed in 80 mL ethanol and stirred for 1.5 h. Then it was centrifuged at a speed 10,000 for 10 min (Sigma 6–16 K Centrifuge), and the supernatant was removed. This washing procedure was repeated twice, and finally the black solid was dried in an oven at 60°C for 48 h (BINDER ED series oven drying). The dried solid was ground in an agate mortar (Aldrich).</p><p>MGH-600: A crucible containing ~0.1 g MOG@IG powder was placed in the center of a laboratory tube furnace equipped with a quartz glass tube (furnace type: LT 50/300/13) and heated (temperature ramp 5°C/min) under N2 flow (50 mL/min) at 600°C for 6 h. After cooling down to room temperature, a black powder was isolated.</p><p>MGH-400: A crucible containing ~0.1 g MOG@IG powder was placed in the center of a laboratory tube furnace equipped with a quartz glass tube (furnace type: LT 50/300/13) and heated (temperature increase 5°C/min) under N2 flow (50 mL/min) at 400°C for 6 h. After cooling down to room temperature, a black powder came out.</p><p>MGH-800: A crucible containing ~0.1 g MOG@IG powder was placed in the center of a laboratory tube furnace equipped with a quartz glass tube (furnace type: LT 50/300/13) and heated (temperature increase 5°C/min) under N2 flow (50 mL/min) at 800°C for 6 h. After cooling down to room temperature, a black powder came out.</p><!><p>X-ray diffraction patterns were recorded with a X'Pert PRO MPD diffractometer Malvern Panalytical (Worcestershire, United Kingdom) in the Bragg–Brentano geometry equipped with Co-Kα radiation source (40 kV, 30 mA, λ = 0.1789 nm).</p><p>Fourier transform infrared (FTIR) spectra were recorded on an iS5 FTIR spectrometer Thermo Fisher Scientific (Brno, Czech Republic) using the Smart Orbit ZnSe ATR accessory. Briefly, a droplet of an ethanolic dispersion of the test powder material was placed on a ZnSe crystal and left to dry and form a film. Spectra were acquired by summing 100 scans, using N2 gas flow through the ATR accessory.</p><p>X-ray photoelectron spectroscopy (XPS) was carried out with a PHI VersaProbe II [Physical Electronics (Münich, Germany)] spectrometer using an Al Kα source (15 kV, 50 W). The obtained data were evaluated with the MultiPak (Ulvac; PHI, Inc.) software package.</p><p>Raman spectra were collected using a DXR Raman spectroscope (Thermo Scientific [Brno, Czech Republic)] equipped with a laser operating at a wavelength of 633 nm.</p><p>The 57Fe zero-field Mössbauer spectra were recorded at room temperature employing a Mössbauer spectrometer (MS2007) operating in a constant acceleration mode and equipped with a 50 mCi 57Co(Rh) source (Pechousek et al., 2010; Pechoušek et al., 2012). The acquired 57Fe Mössbauer spectra were processed (i.e., noise filtering and fitting) using the MossWinn software program (Klencsár et al., 1996). The values of the isomer shift were referred to α-Fe foil sample at room temperature.</p><!><p>Samples were analyzed using a Quantum Design Physical Properties Measurement System [PPMS DynaCool system (Darmstadt, Germany)] with the vibrating sample magnetometer option. The experimental data were corrected for the diamagnetism and signal of the sample holder. The temperature dependence of the magnetization was recorded in a sweep mode of 1 K/min in the zero-field-cooled (ZFC) and field-cooled (FC) measuring regimens. To get the ZFC magnetization, the sample is first demagnetized at a temperature higher than the blocking temperature (magnetic moments of all particles are randomly oriented), and after that, it is cooled down without applied magnetic field to a temperature lower than the blocking temperature. In the last step, an external magnetic field (1,000 Oe) is applied, and the magnetization is recorded upon warming the sample. To obtain the FC magnetization curve, almost the same process is performed, but with applied external magnetic field during cooling of the sample.</p><p>Surface area and pore size analyses were performed by means of N2 adsorption/desorption measurements at −196°C, on a volumetric gas adsorption analyzer [3Flex; Micromeritics (Norcross, Georgia, United States)] up to 0.9626 bar. The sample was degassed under high vacuum (7 × 10−2 mbar) for 12 h at 110°C, whereas high-purity (99.999%) N2 and He gases were used. The Brunauer–Emmett–Teller (BET) area was determined assuming a molecular cross-sectional area of 16.2 Å2 for N2 (−196°C). The isotherms were further analyzed by means of non-local Density Functional Theory (DFT) slit pore kernels for N2.</p><p>The samples were also analyzed by scanning electron microscopy (SEM) on a Hitachi SU6600 instrument (Mannheim, Germany) with an accelerating voltage of 5 kV. Transmission electron microscopy (TEM) images were obtained on a JEOL 2100 (Tokyo, Japan) instrument equipped with an LaB6-type emission gun operating at 200 kV. STEM-HAADF (high-angle annular dark-field imaging) analyses for elemental mapping of the products were performed with an FEI Titan HRTEM (Tokyo, Japan) (high-resolution TEM) microscope operating at 200 kV. For these analyses, a droplet of a dispersion of the material in ethanol with concentration of ~0.1 mg mL−1 was deposited onto a carbon-coated copper grid and dried.</p><!><p>All electrochemical measurements were performed using a PGSTAT128N potentiostat (Metrohm Autolab B.V., Prague, Czech Republic) monitored by NOVA software (version: 1.11.2). A typical three-electrode configuration was used. Bare or MGH-600 sample modified GCEs were used as working electrodes; a saturated Ag/AgCl (2Theta, Český Tešín, Czech Republic) and a platinum wire electrode served as reference and counter-electrode, respectively. Electrochemical impedance spectroscopy (EIS) measurements were performed in 0.1 mol L−1 KCl electrolyte containing 5 mmol L−1 K3Fe(CN)6 redox probe; otherwise, PBS (pH 7.0) was used as a supporting electrolyte. Glassy carbon electrodes were modified as follows. They were first polished on wet silicon carbide paper using 1 and 0.05 μm Al2O3 powder sequentially and then washed in water and ethanol for a few minutes, respectively. Thereafter, 10 μL drop of MGH-600 aqueous suspension in (2 g L−1) was coated onto the GCE surface and allowed to dry at laboratory temperature to form a thin film.</p><!><p>The solvothermallly prepared iron organic gel without graphene had a dark red-brownish color (Scheme S1), whereas in the presence of isophthalate graphene (IG), a black gel was formed (Scheme 1). The DMF present in the Teflon-lined autoclave was completely immobilized in the porous gel, as verified by the "tube inversion" method (Scheme S2). Isophthalate graphene was used in order to direct in situ the interfacial gelation along the surface of IG through coordination of the metal clusters with the isophthalate groups anchored to the graphene. Moreover, it acted as a physical cross-linker and as a directing agent for the formation of the porous structure. Isophthalate graphene served as a structural reinforcement nanofiller, triggering the growth of robust ordered lamellar structures and increased conductivity. The MOG@IG displayed "honeycomb" porous three-dimensional (3D) architecture (Scheme 1) (Wang et al., 2015; Vermisoglou et al., 2018). Isophthalate graphene's role as a structure-directing agent could be fulfilled up to a certain concentration, while excessive amounts (e.g., double the amount used in this work) inhibited the gelation process. A 3D MOG network is anticipated to be formed by a self-assembly process in between IG interfaces where the metal would be coordinated to the organic linkers, and other non-covalent interactions occur between the constituents, such as hydrogen bonding or π-π stacking, which attributes to the profound gelation ability (Jayaramulu et al., 2017). Metal–organic frameworks are built up by various metals and organic linkers to produce 3D crystalline porous coordination networks under coordination continuation conditions. However, under coordination perturbation conditions, solvothermal treatment will lead to MOG formation (Li et al., 2013). The coordination of 5-aminoisopthalate and iron ion clusters yields octahedrally coordinated Fe3+ with carboxylate oxygen atoms because of the stronger coordination of Fe-O compared to Fe3+ cation- aqueous solvent interactions. Therefore, Fe3+ metal ions and 5-aminoisopthalate form MOF-like structure, which aggregates to an amorphous MOG (Scheme S1). The introduction of IG disrupts the MOF crystal growth, enhancing mismatch growth over oriented crystallization, where the MOF nanoparticles initially undergo controlled growth and are selectively chelated with oxygen functionalities of IG sheets (Scheme 1).</p><!><p>Schematic illustration of IG-based metal–organic gel (MOG@IG) (inset shows optical image of black gel), which produced (after solvent removal) hierarchical porous metal–metal carbide–metal oxide composite (M/M3C/MOx) under carbonization at various temperatures.</p><!><p>By removing the DMF solvent from the MOG (Scheme S1) by a mild and slow-drying process, the as-produced MOG powder was obtained. The powder XRD shows broad reflections, and it clarifies the amorphous behavior (Figure 1a). The participation of carboxylate groups in bonds with Fe3+ was verified by FTIR spectroscopy data. In MOG@IG (powder) spectrum (Figure 1b), the observed vibrational frequencies νasym (COO−) (1,646 and 1,569 cm−1) and νsym (1,369 cm−1) for the carboxylate ligands indicate on the coordination of the carboxylic acid groups with the metal ions through deprotonation (Vermisoglou et al., 2014). Fourier transform infrared spectra of MOG, as well as the parent materials, are presented in Figures S1A–C. X-ray photoelectron spectroscopy survey data, high-resolution C 1s, Fe 2p, and O 1s spectra are presented in Figures S2A–D, whereas the atomic percentages (at. %) of various functional groups present in IG and MOG@IG composite obtained from deconvolution of the high-resolution C 1s XPS spectrum are summarized in Table S1. The C1s XPS spectrum of MOG@IG powder compared to that of IG (Figure S2B) clearly indicates the presence of the ligand functional groups. Moreover, from high-resolution Fe 2p XPS spectrum (Figure S2C), the fingerprint of Fe3+ electronic structures and the absence of Fe2+ were verified, whereas the peak separation ~13.9 eV was equal to the peak separation of MIL-100(Fe) attributed to α-Fe2O3 nodes in the MOG framework. Further, in the high-resolution O 1s XPS spectrum (Figure S2D) the peaks at 530.1, 531.8, and 533.3 eV are assigned to the Fe-O, O=C, and O–C bonds in MOG@IG.</p><!><p>(a) Simulated XRD pattern of MIL-100(Fe) and experimental XRD patterns of MOG and MOG@IG powders; (b) FTIR spectrum of MOG@IG powder; (c) dark-field HRTEM image of an MOG@IG flake used for EDS chemical mapping: (d) carbon map, (e) oxygen map, (f) nitrogen map, (g) iron map, (h) chlorine map (Cl acts as counter-anion stemming from FeCl3·6H2O precursor), (i) fluorine map (F stemming from IG), and (j) overall map of all these elements.</p><!><p>The Raman spectrum of MOG powder (Figure S3, bottom) has the typical characteristic signals of MIL-100 (Fe), as reported in the literature (Lohe et al., 2009; Wan et al., 2018; Gong et al., 2019). These findings along with FTIR data support MIL-100 (Fe)–like features in the MOG material. In the presence of graphene (Figure S3, top), the graphene characteristics prevail in the Raman spectrum of MOG@IG as it is documented by the D and G peaks. The intensity ratio of D to G signal exceeds 1 (i.e., 1.16) anticipated for covalently functionalized graphene (Vermisoglou et al., 2019). In order to confirm the purity of MOG@IG sample, 57Fe Mössbauer spectroscopy was used (Figure S4), and Mössbauer hyperfine parameters, derived from spectra fitting, are summarized in Table S2. The spectral profile can be decomposed to the one doublet component corresponding to the Fe3+ ions octahedrally coordinated in a high-spin state (S = 5/2).</p><p>Figure S5A depicts a typical SEM image of MOG@IG before solvent removal, where a sponge-like morphology is observed. In the corresponding TEM image of MOG@IG (Figure S5B), IG flakes can be observed in the gel environment and are also present in MOG@IG powder after the solvent removal (Figure S5C). Dark-field HRTEM images of an MOG@IG flake were used for energy-dispersive X-ray spectroscopy (EDS) elemental mapping (Figure 1c). Energy-dispersive X-ray spectroscopy density maps (Figures 1d–j) revealed a dense and homogeneous distribution of all the involved elements, that is, C, O, N, Fe indicating uniformly coexisting MOG and IG. This implies highly organized structures where the accommodation of MOG structure between the graphene layers or alternatively the incorporation of graphene into MOG is homogeneous.</p><p>MOG@IG powder was subjected to carbonization at 600°C for 6 h under N2 atmosphere in order to improve properties, such as BET surface area and conductivity, which would upgrade its performance, for example, in electrochemical sensing applications. The FTIR spectrum of the as-produced MGH-600 (Figure 2a) reveals C sp2 hybridization and absence of the characteristic functional MOG groups. The XRD pattern of MGH-600 XRD (Figure 2b) confirms the presence of graphene (low intense broad reflection at 2θ = 30.5°, Co k-alpha radiation λ = 1.9373 Å) of Fe, iron carbide (Fe3C), and magnetite (Fe3O4) (JCPDS cards no. 00-041-1487 for graphite, No. 03-065-4899 for Fe, no. 01-089-2722 for Fe3C, and no. 00-076-0956 for Fe3O4). Fourier transform infrared spectra and XRD patterns of the samples MGH-400 and MGH-800, where the carbonization temperatures were 400 and 800°C, are presented in Figures S1E–G, S6.</p><!><p>(a) FTIR spectrum and (b) XRD pattern of MGH-600; (c) Raman spectrum on a MGH-600 particle (bottom) and (d) on graphene flake (top) of MGH-600; (e) Mössbauer spectrum of MGH-600; (f) High-resolution N 1s spectrum of MGH-600; (g,h) N2 sorption isotherms of MOG@IG powder and MGH-600 and the corresponding PSD; (i,j) Magnetization and mass susceptibility measurements of the MGH-600 sample; (k) MGH-600 (dispersed in ethanol) behavior under the application of a magnetic field.</p><!><p>Raman spectroscopy can provide further insight on the structure of the graphite-encapsulated nanoparticles (Figure 2c) and on the graphene flakes (Figure 2d) present in the composite material MGH-600. Both spectra bear the characteristic graphene D (~1,332 cm−1) and G (~1,585 cm−1) bands assigned to disorder/defects and C sp2, but the spectrum of the encapsulated nanoparticles exhibits in the range 200–600 cm−1 the iron carbide and/or zero valent iron peaks, with the latter possibly being overlapped by the former (Liu et al., 2014; Alahmadi and Siaj, 2018). Moreover, the spectrum of the graphene flake reveals a symmetrically shaped 2D peak (~2,666 cm−1) implying few layered graphene flakes. This is also supported by an intensity ratio ID/IG ~0.9 < 1. Further increase of the carbonization temperature to 800°C triggers an even more intense symmetric and low full width at half maximum 2D band, indicating fewer graphene layers, but this improvement in graphene quality is accompanied by a larger size of iron-containing nanoparticles (see Figures S7–S9; Raman spectrum, SEM images, and TEM images, respectively). To get a deeper insight into the chemical nature of the nanoparticles, 57Fe Mössbauer spectroscopy at room temperature was employed (Figure 2e). A fitting model consisting of four sextets was adopted to correctly describe the spectrum profile. The dominant sextet component reflects the presence of zero valent iron nanoparticles (nZVI) in the system with determined Mössbauer hyperfine parameters depicted in Table S2. The sextet with lowest value of hyperfine magnetic field belongs to the Fe3C nanoparticles present in the system. The last two sextets in the spectrum confirm the presence of magnetite, where the sextet with the higher magnetic hyperfine field defining the Fe3+ ions located in the tetrahedral sites, whereas the sextet with the lower values of the hyperfine magnetic field is attributed to the Fe2+ and Fe3+ ions occupying the octahedral sites in the magnetite spinel crystal structure. Mössbauer spectra of MGH-400 and MGH-800 are illustrated in Figure S10.</p><p>The XPS survey spectra reveal a nitrogen content of ~4.1 at. %, and the high-resolution XPS N1s spectrum (Figure 2f) contains three peaks at 398.6, 399.9, and 401.5 eV corresponding to pyridinic N, pyrrolic N, and graphitic N, implying nitrogen-doped MGH-600 in accordance with the literature (Guo et al., 2018b). The BET-specific surface areas derived from nitrogen adsorption/desorption isotherms were 58 and 218 m2/g for MOG@IG powder and MGH-600, respectively (Figure 2g). Mesopores still exist in MGH-600, but also extended microporosity appears with pore size distribution centered at ~1.1 nm (Figure 2h). During the carbonization process, the 5-aminoisophthalate linkers present in the MOG@IG act not only as N source leading to disrupted N-doped graphene but also an etching source due to ammonia gas that is produced from polycondensation reactions creating thus microporosity (Tang et al., 2019). Nitrogen sorption isotherms, BET surface areas, and the corresponding Pore Size Distribution (PSD) for all samples are presented in Figures S11, S12.</p><p>To unveil the magnetic properties of the MGH-600 sample, hysteresis loops and ZFC/FC magnetization curves were recorded (Figures 2i,j). The magnetization vs. applied field at room temperature does not show a hysteresis (Figure 2i) indicating superparamagnetic behavior of the nanoparticles, where the spins of all magnetic nanoparticles fluctuate between the orientations of the easy axis of magnetization. As the temperature decreased to 5 K, the sample shows certain values of coercivity (HC) and remanence (MR) reflecting that the system is in a blocking state below transition temperature (Tuček et al., 2006). The saturation magnetization of nZVI (~130 emu/g) is reduced with respect to the value commonly observed for nZVI (~200 emu/g) due to normalization to the weight of the sample also containing Fe3C nanoparticles and a carbon scaffold. Nevertheless, the system shows a very strong magnetic response as evidenced by reaching the magnetic saturation under small applied magnetic fields (below 1 T, see Figure 2i).</p><p>From the magnetic point of view, the blocked state is very often also documented by a maximum at the ZFC magnetization curve recorded during the ZFC-FC measurement (Figure 2j). The onset of a maximum in the ZFC curve is significant around 50 K, suggesting the presence of a superparamagnetic fraction. The superparamagnetic fraction is probably composed of Fe3C nanoparticles, because the rest of the ZFC-FC curves are dominated by the usually observed response of nZVI nanoparticles. MGH-600's behavior under the application of a magnetic field is illustrated in Figure 2k.</p><p>Figure 3a shows an SEM image of the MGH-600 material, which comprised curved sheets, and because of this morphology, restacking is prevented, resulting thus in a high BET-specific surface area. Furthermore, the presence of carbon-encapsulated iron/iron carbide/iron oxide nanoparticles on the graphene interfaces hinders aggregation and restacking. Such a nanoparticle can be observed in the TEM micrographs (Figure 3b) with a size close to 50 nm. In the same image, thin almost-transparent folded graphene sheets are observed, which are indicative of an extensively exfoliated material. This extended exfoliation could be attributed (a) to the initially functionalized graphene that was used for the synthesis of MGH-600; (b) to solvothermal conditions, where under high temperature and pressure the solvent molecules penetrate between the graphene sheets; and mostly (c) to pyrolysis conditions, where decarboxylation and condensation reactions take place, and gaseous species, such as NH3 or CO2 can be rapidly developed in parallel with iron-containing nanoparticles forming. Going from MOG@IG to carbon-encapsulated nanoparticles has an additional advantage that both the metal and the carbon source are present in the parent material. A TEM image of an iron-containing particle is presented in Figure 3c, and EDS density maps (Figures 3d–i) revealed the presence of carbon and nitrogen extending throughout the image also out of the particle area, whereas oxygen is more dense on the upper part of the particle as if the iron-containing particle is surrounded by an N-doped graphitic layer and preferentially oxide on the top (Figure 3j). The nitrogen mapping is an additional evidence of the presence of N-doped graphene.</p><!><p>(a) SEM and (b) TEM morphological characteristics of MGH-600; (c) HRTEM image of an iron-containing nanoparticle of MGH-600 and the corresponding EDS chemical mapping: (d) carbon map, (e) iron map, (f) nitrogen map (g) oxygen map, and overall maps of (h) iron and carbon, (i) iron, carbon and nitrogen, and (j) iron and oxygen elements.</p><!><p>The electrochemical performance of MGH-600 was studied by means of cyclic voltammetry (CV), EIS, and square-wave voltammetry (SWV). This material was chosen to be studied thoroughly among MGH-400 and MGH-800 because the CV response of the GCE modified with different MGH samples in the presence of PBS buffer (pH 7.0) containing both DA (cDA = 2.5 mmol L−1) and AA (cAA = 2.5 mmol L−1) had the maximum ability to facilitate the electron transfer and allow the separation of both molecules (Figure S13). This could be attributed to a "balance" between graphene formation and particle size, giving thus rise to a high BET surface area (Figure S11). As the pyrolysis temperature increased from 400 to 800°C, the qualitative Raman spectra characteristics of graphenes, such as low ID/IG intensity ratio and a symmetric intense 2D peak were improved (Figure 2d and Figure S7). Nevertheless, this improvement was accompanied by iron-containing nanoparticle aggregation as it can be observed in TEM images (Figure S9). The threshold for having graphene nature quality avoiding nanoparticle aggregation corresponded to pyrolysis temperature of 600°C. This can be also supported by the BET surface area that was maximized at this temperature (Table S3), as well as the performance in CV measurements (Figure S13). Figure 4A shows a set of CVs recorded with the bare GCE and GCE modified with MGH-600 sample in the presence of 0.1 mol L−1 KCl electrolyte containing 5 mmol L−1 ferricyanide(III) as an electroactive probe. As can be seen, the bare GCE exhibits a faradaic response of ferricyanide(III) giving the current density of ja = 0.72 mA cm−2 (peak-to-peak separation ΔEp = 160 mV). As it is evident, the presence of the MGH-600 sample can significantly boost the voltammetric performance (ja = 1.57 mA cm−2) and reduce the value of peak-to-peak separation up to ΔEp = 90 mV to make the electrochemical process more reversible. It is very well-known that the estimation of the heterogeneous electron transfer rate constant, k0, has a paramount importance when the electrochemical performance of a novel material is examined (Randviir, 2018). Because of this reason, a method of EIS was employed. A closer inspection revealed that the GCE modified with MGH-600 exhibits significantly lower value of charge-transfer resistance (Rct = 75.7 Ω) compared to the unmodified GCE (Rct = 370 Ω). It should be noted that the Rct value calculated from the equivalent circuit fitting in EIS (for circuit details, see inset in Figure 4B) is inversely proportional to the exchange current density via the equation (Randviir and Banks, 2013; Randviir, 2018):</p><p>where i0 = nFAk0c. Following this fact, one can conclude that</p><!><p>(A) CV response of bare GC electrode and GC electrode modified with MGH-600 sample in the presence of 0.1 mol L−1 KCl electrolyte containing 5 mmol L−1 ferricyanide(III). (B) EIS response of bare GC electrode and GC electrode modified with MGH-600 sample in the presence of 0.1 mol L−1 KCl electrolyte containing 5 mmol L−1 ferricyanide(III); inset: modified Frumkin–Melik–Gaykazyan circuit used for fitting of impedance data; additional parameters: 5-mV AC amplitude, a bias potential of 220 mV, the frequency range from 0.1 Hz to 100 kHz. (C) CVs response of the bare GC electrode and GC electrode modified with MGH-600 sample in the presence of PBS buffer (pH 7.0) containing both DA (2.5 mmol L−1) and AA (2.5 mmol L−1). (D) SWV records (after the background subtraction) of the GC electrode modified with MGH-600 sample in the presence of various concentrations of DA and constant concentration of AA (1 mmol L−1); additional parameters: amplitude 25 mV, step height 5 mV, frequency 25 Hz.</p><!><p>Considering the aforementioned k0 was estimated to be 2.03 × 10−3 and 9.95 × 10−3 cm s−1 for bare GC and GCE modified with the MGH-600 sample, respectively. As it stands, the obtained EIS results are in good agreement with those obtained by CV and prove that MGH-600 has the ability to enhance electron transfer. Such an improvement can be explained by the structure of MGH-600. As mentioned previously, MGH-600 exhibits a highly porous structure where carbon atoms in sp2 hybridization prevail. Such findings together with the fact that the material itself is N-doped create a plausible explanation of the nature of this highly conductive system. Furthermore, the MGH-600 sample was tested as a promising catalyst for the electrochemical determination of DA and AA (further abbreviated as DA and AA, respectively). Figure 4C displays a CV response of the bare GCE and GCE modified with MGH-600 in the presence of PBS buffer (pH 7.0) containing both DA (2.5 mmol L−1) and AA (2.5 mmol L−1). It is possible to recognize that with the bare GCE there is no chance to separate both molecules, as discussed in the Introduction. On the contrary, MGH-600 has the great ability to facilitate the electron transfer and then allows the separation of both analytes. While SWV offers higher sensitivity and good separation background current, we decided to use this technique to further study the DA detection. Figure 4D shows the typical SWV record (after background subtraction) of the GCE modified with MGH-600 in the presence of various concentrations of DA. As can be seen, the current density showed a good linear relationship vs. the DA concentration and was expressed as ja = 0.0113c – 0.0257 (R2 = 0.9935) and ja = 0.0148c – 0.0043 (R2 = 0.9965) in the ranges of 0.5–5 and 10–50 μmol L−1, respectively. Moreover, the addition of AA as a common interferent has no significant influence during the determination of DA. Using the first concentration range, the values for LoD (limit of detection) and LoQ (limit of quantification) were calculated to be 0.44 and 1.33 μmol L−1, respectively. The presence of two linear regression equations reflects the different adsorption behavior of DA at different concentration levels. From the beginning, rapid adsorption of DA on the GCE modified with MGH-600 leads to a rapid increase of the current density. On the other hand, another increase of DA concentration results in slower increase of current density. Such observation can be explained by impurities coming from the oxidation processes of DA, which reduce the kinetics of electron transfer. Further, our results are comparable with various MOF-derived/iron-based hybrid nanocomposite materials in the literature in terms of performance in DA sensing (Table S4). To show the practical applicability of the MGH-600 sample as a successful sensing platform, a stability test was performed using CV. Figure S14 depicts that even after 15 months the electrode modified with the MGH-600 sample exhibits similar current response toward DA determination as freshly synthesized sample (the drop of current density was found to be 13.1% only). Moreover, the 15-months-old sample still has the same ability as the fresh sample to distinguish between both DA and AA molecules. This sample was also investigated microscopically after this term. The TEM images (Figure S15) illustrate graphene sheets almost transparent with few aggregates of iron-containing nanoparticles. This justifies the small drop of performance in electrochemical testing and confirms the significant stability of sample.</p><!><p>In summary, synthesis of gel-derived MOG network with homogeneously incorporated isophthalate graphene participating as a structure-directing agent led in porous honeycomb lamellar structures. The graphene incorporation in a uniform way into this structure enriches its properties with all the outstanding properties of graphene especially regarding conductivity and specific surface area. This material acts as a scaffold and by carbonization results in magnetic graphene hybrids that could have a wide range of potential applications, among them highly selective sensing of DA in presence of AA in ratios similar to those of blood serum. The stability of these hybrids based on the inertness of graphene sheets and the carbon-encapsulated M/M3C/MOx-containing particles render them exceptionally appealing both for biosensing and magnetic applications.</p><!><p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://data.mendeley.com/datasets/958n75m59g/draft?a=5f81a7c5-09b4-401d-a9f6-1b1fb56912fe.</p><!><p>EV, PJ, RZ, RF, KJ, and MO designed the study. EV and KJ synthesized the materials. EV, OM, VK, and AS characterized the materials. EV interpreted FTIR and Raman spectra and interpreted FTIR, XPS, Raman, BET, microscopy and mapping, and XRD. OM performed and interpreted the magnetic and Mössbauer measurements. VK performed and interpreted BET measurement. AS provided the mechanistic insights. PJ carried out and interpreted the electrochemical experiments. All authors contributed to the article and approved the submitted version.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

A diketopyrrolopyrrole dye-based dyad on a porous TiO2 photoanode for solar-driven water oxidation†

Dye-sensitised photoanodes modified with a water oxidation catalyst allow for solar-driven O2 evolution in photoelectrochemical cells. However, organic chromophores are generally considered unsuitable to drive the thermodynamically demanding water oxidation reaction, mainly due to their lack of stability upon photoexcitation. Here, the synthesis of a dyad photocatalyst (DPP-Ru) consisting of a diketopyrrolopyrrole chromophore (DPPdye) and ruthenium-based water oxidation catalyst (RuWOC) is described. The DPP-Ru dyad features a cyanoacrylic acid anchoring group for immobilisation on metal oxides, strong absorption in the visible region of the electromagnetic spectrum, and photoinduced hole transfer from the dye to the catalyst unit. Immobilisation of the dyad on a mesoporous TiO2 scaffold was optimised, including the use of a TiCl4 pretreatment method as well as employing chenodeoxycholic acid as a co-adsorbent, and the assembled dyad-sensitised photoanode achieved O2 evolution using visible light (100 mW cm−2, AM 1.5G, λ > 420 nm). An initial photocurrent of 140 μA cm−2 was generated in aqueous electrolyte solution (pH 5.6) under an applied potential of +0.2 V vs. NHE. The production of O2 has been confirmed by controlled potential electrolysis with a faradaic efficiency of 44%. This study demonstrates that metal-free dyes are suitable light absorbers in dyadic systems for the assembly of water oxidising photoanodes.

a_diketopyrrolopyrrole_dye-based_dyad_on_a_porous_tio2_photoanode_for_solar-driven_water_oxidation†

Introduction<!>Synthesis and characterisation<!>Photophysical properties<!>Electrochemical properties<!>Photoelectrochemistry under sacrificial conditions<!>Photoelectrochemical water oxidation<!>Oxygen quantification<!>Performance and comparison with state-of-the-art<!>Conclusions<!>Conflicts of interest

<p>The integration of a molecular dye and a water oxidation catalyst (WOC) onto an n-type metal oxide (e.g., titanium dioxide, TiO2) semiconductor (SC) film on a conductive substrate (e.g., fluorine-doped tin oxide, FTO), produces a dye-sensitised photoanode for visible light-driven O2 evolution in photoelectrochemical (PEC) cells.1,2 Dye-sensitised photoanodes operate by photoexcitation of the dye (S), which results in ultra-fast (typically sub-ns) electron injection from the excited state (S*) to the conduction band (CB) of the semiconductor.3 This step is followed by hole transfer to the WOC, which regenerates the oxidised dye (S+). Repeated cycles allow the catalyst to accumulate four holes to oxidise water to O2.4–6 Ruthenium complexes are the most commonly employed molecular WOCs due to their fast O2 evolution rates at low overpotentials, with [RuII(bda)(pic)2] (bda = 2,2′-bipyridine-6,6′-dicarboxylic acid, pic = 4-picoline) displaying benchmark performance.7,8</p><p>Co-immobilisation of the dye and WOC on an electrode results in fast electron–hole recombination at the molecule–electrode interface, thereby resulting in limited efficiency.6,9 These unfavourable recombination dynamics can in principle be overcome by covalently linking the chromophore to the catalyst, forming a dyadic system in which the catalyst is placed farther away from the electrode surface (Fig. 1). Dyads thereby enable fast interfacial electron transfer from the dye to semiconductor electrode, and intramolecular quenching of S+ by the WOC combined with slow recombination of semiconductor electrons with holes accumulated in the oxidised WOC.3,10</p><p>Dyads have previously been constructed using Ru-based dyes and [RuII(bda)] WOCs, and have been integrated in TiO2 photoanodes either by immobilisation of the synthesised assembly,11 or by in situ polymerisation.12–14 However, dyad photoanodes typically rely on precious-metal chromophores, and the need for reduced cost has led to the exploration of earth-abundant chromophores with more intense visible light absorption, embodied by metal porphyrins15 and organic dyes.16 An example of a zinc porphyrin-based dyad has been reported, but the chromophoric unit lacks sufficient oxidation potential for light-activation of the [Ru(bda)]-based WOC.15 Organic dyes, frequently designed with push–pull architectures, have been co-immobilised with [RuII(bda)]-type catalysts on dye-sensitised photoanodes, albeit with low efficiencies.17–23</p><p>Diketopyrrolopyrroles (DPPs) are a class of chromophores known for their high photostability and intense light absorption, which can be tuned to absorb even red and infra-red photons.24,25 Immobilisation onto metal oxides in both n-type and p-type dye-sensitised solar cells (DSSCs) has been achieved using a surface anchoring group.26–31 Recently, DPPs were also co-immobilised with molecular catalysts on colloidal TiO2 nanoparticles, and CuCrO2 delafossite and NiO photocathodes for visible light-driven H2 evolution.32,33</p><p>In this study, we report the synthesis, optical properties, electrochemistry and PEC performance of a bespoke molecular dyad, DPP-Ru (Fig. 1), where a tailor-made DPP chromophore is covalently linked to a [RuII(bda)]-type WOC. The chromophore unit contains a pyridine moiety to coordinate to the ruthenium catalyst, and an alkyl spacer chain to provide flexibility for the dimerisation of the Ru unit for improved catalysis.11,34–36 A thiophene unit increases planarity and shifts the absorption maximum to longer wavelengths, allowing more incident solar photons to be harvested.37,38 The incorporation of bulky alkyl chains on the DPP core allow for increased hydrophobicity and limit π–π aggregation of the molecule.25DPP-Ru is then immobilised on a porous TiO2 electrode via a cyanoacrylic acid anchoring group, which allows for localisation of the LUMO near the electrode surface, facilitating electron injection into the bulk of the TiO2 semiconductor.30 Optimisation of immobilisation conditions and surface coverage results in a dyad-sensitised photoanode for light-driven water oxidation to O2.</p><!><p>The DPP-Ru dyad (Fig. 1b) was prepared by a convergent synthesis protocol, firstly forming the bespoke chromophore, DPPdye, followed by complexation to the ruthenium moiety, RuWOC [RuII(bda)(dmso)(pic)] (dmso = dimethyl sulfoxide) (Scheme 1). The synthesis of DPPdye started by preparation of the bridging moiety, 1, through a two-step synthesis from 4-picoline (Scheme S1†). A Suzuki cross-coupling with DPPI (synthesised by a previously reported procedure)39 afforded DPPII with a yield of 95%. A Knoevenagel condensation with cyanoacetic acid in the presence of piperidine afforded DPPdye in 84% yield. Finally, reflux of RuWOC (synthesised following a previously reported procedure)40 with DPPdye in methanol (MeOH) and triethylamine afforded the dye-catalyst assembly DPP-Ru in 31% yield. The crude product contained a mixture of DPPdye, DPP-Ru, [RuII(bda)(pic)2] and [RuII(bda)(DPPdye)2], and accounts for the lower yield. The compounds were purified by column chromatography, and the composition and purity were confirmed by 1H, 13C and 11B NMR spectroscopy (Fig. S1–S5†), high-resolution mass spectrometry, infrared spectroscopy and elemental analysis (see ESI for details†).</p><!><p>The UV-vis absorption spectra of DPPdye, DPP-Ru and [RuII(bda)(pic)2] were recorded in N,N-dimethylformamide (DMF) solution (Fig. 2a). The spectrum of DPPdye features an intense band at 499 nm (ε = 27.9 mM−1 cm−1), matching the highest intensity of the solar spectrum, and a tailing absorption up to 560 nm. This characteristic DPP-absorption is attributed to a π–π* HOMO–LUMO transition. Density functional theory (DFT) calculations on similar DPP chromophores have indicated that this transition originates from the DPP core and extends to the cyanoacrylic acid group.39 The second band at 390 nm can be attributed to a HOMO−1 to LUMO and HOMO to LUMO+1 transition.39</p><p>Due to the break in conjugation between the dye and the catalyst, introduced by the ethylene-bridge, only a marginal change in the DPP absorption spectrum is observed upon complexation with the Ru centre in DPP-Ru. The dyad also features a strong absorption band at 302 nm, also observed in the [RuII(bda)(pic)2] spectrum, which is characteristic of [RuII(bda)] complexes.41</p><p>Upon photoexcitation at 499 nm, the emission spectrum of DPPdye shows a broad band centred at 587 nm, with a vibronic shoulder at 627 nm, in aerated DMF solution (Fig. S6†). The large Stokes shift is typical of phenyl flanked DPP dyes, due to their torsion angle.42 The emission trace is similar for DPP-Ru (Fig. S7†). Absolute quantum yield measurements for DPPdye reached 65%, whereas DPP-Ru achieved 4%. This efficient luminescence quenching is indicative of an intramolecular electron transfer from the ruthenium centre to the excited chromophoric unit.43</p><p>Immersion of a mesoporous TiO2 film (anatase nanoparticles, ca. 20 nm diameter, ca. 6 μm thick) coated on a glass slide in a solution of DPPdye and DPP-Ru in dichloromethane (DCM) leads to a strong colouration of the electrodes, demonstrating the affinity of the molecules to the metal oxide surface.44 The spectra also remain largely unchanged upon immobilisation, confirming that the molecules retain their absorption properties on the electrode (Fig. 2b).</p><!><p>Using cyclic voltammetry (CV), the electrochemical properties of DPPdye and DPP-Ru were examined in solution (DMF) and when chemisorbed on a mesoporous indium tin oxide (mITO; particle size < 50 nm, film thickness ∼3 μm)45–47 electrode in acetonitrile (MeCN), containing tetrabutylammonium tetrafluoroborate (TBABF4, 0.1 M) as the supporting electrolyte. MeCN was used for the electrochemical experiments with mITO due to the lower solubility of the molecules in MeCN than DMF, which increases their anchoring stability on the electrode. For irreversible oxidations, the half-peak potentials (E(p/2)) were used to estimate the thermodynamic oxidation potential (E(S+/S)).48 For DPPdye, an irreversible oxidation is observed with a potential of +1.22 V vs. normal hydrogen electrode (NHE) in DMF solution and of +1.29 V vs. NHE for the mITO|DPPdye electrode in MeCN (Fig. S8†).</p><p>When dissolved in DMF (Fig. S9a†), DPP-Ru features a reversible oxidation at +0.60 V vs. NHE assigned to the RuIII/RuII couple.34 A second oxidation, attributed to the DPP unit, was observed at E(S+/S) = +1.29 V vs. NHE. Upon immobilisation (Fig. S9b†), the RuIII/RuII couple could not be observed, possibly due to the high capacitance of the ITO electrodes or spatial separation from the electrode. The oxidation of the DPP unit was observed at +1.34 V vs. NHE, similar to the value recorded in DMF solution.</p><p>The electrochemical properties were also confirmed in aqueous sodium acetate (NaOAc, 0.1 M, pH 5.6) solution, in which the oxidation of the chromophore on a mITO|DPPdye electrode was observed at +1.29 V vs. NHE (Fig. S10a†). A significantly higher current, attributed to catalysis, was obtained for a mITO|DPP-Ru electrode (Fig. S10b†).</p><p>Thus, the oxidation potential of the DPP unit in both organic and aqueous conditions is more positive than the reported onset of catalysis of [RuII(bda)(pic)2] (Ecat = +1.1 V vs. NHE), and should therefore provide sufficient driving force for water oxidation.34</p><p>Given the energy of the 0–0 transition for DPPdye and DPP-Ru, (E0–0 = 2.24 eV, Fig. S6 and S7†), the oxidation potential of the excited chromophore (E(S+/S*)) in DMF solution can be estimated to be −1.02 and −0.95 V vs. NHE, respectively. This allows for sufficient thermodynamic driving force for electron injection into the conduction band of TiO2 at a wide range of pH values (ECB(TiO2) = −0.57 V vs. NHE at pH 7),49 and confirms that the dye meets all of the thermodynamic requirements to be incorporated in a dyad-sensitised photoanode for water oxidation.</p><!><p>PEC experiments were carried out at room temperature in a N2-purged one-compartment three electrode electrochemical cell using a platinum counter electrode, a Ag/AgCl/KClsat reference electrode and a sensitised TiO2 film (mTiO2, procedure in ESI†) as the working photoelectrode. Linear sweep voltammetry (LSV) experiments were performed under chopped light irradiation and a potential of +0.2 V vs. NHE was applied for chronoamperometry experiments. UV-filtered simulated solar light was used for all PEC measurements (100 mW cm−2, AM 1.5G, λ > 420 nm), avoiding direct excitation of the TiO2 semiconductor.</p><p>To evaluate the maximum photocurrent that can be extracted from the dye, without the kinetic limitations of water oxidation catalysis, PEC measurements were performed on a mTiO2|DPPdye electrode in the presence of triethanolamine (TEOA) as a sacrificial electron donor in aqueous electrolyte solution (0.1 M, pH 7). The photoanodes were prepared by soaking mTiO2 electrodes in a solution of DPPdye (0.2 mM in DCM) overnight, followed by rinsing and drying in air (see ESI for details†). Photocurrents of up to 1.3 mA cm−2 were observed for the mTiO2|DPPdye electrode (Fig. 3a), which confirms the feasibility of electron injection into the CB of TiO2. These currents are much higher than those typically obtained for organic dyes on TiO2 electrodes in aqueous conditions with an electron donor, and slightly lower than the ones obtained in aqueous DSSCs, albeit without any electrode or electrolyte optimisation.17,23,50–54 During a four hour chronoamperometry experiment (Fig. S11†), a steady decrease of the photocurrent and electrode decolouration was observed, which can be attributed to dye decomposition, and to hydrolysis and desorption of the carboxylate anchoring group at neutral pH.55,56</p><!><p>For water oxidation catalysis, the sacrificial electron donor solution was replaced by an aqueous NaOAc solution (0.1 M, pH 5.6). The mTiO2 electrodes were immersed in a solution of DPP-Ru (0.1 mM) in MeOH overnight, followed by rinsing and drying in air. During the LSV experiments (Fig. S12a†), photocurrents were observed with an onset of −0.43 V vs. NHE, approximately 60 mV more positive than the conduction band of TiO2 (ECB(TiO2) = −0.49 V vs. NHE at pH 5.6).49 At more positive potentials, the photocurrents spike at 200 μA cm−2, but quickly decay afterwards. This response can be attributed to an initial fast electron injection from the dye into TiO2, followed by charge accumulation and recombination between the electrode and the oxidised dyad.5,9 At −0.1 V vs. NHE, a net photocurrent of 18 μA cm−2 was observed.</p><p>To improve the photocurrent response, the TiO2 electrodes were treated with a titanium tetrachloride solution (TiCl4, TiCl4–mTiO2, details in ESI†), a straightforward method used to improve the efficiency of DSSCs by increasing the electron diffusion coefficient.57,58 PEC experiments were performed as described above, with immobilisation of DPP-Ru on TiCl4–mTiO2 electrodes carried out in different solvents (MeOH, DMF and DCM) to identify the optimised immobilisation conditions (Fig. S13†). In agreement with previous studies using Ru and porphyrin photoabsorbers, in which the immobilisation solvent plays a role in the ordering of the molecules on the surface, and thus on the electron transfer dynamics, higher photocurrents were obtained when using a polar protic solvent.9,59–61 The currents observed with TiCl4–mTiO2|DPP-Ru electrodes were significantly higher than for the untreated mTiO2|DPP-Ru electrodes. Interestingly, the initial photocurrent of the TiCl4–mTiO2|DPPdye electrode was similar to that of the TiCl4–mTiO2|DPP-Ru electrode under identical conditions (Fig. S14a†). However, the UV-visible absorption spectrum of TiCl4–mTiO2|DPPdye after the PEC experiment showed decomposition of the chromophore, whereas the spectrum of TiCl4–mTiO2|DPP-Ru remained largely unchanged (Fig. S14b†). Therefore, the high photocurrents of the TiCl4–mTiO2|DPPdye electrode in the absence of hole scavenger can be attributed to light-driven dye degradation.</p><p>The origin of the modest performance of TiCl4–mTiO2|DPP-Ru may be ascribed to aggregation of the dyad on the electrode. The presence of aggregates has been shown to slow down electron injection, and shorten the lifetime of the radical dye cation, leading to a much lower power conversion in DSSCs.62 Aggregate formation can be limited by addition of a co-adsorbent, often chenodeoxycholic acid (CDCA), which improves the efficiency of DSSCs despite decreasing the loading of the dye on the electrode.26,27,31,39 Furthermore, the use of co-adsorbents can impact the PEC performance by altering the wettability of the electrode or the CB level of TiO2.53,63,64 While this approach has been successfully implemented to stabilise dyad-sensitised photocathodes for H2 evolution,65 it has not yet been explored in water oxidising photoanodes.</p><p>The loading of the dyad on the surface was optimised in two stages. Firstly, the concentration of CDCA in the immobilisation bath was varied. Despite this leading to a lower DPP-Ru loading (Fig. S15a†), higher photocurrents were reached when CDCA was added to the immobilisation bath (Fig. S16†). Similar loading and photocurrents were observed for all concentrations of CDCA studied. The loading of the dyad on the surface and photoanode performance could be further controlled by varying the concentration of DPP-Ru in the immobilisation bath while keeping a constant concentration of CDCA (Fig. S17 and S18†). Decreasing the dyad concentration resulted in lower absorbance of the films and lower photocurrents. Furthermore, increasing the concentration resulted in a higher absorbance, but without an accompanied increase in photocurrent response.</p><p>Further optimisation of the PEC conditions was attempted by varying the electrolyte solution (Fig. S19†). A similar peak current was obtained in sodium sulfate (0.1 M, pH 7) solution with a faster decrease in photocurrent, which is consistent with hydrolysis of the molecule at neutral pH.</p><p>The optimised conditions for PEC experiments were an aqueous NaOAc electrolyte solution (0.1 M, pH 5.6) with a TiCl4–mTiO2|DPP-Ru/CDCA electrode prepared by immobilisation in MeOH solution (0.1 mM DPP-Ru and 20 mM CDCA), capable of affording a light harvesting efficiency close to unity up to 530 nm (Fig. S20†). In the chronoamperometry experiment (Fig. 3b), photocurrents of 140 μA cm−2 after 10 s illumination are observed in the presence of the co-adsorbent, which represent a 3.5 fold increase compared to PEC experiments in the absence of CDCA.</p><p>The decrease in photocurrent could arise from decomposition of the chromophore, implied by the irreversibility of its oxidation, as observed in cyclic voltammetry measurements. Nonetheless, the UV-vis spectra of TiCl4–mTiO2|DPP-Ru/CDCA electrodes after the experiment (Fig. S15b†) show only a slight decrease in the absorption band at 499 nm, suggesting continued integrity of the chromophore on the electrode. The decrease in photocurrent is therefore not attributed to desorption of the molecule or decomposition of the chromophore, but rather to the detachment or decomposition of the WOC. Different deactivation mechanisms have been proposed for [RuII(bda)]-catalysts, which usually occur during the rate-limiting steps when the Ru centre is in the higher oxidation states.66 The effect of CDCA addition, which increases the distance between dyad molecules on the electrode surface, is unknown both on the decomposition pathways and the dimerisation pathway, to which the early catalytic onset is attributed.34 Further work utilising pump–probe spectroscopic techniques could be used in future studies to gain insight on the role of CDCA in the system.</p><!><p>To evaluate the faradaic efficiency (FE) of our photoanode for oxygen evolution, collector–generator (CG) cells were fabricated as described previously.67 Illumination of a bare TiCl4–mTiO2 electrode for 10 min (Fig. S21†) leads only to a negligible photocurrent background, due to the 420 nm cut-off filter preventing band gap excitation of the TiO2 semiconductor. While a high photocurrent was produced by the TiCl4–mTiO2|DPPdye electrode (Fig. S22†), this only leads to a marginal current increase by the collector, demonstrating that no O2 originates from the dye-sensitised electrodes in the absence of the WOC unit.</p><p>The fully assembled TiCl4–mTiO2|DPP-Ru/CDCA electrode displays an initial photocurrent of 140 μA cm−2 after 10 s illumination, which decays to 17 μA cm−2 over the course of 10 min of PEC operation. In contrast to control experiments, an increase in the O2 reduction current by the collector electrode was recorded for the dyad photoanode, corresponding to a FE for O2 of 44 ± 3.2% (Fig. 4). Trapped O2 in the porous electrode cannot be accounted for and hence lowers collector efficiency (details in the ESI†). In addition, the moderate FE can also be partially attributed to decomposition of the photocatalyst.</p><!><p>Inductively coupled plasma optical emission spectrometry (ICP-OES) based on Ru determination, after digestion of fresh TiCl4–mTiO2|DPP-Ru/CDCA electrodes in nitric acid, revealed an initial loading (Γ0) of 11.7 ± 1.04 nmol cm−2 of the dyad. This loading is lower than for other molecules on mesoporous TiO2 electrodes, but in line with the large steric footprint of the dyad and the presence of CDCA.15,45,68,69 This translates to a turnover number (TON) of 2.3 ± 0.6 for O2 evolution for the catalyst (TONcat) and 9.2 ± 2 for the dye (TONdye). ICP-OES revealed a loading of 7.1 ± 0.7 nmol cm−2 of the dyad after the experiment, suggesting catalyst detachment or desorption of the dyad assembly as partly responsible for the decreasing photocurrent.</p><p>A molecular dyad made of a zinc porphyrin chromophore and a [RuII(bda)] WOC was previously reported and immobilised on a TiO2 electrode.15 CV measurements showed that in aqueous conditions the chromophore did not possess sufficient driving force to activate the catalyst. Despite this, during photolysis, O2 was measured via gas chromatography corresponding to a FE of 33% and a TONcat of 1.3, but the role of direct excitation of TiO2 was not ruled out under the employed experimental conditions. A Ru dye-[RuII(bda)] catalyst dyad was able to evolve O2 with a FE of 30% on TiO2 and 74% on SnO2/TiO2 electrodes.11 The FE values for O2 evolution reported here compare favourably to the precious-metal chromophore dyad, and show for the first time catalytic turnover of both catalyst and dye using a dyad with a metal-free chromophore. The infancy of organic chromophores compared to Ru dyes for PEC in aqueous conditions is reflected in the superior stability of the Ru-dye based water oxidation dyad, but future organic chromophore development and optimisation opens the door to the replacement of precious metal with earth-abundant chromophores.</p><p>Despite higher dye loadings, photocurrents obtained for co-immobilised systems with organic push–pull dyes on SnO2/TiO2 electrodes are typically low and FEs for O2 evolution are in the range of 10%.17,23 Embedding the chromophore in a thin metal oxide layer by atomic layer deposition (∼1 nm, TiO2 or Al2O3) and further immobilisation of the catalyst has been studied as an alternative way of limiting oxidative decomposition of the chromophore.18,19,22 Improved efficiencies, between 11% and 49%, were thus reached. However, comparison with these systems is limited since TON values have not been reported. A TONcat of 3.0 and a TONdye of 2.4 were reported for a borondipyrromethene chromophore co-immobilised with a functionalised [RuII(bda)] catalyst on a TiO2 electrode, with a FE for O2 of 77%.21 When a subporphyrin dye was employed with an analogous catalyst, a TONcat of 27 and a TONdye of 14 were obtained with a FE of 64%.20 Thus, the results obtained highlight the benefit of dyadic systems compared to a co-immobilised approach in making an efficient use of dye molecules relative to the catalyst.</p><!><p>We present an organic dye-ruthenium catalyst dyad consisting of a DPP dye and a [RuII(bda)]-type complex. The chromophore displayed strong light absorption in the visible part of the electromagnetic spectrum, and suitable thermodynamics for electron injection into the conduction band of TiO2 and hole transfer to the Ru WOC. The dyad was then integrated in a TiO2-based photoanode for light-driven water oxidation. Incorporation of CDCA as a co-adsorbent was shown to significantly increase the photocurrents from 40 to 140 μA cm−2 in aqueous sodium acetate solution (0.1 M, pH 5.6), despite a lower dyad loading. The FE for O2 evolution was found to be 44% and corresponds to a TONcat of 2.3 and a TONdye of 9.2. UV-vis absorption measurements indicated that the decrease in current during photolysis was mainly associated to catalyst detachment or decomposition rather than dyad desorption or chromophore decomposition. This study shows that a metal-free dye with sufficient oxidising power can be covalently linked to a molecular catalyst for catalytic O2 evolution on a dyad-sensitised photoanode. Key techniques for accommodating chromophores with strong intermolecular π–π stacking interactions have been highlighted, and the significant benefits of CDCA co-adsorption on molecular dye-sensitised photoanodes for water oxidation has been demonstrated. Future experiments with time-resolved spectroscopy can be used to gain insight on the role of CDCA in enhancing the PEC performance, and serve as a blueprint for subsequent molecular design.</p><!><p>There are no conflicts to declare.</p>

PubMed Open Access

Towards quantitative point of care detection using SERS lateral flow immunoassays

The rapid detection of biomolecules in a point of care (POC) setting is very important for diagnostic purposes. A platform which can provide this, whilst still being low cost and simple to use, is paper-based lateral flow immunoassays (LFIA). LFIA combine immunology and chromatography to detect a target by forming an immunocomplex with a label which traps them in a test zone. Qualitative analysis can be performed using the naked eye whilst quantitative analysis takes place by measuring the optical signal provided by the label at the test zone. There are numerous detection methods available; however, many suffer from low sensitivity and lack of multiplexing capabilities or are poor at providing POC quantitative analysis. An attractive method to overcome this is to use nanoparticles coated in Raman reporters as the labelled species and to analyse test zones using surface-enhanced Raman scattering (SERS). Due to the wide variety of metal nanoparticles, Raman reporter and laser excitations that are available, SERS-based LFIA have been adapted to identify and quantify multiple targets at once. Large Raman microscopes combined with long mapping times have limited the platform to the lab; however, by transferring the analysis to portable Raman instruments, rapid and quantitative measurements can be taken at the POC without any loss in sensitivity. Portable or handheld SERS-LFIA platforms can therefore be used anywhere, from modern clinics to remote and resource-poor settings. This review will present an overview of SERS-based LFIA platforms and the major recent advancements in multiplexing and portable and handheld detection with an outlook on the future of the platform.Graphical abstract

towards_quantitative_point_of_care_detection_using_sers_lateral_flow_immunoassays

Introduction<!><!>Raman mapping SERS-LFIA platform<!><!>Multiplexing from signal-resolved detection<!>Portable SERS-LFIA platform<!><!>All-in-one SERS-LFIA platform<!>Outlook<!><!>Funding<!>Conflict of interest

<p>Lateral flow immunoassays (LFIA) are paper-based devices used for the rapid detection of analytes and biomolecules in clinical practice. The advantages of LFIA are exploited when the test is used in the community because the platform offers a simple-to-use and cheap-to-produce test that can be readily produced at scale. LFIA also have utility for use in hospitals; however, the specific application area and need must be thoroughly defined. For example, point of care (POC) assays based on multiple diverse platforms are being widely developed for a range of biomarkers that inform patient care pathways in hospitals and LFIA may not always be optimally suited. Where LFIA can have utility in hospitals are scenarios where rapidity and low cost are important test characteristics, such as screening for acute disease in emergency settings. The low cost of LFIA makes the platform well-suited for use in resource-poor settings such as diagnosis of infectious diseases in low-income countries. LFIA are also suited to these scenarios as they use smaller sample volumes and have fewer assay steps, shorter assay times and better storage conditions when compared to other detection techniques such as enzyme-linked immunosorbent assays (ELISA) and polymerase chain reactions (PCR). Before 2020, LFIA were probably best known at identifying pregnancy; however, they are now widely used to curb the spread of COVID-19 with 7.6 million tests taken in one month in England in 2021 alone [1].</p><p>The term 'immunoassay' refers to a recognition interaction, usually involving antibodies [2]. Commonly, a capture antibody and labelled detection antibody are used to capture target molecules in a sandwich immunoassay, binding with high affinity and specificity in a test zone on a nitrocellulose section of the LFIA strip. Typically, antibodies are labelled with spherical gold nanoparticles which are used as visual signal generators; however, other labels can be used including quantum dots, magnetic particles, fluorescence microspheres and latex beads. Using COVID-19 and pregnancy LFIA as an example, the test only needs to generate a qualitative result, i.e. a 'yes/no answer', and visual detection, based on the colour of the recognition label, is used as it produces a clear and easy-to-interpret result. The key point is that both COVID-19 and pregnancy LFIA detect protein targets that are not present in biofluids of unaffected individuals. However, when detecting molecules whose concentration can be indicative of a disease, a sign of infection, an unsafe level of hazardous material in an environmental sample or food contamination, it is vital that the LFIA yield quantitative information which can be achieved by externally measuring the amount of label present at the test zone and relating this to the concentration of the molecule [3]. Depending on the label, quantitative analysis can be achieved using colorimetric, fluorescence, electrochemical, and surface-enhanced Raman scattering (SERS) detection.</p><!><p>A Photographs of different LFIA strips run with different pneumolysin concentrations as indicated. SERRS maps using the 1647 cm−1 band of MGITC. B Average SERRS spectra from 50 random points measured in the test lines. C Evaluation of the results obtained for different pneumolysin concentrations using the point of care-based LFIA (red columns) and SERS-based LFIA (black columns) through optical density and SERS measurements, respectively. D Quantification range for pneumolysin employing the optical LFIA strip (red squares) or the SERS-based LFIA strip (black squares). The bars represent the standard deviation from three independent measurements [6]. Reproduced from Ref. 6 with permission from the Royal Society of Chemistry</p><!><p>The Raman mapping approach to SERS-LFIA has been used to detect a number of different clinically relevant biomolecules using different nanoparticle and Raman reporter combinations. For example, gold nanoparticles labelled with MGITC have been used to detect a myriad of biomolecules including HIV-1 DNA [7] and thyroid-stimulating hormone [8]. In these examples, a single biomolecule was detected on each test zone. However, the simultaneous detection of different biomolecules from one sample could be highly beneficial and has several benefits including improving the efficiency of testing, reducing costs and potentially leading to better patient stratification.</p><!><p>A Schematic illustration for the detection of three cardiac biomarkers using SERS-LFIA in a spatially resolved format [13]. B Schematic illustration for the detection of the same three cardiac biomarkers using SERS-LFIA in a signal-resolved format [17]. Panel A reprinted from Biosensors and Bioelectronics, 106, Zhang, D,; Huang, L.; Liu, B.; Ni, H.; Sun, L.; Su, E.; Chen, H.; Gu, Z.; Zhao, X., Quantitative and ultrasensitive detection of multiplex cardiac biomarkers in lateral flow assay with core–shell SERS nanotags, 204–211, 2018, with permission from Elsevier. Panel B reprinted from Sensors and Actuators B: Chemical, 277, Zhang, D.; Huang, L.; Liu, B.; Su, E.; Chen, H.-Y.; Gu, Z.; Zhao, X., Quantitative detection of multiples cardiac biomarkers with encoded SERS nanotags on a single T line in lateral flow assay, 502–509, 2018, with permission from Elsevier</p><!><p>Signal-resolved detection occurs when multiple labels are immobilised at a single test zone and can be identified through their specific signals generated from the label. The key factor is that all signals are collected from the same region simultaneously, offering rapid analysis and return of results. With regard to LFIA devices, this also means no deviation from the traditional device architecture which would incur increased materials costs. Signal-resolved multiplexing on LFIA has been achieved with colorimetric analysis using orange, red and green silver nanoparticles for the detection of different viruses. However, the colour of the mixed signal labels can be difficult to interpret at low concentrations. Fluorescence spectroscopy also struggles in a multiplexing capacity due to its broad emission bands which have large spectral overlap making the labels difficult to deconvolute. SERS is ideal for signal-resolved multiplex detection as it benefits from the fact that a range of different Raman reporters exist, generating characteristic, 'fingerprint' spectra specific to the Raman reporter. If a number of different Raman reporter-labelled nanoparticles are mixed together in a sample, distinct peaks from each of their individual spectra can be picked out of the multiplexed spectrum generated from the mixture and the individual reporters can be identified [15]. In this way, different reporters can be used to represent multiple analytes in a single sample. The presence of characteristic peaks of Raman reporter in the multiplex spectrum can be used for qualitative analysis and the intensity of the peak can be used to gain quantitative information.</p><p>In the context of LFIA, SERS multiplexing has been used to detect multiple biomolecules at once. For example, Wu et al. used gold nanoparticles functionalised with two Raman reporters for the duplex detection of L. monocytogenes and S. typhimurium respectively on a single test zone. Quantitative information was obtained based on decreasing intensity of the peaks from the SERS signal of the Raman reporter present in the multiplex test zone spectrum, with decreasing concentrations of the targets [16]. Zhang et al. used three Raman reporters to code for the presence of cardiac biomarkers myoglobin, cardiac troponin I and creatine kinase-MB isoenzymes respectively in a signal-resolved detection assay [17]. A schematic of this is shown in Fig. 2B depicting the mixed capture antibody test line and three gold nanoparticles coated with the relevant detection antibody and three different Raman reporters. The authors achieved low detection limits, well within the clinical ranges of each biomarker. Sanchez-Purra et al. achieved duplex detection of dengue and zika virus using SERS [18]. Their dipstick LFIA platform was also capable of quantitative analysis. In a different publication, the same researchers demonstrated proof-of-concept study showing that a pentaplex SERS signal could be obtained from a single test region [19]. A generic capture protein was immobilised on the test region of the LFIA device and the control line consisted of a second capture protein. Peaks from each of the individual SERS spectra were clearly visible in the pentaplex spectrum, therefore implying that signal-resolved pentaplex detection can be achieved using SERS, although quantification was not demonstrated.</p><p>The advantages of signal-resolved multiplexed detection include rapid analysis for the detection of multiple analytes from a single sample; therefore, the results offer more information in the time it takes to run a single LFIA device. Smaller quantities of reagents are used both in the preparation and in the running of the device and the device architecture does not need to be drastically changed, lowering the cost associated with materials. However, the immunoreactions taking place must be highly specific and ensure cross-reactivity is at a minimum. Depending on the analysis method, this approach may also be limited to the number of signals that can be generated from a single region and how these can be separated. This is why SERS offers the greatest potential for signal-resolved multiplexing as a range of Raman reporters can be used.</p><p>In these examples, the SERS-LFIA analysis was shown to offer superior sensitivity and multiplexing capabilities and produce quantitative information when compared to other detection methods. However, the pursuit of achieving the most sensitive SERS-LFIA is all in vain if the analysis is limited to benchtop microscope systems in the laboratory to get the necessary readout. LFIA are designed to be rapid, used at the POC and a new portable and handheld SERS 'readout' method is vital to combine both the merits of sensitive SERS and portable and rapid LFIAs. By performing the SERS analysis on portable Raman spectrometers, the SERS-LFIA can be transferred out of the lab to a number of different POC environments, providing rapid, sensitive and quantitative information for many different, clinically relevant biomolecules in real time.</p><!><p>The simplest way to transfer SERS-LFIA analysis to POC, with no loss in sensitivity, is to use a portable Raman spectrometer. In this setup, the laser can be focused onto the test zone using microscope with a 5 or 20 × objective or using a fibre optic probe, and then, a number of scans can be taken to produce an average SERS response. This platform has been applied for the detection of rotavirus [20], S-100β protein [21], microRNA-21 [22], serum amyloid A and C-reactive protein [23], and IgM/IgG covid antibodies [24]. This setup has also been used in a multiplexing capacity for the detection of 6 major mycotoxins in maize, utilising dual Raman reporters and triple test lines [25]. However, the inclusion of a Raman microscope or fibre optic stand has a few disadvantages. These include reducing the portability as it may need to be set up in a central area near a POC setting, for example in a lab at the hospital and the strips taken to the instrument, therefore increasing the time until results. Whereas if a handheld instrument was used, the analysis could take place next to a patient. The microscope also increases the cost of the platform as microscope systems can be expensive. Also, the platform is less user friendly as training would be needed to focusing the laser beam, whilst the open beam could also present a safety issue.</p><!><p>A Image of 3D printed adaptor [26]. B Image displacing how adaptor fits over point and shoot lens [26]. C Schematic representation of the spatially resolved detection of clostridium difficile using point and shoot handheld Raman spectrometer [27]. Reproduced from Refs. 26 and 27 with permission from the Royal Society of Chemistry</p><p>A Schematic of the portable SERS-LFIA detector system with line illumination [30]. B Inside and outside all-in-one portable SERS-LFIA platform [33]. Panel B reprinted from Biosensors and Bioelectronics, Xiao, R.; Lu, L.; Rong, Z.; Wang, C.; Peng, Y.; Wang, F.; Wang, J.; Sun, M.; Dong, J.; Wang, D.; Wang, L.; Sun, N.; Wang, S., Portable and multiplexed lateral flow immunoassay reader based on SERS for highly sensitive point-of-care testing, 112,524, 2020, with permission from Elsevier</p><!><p>An all-in-one enclosed 'handheld' platform which allows the analysis of LFIA strips to take place directly next to the laser source, whilst maintaining safety measures, is vital if SERS-LFIA is ever to be recognised as a POC analysis method. The first steps to achieving this have been reported by Xiao et al. who used a SERS portable reader integrated with a LFIA reaction column (33). Their design and enclosure are shown in Fig. 4B. They hypothesised that the major disadvantage of conventional SERS analysis is the expensive, large spectrometers which can only record the SERS spectrum at one position of the LFIA test strip at a time, and that multiple measurements require the strip to move on the xy translation stage repeatedly. Taking this into account, their proposed reader integrated a LFIA column which was mounted onto a step motor which can be moved up, down, back and forth by adjusting a two-axis translational stage allowing detection of both the test and control lines using a Raman probe with a laser spot of 200 µm. The automated SERS-based lateral flow system was housed in an enclosure with a handle to move the instrument, allowing the SERS-LFIA platform to be brought to the POC.</p><!><p>Combining SERS with LFIA adds the ability to quantify biomarker concentration in POC settings. However, the reader needs to be easy to use and provide the patient and/or clinician with easy-to-interpret actionable results. In healthcare systems, SERS-LFIA would allow measurement of biomarkers rapidly and cheaply out with current settings, for example in family doctor practices, ambulances and pharmacies. There is also a drive to decentralise clinical drug trials and facilitate data collection in patient's homes. This promises to make trials more inclusive, cheaper and potentially safer (early detection of drug toxicity, for example). SERS-LFIA is suited to this new application, where it could be used to monitor biomarkers related to drug toxicity, providing the assay and reader can be optimised for home use. In low-income settings, SERS-LFIA could be very valuable to allow immediate decision-making as the availability of tests is often limited, especially in rural settings. The characteristics of the assay for use in low-income settings such as parts of Africa will be different to those required for home use in Western countries. Key aspects of the target product profile will include resistance to weather conditions (temperature, humidity) and minimal storage requirements, components which can be manufactured locally, low production cost, and results that provide clinicians with actionable information within a specific, locally relevant, patient care pathway.</p><p>However, to date, the majority of research reported so far has been confined to laboratory-based SERS-LFIA due to using benchtop instruments to carry out Raman mapping analysis to obtain average signals across the lateral flow strips. Therefore, the development of portable Raman spectrometers, combined with a suitable sampling accessory and optics to average and maximise the signal readout across the lateral flow strip, is required to move SERS-LFIA detection platforms to the POC. The sampling accessory can limit the portability and stability of the system and if SERS-LFIA is to become a routine LFIA analysis technique used in a clinical setting, all-in-one, handheld, Raman systems need to be developed which allow the LFIA strip and SERS measurements to take place in an enclosed system. This will provide rapid results that are produced next to the patient leading to much faster decision-making in urgent care situations. Enclosed sampling accessories will also mitigate laser safety issues that can occur with open beam microscope and stage systems. All-in-one systems have previously been published, and are in current development, but these tend to use spot illumination. However, in order to obtain high sensitivity measurements and maximise signal readout across the whole LF strip, this method needs to be combined with line illumination to avoid under sampling of the strip, allowing for an ultra-sensitive handheld SERS-LFIA platform.</p><p>Another issue that needs to be addressed when using SERS outside the confines of a controlled laboratory environment is the ability to accurately detect the concentration of a biomolecule in a complex biological sample without having to build a calibration model. In an ideal POC situation, the sample will be run on the LFIA, the strip analysed within 20 min, and the intensity of the SERS signal as read will be directly related to the concentration. This requires a prior calibration model to be built that takes into account the sample component matrix and mitigate against any background interference from the sample matrix. Therefore, data analysis algorithms are required which will relate the SERS signal to the concentration, but also produce an easily interpretable result for the end user who will not be a spectroscopist. Although achievable, the use of nanoparticles and biological matrices can result in aggregation on test lines which can give artificially high SERS signals due to hotspot formation and could give false, high concentration results. Careful consideration into nanoparticle and Raman reporter stability and shelf life is key to obtaining reproducible results, along with control measures such as calibrating against the control line which could also be implemented to standardise the results. Although there are obstacles that need to be overcome, the sensitive, multiplexing, portable technology that this platform can achieve is worth pursuing in order to develop a gold standard handheld SERS-LFIA for the rapid, absolute quantification of clinically relevant biomolecules at the POC. Overcoming these challenges is achievable and we believe that SERS-LFIA will be used at the POC within the next few years.</p><!><p>This article is based on the Robert-Kellner Lecture 2021 held by Karen Faulds.</p><p>Publisher's note</p><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p><!><p>This work received financial support from Medical Research Council (MRC) through grant number MR/V038303/1.</p><!><p>The authors declare no competing interests.</p>

PubMed Open Access

Synthesis, Mechanism of Formation, and Catalytic Activity of Xantphos Nickel \xcf\x80-Complexes

A general synthetic route to the first Xantphos nickel alkyne and alkene complexes has been discovered. Various Ni complexes were prepared and characterized. NMR experiments indicate benzonitrile undergoes ligand exchange with a Xantphos ligand of (Xant)2Ni, a compound that was previously believed to be unreactive. The Ni \xcf\x80-complexes were also shown to be catalytically competent in cross coupling and cycloaddition reactions. (Xant)2Ni is also catalytically active for these reactions when activated by a nitrile or coordinating solvent.

synthesis,_mechanism_of_formation,_and_catalytic_activity_of_xantphos_nickel_\xcf\x80-complexes

<p>Xantphos,1 a bidentate phosphine ligand with a rigid butterfly structure and a large bite angle, is a prolific ligand for a variety of nickel catalyzed reactions including hydrocyanation,2 alkylcyanation,3 cross coupling,4 conversion of ethylene into 1-butene,5 and more recently, cycloaddition.6 One limitation of these reactions and Ni(0) catalyzed reactions7 in general is that the catalyst is formed in situ either from addition of Xantphos to Ni(COD)2 (COD = 1,5-cyclooctadiene) or by reduction of a Ni(II) species in the presence of added Xantphos. Unfortunately, Ni(COD)2 must be handled in a glove box and stored at low temperatures. Furthermore, COD acts as a competitive inhibitor in some of these reactions. The alternative route, namely catalyst formation from a Ni(II) species, typically requires elevated temperatures or addition of a reductant. As such, the need for air- and thermally-stable Ni pre-catalysts that are easily activated is high. The use of LnNi (where L is the desired ligand for catalysis) as a pre-catalyst is not prevalent. In particular, (Xant)2Ni has been avoided as a precatalyst because it is thought to be unreactive owing to its full valence shell and coordination sphere.2c In fact, formation of (Xant)2Ni is generally considered detrimental to catalysis. Not surprisingly, formation of (Xant)2Ni has also thwarted efforts to prepare Xantphos-Ni π-complexes, an important intermediate in a variety of Ni/Xantphos catalyzed reactions.2–6 Herein, we report the serendipitous discovery of a synthetic route to Xantphos Ni π−complexes, an investigation into the mechanism of their formation, and an evaluation of their use as pre-catalysts. We also report the effectiveness of (Xant)2Ni to serve as a viable pre-catalyst in cross-coupling and cycloaddition reactions.</p><p> (1) </p><p>We recently discovered the combination of Ni and Xantphos is one of the most effective catalysts for the cycloaddition of diynes and nitriles to afford pyridines in excellent yields.6 Unfortunately, this catalyst system does not convert untethered alkynes to the desired pyridines. In our efforts to promote the desired 3-component coupling reaction, we reacted stoichiometric amounts of Ni(COD)2 and Xantphos with an equimolar concentrations of benzonitrile and two equivalents of 3-hexyne (eq 1). Surprisingly, we serendipitously isolated (Xant)Ni-alkyne complex 1 in 88% yield rather than the expected pyridine product that would result from cycloaddition of 3-hexyne with benzonitrile. In contrast, reduction of (Xant)NiBr25 by Zn dust in the presence of 3-hexyne only afforded unidentifiable paramagnetic products.</p><p>The 1H NMR of (Xant)Ni(3-hexyne) 1 displayed peaks in the aromatic region and a singlet at 1.29 ppm indicative of a Xantphos ligand. In addition, the spectrum displayed a triplet at 1.12 ppm that integrated to six protons as well as a quartet at 2.15 ppm with an integration of four protons, indicating a species with a 1:1 ratio of Xantphos: 3-hexyne. The 13C NMR spectrum included a multiplet at 135.5 ppm, consistent with an alkyne coordinated to Ni(0).8 IR spectroscopy revealed an alkyne peak at 1821 cm−1, which is about 300 cm−1 shifted down from a free alkyne. These data are in accord with a (Xant)Ni(3-hexyne) structure. Crystals of this complex suitable for x-ray crystallography were grown by diffusion of pentane into a benzene solution of the complex (Fig 1). Notably, when 3-hexyne is added to a solution of Ni(COD)2 and Xantphos, only marginal amounts of (Xant)Ni(3-hexyne) is formed in conjunction with copious (Xant)2Ni as observed by 31P NMR.</p><p>Using the reaction conditions to synthesize 1, Ni π−complexes of diphenylacetylene (2), dimethylfumarate (3), and trans-stilbene (4) were synthesized in 94%, 89%, and 76% yields, respectively (Figure 2). In addition, a Ni-π complex of 2-butyne-1,4-diol (5) was synthesized, albeit in lower yield. The formation of 5 is particularly notable in that the preferred coordination of 2-butyne-1,4-diol is by the alkyne rather than the alcohol -OH.</p><p>ORTEP diagrams of 2 and 3 are shown in figures 3 and 4. Alkyne complex 1 has a Ni-C(42) bond length of 1.894(2) Å and Ni-C(43) bond length of 1.905(2) Å. Complex 2 has a Ni-C(46) bond length of 1.899(3) Å and Ni-C(47) bond length of 1.895(3) Å. These bond lengths are similar to a class of (dippe)Ni(C2R2) (dippe = 1,2-bis(diisopropylphosphino)ethane) alkyne complexes prepared by Jones8a and (dtbpe)Ni(C2R2) (dtbpe = 1,2- bis(di-tert-butylphosphino)ethane) complexes prepared by Hillhouse.8b Alkene complex 3 has a Ni(1)-C(42) bond length of 1.972(2) and a Ni(1)-C(43) bond length of 1.997(2), which are surprisingly similar Ni-C bond lengths to (IMes)2Ni(dimethylfumarate) (Ni-C bond lengths for this complex are 1.984(2) and 1.988(2)) considering the electronic and steric differences between two IMes ligands and Xantphos.8c Interestingly, the P-Ni-P angle is significantly different for complexes 1, 2, and 3 (angles are 118.92(2)°, 108.83(3)°, and 112.11(2)°, respectively). As the angle approaches Xantphos' natural bite angle of 108°,1c one phenyl ring on each P atom also comes closer together. In the case of complex 2, the rings containing C16 and C28 have a plane-plane angle of 15.71° and a centroid-centroid distance of 3.754 Å. Each pair of carbon atoms are directly overlapping, indicating a sandwich π-stacking interaction.9 Each diphenylacetylene phenyl ring is also π-stacking with one of the other Xantphos phenyl rings. The rings containing C34 and C48 have a plane-plane angle of 22.94 and a centroid-centroid distance of 3.960. The rings containing C22 and C45 have a plane-plane angle of 19.33 and a centroid-centroid distance of 3.821. The carbon atoms in each ring are not directly overlapping, consistent with a parallel-displaced π-stacking interaction.</p><p>We embarked on a series of NMR experiments to evaluate the ability of nitrile to disrupt the formation of the typically unreactive (Xant)2Ni. Not surprisingly, when diphenylacetylene was added to a saturated solution of (Xant)2Ni, no reaction occurred (eq 2). However, when 5 equiv benzonitrile was also added, alkyne complex (as well as free Xantphos) was slowly generated and the reaction ultimately reached equilibrium at 24% of alkyne complex 2 (eq 3). Similarly, when diphenylacetylene was added to a solution of 1 equiv Ni(COD)2 and 1 equiv Xantphos, which has been allowed to pre-coordinate for 2 minutes, only 5% yield of alkyne complex 2 formed while 95% of (Xant)2Ni was produced. Conversely, when diphenylacetylene and 5 equiv of benzonitrile were both added to a solution of 1 equiv Ni(COD)2 and 1 equiv Xantphos, a significant increase in the formation of alkyne complex 2 was observed, and any (Xant)2Ni that formed was completely converted to 2 within 6 hours. Taken together, these data suggests that nitrile undergoes initial ligand displacement of one Xantphos on (Xant)2Ni and subsequently is replaced with alkyne (Scheme 1, vide infra).</p><p>In some cases, the formation of (Xant)2Ni can be circumvented by changing the order of reactant addition. When diphenylacetylene and Ni(COD)2 were premixed for 5 minutes prior to the addition of Xantphos, only alkyne complex was observed, regardless of whether benzonitrile was added. Similarly, when a solution of Ni(COD)2 was added to a solution of Xantphos and diphenylacetylene, only alkyne complex was observed. In contrast, when trans-stilbene and Ni(COD)2 were premixed for 5 minutes prior to the addition of Xantphos, (Xant)2Ni was initially the major product instead of the desired alkene complex 3 (2:1). This is consistent with a report by Tolman indicating trans-stilbene is less than an order of magnitude better at binding Ni(0) than COD.10 In this case, addition of benzonitrile does facilitate the quantitative formation of Ni π−complex 4. These reactions were repeated with 3-hexyne instead of diphenylacetylene. The same trends were observed, albeit less pronounced than those observed with diphenylacetylene.</p><p> (2) </p><p> (3) </p><p>These NMR experiments suggest the following series of reactions is possible (Scheme 1). When Xantphos is added to Ni(COD)2, Xantphos displaces one COD ligand to form a (Xant)Ni(COD) species (pathway A). The transient (Xant)Ni(COD) species can undergo a second ligand substitution by either Xantphos to form (Xant)2Ni (pathway B) or by an alkyne to form (Xant)Ni(alkyne) (pathway C). Alternatively, Ni(COD)2 itself can also undergo ligand substitution by an alkyne (pathway D) followed by displacement of COD by Xantphos (pathway E) as evidenced by the effects of order of addition of reagents. The (Xant)Ni(alkyne) complex can react with Xantphos to form (Xant)2Ni, (pathway F). If this happens in the absence of nitrile, this reaction is irreversible. However, in the presence of nitrile, (Xant)2Ni is converted to an intermediate nitrile complex which allows the formation of the desired alkyne complex (pathways G1 and G2).</p><p>The catalytic activity of complexes 1–5 as well as (Xant)2Ni with and without added benzonitrile in cross coupling were evaluated (Table 1). The title complexes, except 2-butyne-1,4-diol complex 5, successfully catalyzed the cross coupling of 1-bromonaphthalene and vinyl zinc bromide in THF at 50 °C to afford 1-vinylnapthalene in good yields (entries 1–4). Surprisingly, the use of (Xant)2Ni as a catalyst also provided 1-vinylnapthalene in both the presence and absence of added nitrile (entries 6–7). Importantly, product yields are comparable to yields when Xantphos and Ni(acac)2 are employed as catalyst.4 Surprised by the success of (Xant)2Ni in this reaction, we investigated the ability of N-methyl-2-pyrrolidone (NMP), an additive used to keep the vinyl zinc reagent homogenous, to cause Xantphos dissociation from (Xant)2Ni. When diphenylacetylene and NMP were added to a saturated solution of (Xant)2Ni, formation of complex 2 was observed albeit in low yield (i.e., 8%). However, NMP is less effective than benzonitrile as ten times the equivalents of NMP, relative to benzonitrile, was required to achieve even moderate yields of complex 2.</p><p>The activity of the complexes in cycloaddition was also assessed. Complexes 1, 2, and 4 (3 mol %) were added to diyne and acetonitrile at room temperature. In each case, high yields of pyridine 6 were obtained (entries 1–2 and entry 4, Table 2). Importantly, these yields are comparable to an isolated yield of 94% when Xantphos and Ni(COD)2 are employed.6 In contrast, complex 3 was not competent in this reaction presumably due to the high affinity of dimethylfumarate for Ni(0) (entry 3). Complex 5, which did not catalyse the cross coupling reaction (vide supra), was also not an effective catalyst for this reaction (entry 5). In addition, (Xant)2Ni did catalyse the cycloaddition with an without added benzonitrile (entries 6 and 7), A higher conversion was observed with added benzonitrile due to activation of the complex, although a slightly lower yield was observed due to incorporation of benzonitrile. It is likely that acetonitrile serves to activate the (Xant)2Ni in the same manner as benzonitrile.</p><p>To assess the possibility for using (Xant)Ni-π complexes as air stable pre-catalysts, the stability of complexes 1 were evaluated. To our dismay, when a solution of 1 was exposed to air, the solution turned from yellow to brown with a marked decrease in the intensity of the singlet in 31P NMR compared to internal standard. After 10 minutes only 13% of the complex remained; within 20 minutes complex 1 had completely decomposed. The sensitivity of 1 in the solid state to air was also investigated. Within 10 minutes of exposing 1 in the solid state to air, only a trace amounts of 1 could be observed by 31P and 1H NMR spectroscopy; complete decomposition of 1 was observed after exposing a sample to air for 30 minutes. In contrast, (Xant)2Ni displayed surprising stability to air. This complex was slightly more stable towards air in solution. After 25 minutes in solution, only trace (Xant)2Ni was detected by 31P NMR; no complex was detected after 35 minutes wherein the solution turned from orange to colourless. However, samples of (Xant)2Ni in the solid state that were exposed to atmosphere for up to 8 h remained intact (as examined by 31P NMR spectroscopy). After 12 h, trace Xantphos and Xantphos oxides were detected, and over time the intensity of these peaks slowly increased. Importantly, after exposure to air for 3 days, ~90% of the solid sample was identified as (Xant)2Ni by 31P NMR spectroscopy, indicating this complex is reasonably air-stable as a solid.</p><p>In conclusion, we have discovered a method to synthesize (Xant)Ni-alkene and -alkyne complexes, characterized them, and evaluated their catalytic activity. The mechanism of their formation was also investigated. Interestingly, we discovered nitrile is capable of facilitating the dissociation of a Xantphos ligand from (Xant)2Ni for productive alkene or alkyne coordination. However, nitrile is not necessary to form Xantphos Ni π-complexes if a strongly coordinating alkene or alkyne is allowed to pre-coordinate to Ni before Xantphos is added. These complexes showed similar catalytic activity to Xantphos and Ni(COD)2 in cycloaddition of diynes and nitriles as well as to Xantphos and Ni(acac)2 in Negishi coupling. Although (Xant)Ni π–complexes 1–5 are not bench stable, they do not need to be stored at low temperatures like Ni(COD)2, and do not require activation like many Ni(II) pre-catalysts. Of particular interest, despite being Ni(0), (Xant)2Ni was shown to be reasonably air stable as a solid and was found to be a competent pre-catalyst when activated by nitrile or a coordinating solvent. This discovery should aid in the experimental simplicity of future Ni Xantphos catalyzed reactions. We believe that further work with these complexes could lend further insight into how nickel Xantphos catalyzed reactions operate and why Xantphos is an excellent ligand for a variety of transition metal catalyzed reactions.</p>

PubMed Author Manuscript

Simulating the Dynamics and Orientations of Spin Labeled Side Chains in a Protein-DNA Complex

Site-directed spin labeling, wherein a nitroxide side chain is introduced into a protein at a selected mutant site, is increasingly employed to investigate biological systems by electron spin resonance (ESR) spectroscopy. An understanding of the packing and dynamics of the spin label is needed to extract the biologically relevant information about the macromolecule from ESR measurements. In this work, molecular dynamics (MD) simulations were performed on the spin labeled restriction endonuclease, EcoRI in complex with DNA. Mutants of this homodimeric enzyme were previously constructed and distance measurements were performed using the Double Electron Electron Resonance experiment. These correlated distance constraints have been leveraged with MD simulations to learn about side chain packing and preferred conformers of the spin label on sites in an \xce\xb1-helix and a \xce\xb2-strand. We found three dihedral angles of the spin label side chain to be most sensitive to the secondary structure where the spin label was located. Conformers sampled by the spin label differed between secondary structures as well. C\xce\xb1-C\xce\xb1 distance distributions were constructed and used to extract details about the protein backbone mobility at the two spin labeled sites. These simulation studies enhance our understanding of the behavior of spin labels in proteins and thus expand the ability of ESR spectroscopy to contribute to knowledge of protein structure and dynamics.

simulating_the_dynamics_and_orientations_of_spin_labeled_side_chains_in_a_protein-dna_complex

Introduction<!>DEER Experiments<!>MD Simulations<!>EcoRI DEER Measurements<!>MD Simulated Distance Distributions<!>Spin Label Dynamics and Conformers<!>Broad Utility of Approach<!>Conclusions

<p>Site-directed spin labeling (SDSL) for electron spin resonance (ESR) spectroscopy has now become a widely utilized method to obtain structural constraints, probe conformational changes, and monitor protein-protein and protein-ligand interactions.1–2 In such experiments the presence of the spin label contributes substantially to the experimental observables. The inherent mobility of the spin label side chain contributes to the dynamics measured in the continuous wave (CW) spectral line shape. Furthermore the length of the spin label adds to the distance constraints that are measured most commonly using the pulsed Double Electron Electron Resonance (DEER) experiment.3–4 Ultimately, the position and mobility of the backbone are sought when performing ESR distance and dynamics measurements on biological systems or nanostructures. For this reason, work has progressed towards deconvoluting the backbone and spin label effects on such measurements through experiment and simulation.</p><p>The DEER experiment has been utilized to probe the flexibility and orientations of terminally spin labeled oligomers [bis-peptides or oligo(para-phenyleneethynylene)s] by analysis of orientational effects5 and distance distribution functions.6 Molecular models have also been developed to more accurately extract backbone details of these oligomers.7–9 In these models, parameters describing the orientation and flexibility of each segment with respect to subsequent segments of the oligomer were optimized such that the simulated distance distributions agreed with experiment. From these studies, end-to-end distance distributions from the oligomer backbone could be extracted, providing insight into the shape and flexibilities of these structures.</p><p>To resolve the backbone details for larger systems, such as peptides and proteins, a systematic understanding of the spin label conformation and packing as well as dynamics is needed. The behavior of the spin label has been probed in various systems by a number of methods, including x-ray crystallography10–17, ab initio calculation18–20, rotamer libraries21–23 as well as molecular dynamics (MD)24–31 and Monte Carlo simulations.32–35 Using x-ray crystallography, Hubbell and coworkers determined preferred conformations of the spin label side chain at solvent accessible helical and loop sites in T4 lysozyme.11–12,14 The spin label conformation can be defined by five dihedral angles (χ1-χ5) along the length of the spin label side chain. These angles are represented on the spin label in Figure 1A. These analyses suggest that for solvent-accessible, non-interacting spin labeled sites, the internal motion of the spin label results primarily from the rotations about the terminal dihedral angles (χ4 and χ5), known as the χ4/χ5 model. At such sites, local interactions with the backbone atoms and disulfide group of the spin label restrained the side chain such that the [χ1, χ2] and occasionally the disulfide bond conformations (χ3) could be resolved. On the other hand, the nitroxide ring was rarely resolved indicating that the χ4 and χ5 angles were highly unconstrained. These structures, taken together with CW-ESR data36–37, led to the formulation of the χ4/χ5 model. At sites where the spin label is involved in interactions with neighboring groups, fully resolved crystal structures of the entire nitroxide side chain were possible.10,13,16</p><p>Freed and coworkers18 used the Hartree-Fock theory to calculate torsional profiles of the five defining dihedral angles of the spin label using fragments of the spin label side chain. Using the minima values from the torsional profiles, as well as steric constraints, 18 possible conformers of the spin label on a polyalanine α-helix were identified. Along these same lines, Hubbell and coworkers19 recently utilized density functional theory to calculate the lowest energy conformations (χ1-χ3) of the spin label on a peptide fragment. The conformers were then modeled on a polyglycine to identify the interactions that stabilize the conformers in a helical environment. This work differed from that of Freed and coworkers due to the inclusion of backbone atoms in the calculations. This enabled the observation of interactions between the Sδ of the spin label and backbone atoms of the peptide fragment.</p><p>Alternatively, several groups have utilized MD simulations to model spin labeled systems comparing the simulated results to experimental CW24–28 or DEER29–31 results. One of the largest challenges in performing MD simulations to model the side chain conformation and dynamics is sufficient sampling. Different techniques have been employed to overcome this problem such as performing the simulations at high temperatures25,30 or in implicit solvent.32 Such conditions, however, can be misrepresentative of the experimental conditions to which the simulations are compared. It has been shown by others that in order to effectively model the spin label, simulations must be performed for long timescales.20,28–29 For example, Roux and coworkers parameterized the MTS spin label and performed long MD simulations (101 ns) using 18 different starting orientations of the spin label on a polyalanine α-helix.20</p><p>As another means to ensure sufficient sampling of the spin label conformer space, Fajer and coworkers developed a Monte Carlo rotamer search technique.33–34 The rotamer search used the Metropolis criterion to identify the lowest energy conformers at the spin labeled site.38 Subsequent MD simulations, using the lowest energy conformers as starting orientations of the spin label, enabled sampling of rotamer minima in the potential energy landscape of the spin labeled system.28 This technique was subsequently expanded using a simulated scaling approach to enhance the conformational sampling of the spin label during the MD production run.39 In this method the molecular dynamics trajectory is coupled to a potential scaling parameter. A walk through the potential scaling parameter space weights the potential energy surface of the spin labeled region. In this way the potential energy barriers of different spin labeled conformations could be crossed, enhancing the spin label sampling during the MD simulation.34</p><p>Significant insight has been gained on the preferred conformations and dynamics of the spin label from these studies. However, the majority of the in-depth analysis has been performed on spin labeled α-helical structures. There exists less information on the behavior of the spin label on other secondary structures such as a β-strand or loop region. Using the cellular retinol-binding protein (CRBP), Hubbell and coworkers performed a thorough analysis of the spin label present on β-strands.40 The dynamics of the spin label on interior and edge strands were investigated using CW-ESR. Allowed conformations of the spin label were derived from spectral analysis and a manual variation of the spin label side chain, which was built into the crystal structure of CRBP at the various spin labeled sites. In addition, a recent crystal structure of the spin labeled β-barrel membrane protein, BtuB, was published by Freed et. al. which resolved the orientation of spin labels present on β-strands of the barrel in or adjacent to the lipid bilayer.17 Furthermore, MD simulations of the spin label on β-strands have been used in conjunction with distance constraints to model protein structures through simulated annealing routines.41–43 However, a detailed analysis of the preferred spin label conformers was not provided. Although these works provide initial insight, more analyses are required to further our understanding of the behavior of the spin label on β-strands.</p><p>Adding to the current understanding of the spin label conformers and dynamics may lead to general rules of packing that may enhance the ability to extract information about protein structure and function from ESR measurements. We can augment this knowledge by performing simulations on a spin labeled protein that has been investigated experimentally. Accordingly, MD simulations were performed, and compared to experiment, to model the nitroxide spin label located on two different secondary structures of the spin labeled EcoRI-DNA complex: 180 (β-strand) and 249 (α-helix). EcoRI is a 62 kDa homodimer restriction endonuclease that binds to and cleaves a specific six base pair sequence GAATTC in DNA. The crystal structure of the specific complex of EcoRI has been determined and many thermodynamic and kinetic studies have been done to understand the extreme binding specificity of this enzyme. For instance, EcoRI binds with an affinity of up to 96,000-fold greater to its specific sequence than to a sequence that differs by one base pair.44–45 The structure of EcoRI consists of a large, stable main domain and two arms (inner and outer) that enfold the DNA.46–47 These arms are highlighted in Figure 1B in blue (inner) and red (outer), the main domain and DNA are silver. This arm region is believed to play a role in the binding specificity of EcoRI due to key contacts made between the arms and the DNA backbone.45,48 To shed light on this region, structural constraints were obtained by performing several distance measurements using the DEER experiment on the specific EcoRI-DNA complex.49 In this work we have leveraged these correlated distance constraints with MD simulations to learn about side chain packing and dynamics of the spin label as well as backbone details at two different spin labeled sites in the EcoRI-DNA complex.</p><!><p>Distance measurements were previously published on the methanethiosulfonate spin labeled (MTSSL) S180C (single) and S180C-K249C (double) mutant proteins in specific EcoRI-DNA complexes.49 In the current study, the DEER experiment was performed on the MTSSL-K249C mutant protein using a Bruker EleXsys CW/FT X-band ESR spectrometer with the Bruker X-band ER-MD5 resonator. The MTSSL-K249C sample was prepared in 30% deuterated glycerol, 65% deuterated water, and 5% protonated water resulting in a final protein concentration of 180 µM. Appropriate salt concentrations (0.22 M) and pH as well as a 4:1 DNA:protein ratio was used to ensure that at least 99% of the sample existed as the protein-DNA complex.50 The sample was flash frozen by plunging the capillary into liquid nitrogen cooled propane. The four-pulse DEER experiment was performed at 40 K using an Oxford ITC 503 temperature controller and CF935 dynamic continuous flow cryostat. The observer Π/2 and Π pulses were 16 and 32 ns respectively, and the pumping pulse was 32 ns. The pump pulse was located at the maximum of the nitroxide spectrum with the observer pulse applied at a frequency ~70 MHz higher. Deuteration of the solvent and glycerol resulted in a phase memory time of 2.5–3 µs, enabling the measurement of the long distance expected for the K249C mutant (Cα-Cα = 5.7 nm). A stepsize of 10 ns was used and the integrated echo intensity was collected for 512 points. The pump pulse began 200 ns before the echo so that the zero time could accurately be determined. The data acquisition time was 75 hours.</p><!><p>Sites 180 and 249 on the crystal structure of the specific EcoRI-DNA complex 46–47 were mutated to nitroxide spin labeled cysteines using the VMD program.51 A Metropolis Monte Carlo Minimization (MMCM) rotamer search was then performed in CHARMM52 using the rotamer search program developed by Fajer et al.33 Parameters describing the spin label force field were taken from the work of Sezer et al.20 The CHARMM27 force field was used for the protein and DNA.53 To ensure the full rotamer space of the spin label was accessed during the rotamer search, ten rotamer searches were performed starting with different initial orientations of the spin label. Each rotamer search was performed until ~1000–1500 conformers had been generated at each spin labeled site. Ten of the lowest energy conformers were selected for both sites separately. Using these conformers, ten doubly labeled (180 and 249) specific EcoRI-DNA complexes were constructed for MD simulation.</p><p>All structures were solvated in an explicit water box and counter ions were added to neutralize the system and provide a salt concentration comparable to experiment ([NaCl] = 0.22 M). All MD simulations were performed using the NAMD program.54 The structures were energy minimized using a conjugate gradient method. After heating the system to 300 K, the system was equilibrated for 1 ns in an NPT ensemble of 1 atm using a Langevin piston. During both the minimization and equilibration steps the protein backbone and DNA were restrained as well as the spin labels. Production runs were performed in an NVT ensemble for 30 ns using a 2 fs timestep. Periodic boundary conditions were used and particle mesh Ewald summation was used to treat the electrostatic interactions. To ensure reliability in the simulated results, the last 20 ns of the simulation, where the protein backbone had fully equilibrated, were used for analysis. Visualizations were done using VMD.51</p><!><p>Distance measurements were previously published on the specific EcoRI-DNA complex to better understand the orientation and behavior of the arm region of this DNA-binding protein.49 The EcoRI mutant proteins were generated as described previously55 and spin labeled at sites 180 (β-strand, outer arm) and 249 (α-helix, main domain). Due to the homodimeric nature of EcoRI, spin labeling of the protein with a single cysteine mutation results in two spin labeled sites in the DNA-bound complex. Double mutations provide four sites for labeling. The intermonomer (180–180 and 249–249) and intramonomer (180–249) distances that were measured are shown in Figure 1B (green brackets). The distance measurement in the outer arm (180–180) was performed to observe changes in this region upon binding to different sequences of DNA. The outer arm to main domain intramonomer (180–249) distance measurement provides yet another point-to-point distance to better triangulate the location of the outer arm upon binding different sequences of DNA. In principle, multiple distances corresponding to the 180–180, 249–249, and 180–249 intermonomer distances could also be detected in the 180–249 double mutant. However, the Cα-Cα distances for these intermonomer constraints are on the order of 6.0 nm and a time domain of only 1.5 µs was collected, thus such long distances were not detected. The 180–180 and 180–249 distance measurements were performed and published previously by Stone et al.49 These distance constraints are augmented by the 249–249 intermonomer distance measured in this work. Site 249 resides in the main domain of EcoRI and has restricted motion. Thus the intersubunit distance between sites 249 was determined to serve as a reference for comparison to the distance information obtained for the arm region.</p><p>Both the 180–180 and 249–249 distance measurements were close to the upper limit of distances measurable by the DEER technique (Cα-Cα= 5.6 and 5.7 nm, respectively). Due to the low modulation frequency for such long distances, there is an inherent uncertainty in the background subtraction and subsequently fitting of the DEER data needed to extract distance distributions from the time domain data. Using the DeerAnalysis200956 program, the previous fit to the 180–180 experimental data was refined. Both sets of data were fit using Gaussian distributions. The raw data and background fit for the 249–249 data is shown in Figure S3 in the Supporting Information as well as a more detailed discussion on the background correction of the data.</p><p>The background subtracted DEER time domain signal and corresponding distance distribution for the 249–249 distance measurement are shown in Figure 2. Unexpectedly, a bimodal distribution was observed for this distance measurement. Based on the Cα-Cα distance from the crystal structure of the specific EcoRI-DNA complex (5.7 nm), the longer distance acquired (7.1 nm) is reasonable taking into account the added length of the spin label. However, a shorter distance (5.1 nm), comprising ~40% of the distance distribution, was also observed. One possibility is that this bimodality arises from different conformers sampled by the spin label resulting in two observed distances. Such an orientation of the spin label would be unlikely, however, as it would have to protrude into the protein to achieve such a distance. Additionally, two spin label conformers would likely result in a trimodal distribution due to the combination of the spin label conformations and the distances between them.</p><p>A second possibility is that oligomerization of the EcoRI complex occurs in solution, such that a second, shorter inter-complex distance of 5.1 nm would be detected in our experiments. Oligomerization of EcoRI into a trimer of dimers has been observed in the crystal structure of the complex and modeling (Supporting Information) with plausible assumptions suggests that this could produce approximately the observed distance. However, we do not know if oligomerization occurs in solution under these conditions, and we are currently testing this possibility experimentally.</p><p>The possibility of oligomerization occurring in solution is further supported by the fact that the 249–249 DEER signal possesses a larger modulation depth than expected (from theoretical calculations and calibration experiments as discussed in the Supporting Information). This signifies a larger number of coupled spins than expected from just two spin labeled 249 sites in the EcoRI-complex, suggesting that higher order oligomers may have formed in this sample. Indeed, the modulation depth (Δ) for the 249–249 results (Δ = 0.41) is greater than that of the 180–180 results (Δ = 0.68), even though the experiments were performed under similar conditions. Ultimately, the 7.1 nm distance was primarily considered when comparing the simulated and experimental distance distributions.</p><!><p>Although the DEER data provides structural constraints in the distances between the spin labels, the backbone Cα-Cα distances and distributions are more biologically relevant to understanding the backbone structure and dynamics of EcoRI. To this end, MD simulations were performed on the specific EcoRI-DNA complex to model the spin labeled sites which were investigated experimentally: 180 (β-strand) and 249 (α-helix). Ten independent runs with different starting spin label conformations were performed to effectively sample the spin label rotamer space and test for convergence of the individual structures to a common preferred conformer or conformers. To identify the relevant simulated data, distance distributions between the nitrogen atoms of the spin label were constructed from the MD trajectories and compared to those obtained from the DEER experiment. By using the experimental results to identify which simulations to use for further analyses, the simulations were not biased by experimental restraints which can perturb the simulated results.57</p><p>Distance distributions were constructed, from all 10 parallel runs, for each of the experimentally measured distances: 180–180 intermonomer, 180–249 intramonomer, and 249–249 intermonomer, resulting in a total of 40 simulated distance distributions (two 180–249 intramonomer distances extracted from simulated results). MD runs, for which the simulated results reproduced those of the experiment, were used to draw conclusions about the backbone details of the specific EcoRI-DNA complex. Two criteria were used to compare the simulated and experimental results. First, agreement on the average distance and standard deviation of the experimental and simulated distance distributions was assessed. Agreement of all four distance distributions (180–180, 249–249, and both 180–249) with experiment was assessed simultaneously. The 180–249 intramonomer distance measurement was essential as it provides a correlation between the 180–180 and 249–249 experimental results. Because of this, the conformation of the spin label must be such that not only are the 180–180 and 249–249 distance distributions in agreement with experiment, but also the 180–249 in both monomers. Secondly, the local backbone root mean square deviations (RMSD) of the spin labeled sites and ~30 surrounding residues were considered. The RMSD measures the magnitude of variation in the position of the backbone atoms from a reference point, in this case the backbone atom positions at the beginning of the 30 ns production run. Using this RMSD, the initial drift and eventual equilibration of the atom positions can be observed. Simulated results with RMSDs that are either high or continually increase throughout the simulation may depict artificial behavior of the system due to a lack of equilibration or convergence near the spin labeled site. Thus, only simulated results from stable, equilibrated runs were considered.</p><p>Of the 10 parallel simulations performed on the doubly labeled (180 and 249) system, two runs had excellent agreement with experiment (runs i and ii). In these runs, all four constraints (180–180, 249–249, and both 180–249) agreed with the respective experimental distance distributions and possessed stable local backbone RMSDs. The resultant distance distributions of these runs are presented in Figure 3 where the experimental distributions are shown in black and the simulated in red. In the case of the 180–249 intramonomer distance distributions two simulated results were measured, one within each monomer of the EcoRI-DNA complex. These are shown individually as solid or dashed red lines. The local backbone RMSD trajectories are also shown in gray for sites 180 and 249, respectively. Two of the remaining 8 runs possessed unstable RMSDs even after 30 ns of simulation (runs iii and iv, Figure S1 in Supporting Information). Of the remaining 6 runs, the RMSDs were stable, however, only two or three of the simulated distributions agreed with experiment. Run v, shown in Figure 4, is an example of this partial agreement between the simulated and experimental results. In this run the 180–180 and both of the 180–249 simulated distance distributions are found to compare well with that of the experimental distribution. The 249–249 distribution however does not, due to a bimodal distribution (within the 7.1 nm experimental distance measurement) and an average distance larger than experiment. The remaining runs are shown in Figure S2 of the Supporting Information. Using such stringent criteria to identify the relevant simulation results increases the confidence in the data extracted from the simulations. It should be noted that in all 10 of the simulated 249–249 distance distributions, a distance corresponding to the shorter (5.1 nm) experimental distance was never observed. This supports the suggestion that a second conformation of the spin label is not the cause of the second, shorter experimental distance observed in the 249–249 DEER results.</p><p>MD runs that agreed with experimental data were used to extract backbone Cα-Cα distance distributions. Figure 5 shows simulated Cα-Cα distance distributions (blue) overlaid on the validated nitroxide-nitroxide (red) distributions. The gray dashed vertical line indicates the Cα-Cα distance obtained from the crystal structure of the specific EcoRI-DNA complex. The mean Cα-Cα 180–180, 180–249, and 249–249 distances from simulation were only 0.1–0.2 nm longer than that of the crystal structure. This small discrepancy may be attributed to the tighter packed structure of EcoRI in the crystalline state versus solution where the protein is more flexible and on average experiences larger Cα-Cα distances.</p><p>The standard deviations of the Cα-Cα distance distributions provided insight into the backbone mobility at the two spin labeled sites. The standard deviations of the 180–180 Cα-Cα distance distributions were merely 0.02 nm larger than those of the 249–249 results, indicating that the backbone at site 180 (β-strand) is slightly more mobile than at site 249 (α-helix). This similarity may be due to both spin labeled sites being located on stable secondary structural motifs, 180 on a β-strand and 249 on an α-helix. The slight increase in the backbone mobility at site 180 may arise from the β-strand being located on the outer arm of EcoRI. Indeed the RMSD values found at site 180 are slightly higher than those at site 249, contributing to the proposal that the arm region of EcoRI is slightly more mobile than the main domain. These results agree with the proposed order and rigidity of the main domain compared to the arm region in the crystal structure of the EcoRI apoenzyme.58 CW experiments have been performed and analyses of this data are currently underway to further investigate the dynamics of these different spin labeled sites in the EcoRI-DNA complex in solution.</p><p>Although there are clear differences in the nitroxide-nitroxide distributions between MD runs that agree with experiment and those that do not, the Cα-Cα distributions were fairly similar for all runs. The only exception to this occurred in runs that possessed an unstable RMSD and were found to have Cα-Cα distributions with larger standard deviations. This shows that MD simulations can distinguish spin label conformations even in the context of relatively invariant backbone distributions. Thus, favored spin label conformations can be extracted by comparing MD simulations with experimental data that provide multiple constraints.</p><p>Simulations were also carried out using the rotamer library approach implemented in the Multiscale Modeling of Macromolecules (MMM) open-source package.21,59 Spin label scans were performed at sites 180 and 249 in the specific EcoRI-DNA complex. Although the program successfully replicated the 180–180 experimental distance distribution neither the 180–249 or 249–249 distributions agreed with experiment. The distance distributions comparing the experimental data and the distributions obtained from the rotamer library are shown in Figure S5 in the Supporting Information. It can be seen in these fits that the 180–180 distribution agrees well with respect to the average distance as well as the standard deviation. However, the 249–249 distribution from the rotamer library possessed a lower average distance and a slightly broader distribution compared to experiment. The most significant difference arises from that of the 180–249 distribution in which the rotamer library predicted an average distance 0.6 nm lower than the experimental distribution. This indicates that although the 180–180 simulation agreed with experiment, appropriate rotamers may not have been modeled which also agree with the 180–249 distribution.</p><!><p>In this work the MD results provided insight into the dynamics and conformers of the spin label located at sites in different secondary structures: 180 (β-strand) and 249 (α-helix). Spin label dynamics and conformations were analyzed using those simulations that were determined to be consistent with the experimental distance distributions.</p><p>Polar plots, such as those used in previous works25–26,28, were constructed for each of the five dihedral angles that define the spin label side chain conformation (χ1-χ5). These plots are shown in Figure 6 for both sites 180 and 249. Each plot for a given dihedral angle displays the values sampled by that angle for both of the validated MD runs combined (runs i and ii). The radial distance from the center reflects the occupancy of that dihedral angle value throughout the portion of the simulation used for analysis (last 20 ns). In addition, the distribution about a value provides insight into the flexibility of that dihedral angle.</p><p>It can be seen from these polar plots that the dihedral angles sampled by sites 180 and 249 are similar to those found in the torsional potential energy surfaces constructed by Tombolato et al.18 One exception to this is the value of χ4 at site 180, where it samples a dihedral value of +110° in addition to the expected +75°. One can observe differences in the population of the dihedral angles sampled as well as the distribution about these angles between sites 180 and 249. The biggest difference arises between dihedral angles χ1, χ2, and χ4. A significant example is seen in the χ1 occupancy of the +65° conformation. At site 180, which resides on an edge β-strand, this χ1 conformation is significantly sampled. However at the α-helical site 249, this χ1 conformation is infrequent. Similar trends are seen in values occupied by the χ2 and χ4 dihedral angles. Both the ±90° values of χ3 are accessed at each site and χ5 is equally flexible and samples a variety of values at both sites.</p><p>Similar polar plots were constructed for the simulated results which did not agree with experiment (Figure S6 – Supporting Information). These plots show a different pattern in the dihedral angles that were sampled and their occupancy compared to the runs which were able to replicate the experimental distance distributions. The most significant difference at site 180 is the decrease in the χ1 = +65° conformer and an increase in χ2 = χ4 = 180°. The spin label conformation is extended when χ2 = χ4, leading to an increase in the average nitroxide-nitroxide distance. This is true for any χ1 or χ3 orientation. Thus, conformations of the spin label at site 180 where χ2 = χ4 are more likely to not agree with experiment due to a larger average distance. At site 249 the polar plots which did not agree with experiment show a significant increase of χ2 = χ4 = 180° as well as χ4 = +75°. Similar to site 180, an increase in χ2 = χ4 conformers at site 249 could lead to average nitroxide-nitroxide distances larger than experiment. There are also changes in the χ3 profile for both sites, however, the occupancy of χ3 is influenced by the initial assignment of the conformation and therefore no conclusions were drawn about changes in χ3 between the different sets of fits. Comparison of the polar plots highlights the significance of identifying and analyzing such validated simulation results because it exposes conformers that are sampled in MD runs which are not experimentally relevant.</p><p>No correlation was found between the starting rotamer used for the spin label and agreement with experiment. However, starting with different rotamers of the spin label does enhance the sampling of the spin labeled location. For instance, although in each of the ten runs the starting orientation of the spin label was the same in both monomers of the EcoRI complex, the two spin labels still sampled different conformers. By enhancing the conformers sampled throughout the simulation, the chance of identifying conformers which agree with experiment is increased.</p><p>The distribution and jumps about these dihedral angles provides insight into the dynamics of the spin label. The χ4 and χ5 polar plots show several dihedral angles sampled as well as broad distributions about these values. This indicates increased torsional oscillations and jumps about the two terminal angles of the spin label. These oscillations and jumps are also evident in the time-dependent trajectories of χ4 and χ5 (Figure S7 and S8 – Supporting Information). The fast dynamics of χ4 and χ5 agrees with the previously proposed χ4/χ5 model of motion in which the main contributor to the spin label mobility has been proposed to arise from motion about the χ4 and χ5 dihedral angles.36–37</p><p>Conformers found in runs i and ii of the validated results were identified at sites 180 and 249, allowing comparison of the conformers sampled by the spin label at different secondary structures. To identify the conformers sampled from the simulated results, the dihedral angles were rounded to those found in the torsional potential energy profiles of the spin label.18 The conformers identified are listed in Figure 7 along with a pictorial representation to visually demonstrate the difference in the conformers at each site. The conformers shown in Figure 7 were the highest occupied in runs i and ii. Due to the flexibility in the χ5 angle, all possible values of χ5 were considered when identifying the conformers.</p><p>Using the cellular retinol-binding protein (CRBP), Lietzow and Hubbell suggested preferred geometries of several spin labeled sites on interior and edge β-strands by CW-ESR analysis and manual variation of the spin label conformation built into the CRBP crystal structure.40 From this work they proposed that edge strands, such as where 180 is located, favor [χ1, χ2] conformations of [+60, −60] and [+60, 180] (dihedral values as used by Hubbell and coworkers).40 This is due to the non-hydrogen bonding (NHB) neighbor of the β-strand lying close to the spin label and therefore preventing the commonly observed [−60, −60] conformation. Indeed, the [−60, −60] conformer was rarely occupied in the validated MD results at site 180, but neither was the [+60, 180] conformation. The [+65, −75] conformer was observed, however. Other conformers were also observed such as [−60, +75], [−60, 180] and χ1 = 180° conformers. These conformers may arise from the degree of strand twist in the β-strand or local side chain interactions at site 180. It was proposed that when the degree of strand twist increases the residues will spread out and reduce side chain - spin label interactions.40 In addition, different conformers of the spin label at 180 reside in close proximity to residues in the outer arm of EcoRI. For example, the [180, +75] conformer is positioned in close proximity to an asparagine residue on the adjacent β-strand, which is the NHB neighbor of site 180. As pointed out by Lietzow and Hubbell40, spin labels present on β-strands are expected to interact more with NHB neighbors that are β-branched residues, such as valine or isoleucine. It can be reasoned that due to the fact that the NHB neighbor of site 180 is not β-branched there exists little interaction between the two residues. Taken together with the strand twist present in the β-strand at site 180, alternative conformations of the spin label are possible.</p><p>As noted previously, most studies that have investigated spin label conformations and dynamics have been performed on α-helical sites. Although site 180 provides insight into the behavior of the spin label on a different secondary structure such as a β-strand, modeling on an α-helical motif, such as at site 249, provides a reference to compare these MD simulations with the work of others. Using x-ray crystallography, several preferred spin label conformers have been identified on solvent accessible α-helical sites in T4 lysozyme. From these structures the most preferred [χ1, χ2] conformations were found to be: [−60, −60], [180, +60], and to a lesser extent [180, −60]. These conformers are also found to be energetically favorable in the DFT calculations performed by Warshaviak et al.19 The [−60, −60] and [180, +60] spin label conformers are believed to be stabilized by the Sδ⋯H-Cα interaction of the spin label with the protein backbone.11,19 In the [180, −60] conformation the Sδ apparently interacts with the backbone C=O.19 At site 249 two of these three preferred conformers were significantly sampled in the validated simulations: [−60, −75] and [180, −75]. Tombolato et al. and Sezer et al. both found the [−60, 180] conformer to be the most probable in their simulations on a polyalanine α-helix.18,20 The [−60, 180] conformation was observed at site 249, however, not as significantly as in the works of Tombolato et al. and Sezer et al. Lastly, the [180, 180] conformer was also sampled at site 249. The [−60, −75], [180, −75] and [180,180] were also observed in the work of both Tombolato et al. and Sezer et al., however to a lesser extent.</p><p>Hubbell and co-workers have shown that the [−60, 180] and [180, 180] conformers are sterically allowed at α-helical sites (i.e. those modeled in T4 lysozyme), but are rarely observed in the crystal structures. For example, the [−60, 180] conformer has been observed only once, and that at a crystal contact site.14 It is proposed that these conformers are not stabilized by the Sδ⋯H-Cα interaction, and thus their χ2 angles are less constrained, so that mobility or distribution among conformers produces weak crystallographic electron densities. Such disorder is not observed in the solution CW spectra.11 Additionally, the [−60,180] conformation was found to possess the highest relative energy in the recent DFT calculations.19 The MD force field used in this work lacks the appropriate details, such as polarizability, to observe the possible lone pair interaction between the spin label Sδ atom and the hydrogen from the backbone H-Cα. Thus, these conformers may be less probable in experiment due to the stabilization of other conformers, i.e. [−60, −60], [180, +60], and [180, −60], by this interaction. Such discrepancies between simulation and experiment expose the limitations of the current simulation techniques. Even if the simulations are extended or general sampling is increased, the spin label may still sample conformers that are less likely to be observed experimentally. Thus, agreement between the MD results and experiment may not always be plausible even if the simulations are carried out for much longer timescales. Ultimately, only the conformers that agree with the experimental constraints should be considered.</p><p>Different preferred conformers were occupied by the spin label present on different secondary structures. Site 180, present on an edge β-strand, was the only site where the χ1 = +65° conformer was significantly sampled. It has been mentioned that such a conformation of the χ1 dihedral angle is sterically forbidden in nearly all α-helical sites11, and in fact this conformer was rarely occupied at the 249 site. Interestingly, no one preferred conformer was the same for site 180 and 249. This underscores the sensitivity of the spin label to the secondary structural location.</p><!><p>We have shown in this work the value of using MD simulations to model the spin label conformer and dynamics at two different secondary structures. Insight gained into the behavior of the spin label on a β-strand is significant due to the limited amount of information that exists on the behavior of the spin label in β-strands or β-sheets. In addition, we have demonstrated the need to extend MD simulations to longer timescales (> 10 ns) to ensure backbone equilibration of the system as well as to effectively sample the spin label conformers. We have also shown that the use of correlated experimental distance constraints can provide strict criteria for agreement between simulation and experiment, and thus for identifying the most probable conformers in solution. Since the favored conformations of the spin label are likely to depend primarily on highly local features of its secondary structure environment, these favored conformations can then be used to deconvolute positional distributions of the spin label from positional distributions of the backbone. The potential utility of our approach is thus in establishing the favored spin label conformation for a particular location in a protein. This information can then be used to extract differences in backbone distributions when comparing complexes of the same protein (whose secondary structure should often be conserved) with different ligands or under different solution conditions. This work underscores the need for new methods to simulate spin label packing and conformations in different systems and at different secondary structures. Methods such as the rotamer search33–34,39 and rotamer library21–23 provide alternative means to account for spin label conformational distributions.</p><!><p>ESR-DEER experiments on proteins yield distance distributions which convolute the effects of backbone positions and motions with preferred conformations and dynamics of the spin label moieties. These factors can be deconvoluted by MD simulation, provided that the simulations accurately reproduce the experimental ESR-DEER data. This we have done successfully for spin labeled sites 180 and 249 of the specific EcoRI-DNA complex, also allowing us to compare spin label behaviors when located on a β-strand or an α-helix. These simulation studies enhance our understanding of the behavior of spin labels in proteins and thus expand the ability of ESR spectroscopy to contribute to knowledge of protein structure and function.</p>

PubMed Author Manuscript

UV-Induced Photodegradation of Naproxen Using a Nano γ-FeOOH Composite: Degradation Kinetics and Photocatalytic Mechanism

Naproxen (NPX) is one of the most common pharmaceutical and personal care products found in surface water, which is recalcitrant to degradation by biological treatment or complete removal via traditional sewage treatment processes. In this study, nanoscale γ-FeOOH was synthesized and characterized by X-ray diffraction, scanning electron microscopy, surface analysis, and analysis of the forbidden bandwidth. Under UV irradiation, γ-FeOOH had the capacity to rapidly photodegrade NPX. The photodegradation rate of NPX was dependent on the concentration of γ-FeOOH in solution, initial NPX concentration, and pH. By increasing the concentration of γ-FeOOH, the NPX photodegradation rate was increased and then remained stable. Furthermore, the highest photodegradation rate for NPX was observed under acidic conditions. Through the analysis of the active substances (such as h+, e−, OH, 1O2, and O2·-) by electron spin resonance, the photocatalytic mechanism of NPX degradation on γ-FeOOH was determined to be semiconductor photocatalysis.

uv-induced_photodegradation_of_naproxen_using_a_nano_γ-feooh_composite:_degradation_kinetics_and_pho

Introduction<!>Materials and Reagents<!>Synthesis of Nanostructured γ-FeOOH<!>Characterization of Nanostructured γ-FeOOH<!>Photoreaction Apparatus and Procedure<!><!>Photodegradation of NPX by γ-FeOOH<!>Langmuir–Hinshelwood Kinetics<!>Active Species Analysis<!>Characterization of γ-FeOOH<!><!>Characterization of γ-FeOOH<!><!>Effect of γ-FeOOH Dosage on the Photocatalytic Degradation of NPX<!><!>Effect of γ-FeOOH Dosage on the Photocatalytic Degradation of NPX<!>Effect of Initial NPX Concentration on the γ-FeOOH/NPX System<!><!>Effect of Initial NPX Concentration on the γ-FeOOH/NPX System<!>Effect of pH on the γ-FeOOH/NPX System<!><!>Effect of pH on the γ-FeOOH/NPX System<!>Analysis of the Photocatalytic Degradation Mechanism of γ-FeOOH<!><!>Analysis of the Photocatalytic Degradation Mechanism of γ-FeOOH<!><!>Analysis of the Photocatalytic Degradation Mechanism of γ-FeOOH<!>Identification of Intermediates<!><!>Conclusions<!>Data Availability Statement<!>Author Contributions<!>Conflict of Interest

<p>With continuous improvements in anthropogenic living standards, the contamination of natural waterways has become an unavoidable and often neglected environmental issue. At present, however, water monitoring standards do not include pharmaceutical and personal care products (PPCPs), which are recalcitrant to biodegradation or complete removal via traditional sewage treatment processing technologies (Christina et al., 2014). Concurrently, PPCPs are constantly released into the environment from the medical and livestock industries; hence, they have garnered the attention of researchers and the public due to their "pseudo persistence." Common PPCPs include non-steroidal anti-inflammatory and analgesic drugs such as Ibuprofen, Naproxen, Aspirin, and Diclofenac. Naproxen (NPX) is a commonly used anti-inflammatory and analgesic with negligible side effects; thus, it is one of the four most commonly consumed prescriptions on a global scale (Jones et al., 2002). Although the NPX concentration in water is low, it has accumulated to ng/L concentration levels (Dai et al., 2014). Medical studies have revealed that the long-term ingestion of trace NPX levels can induce heart disease, stroke, and toxic pulmonary effects (Isidori et al., 2005; Karl et al., 2006; Domínguez et al., 2011; Hasan et al., 2012). Current NPX treatment methods encompass adsorption (Xu et al., 2009; Hasan et al., 2012) photocatalytic degradation (Méndez-Arriaga et al., 2008), and radiation (Zheng et al., 2011), which commonly employ FeOOH (the primary component of rust, a corrosion product on metal surfaces) (Molgaard, 1974). It has been reported that FeOOH exists not only in marine shellfish (Lee et al., 2000), but also within soils, sediments, and water, and the physical and chemical properties of FeOOH are stable. This compound possesses a relatively large surface area, which likely plays a critical role in the removal of contaminants from the natural environment (Fortin and Langley, 2005; Zhou et al., 2007); hence, it is receiving increased attention in the areas of environmental restoration and governance.</p><p>Nano-γ-FeOOH exhibits surface resident and interfacial effects as well as unique properties at the nanoscale and quantum levels (Nurmi et al., 2005). It can effectively adsorb organic matter in water and demonstrates a good flocculation effect. Under certain conditions of light and oxygen exposure, it may also catalyze the degradation of adsorbed organic matter without producing secondary pollution. At present, γ-FeOOH is mainly used for industrial desulfurization; thus, there have been few studies on the adsorption and photocatalysis of PPCP contaminants. Further, investigations of NPX-related adsorption and photocatalytic processes and mechanisms have rarely been reported.</p><p>For this investigation, nano-γ-FeOOH is synthesized, and on the basis of previous studies that examined its adsorption performance for NPX (Zhanyi et al., 2018), the primary focus here is centered on the effects of nano-γ-FeOOH on the photocatalytic degradation of NPX. The effects of the photocatalyst dosage, initial NPX concentration, pH, and other factors are investigated. This work culminates in the proposal of an environmentally compatible photocatalytic strategy for the effective treatment of NPX-infused wastewater.</p><!><p>NPX (A-methyl-6-methoxy-2-naphthaleneacetic acid, 98% purity) was obtained from West Asia Reagent Company. Acetonitrile (CR), methanol (CR), and ethanol (CR) were obtained from USA ACS Enke Chemical. FeSO4·7H2O (AR), NH3·H2O (AR), EDTA (AR), NaOH (AR), H2SO4 (AR), KI (AR), IPA (Isopropanol, AR), NaN3 (AR), and p-BQ (p-Benzoquinone, AR) were obtained from Shanghai Aladdin Bio-Chem Technology Co., Ltd. Ultrapure water employed in the experiments was obtained via an integrated Smart2 Pure ultrapure water system, obtained from TKA Wasseraufbereitungs system GmbH, Germany.</p><!><p>Freshly prepared under magnetic stirring, 10 ml of pure NH3·H2O was added to a 110 ml 0.3 mol·L−1 FeSO4 solution, which had a pH of 8.6. Subsequently, 10 ml of 0.015 mol·L−1 EDTA and ultrapure water were added to a 150-ml volume. Then, 1 L·min−1 O2 was introduced into the solution for about 30 min until the precipitation color changed from blue-green to orange under a controlled system temperature of 20°C, after which the pH was maintained at 4.3. Once the orange precipitate was filtered and rinsed, it was placed in a vacuum drying oven for 24 h at 30°C. Thereafter, the sample was finely ground and screened (200 mesh) (He et al., 2005).</p><!><p>X-ray diffraction (XRD) was carried out with a Cu K(α) source (λ = 0.15406 nm) at 40 kV and 30 mA over the range of 2θ = 20–80°.</p><p>Scanning electron microscopy (SEM) was used for investigating the morphology and dispersion of the samples. Prior to measurements, the sample was affixed to an aluminum sheet and sprayed with gold.</p><p>BET surface area (BET) analysis was used to determine the pore structure, specific surface area, and porosity of the samples. The porosity and pore distribution were determined by a nitrogen adsorption–desorption isotherm and the Barrett–Joyner–Halenda (BJH) method.</p><!><p>The photocatalytic NPX degradation experiments using γ-FeOOH were carried out using a multifunctional photochemical reaction instrument with magnetic stirring bars and a cooling circulation system (Figure 1). The illumination source in the experiment was a 300-W mercury lamp (Table 1), which was 10 cm away from the quartz tubes, and the temperature was held steady at 25°C during all tests. Prior to the photocatalytic degradation tests, the γ-FeOOH/NPX system was allowed to reach adsorption–desorption equilibrium in the dark for 240 min (He et al., 2005; Zhanyi et al., 2018). Subsequently, each experiment was conducted in triplicate with 20-ml samples under UV irradiation, and the rotary reactor was rotated at 5 rpm for 1 min, accompanied by constant magnetic stirring at 100 rpm for 1 min. A 10-ml sample was extracted via syringe every 2 min for each test and immediately passed through a 0.45-μm filter. The filtrate was then analyzed by high-performance liquid chromatography.</p><!><p>Multifunctional photochemical reaction instrument.</p><p>Mercury lamp energy distribution.</p><!><p>To determine the effect of γ-FeOOH dosage, 0.05, 0.1, 0.2, 0.4, and 0.6 g·L−1 of γ-FeOOH was added to the NPX solution at a concentration of 10 mg·L−1.</p><p>To determine the effect of initial NPX concentration, NPX solutions with several concentrations of 5, 10, 20, 30, and 40 mg·L−1 were prepared, to which 0.2 g·L−1 of γ-FeOOH was added.</p><p>To determine the effect of pH, the pH was adjusted to 5, 7, and 9 by adding 0.1 mol·L−1 H2SO4 or 0.1 mol·L−1 NaOH to the NPX solution with a concentration of 10 mg·L−1, to which exactly 0.2 g·L−1 of γ-FeOOH was added.</p><p>The above experiments proceeded as described above.</p><!><p>Heterogeneous photocatalysis includes two basic reaction steps, which are physical adsorption and a chemical reaction. For our experiments, Langmuir–Hinshelwood kinetics (L–H equation) were employed to fit the relationship between the photocatalytic reaction rate (r) and solution concentration (C):</p><p>where r is the initial photodegradation rate of NPX measured in mg·L−1·min−1, kL−H is the photocatalytic degradation rate constant measured in mg·L−1·min−1, K is the adsorption constant of NPX on the surface of γ-FeOOH measured in L·mg−1, and C is the instantaneous concentration of NPX measured in mg·L−1.</p><p>There was a linear relationship between the reciprocal of r (1/r) and the reciprocal of C (1/C). Linear fitting was applied with the data from the experiment; hence, the photocatalytic degradation rate constant kL−H and the adsorption constant K were obtained and found to be independent of the NPX concentration.</p><!><p>In order to investigate the role of free radicals in the photocatalytic degradation of NPX, radical quenching experiments were carried out. Four solutions were prepared, comprising 10 mg·L−1 NPX and 0.2 g·L−1 γ-FeOOH, to which 50 mmol·L−1 potassium iodide (KI), 0.10 mmol·L−1 isopropanol (IPA), 0.01 mmol·L−1 sodium azide (NaN3), and 0.01 mmol·L−1 benzoquinone (BQ) were added. In particular, KI was employed to quench the h+ and ·OH radicals (Zhang et al., 2011).</p><!><p>The physical properties of metal oxides, such as their crystal structures and surface characteristics, may influence their photocatalytic activity. Eight peaks were observed in the XRD pattern of FeOOH that were attributed to the (120), (011), (031), (111), (060), (220), (151), and (080) planes, indicating the presence of the γ structure (Figure 2A). When compared with the standard diffraction peaks of γ-FeOOH, the prepared powder was in the form of a pure crystal phase.</p><!><p>(A) XRD pattern of γ-FeOOH, (B) SEM image of γ-FeOOH, (C) N2 adsorption-desorption isotherm and pore size distribution of γ-FeOOH, (D) XRD pattern of recycled γ-FeOOH.</p><!><p>Surface morphological studies of γ-FeOOH by SEM revealed that the prepared powder was in the form of a mixed crystal phase, which contained, for the most part, nanoparticles (~50 nm) and short nanorods (~200 nm in length) (Figure 2B), due to differences in pH during the preparation of γ-FeOOH (Farcasiu et al., 1991). The smooth and dispersible properties of the mixed crystal phase revealed that the morphology was relatively regular.</p><p>The adsorption capacity of metal oxides for organic pollutants is affected by the BET size. On the basis of the N2 adsorption–desorption isotherm and pore size distribution, the specific surface area of γ-FeOOH was determined to be 125.7 m2·g−1 (Figure 2C). As shown in Figure 2C, we found that there was a significant hysteresis loop in the adsorption–desorption curve, which means that the sample possessed a mesoporous structure. According to the BJH desorption curve method (Kruk et al., 1997), which was employed to calculate the pore size distribution, the pore size range of the sample was ~50 nm. In photocatalytic experiments, γ-FeOOH was recovered and washed with pure water three times before drying. The XRD pattern showed no obvious change (Figure 2D) after this test. The degradation of NPX was reduced by only 1% when performing photodegradation with the recovered γ-FeOOH. These results show that the γ-FeOOH photocatalyst is highly stable.</p><p>As shown in Figure 3A, γ-FeOOH displayed a typical absorption edge at ~650 nm, and a bandgap width of 1.94 eV was calculated (Figure 3B). In order to further study the bandgap position of the semiconductor γ-FeOOH, X-ray photoelectron spectroscopy (XPS) was used to probe the valence band (XPS-VB). This revealed that the valence band of γ-FeOOH was located at 1.80 eV, as shown in Figure 3C. Therefore, it can be deduced that the rewind position of γ-FeOOH was −0.14 eV and the band gap structure is shown in Figure 3D.</p><!><p>(A) UV-Vis diffuse spectra of γ-FeOOH, (B) bandgap width of γ-FeOOH, (C) XPS-VB spectra of γ-FeOOH, and (D) band structure alignments of γ-FeOOH.</p><!><p>A suspension was formed in the multiphase photocatalytic reaction system, as the catalyst is insoluble in water. With increased catalyst dosages, the effective surface area of the solution was increased; hence, its reaction efficacy was enhanced proportionally. Excessive catalyst loading caused reflection and scattering, which reduced the transmittance of the solution and thus the catalytic efficiency. It was observed that the γ-FeOOH dosage played a very important role in the photodegradation of NPX. To investigate the effect of γ-FeOOH dosage on the photodegradation of NPX, γ-FeOOH solutions were prepared at concentrations of 0.05, 0.1, 0.2, 0.4, and 0.6 g·L−1, which were then introduced into separate NPX solutions. As shown in Figure 4A, the data collected from the photodegradation of NPX following the addition of different concentrations of γ-FeOOH were fitted to a first-order kinetic equation. It was observed that the NPX photodegradation rate increased with increased γ-FeOOH loading in water.</p><!><p>(A) Influence of γ-FeOOH dosage on NPX photodegradation, and (B) influence of γ-FeOOH dosage on the NPX photodegradation rate constant.</p><!><p>When the dosage of γ-FeOOH was varied from 0.05 to 0.6 g·L−1, the NPX photodegradation rate increased from 0.0344 to 0.0509 min−1. The position and photogenic charge of photocatalytic reactions in the system were enhanced with increased γ-FeOOH loading; however, the shielding, reflection, and scattering of light were increased with higher γ-FeOOH loads. With appropriate loads of γ-FeOOH, the transmittance of light in the solution decreased and the reaction rate slowly increased.</p><p>During the process of photodegradation, the relationship between the reaction rate constant k and the concentration of γ-FeOOH was fitted to the following empirical formula (Galindo et al., 2001):</p><p>where n is the correlation index and [γ-FeOOH] is the concentration of γ-FeOOH (g·L−1).</p><p>The kinetic constants of NPX photodegradation and the dosage of γ-FeOOH (0.05 to 0.6 g·L−1) in this experiment were analyzed by linear regression, with the relationship between k and [γ-FeOOH] shown in Figure 4B:</p><p>To: k = 0.05577[γ − FeOOH]0.1394</p><!><p>It has been suggested that the charge transfer process between the contaminants adsorbed to the catalyst surface and the light-generated active species (h+, ·OH, and O2·) facilitates the photocatalytic oxidation of pollutants in solution. Therefore, the coverage of pollutants on the catalyst surface has an important influence on photocatalytic activity.</p><p>In this section, the photodegradation of NPX by 0.2 g·L−1 γ-FeOOH was investigated at initial NPX concentrations of 5, 10, 20, 30, and 40 mg·L−1, with the results shown in Figure 5A. These experiments revealed that the photodegradation of NPX followed first-order kinetics at different initial concentrations upon the addition of γ-FeOOH. The activities of semiconductor photocatalysts arise primarily from photogenic e− and h+, where, in the competitive process of photocatalysis, they may be recombined very rapidly (generally at the nanosecond level) (Hoffmann et al., 1995). From the kinetics perspective, only the adsorbents on the surface of the catalyst may be oxidized by e−. However, our results revealed that the NPX photodegradation rate decreased with higher initial concentrations in solution.</p><!><p>(A) Influence of initial NPX concentrations on the photodegradation of γ-FeOOH/NPX; (B) the initial reaction rate r0 as a function of initial NPX concentration C0; (C) Langmuir-Hinshelwood model of photocatalytic NPX degradation by γ-FeOOH; (D) influence of initial NPX concentrations on the photodegradation rate constant of γ-FeOOH/NPX.</p><!><p>Under a certain light intensity, higher initial NPX concentrations resulted in a lower population of photons available per NPX molecule; hence, a lower photodegradation rate was obtained. An identical result was reported in previous NPX research (Ma et al., 2013). Secondly, higher initial NPX concentrations, with additional particles adsorbed to the γ-FeOOH surface, acted to lower the number of photocatalytically active sites that were available at the surface. Hence, the population of photogenerated e−/h+ pairs per unit of time was correspondingly reduced. Simultaneously, prior to the photodegradation of NPX molecules, they were required to undergo charge exchange with the active species generated at the γ-FeOOH surface and diffuse into the solution. Finally, when the initial NPX concentration was increased, it was difficult to completely decompose the reaction-generated intermediate products in a timely manner. This increased the opposition against adsorption to the surface of the γ-FeOOH, where these intermediates could once again reform the NPX matrix. Therefore, the photodegradation rate was finally decreased.</p><p>We considered the derivative of the obtained first-order kinetic equation with respect to t and set t = 0 to obtain the photodegradation rate r0 under different initial concentrations of C0, as shown in Figure 5B. When the initial concentration of NPX was increased from 5 to 40 mg·L−1, the initial photodegradation rate r0 also increased gradually, from 0.1415 to 0.7997 mg·L−1·min−1. This indicated that the photocatalytic degradation of NPX occurred on the surface of γ-FeOOH, and the photodegradation rate was an increasing function of the level of surface adsorption. When the Metastable-Equilibrium Adsorption Theory (Pan and Liss, 1998) is regarded under certain thermodynamic conditions, the adsorption amount is related to the surface binding strength and the adsorption configuration, while being balanced with the concentration of the solute. In this section, when the initial NPX concentration was raised, the coverage rate of the NPX molecules on the surface of γ-FeOOH increased accordingly. Consequently, the electron transfer efficiency of the NPX molecules that was adsorbed to the surface and the photogenerated charge were increased, which led to an increase of the initial photodegradation rate r0.</p><p>A large quantity of experimental data has indicated that the photocatalytic degradation of organic pollutants on the surface of semiconductors conforms to the Langmuir–Hinshelwood kinetic equation (Hoffmann et al., 1995; Houas et al., 2001; Andreozzi et al., 2003; Du et al., 2008; Li et al., 2008). The applicable premise of the L–H kinetic equation is that the organic pollutant molecules are adsorbed to a solid surface (Turchi and Ollis, 1990; Alfano et al., 1997). Although researchers have not clarified the photocatalytic mechanisms of FeOOH, surface complexes (Faust and Hoffmann, 1986) and semiconductor-initiated photocatalytic mechanisms (Bandana et al., 1999) have had their respective supporters. More recent studies have supported semiconductor photocatalytic mechanisms and highlighted the role of organic pollutant molecules adsorbed to the FeOOH surface (Bandana et al., 1999, 2001a,b). In examining the FeOOH-facilitated photocatalysis of orange II, Du et al. (2008) analyzed the initial reaction rate, amount of FeOOH surface adsorption, and the position of the FeOOH activity. Thus, Du considered that the FeOOH photocatalytic reaction takes place at the solid surface; therefore, the available L–H kinetic equation could be employed to describe FeOOH photocatalysis. Based on this, 1/C0 and 1/r0 were calculated according to Equation (2), and a plot was created for 1/C0-1/r0 (as shown in Figure 5C). A linear relationship was found between them within the experimental concentration range (R2 = 0.9996), kL−H = 2.1867 mg·L−1·min−1, K = 0.01377 L·mg−1. This signified that the photocatalytic degradation of NPX on the surface of γ-FeOOH satisfies the L–H kinetic equation, and that the adsorption of NPX on γ-FeOOH is of importance to its photocatalytic degradation (Li et al., 2008).</p><p>Within the range of experimental concentrations, the photodegradation kinetic constant of NPX gradually decreased (from 0.0285 to 0.0200 min−1), whereas the correlation coefficient R2 decreased from 0.9949 to 0.9791. The relationship between the reaction rate constant k and the initial substrate concentration during the photocatalytic process could be generally described by the following empirical formula:</p><p>where n is the correlation index and [NPX] is the initial concentration of NPX (mg·L−1).</p><p>Linear regression was used to analyze the relationship between the NPX photodegradation kinetic constant and its initial concentration (5–40 mg·L−1) within the experimental range. It can be seen in Figure 5D that the relationship between the reaction rate constant k and NPX concentration was as follows:</p><!><p>It is understood that pH is a critical factor that influences the photocatalytic degradation kinetics during semiconductor multiphase photocatalysis. First, pH can change the charge properties of the catalyst surface and affect how organic molecules adsorb on the catalyst surface (Barnard et al., 2005). Secondly, photogenerated charge carriers can combine with H+/OH− in solution to form active species, such as OH−, which can capture photogenerated holes H+ to form ·OH. Finally, pH may alter the electron cloud density distribution of organic molecules, thus affecting photocatalytic degradation.</p><p>As the effects of pH on photocatalytic degradation kinetics are relatively complex, definitive studies of γ-FeOOH are relatively rare. In this section, to investigate the effects of initial pH on the photodegradation of γ-FeOOH/NPX reaction systems, the initial NPX concentration was established as 10 mg·L−1, whereas that of γ-FeOOH was 0.2 g·L−1, and the initial pH of the photodegradation solution was set at 5, 7, and 9. As shown in Figure 6A, at a pH of 5, the γ-FeOOH /NPX system demonstrated the fastest photocatalytic rate with a pH of 9 in the second place, while the slowest rate was observed at a pH of 7, much the same as the photocatalytic rates observed in water (Figure 6B).</p><!><p>(A) Influence of the pH value on photodegradation rate constant of γ-FeOOH/NPX, and (B) influence of the pH value on photodegradation of NPX.</p><!><p>As pHZPC = 8.47 for γ-FeOOH, the hydroxylation of the γ-FeOOH surface in an alkaline solution could allow OH− to react with h+ to produce ·OH as follows:</p><p>Concurrently, the ether bonds of the NPX molecules are less stable under acidic conditions (Chen et al., 2013). Hence, γ-FeOOH was favorable for the photocatalytic degradation of NPX at pH < 7.</p><p>Based on the above analysis, when the pH was low, the stability of the ether bonds within the NPX molecules was decreased, which enabled the γ-FeOOH-based photocatalytic degradation of NPX. When the pH was high, OH− combined with h+ to form ·OH, which facilitated the photocatalytic degradation of NPX. Due to the combined effect of these two factors, the reaction rate was lowest when the pH was 7 within the range of our experiments.</p><!><p>Quenching experiments were carried out (Figure 7A) by measuring the generation of active species during the photodegradation of NPX in pure water. It can be seen that there was not only direct photodegradation caused by 3NPX*, but also self-sensitized photodegradation involving hydroxyl radicals (·OH), singlet oxygen (1O2), and superoxide anions (O2·-) which were produced in the photodegradation process of NPX (Figure 7B) (Zhanyi et al., 2018).</p><!><p>(A) Influence of scavengers on the NPX photodegradation rate constant, and (B) photodegradation of NPX in the water.</p><!><p>To further investigate the active radicals that participate in the photodegradation of NPX, electron paramagnetic resonance (EPR) measurements were carried out. As shown in Figure 8A, there was no signal in the dark, while the signal 1:1:1:1 appeared after 5 min of illumination. It could thus be concluded that O2·- was present and its concentration would be increased by illumination. As shown in Figure 8B, it was observed that the signal 1:2:2:1 appeared. This suggests that ·OH appeared and increased in concentration with illumination. It was also confirmed that 1O2 was present by TEMP from Figure 8C, while the signal 1:1:1 was detected in the light. So, the active radicals in the γ-FeOOH/NPX system were evidenced by electron spin resonance (ESR).</p><!><p>(A) ESR spectra of the DMPO-O2·-, (B) DMPO-·OH, (C) TEMP-1O2, and (D) influence of scavengers on the γ-FeOOH/NPX photodegradation rate constant.</p><!><p>Photocatalytic degradation typically generates a variety of active substances, such as h+, e−, ·OH, 1O2, and O2·- (Hao et al., 2016), with the production processes shown in Equations (8)–(14):</p><p>According to the quenching experiment described in the section "Active Species Analysis," when KI, IPA, NaN3, and BQ were added to the solution, the photocatalytic NPX degradation rate was reduced by different degrees, as shown in Figure 8D. It may be seen from Figure 8D that free radicals such as h+, e−, ·OH, 1O2, and O2·- were involved in the γ-FeOOH-mediated photocatalytic degradation of NPX.</p><p>On one hand, γ-FeOOH is a semiconductor material with an energy band structure, where the energy barrier (Eg) between the valence band (VB) and the conduction band (CB) is only 2.2 eV. When the γ-FeOOH surface was irradiated with photons of energy equal to or greater than the forbidden band, the e− in the VB were excited and jumped to the CB, with h+ being generated in the VB to form e−/h+ pairs. Because of the discontinuous region between the energy bands, the resulting e−/h+ pairs had greater longevity; hence, they migrated to the particle surface in large quantities. The oxidizing properties of the nanoparticle surfaces were potent enough to oxidize the NPX molecules that were adsorbed to the γ-FeOOH surfaces. Additionally, the cavities reacted with H2O molecules, which were also attached to the surface of γ-FeOOH, which then generated ·OH. Due to the strong oxidization ability of ·OH, the NPX molecules on the surface of γ-FeOOH could also be oxidized and degraded. Simultaneously, conducting electrons were combined with O2 at the surface of the γ-FeOOH to generate O2·-, which could also facilitate the oxidative degradation of NPX.</p><p>On the other hand, under sunlight exposure, Fe (III) could accelerate the oxidation of carboxylic acid. As NPX contains a carboxyl group, it could form strong complexes with Fe (III), which rapidly photochemically reacted under light irradiation (Zuo and Hoigne, 1992; Faust and Zepp, 1993), thereby accelerating the oxidative degradation of NPX. Several studies have suggested that the photochemical reaction of these complexes follows the H2O2 production process in water.</p><p>For this photodegradation experiment, the effect of hydrokinetics must also be considered, as light exposure under stirring was first applied. With agitation, the mass transfer rate of NPX from the solution to the γ-FeOOH surface was increased, so additional NPX was oxidized prior to e−/h+ recombination and thus the photodegradation of NPX was increased. Moreover, DO present in the solution could capture the photogenerated electrons generated during the photocatalytic process, which reduced the probability of the recombination of photogenerated electrons and holes, and thus increased the probability of holes oxidizing the NPX. When exposed to UV light, the e− at the surface of the γ-FeOOH could reduce O2 to O2·-, as shown in Equation (20). Subsequently, O2·- reacted with photogenerated holes h+ to form ·OH or peroxide in the presence of organic capture agents, as in Equations (21)–(23). Each of these species contributed to the photodegradation of NPX.</p><!><p>The degradation by-products of NPX on the γ-FeOOH /NPX system were identified by Thermo Scientific Ultimate 3000 RSLC and Q Exactive Orbitrap (HRLC-MS-MS). As shown in Figure 9, seven intermediates were detected. From attacked by h+, e−, ·OH, 1O2, and O2·-, compounds were generated because of the losses of the CO2, H2O, and/or CH3 group. According to the deduced structure of the compounds and the early study, we speculated the reasonable reaction approach as shown in Figure 10.</p><!><p>HRLC-MS-MS spectrum of the intermediates on the γ-FeOOH/NPX system.</p><p>Speculated degradation approach of NPX on the γ-FeOOH/NPX system.</p><!><p>This study concludes that the photodegradation rate of NPX was positively correlated with the concentration of γ-FeOOH in solution, which was related to the absorption of light energy. With increased initial concentrations of NPX, the photodegradation rate decreased while the γ-FeOOH concentration was constant. This was because the population of photons available per NPX molecule was reduced due to the invariable intensity of light, and the numbers of e−/h+ pairs generated on the surface of the γ-FeOOH were reduced per unit. At the same time, the intermediate products generated by the reaction could not be completely decomposed in time, so they engaged in a reverse reaction to reconstitute the NPX matrix. At the tested pH values (5.0, 7.0, and 9.0), the photocatalytic rate was noticeably accelerated at higher and lower pH, while the worst pH for photocatalysis was 7.0. Based on quenching experiments and analysis of the photocatalytic mechanism, we conclude that the photocatalysis of NPX degradation by γ-FeOOH is derived from semiconductor photocatalysis. At last, the intermediates of NPX on the γ-FeOOH /NPX System were identified by HRLC-MS-MS.</p><!><p>All datasets generated for this study are included in the manuscript.</p><!><p>ZL and GL formulated the problem and designed the experiments. ZL, XJ, and XW performed the experiments. ZL and QS took part in data collection and analysis and wrote the paper. QS and CL revised the manuscript.</p><!><p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>

PubMed Open Access

Isotopic labeling of mammalian G protein-coupled receptors (GPCRs) heterologously expressed in Caenorhabditis elegans*

High-resolution structural determination and dynamic characterization of membrane proteins by nuclear magnetic resonance (NMR) require their isotopic labeling. Although a number of labeled eukaryotic membrane proteins have been successfully expressed in bacteria, they lack posttranslational modifications and usually need to be refolded from inclusion bodies. This shortcoming of bacterial expression systems is particularly detrimental for the functional expression of G protein-coupled receptors (GPCRs), the largest family of drug targets, due to their inherent instability. In this work we show that proteins expressed by a eukaryotic organism can be isotopically labeled and produced with a quality and quantity suitable for NMR characterization. Using our previously described expression system in Caenorhabditis elegans, we showed the feasibility of labeling proteins produced by these worms with 15N,13C by providing them with isotopically labeled bacteria. 2H labeling also was achieved by growing C. elegans in presence of 70% heavy water. Bovine rhodopsin, simultaneously expressed in muscular and neuronal worm tissues, was employed as the \xe2\x80\x98test\xe2\x80\x99 GPCR to demonstrate the viability of this approach. Although the worms\xe2\x80\x99 cell cycle was slightly affected by the presence of heavy isotopes, the final protein yield and quality was appropriate for NMR structural characterization.

isotopic_labeling_of_mammalian_g_protein-coupled_receptors_(gpcrs)_heterologously_expressed_in_caeno

Introduction<!>Maintenance of worms and generation of transgenic (TG) worm lines<!>Stable isotope labeling of HB101<!>Stable isotope labeling of nematodes<!>Analysis of worm brood sizes<!>Analysis of growth rates<!>Analysis of egg hatching rate<!>Immunohistochemistry (IHC)<!>Immunoblotting<!>In vivo light-response assays<!>Labeling bacteria and nematodes with 13C6,15N2-lysine and proteomic sample preparation for LC-MS/MS analyses<!>LC-MS/MS analyses<!>Identification and quantification of heavy-lysine labeled and unlabeled peptides and proteins<!>Statistical analyses<!>Simultaneous expression of (b)opsin in worm muscles and neurons<!>An optimized protocol for culturing isotopically labeled transgenic worms<!>Triple-labeled (b)isorhodopsin is functional and correctly expressed<!>The isotopic labeling yield is suitable for NMR structural studies<!>DISCUSSION

<p>Drug design, lead generation and optimization are greatly facilitated if the structure of the biological target is known. This is particularly true when complexes between a ligand and target can be obtained. Although X-ray crystallography remains the current gold standard for structural determination, recent advances in solution-state NMR techniques to overcome molecular weight limitations offer an alternative approach for structural determination [1]. An added advantage of NMR structure determination is that it is less sensitive to disordered regions of the protein [2], allowing the analysis of protein targets that could be refractory to crystallization. Moreover, NMR offers the possibility of quantitative dynamics and binding studies for membrane proteins (MPs) complexed with ligands and drugs in a solution closely resembling their native environment. Despite the increasing importance of structure-based methods in modern pharmacological research and the fact that about 60% of drug targets are MPs [3], only a small fraction of protein structures solved to date at atomic resolution correspond to MP structures with a native sequence. The GPCR family of MPs represents the largest class of drug targets because drugs designed to interact with GPCRs are marketed in virtually every therapeutic area [4–8]. Structure-based drug design for GPCRs is advancing at a steady pace due to several crystal structures solved in the past few years. However, bovine rhodopsin remains the only vertebrate GPCR with a native sequence whose crystal structure has been determined at atomic resolution. Thus, novel technologies to elucidate the structures and provide conformational dynamics of GPCRs in native-like environments remains both highly desirable and challenging. The only GPCR structure solved to date by solid-state NMR is that of a ligand-free form of chemokine receptor CXCR1 [9], which was 15N- and 13C-labeled in E. coli, solubilized with SDS from inclusion bodies, purified in hexadecyl- and dodecyl-phosphocholine (DPC) and refolded in phospholipic proteoliposomes by detergent dialysis. Another somewhat successful example of expression of a GPCR in bacteria is the serotonin receptor 5-HT4 [10], which also had to be refolded from 6 M urea. A major disadvantage of expressing mammalian GPCRs in bacteria is the uncertainty about the percentage of protein that is correctly folded in the final reconstituted, purified sample.</p><p>Here we describe the feasibility of triple isotopic labeling (2H-, 15N and 13C) of proteins expressed in a eukaryotic system (C. elegans). We chose worms heterologously expressing bovine rhodopsin, a GPCR critical for vision signaling, as our primary target for proof of concept for two reasons: 1) rhodopsin's signature absorbance allows a convenient quality control for protocol optimization; 2) rhodopsin's well-characterized biochemical properties allow functional comparisons of isotopically-labeled and non-labeled samples. The advantage of this particular expression system is that mammalian GPCRs expressed in TG worms: 1) are post-translationally modified and properly folded, 2) exhibit the same pharmacological, photochemical and G protein signaling properties as do their counterparts obtained from a native source, 3) scalability, 4) phenotypic diversity, and 5) relatively facile genetic manipulation among others [11, 12]. Proteins expressed in the worms can be easily labeled simply by providing them with 15N-,13C-labeled E. coli or adding 2H2O to the worm culture media.</p><p>Here we demonstrate the feasibility of isotopically labeling mammalian GPCRs in the C. elegans expression system to characterize their structure, stability, interactions and dynamics in solution by NMR. This strategy leverages the power of the C. elegans protein expression system for producing experimental quantities of GPCRs (or other MPs) combined with isotopic labeling to produce samples suitable for structure determination with state-of-the-art NMR methods.</p><!><p>Worms used for this study were maintained by standard methods [13]) including culture on nematode growth medium plates (NGM)(0.25% peptone, 51 mM NaCl, 25 mM K3PO4, 5 μg/ml cholesterol, 1 mM CaCl2, and 1 mM MgCl2) with OP50 bacteria, cryostorage, and recovery from stocks. Compositions of media and solutions, as well as detailed protocols for their use, were previously published in Ref. [13]. Transgenic worm lines expressing bovine aporhodopsin ((b)opsin) in either muscles or neurons also have been described [11, 12]. Hermaphrodites expressing (b)opsin in muscles were crossed to males expressing (b)opsin in neurons. By screening for the fluorescent marker DsRed in F3 progeny, we obtained a homozygous worm line expressing (b)opsin in both muscles and neurons ([M,N](b)opsin).</p><!><p>Unlabeled E. coli HB101 were grown in an incubated shaker (I2500 series; New Brunswick Scientific, Edison, NY, USA) (37°C, 180 rpm) with M9 minimal medium of the following aqueous composition: 42.25 mM Na2HPO4, 279.41 mM KH2PO4, 8.56 mM NaCl,, 18.70 mM NH4Cl,, 113.51 μM CaCl2, 8.92 μM EDTA-Na2, 15.41 μM FeCl3, 1.50 μM CuSO4, 1.19 μM MnSO4, 0.1673 μM ZnSO4, 0.2080 μM CoCl2, 40.93 nM biotin, 33.24 nM thiamine, 2 mM MgSO4, and 22.20 mM glucose. The medium was adjusted to pH 7.4 with 10 M NaOH.</p><p>The same culture conditions were used to culture isotopically labeled HB101 except that ~99% 2H2O (for 2H labeling), 18.35 mM 15NH4Cl (for 15N labeling), and 10.74 mM labeled glucose (13C6H12O6) (for 13C labeling) were substituted for either H2O, NH4Cl or glucose, respectively, in M9 minimal medium. All media were sterilized by filtration.</p><!><p>For solid phase culturing, worms were grown on peptone-free NGM plates with 51 mM NaCl, 25 mM K3PO4, 5 μg/ml cholesterol, 1 mM CaCl2, and 1 mM MgCl2 in either H2O or 700 g/L 2H2O. For liquid phase culture, worms were grown in S-medium (100 mM NaCl, 39.79 mM KH2PO4, 10.22 mM K2HPO4, 12.93 μM cholesterol, 10 mM citric acid monohydrate, 20.66 mM KOH, 3 mM CaCl2, 3 mM MgSO4, 24.89 μM FeSO4, 55.32 μM Na2EDTA, 15.58 μM ZnSO4, and 11.69 μM CuSO4) in either H2O or 800 g/L 2H2O. Isotope-labeled worms were provided with HB101 containing the same isotope, e.g., 13C-,15N-labeled HB101 for 13C-,15N- labeled worms, using previously described worm culture protocols [14].</p><!><p>Worms were synchronized to L1 (first larval stage) by standard methods [14]. Six L1 animals were transferred onto peptone-free NGM plates specially made with isotopic media and then provided with HB101 labeled with the same isotope. Total F1 larvae were counted.</p><!><p>About 200 synchronized L1 worms were transferred into H2O or 2H2O S-medium and provided with unlabeled or isotopically-labeled HB101. Lifetime cycles (from L1 to L1 progeny) were quantified. The ratio of the lifetime cycle of control worms (46 ± 2 h) raised under non-labeling conditions, over the experimental worm lifetime cycle was defined as the relative growth rate.</p><!><p>Synchronized young adult worms were raised in 70% 2H2O containing S-medium and provided 2H-labeled (98%) HB101. One hundred of their eggs were transferred to S-medium containing unlabeled, 13C-, or 15N-labeled HB101. Hatched F1 L1 worms were then observed for 4 days.</p><!><p>IHC was performed as previously published [11, 12]). Briefly, age-synchronized day 1 animals were sandwiched between 2 cover glasses, buried in dry ice for 30 min, and then fixed with 100% methanol (10 min) followed by 100% acetone (10 min). Then worms were washed with PBS (137 mM NaCl, 2.7 mM KCl, 8.1 mM Na2HPO4·2H2O, and 1.76 mM KH2PO4, pH 7.4) for 0.5 h and incubated with PBS containing Alexa-488-conjugated 1D4 antibody and 0.1% Triton X-100 overnight at 4°C. Stained worms were subsequently washed 3 times with PBS and examined by confocal microscopy. All experiments were done with a Leica TCS SP2 confocal microscope (Leica Microsystems, Bannockburn, IL, USA). Either live worms immobilized with 10 mM NaN3 on 2% agarose pads or methanol/acetone-fixed worms were used. Fluorescent probes employed were DsRed (λex=543 nm; λem=580–630 nm) and Alexa-488 (λex=488 nm; λem=510–530 nm).</p><!><p>Immunoblotting was carried out by a published protocol [11]. Briefly, worms were sonicated and centrifuged to remove debris. The resulting supernatant was mixed in electrophoresis loading buffer, vortexed, centrifuged briefly, and samples were analyzed by immunoblotting after SDS-PAGE on 4–12% Bis-Tris polyacrylamide gels (Invitrogen, Carlsbad, CA, USA). Quantification of signals in immunoblotted gels was done by obtaining their digital pictures with ImageJ software [15]. Area values of bands were measured and compared with areas of purified (b)opsin or control samples loaded on the same gel.</p><!><p>In vivo light-response assays were performed as previously described [12] with some modifications. Briefly, one day before such experiments, unlabeled L4 animals raised at 20°C were transferred onto NGM plates seeded with 100 μl HB101 bacteria culture containing either DMSO vehicle control (no retinal), 10 μM 9-cis-retinal or 10 μM all-trans-retinal (Toronto Research Chemicals, Toronto, ON, Canada). Triple isotopically labeled (2H, ~70%; 13C,15N,~100%) animals were transferred onto peptone-free NGM plates containing 80% 2H2O seeded with 100 μl of triple isotopically labeled (2H, ~70%; 13C,15N,~100%) HB101 culture medium containing either DMSO vehicle control (no retinal), 10 μM 9-cis-retinal or 10 μM all-trans-retinal. The resulting plates were wrapped with aluminum foil and stored in a cardboard box overnight at 20°C. Light response experiments were carried out at 22°C in a dark room with a Zeiss Stemi SV11-Apo microscope (Carl Zeiss, Oberkochen, Germany) and 7 lux of transmitted white light was used to visualize (b)opsin-expressing animals. For each light-response assay, a day-1 worm was transferred onto an unseeded NGM plate. About 5 seconds later,1000 lux of blue light (488±20 nm) was delivered over 1 s to animals from a metal halide short arc bulb housed in an EXFO X-Cite 120PC-Q unit (Lumen Dynamics, Mississauga, ON, Canada) through a Kramer USFAC and animals then were continuously imaged for another 1 min.</p><p>Worm locomotion before and after illumination was recorded by AVI movies. Light intensity output of the EXFO unit was calibrated to reach a targeted intensity (±5%) at the microscopic field, measured with a Macam L203 Photometer (MacamPhotometrics, Livingston, UK). The light-response index was defined as described in [12]: 5 = complete lack of motion >10 s; 4 = complete lack of motion > 10 s except for head shaking; 3 = lack of motion 2–10 s; 2 = lack of motion ≤ 2 s; 1= changed locomotion speed or direction; and 0 = no change noted in motor activity.</p><!><p>These procedures have been described in detail [14]. Briefly, arginine and lysine auxotrophic Escherichia coli AT713 bacteria were cultured in M9 basal medium supplemented with arginine (100 μg/ml), cysteine (100 μg/ml) and lysine (100 μg/ml either 12C6,14N2-lysine) or 13C6,15N2-lysine) (Cambridge Isotope Laboratories, Andover, MA)) (M9 with amino acid supplementation) in an incubator shaker (3°C, 200 rpm until OD600 reached 1.5), pelleted by centrifugation, and killed with 100% ethanol.</p><p>Age-synchronized animals were cultured to day 3 on peptone-free NGM plates seeded with regular or heavy lysine-labeled AT713 bacteria along with 25 mg/l 5′-FUDR (5-fluoro-2′deoxyuridine, Geel, Belgium) starting from day 0. Then bacteria were separated from nematodes by an H2O wash and nematodes were pelleted by centrifugation. Equal weights of heavy lysine-labeled and unlabeled WT worms were suspended in 100 mM ammonium bicarbonate containing 4% perfluorooctanoic acid (w/v), and proteins were extracted by ultrasonication (4.5 kHz three times for 9 s with a 3-min pause on ice between pulses) using a Virsonic 100 ultrasonic cell disrupter (SP Scientific, Warminster, PA). Extracted proteins were reduced with dithiothreitol and S-alkylated with iodoacetamide, and then digested by Lys-C as described previously [14].</p><!><p>LC-MS/MS analyses were conducted using an UltiMate 3000 LC systems (Dionex Inc.) interfaced to Velos Pro Ion Trap and Orbitrap Elite Hybrid Mass Spectrometer (Thermo Scientific, Bremen, Germany). The platform was operated in the nano-LC mode, with the standard nano-ESI (Proxeon Biosystems) source. The spray voltage was set at 1.2 kV and the temperature of the heated capillary was set to 200°C. The solvent flow rate through the column was maintained at 300 nL/min. Lys-C digests were injected onto a reversed-phase 0.3 × 5 mm C18 PepMap trapping column with a 5-μm particle size (Dionex Inc.) equilibrated with 0.1% formic acid/1% acetonitrile (v/v). The column was washed for 5 min with the equilibration solution at a flow rate of 25 μL/min using an isocratic loading pump operated through an autosampler. The trapping column was then switched in-line with a reversed-phase 0.075 × 150-mm C18 Acclaim PepMap 100 column (Dionex Inc.), and peptides were eluted using a linear gradient of 2 to 37% acetonitrile in aqueous 0.1% formic acid over 180 at a flow rate of 300 nL/min. The eluent was directly introduced into the mass spectrometer. The mass spectrometer was operated in a data-dependent MS to MS/MS switching mode, with the 10 most intense ions in each MS scan subjected to MS/MS analysis. Full MS scanning was performed at a resolution of 120,000 ("full width at half maximum") in the Orbitrap detector, and MS/MS was performed in the ion trap detector in a collision-induced dissociation mode. The threshold intensity for the MS/MS trigger was set at 3000. Fragmentation was carried out in the collision-induced dissociation mode with a normalized collision energy of 35. The data were completely collected in the profile mode for the full MS scan and in the centroid mode for the MS/MS scans. The dynamic exclusion function for previously selected precursor ions applied the following parameters: repeat count of 1, repeat duration of 40 s, exclusion duration of 90 s, and exclusion size list of 500 (ions). Xcalibur software (Version 2.2 SP1 build 48, Thermo-Finnigan Inc., San Jose, CA) was used for instrument control, data acquisition, and data processing.</p><!><p>Proteins were identified by comparing all experimental peptide MS/MS spectra against the Wormbase database using Mascot database search software (version 2.1.04, Matrix Science, London, UK). Carbamidomethylation of cysteine was set as a fixed modification, whereas oxidation of methionine to methionine sulfoxide, acetylation of the N-terminal amino group, and the replacement of C-terminal lysine with heavy-Lys were considered to be variable modifications. The mass tolerance was set to 10 ppm for the precursor ion and to 0.8 Da for the product ion. Strict Lys-C specificity was applied, and missed cleavages were not allowed. Criteria for significant peptide identifications included the following: peptides must be composed of at least six amino acid residues and have a minimum mascot score of 20. The false discovery rate was calculated from the following equation: N(decoy)•2/N(decoy) + N(target), and the threshold rate was set to ≤0.01 for peptide identification. Protein isoforms and proteins that could not be distinguished based on the peptides identified were reported as a single protein group. ProteomicsTools version 2.4.1 was used to obtain the intensities of heavy-lysine labeled and unlabeled proteins [16].</p><!><p>Statistical significance was analyzed with Statistica software (StatSoft, Tulsa, OK, USA). T-tests, ANOVA with Dunnet's post-hoc analyses were used for their appropriate applications. Error bars indicate means ±SE. P values <0.05 were accepted as defining statistically significant differences.</p><!><p>We demonstrated previously that (b)opsin can be expressed in worm muscular [M] or neuronal [N] tissue in a homogeneously glycosylated and functional form [11]. Indeed over 1 milligram of functional bovine isorhodopsin ((b)opsin reconstituted with 9-cis-retinal) and other vertebrate GPCRs could be obtained in a pure form from a 10-L worm culture. To maximize the expression of (b)opsin we hypothesized that expressing it in both, muscles and neurons would show an additive effect in the total amount of protein without negatively affecting the TG worm life cycle. Quantification of the expression level showed that the expression level of (b)opsin in [M,N](b)opsin worms was in fact about twice the amount expressed in [M](b)opsin and [N](b)opsin worms, reaching a final yield of ~3 mg per 10-L of cell culture (Fig. 1A,B). Because the glycosylation pattern is similar in both tissues, most of the (b)opsin migrated as a single band upon electrophoresis. After reconstituting the (b)opsin with 9-cis-retinal, purification of ground-state (b)isorhodopsin to >99% homogeneity and functionality was relatively simple in two chromatographic steps (Fig. 1C). The absorption spectra before (Fig. 1C) and after illumination were identical to spectra of bovine rhodopsin [17]. Consequently, this [M,N](b)opsin TG worm line was adopted for our remaining experiments involving (b)opsin expressed in worms.</p><!><p>Isotopic labeling of proteins expressed in TG worms was achieved by providing the worms with E. coli grown in isotopic media. We tested whether different isotopes had noxious effects on worm growth which could lower the final protein yield. For example, isotopic labeling might: 1) delay the reproduction of TG worms, 2) suppress the growth of TG worms, or 3) lower heterologous GPCR expression in TG worms.</p><p>We cultured (b)opsin expressing TG worms in 1H or 2H-containing liquid medium and provided them with non-labeled, 2H-labeled, 13C-,15N-labeled or 2H-,13C-,15N-labeled bacteria (E. coli HB101, food of nematodes) following a previously published protocol [11]. Similar to E. coli, both the growth rate and breeding of (b)opsin expressing TG worms were significantly affected by 2H-labeling, such that worms grew only half as fast and had half the progeny per hermaphrodite in 70% 2H2O-containing liquid medium (Fig. 2). Also similar to E. coli, 13C,15N-labeling had little effect (<10%) on both the breeding and growth of TG worms. Importantly, eggs produced by 13C-,15N-labeled TG worms hatched and matured into Day 4 larva (L4) at the same rate as eggs produced by unlabeled TG worms in 70% 2H-containing liquid medium (Fig. 2C). Because 2H2O is needed only during the protein production/fermentation steps, this worm culturing problem can be addressed by culturing 13C,15N-labeled TG nematodes in the initial steps to collect eggs. Once in the fermenter, we used 70% 2H-containing liquid medium and maintained transgenic worms with either 13C,15N-labeled or 2H,13C,15N-labeled bacteria. With the latter protocol, the negative effect of 2H labeling on TG worm breeding and growth had only a minor effect on fermenter preparation. This modification extended the culture time in a fermenter, the rate-limiting step of TG worm production, from ~3.5 days for unlabeled TG worms [11, 12] to ~7 days.</p><p>We next used this modified protocol to culture unlabeled and triple-labeled TG worms and compare their (b)opsin expression levels. We found that isotopic labeling reduced (b)opsin expression by ~30% (not shown). Thus, we were able to produce 2 mg of a triple- and double-labeled GPCR from a 10-L worm culture in 10 days. We conclude that an optimized culturing protocol with a 70% 2H-containing liquid medium is suitable for producing 13C, 15N and 2H-labeled transgenic worms.</p><!><p>The promoters myo-3 (Pmyo-3; [18]) and H20 (PH20; [19]), that drive strong gene expression in muscles and the nervous system, respectively, were chosen to control the co-expression of (b)opsin in these two worm tissues. Muscles comprise the greatest portion of the worm body mass, and the nervous system has the largest numbers of a specific cell type; e.g., 302 of the 959 total somatic cells in an adult worm are neurons. In examining whether isotopic labeling affects the folding of heterologous receptors and their association with membranes, we found that isotopic labeled transgenic worms cultured under optimized conditions (13C, 15N,~100%; 2H, ~70%) exhibited the same cellular distribution of (b)opsin in the nervous system and muscles as did unlabeled transgenic worms (Fig. 3A). Also (b)opsin expression was modestly (~30%) reduced in isotopically labeled transgenic worms compared with unlabeled transgenic worms (Fig. 3B). The presence of (b)opsin was detected by IHC with Alexa-488-conjugated 1D4 antibody, with a C-terminus epitope identical to that of rhodopsin.</p><p>Worms do not have vision and thus do not respond to visible light [11, 12]. However, when (b)opsin expressed in TG worms is reconstituted with 11-cis-retinal, the resulting ground-state rhodopsin, (b)Rho, becomes light sensitive, mimicking rhodopsin in the retina (not shown). Bovine opsin reconstituted with 9-cis-retinal, known as isorhodopsin, has similar biophysical properties to rhodopsin except that its maximum absorbance is blue-shifted to ~485 nm. Illumination of (b)isorhodopsin results in the isomerization of 9-cis-retinal into all-trans-retinal, and the consequent activation of rhodopsin [11, 12]. We previously demonstrated that photoactivation of (b)isorhodopsin in neurons of TG worms results in an instantaneous but transient muscular paralysis [12]. Just as unlabeled TG worms expressing (b)isorhodopsin, triple-labeled TG worms exhibited locomotive paralysis in response to a 488 nm light pulse (Fig. 3C) although there was a slight reduction in light sensitivity. This reduction is likely attributable to a reduced expression of the receptor (Fig. 3B) or the isotopic effect on G protein activation. Moreover, absence of 9-cis- or 11-cis-retinal prevented this response to light. The latter observation demonstrates that triple-labeled (b)isorhodopsin is functional in vivo. Indeed, both unlabeled and labeled recombinant (b)opsin displayed immunoreactive bands of (b)opsin monomer (Fig. 3B).</p><!><p>To estimate the isotopic labeling yield of (b)opsin in TG worms, we used our "stable isotope labeling by amino acids in worms" strategy (an adaptation of "stable-isotope labeling with amino acids in cell culture" (SILAC)) [20] to quantify the incorporation of 15N2,13C6-lysine, an essential amino acid for worms and the E. coli species used [21], into TG worms. In SILAC, stable isotope-labeled amino acids are incorporated into cellular proteins through endogenous protein synthesis, allowing accurate quantification of all native proteins without subsequent chemical modification. Our technique involves mixing equal amounts of labeled and unlabeled sample prior to mass spectral analysis. The worms were obtained by the optimized culturing protocol described above. With this relatively inexpensive and accurate quantitative proteomic approach [22, 23], we identified a total of 1947 worm proteins (one tenth of the worm genome) and found that the average labeling yield of 15N2,13C6-lysine was over 97.5%. Fig. 4 shows plots of the intensities of unlabeled peptides against their labeled counterparts for ~2000 proteins. The slope of the linear regression fitting line (1.0064) indicates virtually complete labeling yield. Thus, it is reasonable to conclude that heterologous GPCRs also will be labeled with 15N2,13C6-Lys at about the same yield.</p><!><p>Structural characterization of membrane proteins usually involves the heterologous expression of milligram amounts and their purification. In addition, NMR studies require the isotopic labeling of the target protein. Bacterial expression systems have been used routinely to label membrane proteins for NMR. However, the functional expression of mammalian GPCRs in bacteria is extremely challenging due to their instability and the number of posttranslational modifications required for maintaining their native functional conformation. Although several groups have reported successful refolding of GPCRs from exclusion bodies, it remains uncertain as to what percentage of the final purified sample was properly folded after the harsh treatment involved in refolding. A similar approach for labeling rhodopsin in a eukaryotic expression system was previously described for HEK293S cells [24]. Expression of GPCRs in mammalian cells has advantages over other expression systems but it also has disadvantages, such as the heterogeneity of post-translational modifications of the heterologously expressed receptor.</p><p>The aim of this work was to demonstrate the feasibility of isotopically labeling GPCRs heterologously expressed in a eukaryotic organism (C. elegans). We first started by increasing the heterologous protein yield through co-expressing bovine aporhodopsin ((b)opsin) in both neurons and muscles). (b)Opsin can easily be reconstituted into ground-state rhodopsin (b)rhodopsin by incubating worms or worm membrane extracts with 11-cis retinal. Alternatively, (b)isorhodopsin can be obtained by incubation with 9-cis-retinal, a chemically more stable isomer. The purification yield is at least 3 mg of (b)isorhodopsin for a 10-L fermentation, and we show that the resulting protein can be easily obtained at a purity and functionality of >99%.</p><p>Next, we explored the effect of isotopic labeling on worm growth, which will ultimately affect the final protein yield. Not surprisingly, the worms' cell cycle was affected by the presence of heavy elements, especially 2H, much like what was previously observed in E. coli [25]. Fortunately, by modifying our culture protocol, we obtained a uniform 13C-,15N-labeling, and 70% 2H labeling of C. elegans proteins. This was achieved by providing the worms with 13C-,15N-labeled bacteria and adding 70% 2H2O to the worm culture media.</p><p>Additionally, we demonstrated that triply isotopically labeled (13C, 15N,~100%; 2H, ~70%) GPCRs expressed in worms are functional as judged by a phenotypic assay described previously [12]. Instantaneous but transient paralysis of worms upon illumination indicates that the exogenous (b)isorhodopsin can be activated to its meta II state which also couples to the worms' endogenous G proteins.</p><p>The uniformity of 13C-,15N-labeling was assessed by an adaptation of the SILAC strategy for quantification of isotopic labeling by mass-spectrometry. By feeding worms with 13C-,15N-labeled lysine, we demonstrated that the average labeling of ~2,000 expressed proteins was ~97.5%, which is appropriate for NMR studies.</p><p>In summary, we developed a set of techniques to obtain single labeled (15N), double labeled (2H,15N)- and triple labeled (2H,13C,15N) vertebrate GPCRs (and potentially other membrane proteins) of a sufficient quality and quantity for NMR structural studies in solution. This strategy combines the advantages of protein expression in eukaryotes (i.e., proper folding and posttranslational modifications), expression in liquid cell culture (scalability, high yield and a rapid cell cycle), and the possibility of uniform isotopic labeling for NMR studies. Thus, this system combines the advantages of in vivo animal expression and unicellular cell expression in suspension. It is particularly reassuring that C. elegans worms express about 1,100 endogenous GPCRs (5% of its genome), many of them with human homologs. In addition, worms feed on E. coli and, therefore, proteins in the worms can be labeled by maintaining them with isotopically labeled bacteria.</p>

PubMed Author Manuscript

Endogenous Rab29 does not impact basal or stimulated LRRK2 pathway activity

Mutations that enhance LRRK2 protein kinase activity cause inherited Parkinson's disease. LRRK2 phosphorylates a group of Rab GTPase proteins, including Rab10 and Rab12, within the effector-binding switch-II motif. Previous work has indicated that the PARK16 locus, which harbors the gene encoding for Rab29, is involved in Parkinson's, and that Rab29 operates in a common pathway with LRRK2. Co-expression of Rab29 and LRRK2 stimulates LRRK2 activity by recruiting LRRK2 to the surface of the trans Golgi network. Here, we report that knock-out of Rab29 does not influence endogenous LRRK2 activity, based on the assessment of Rab10 and Rab12 phosphorylation, in wild-type LRRK2, LRRK2[R1441C] or VPS35[D620N] knock-in mouse tissues and primary cell lines, including brain extracts and embryonic fibroblasts. We find that in brain extracts, Rab12 phosphorylation is more robustly impacted by LRRK2 inhibitors and pathogenic mutations than Rab10 phosphorylation. Transgenic overexpression of Rab29 in a mouse model was also insufficient to stimulate basal LRRK2 activity. We observed that stimulation of Rab10 and Rab12 phosphorylation induced by agents that stress the endolysosomal system (nigericin, monensin, chloroquine and LLOMe) is suppressed by LRRK2 inhibitors but not blocked in Rab29 deficient cells. From the agents tested, nigericin induced the greatest increase in Rab10 and Rab12 phosphorylation (5 to 9-fold). Our findings indicate that basal, pathogenic, as well as nigericin and monensin stimulated LRRK2 pathway activity is not controlled by Rab29. Further work is required to establish how LRRK2 activity is regulated, and whether other Rab proteins can control LRRK2 by targeting it to diverse membranes.

endogenous_rab29_does_not_impact_basal_or_stimulated_lrrk2_pathway_activity

Introduction<!>Reagents<!>Generation of MJFF rabbit monoclonal Rab29 total antibodies (MJF-30)<!>Other antibodies<!>Quantitative immunoblot analysis<!>Mice<!>Generation of Rab29 knock-out mice<!>Generation of Rab29 knock-out LRRK2[R1441C] and Rab29 knock-out VPS35[D620N] knock-in mice<!>Generation of transgenic Rab29 overexpressing mice<!>Mouse genotyping<!>Preparation of mouse tissue lysates<!>Quantitative real-time RT-PCR analysis of Rab29 mRNA from mouse tissue<!>LRRK2 fragment purification and Rab29 pulldown assay<!>Microsome enrichment by fractionation<!>Cell culture, treatments and lysis<!>Generation of MEFs<!>siRNA-mediated knockdown of target proteins in MEFs<!>MLi-2 inhibitor washout in MEFs<!>Immunofluorescence microscopy<!>Generation of primary lung fibroblasts<!>Statistics<!>Expression of Rab29 in mouse tissues and cells<!>Detection of endogenous Rab29 in human and mouse extracts with novel Rab29 monoclonal antibodies.<!>Rab29 knock-out does not impact basal LRRK2-mediated phosphorylation of Rab10 and Rab12 in mouse tissues and MEFs<!>Knock-out of Rab29 does not affect basal LRRK2 activity.<!>Generation and characterization of Rab29 overexpressing transgenic mice<!>Characterization of MJFF transgenic Rab29 overexpressing mouse.<!>Generation and characterization of Rab29 overexpressing transgenic mice<!>Transgenic Rab29 in overexpressing mouse is functional and competent for binding GTP.<!>Transgenic overexpression of Rab29 does not impact basal LRRK2-mediated phosphorylation of Rab10 and Rab12 in mouse tissues and cells<!>Overexpression of Rab29 does not impact LRRK2-mediated Rab10 phosphorylation.<!>Knock-out of Rab29 does not reduce elevated Rab10 and Rab12 phosphorylation in LRRK2[R1441C] knock-in mice<!>Knock-out of Rab29 does not reduce elevated Rab10 phosphorylation in pathogenic LRRK2[R1441C] knock-in mice.<!>Knock-out of Rab29 does not reduce elevated Rab10 and Rab12 phosphorylation in LRRK2[R1441C] knock-in mice<!>Knock-out of Rab29 does not reduce elevated Rab10 and Rab12 phosphorylation in VPS35[D620N] knock-in mice<!>Rab29 knock-out does not reduce the enhanced LRRK2-mediated phosphorylation of Rab10 in VPS35[D620N] knock-in mice.<!>Monovalent cation ionophore antibiotics nigericin and monensin stimulate LRRK2-mediated phosphorylation of Rab10 and Rab12 in wildtype and Rab29 knock-out cells<!>Cation ionophores nigericin and monensin, and lysosomal stressors chloroquine and LLOMe enhance LRRK2-mediated Rab10 and Rab12 phosphorylation in wildtype and Rab29 knock-out MEFs.<!>Monovalent cation ionophore antibiotics nigericin and monensin stimulate LRRK2-mediated phosphorylation of Rab10 and Rab12 in wildtype and Rab29 knock-out cells<!>Rate of recovery of Rab10 phosphorylation after washout of MLi-2 LRRK2 inhibitor is not impacted by Rab29 knock-out<!>Rab29 knock-out does not impact recovery of LRRK2 activity following washout of LRRK2 inhibitor.<!>Evidence that Rab32 is not compensating for loss of Rab29 in regulating LRRK2<!>Knockdown of Rab32 does not impact LRRK2 activity in the absence of Rab29.<!>Discussion

<p>Autosomal dominant missense mutations that hyperactivate LRRK2 (leucine-rich repeat kinase 2) are one of the most common causes of familial Parkinson's disease (PD) [1–4]. Age of onset and progression of LRRK2-driven PD is virtually indistinguishable from sporadic PD, which comprises the vast majority of the patient population. LRRK2 is a large, multi-functional protein kinase that encodes two central catalytic regions, a Roc-type GTPase domain adjacent to a COR (C-terminal of Roc) domain, which is followed by a serine/threonine protein kinase domain. These enzymatic regions are surrounded by several domains, including N-terminal armadillo and ankyrin domains, leucine-rich repeats and a C-terminal WD-40 repeat [5]. The most prevalent LRRK2 pathogenic variants map to either the GTPase Roc [N1437H, R1441C/G/H] or COR [Y1699C] domains, or the kinase domain [G2019S, I2020T], and act as gain-of-function mutations by enhancing LRRK2 kinase activity [6–10]. The mutations within the GTPase Roc/COR domain are proposed to inhibit GTPase activity and enhance GTP binding [11–13]. The mutations within the GTPase domain do not directly activate LRRK2 activity in vitro, but enhance interaction with Rab29 located at the Golgi [14,15]. This leads to the recruitment of LRRK2 to the Golgi membrane surface which enhances its kinase activity, as evidenced by increased autophosphorylation at Ser1292 and phosphorylation of its physiological Rab protein substrates, through a yet undefined mechanism [14,16,17]. Mutations within the kinase domain directly stimulate LRRK2 activity by promoting a more closed, active conformation of the catalytic moiety [18–20]. The VPS35[D620N] autosomal dominant mutation that causes PD markedly elevates Rab protein phosphorylation by LRRK2 through an unknown mechanism [21]. LRRK2 is constitutively phosphorylated on several well-studied serine residues in its N-terminus, specifically Ser910, Ser935, Ser955 and Ser973, and these sites are rapidly dephosphorylated upon pharmacological inhibition of LRRK2 [22,23]. LRRK2 protein kinase inhibitors are currently in early stage clinical trials for LRRK2-driven PD [24,25].</p><p>Well-characterized and validated substrates of LRRK2 comprise a subset of Rab GTPases that include Rab8A, Rab10, Rab12 and Rab29 [7,26]. Rab GTPases are crucial regulators of intracellular vesicle trafficking, implicated in vesicle formation and transport between target membranes in a tightly controlled network [27]. They influence biology by interacting with specific effector proteins when complexed to GTP. LRRK2 phosphorylates Rab proteins at a highly conserved Ser/Thr residue located at the center of the effector-binding region of these enzymes that is also known as the Switch-II motif [7,26,28]. This phosphorylation event appears to act in two ways. Firstly, it prevents Rab proteins interacting with many of their known interactors including guanine nucleotide exchange factors (GEFs) and guanine nucleotide dissociation inhibitors (GDIs) that are required for the shuttling of Rab proteins between membrane compartments. This results in the LRRK2-phosphorylated Rab proteins accumulating on the surface of the compartment on which they are phosphorylated [7,29]. Secondly, LRRK2-phosphorylated Rab8A and Rab10 bind preferentially to a set of effectors, such as RILPL1 and RILPL2, which are implicated in ciliogenesis [26]. These effectors possess a RH2 domain that functions as a phospho-Rab recognition domain [30]. Pathogenic LRRK2 mutants decrease primary cilia formation in cell culture in a manner that is rescued upon LRRK2 inhibition [26]. The ability of LRRK2 to inhibit ciliogenesis requires RILPL1 binding to LRRK2-phosphorylated Rab8A and Rab10 [31,32]. Recent work showed that LRRK2-phosphorylated Rab proteins are dephosphorylated by a highly selective PPM1H protein phosphatase [33].</p><p>Significant effort has focused on Rab29, also known as Rab7L1, and its possible roles in regulating LRRK2. The gene encoding Rab29 lies within a genetically complex locus termed PARK16, which is implicated with increased PD risk [34–37]. The PARK16 locus contains five genes, and it is not clear which of these genes is relevant for PD or how the numerous variants identified within this locus affect gene expression and/or function. Single nucleotide polymorphisms in non-coding regions of the PARK16 locus have been linked to increasing the transcriptional regulation of Rab29 mRNA [15,38,39]. Several earlier studies alluded to the possibility of Rab29 and LRRK2 acting in converging pathways, by demonstrating epistatic interactions between polymorphisms in the LRRK2 and Rab29 genes that increase PD risk [39,40]. Physical interaction between LRRK2 and Rab29, either in vitro or based on a co-immunoprecipitation analysis, has also been demonstrated [15,39,41,42]. Furthermore, analysis of genetic models reveals that Rab29 and LRRK2 operate co-ordinately to control axon elongation in Caenorhabditis elegans, and lysosomal trafficking and kidney pathology in mice [43]. A recent study reports that combined knock-out of LRRK2 and Rab29 does not result in a PD-relevant neuronal pathology or behavioral abnormalities [44]. Rab29 has been implicated in maintaining Golgi morphology and in mediating the retrograde trafficking of the mannose-6-phosphate receptor (M6PR), which recognizes and delivers lysosomal enzymes from the trans Golgi to late endosomes and lysosomes [45,46]. An intriguing finding that implicates Rab29 in immune response demonstrated its recruitment to Salmonella typhi-containing vacuoles and Rab29 involvement in the generation of typhoid toxin transport intermediates that release the toxin into the extracellular environment [47].</p><p>Rab29 belongs to a subfamily of Rab GTPases with Rab32 and Rab38, which are localized to melanosomes and are involved in regulating the trafficking of melanogenic enzymes between the trans Golgi and melanosomes [48]. Rab29 is unique among the Rab proteins targeted by LRRK2 in that it possesses two adjacent phosphorylated residues within its Switch-II motif, namely Thr71 and Ser72. Ser72 aligns with the phosphorylation site found in other LRRK2 substrates. To our knowledge there is no evidence that endogenous Rab29 is directly phosphorylated by LRRK2, however, in overexpression studies, LRRK2 triggers phosphorylation of both Thr71 and Ser72 in a manner that is blocked with LRRK2 inhibitors [14,26]. Based on mutagenesis overexpression experiments, phosphorylation of these sites on Rab29 was proposed to function as a negative feedback loop to block the activation of LRRK2 by Rab29 [14]. Rab32 and Rab38 are not phosphorylated by LRRK2 and do not possess a Ser/Thr residue at the equivalent position within their switch-II motif [26]. Recent work has established that the activation of LRRK2 by Rab29 occurs irrespective of the identity of the membrane to which Rab29 is attached [29], and requires Rab prenylation and nucleotide binding by both LRRK2 and Rab29 [16,29]. Thus, numerous genetic studies in addition to data presented in vitro, in cells, and in model organisms, provide substantial evidence that LRRK2 and Rab29 pathways intersect.</p><p>Previous work showing that LRRK2 is activated by recruitment to the Golgi via interaction with Rab29 is largely based in overexpression experiments in which both Rab29 and wildtype or pathogenic mutants of LRRK2 are co-expressed. In this study, we sought to investigate the physiological relevance of Rab29 as a regulator of endogenous LRRK2 in cell lines as well as in mouse tissues. We describe our efforts to thoroughly characterize four different mouse models that we generated to assess Rab29 impact on basal activity of wildtype and the LRRK2[R1441C] pathogenic mutant. Our data demonstrate that knock-out or moderate transgenic overexpression of Rab29 in a new mouse model we created, does not significantly impact the ability of LRRK2 to phosphorylate Rab10 or Rab12. Furthermore, we show that knock-out of Rab29 does not impact the ability of the VPS35[D620N] mutation or monovalent cation ionophore antibiotics nigericin and monensin to promote Rab10 and Rab12 protein phosphorylation. Our data indicate that Rab29 is not a major regulator of basal wildtype or LRRK2[R1441C] activity as measured in whole cell or tissue extracts that we have analyzed. Further work is, therefore, required to clarify how LRRK2 activity is regulated.</p><!><p>MLi-2 LRRK2 inhibitor was synthesized by Natalia Shpiro (University of Dundee) and was first described to be a selective LRRK2 inhibitor in previous work [49]. Microcystin-LR was purchased from Enzo Life Sciences (ALX-350-012), oriole fluorescent gel stain was purchased from Bio-Rad (#161-0495), and nigericin was purchased from Invivogen (tlrl-nig). Monensin sodium salt (M5273), Leu-Leu methyl ester hydrobromide (LLOMe) (L7393) and chloroquine diphosphate salt (C6628) were purchased from Sigma–Aldrich.</p><!><p>Rabbit immunization and rabbit antibody generation was performed by Abcam Inc. (Burlingame, CA). To generate the Rab29 total antibodies, full length recombinant proteins as well as N-terminal and C-terminal peptides were used. Abcam performed three subcutaneous injections using the immunogens conjugated with keyhole limpet hemocyanin (KLH), followed by two subcutaneous injections using the immunogens conjugated with ovalbumin. Target immunogen is described in Table 1. Following the initial injections with full-length proteins, booster immunizations using N-terminal and C-terminal peptides were performed. The provided bleeds (one bleed pre-immunization, two bleeds after immunization with full-length protein, one bleed after additional immunization with the N- and C-terminal peptides) from immunized animals (six rabbits —E8767–E8772) were tested at 1 : 1000 dilution using lysates of A549 wildtype and Rab29 knock-out cell lysates. Rabbits producing the best antibody were chosen for monoclonal antibody generation. Hybridoma fusion was performed according to an established protocol [50]. Abcam used a process omitting the multi-clone stage and provided 81 single clones directly. Single-clone supernatants were screened using immunoblots of A549 wildtype and Rab29 knock-out cell lysates. The top eight clones that gave the most robust signal were additionally tested using MEF lysates to check for human/mouse Rab29 specificity. Clone #124 was able to detect both human and mouse Rab29, while clone #104, which only detected human Rab29, showed the strongest and cleanest signal. Based on these results, clones #104 (human selective catalog number ab256527) and clone #124 (human + mouse selective antibody catalog number ab256526) were chosen for recombinant antibody generation and are now commercially available from Abcam.</p><!><p>The MJFF rabbit monoclonal antibody Rab10 pThr73 was previously characterized [51] and purchased through Abcam (ab230261). The MJFF rabbit monoclonal Rab12 pSer105 (equivalent phosphorylation site to human pSer106) antibody was described previously [21] and is available from Abcam (ab256487). Recombinant anti-LRRK2 pSer1292 MJFR-19-7-8 (ab203181), recombinant anti-Rab8A MJF-R22 antibody (ab237702), recombinant anti-M6PR (cation independent) antibody (ab124767) and rabbit polyclonal antibody VDAC1 were also purchased from Abcam (ab15895). The mouse monoclonal antibody against total LRRK2 (C-terminus) was purchased from NeuroMab (clone N241A/34, #75-253). Rabbit monoclonal anti-Rab10 (#8127), mouse monoclonal alpha-tubulin (#3873) and rabbit monoclonal PDI (#3501) were purchased from Cell Signaling Technology. Mouse monoclonal Rab32 (B-4) antibody was purchased from Santa Cruz Biotechnology (sc-390178) and was diluted 1 : 200. The mouse monoclonal anti-Rab10 total antibody was purchased from Nanotools (#0680–100/Rab10-605B11) and used at a final concentration of 1 μg/ml. Mouse anti-glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was purchased from Santa Cruz Biotechnology (sc-32233) and was used at 1 : 2000. Mouse monoclonal ACBD3 antibody was purchased from Sigma (WH0064746M1) and used at 10 μg/ml for immunofluorescence. Rabbit monoclonal antibodies for total LRRK2 (N-terminus) (UDD3) and pSer935 LRRK2 (UDD2), and sheep polyclonal antibodies Rab29 total (S984D), Rab12 total (SA227), Rab35 total (SA314) and PPM1H total (DA018) were purified by MRC PPU Reagents and Services at the University of Dundee and were all used at a final concentration of 1 μg/ml. All rabbit and mouse primary antibodies were diluted 1 : 1000 (unless otherwise stated) in 5% (w/v) bovine serum albumin (BSA) dissolved in TBS-T (50 mM Tris base, 150 mM sodium chloride (NaCl), 0.1% (v/v) Tween 20). Sheep polyclonal antibodies were diluted in 5% (w/v) skim milk powder dissolved in TBS-T. Goat anti-mouse IRDye 800CW (#926-32210), goat anti-mouse IRDye 680LT (#926-68020), goat anti-rabbit IRDye 800CW (#926-32211) and donkey anti-goat IRDye 800CW (#926-32214) IgG (H + L) secondary antibodies were from LI-COR and were diluted 1 : 10 000 in 5% (w/v) milk in TBS-T.</p><!><p>Cell or tissue extracts were mixed with a quarter of a volume of 4× SDS–PAGE loading buffer [250 mM Tris–HCl, pH 6.8, 8% (w/v) SDS, 40% (v/v) glycerol, 0.02% (w/v) bromophenol blue and 5% (v/v) 2-mercaptoethanol] and heated at 95°C for 5 min. Samples ranging from 15 to 40 μg were loaded onto a NuPAGE 4–12% Bis–Tris Midi Gel (Thermo Fisher Scientific, Cat# WG1402BOX or Cat# WG1403BOX) or self-cast 10% Bis-Tris gel and electrophoresed at 130 V for 2 h with NuPAGE MOPS SDS running buffer (Thermo Fisher Scientific, Cat# NP0001-02). At the end of electrophoresis, proteins were electrophoretically transferred onto a nitrocellulose membrane (GE Healthcare, Amersham Protran Supported 0.45 µm NC) at 90 V for 90 min on ice in transfer buffer (48 mM Tris–HCl and 39 mM glycine supplemented with 20% methanol). The transferred membrane was blocked with 5% (w/v) skim milk powder dissolved in TBS-T (50 mM Tris base, 150 mM sodium chloride (NaCl), 0.1% (v/v) Tween 20) at room temperature for 1 h. Membranes were washed three times with TBS-T and were incubated in primary antibody overnight at 4°C. Prior to secondary antibody incubation, membranes were washed three times for 15 min with TBS-T. The membranes were incubated with secondary antibody for 1 h at room temperature. Thereafter, membranes were washed with TBS-T three times with a 15 min incubation for each wash, and protein bands were acquired via near-infrared fluorescent detection using the Odyssey CLx imaging system and quantified using the Image Studio software.</p><!><p>Mice selected for this study were maintained under specific pathogen-free conditions at the University of Dundee (U.K.). All animal studies were ethically reviewed and carried out in accordance with the Animals (Scientific Procedures) Act 1986 and regulations set by the University of Dundee and the U.K. Home Office. Animal studies and breeding were approved by the University of Dundee ethical committee and performed under a U.K. Home Office project license. Mice were housed at an ambient temperature (20–24°C) and humidity (45–55%) and were maintained on a 12 h light/12 h dark cycle, with free access to food (SDS RM No. 3 autoclavable) and water. For the experiments described in Figure 2B–D and Supplementary Figure S1 (Rab29 knock-out model), Figure 5A–F (transgenic Rab29 overexpression model), Figure 6B–E and Supplementary Figure S4 (Rab29 knock-out LRRK2[R1441C] knock-in model) and Figure 7B–E and Supplementary Figure S6 (Rab29 knock-out VPS35[D620N] knock-in model), 6-month-old littermate matched or matched mice of the indicated genotypes were injected subcutaneously with vehicle [40% (w/v) (2-hydroxypropyl)-β-cyclodextrin (Sigma–Aldrich #332607)] or MLi-2 dissolved in the vehicle at a 30 mg/kg final dose. Mice were killed by cervical dislocation 2 h following treatment and the collected tissues were rapidly snap frozen in liquid nitrogen. For the experiment outlined in Supplementary Figure S2 (transgenic Rab29 overexpression model), mice ranging from 3 to 4 months and of the indicated genotypes were dosed, killed and the tissues were isolated as outlined above. For the studies involving 18–24 mice which took place over multiple days, the genotypes and treatments were randomized each day to account for any temporal differences, such as light and ventilation. A general overview of the mouse models utilized in this study is outlined in Table 2.</p><!><p>Rab29 knock-out mice are made available through the Wellcome Trust Sanger Institute, distributed by Infrafrontier: EMMA mouse repository (EM: 05517), and were characterized previously [43]. LacZ-knock-in Rab29tm1a(EUCOMM)Wtsi mice were bred with Taconic Total Body Cre mice expressing Cre recombinase (Model 12524), which recognizes the loxP sites that flank the inserted promoter-driven neomycin cassette and exon 4 of Rab29, which is critical for expression. Following the deletion of exon 4, the mice were then bred and maintained on a C57Bl/6j background to remove the Cre recombinase allele, and to produce the experimental animals used in this study. The genotypes of the Rab29 knock-out mice were confirmed by PCR using genomic DNA isolated from ear biopsies and primers that amplify the entire Rab29 gene, as well as by immunoblotting.</p><!><p>The generation of LRRK2[R1441C] knock-in mice and VPS35[D620N] knock-in mice were described previously [21,26]. Rab29 knock-out heterozygous mice were crossed with LRRK2[R1441C] or VPS35[D620N] knock-in homozygous mice to produce double heterozygous mice for Rab29 knock-out and LRRK2[R1441C] or VPS35[D620N] knock-in. Double heterozygous mice were crossed to produce the following genotypes: Rab29 wildtype/LRRK2 (or VPS35) wildtype, Rab29 knock-out/LRRK2 (or VPS35) wildtype, Rab29 wildtype/LRRK2[R1441C] (or VPS35[D620N]) or Rab29 knock-out/LRRK2[R1441C] (or VPS35[D620N]) (1/16 frequency of indicated genotypes by Mendelian inheritance). Double homozygous mice of the aforementioned genotypes were then expanded as four different subsets to produce additional double homozygous mice for mouse embryonic fibroblast (MEF) generation and MLi-2 injection studies. Matched mice of the same generation were used for experimental studies.</p><!><p>The Michael J. Fox Foundation for Parkinson's Research generated the transgenic Rab29-overexpressing mouse model (C57BL/6NTac-Gt(ROSA)26Sortm1(Pgk-Rab29)Tac), which is made available through Taconic (Model 16552). The constitutive knock-in of Pgk-Rab29 in the ROSA26 locus via targeted transgenesis was undertaken by Taconic. The Rab29 sequence was synthesized according to the NCBI transcript NM_144875.2. The following elements were inserted into the ROSA26 locus (NCBI gene ID: 14910) using recombination-mediated cassette exchange (RMCE): a Pgk promoter, the Rab29 open reading frame together with a Kozak sequence (GCCACC), the human growth hormone (hGH) polyadenylation signal and an additional polyadenylation signal. The RMCE vector was transfected into the Taconic Biosciences C57Bl/6 embryonic stem (ES) cell line equipped with RMCE docking sites in the ROSA26 locus. The ES cell line pre-equipped with F3/FRT — RMCE docking sites was grown on a mitotically inactivated feeder layer comprised of MEFs in ES cell culture medium containing Leukemia inhibitory factor and Fetal Bovine Serum. The cells were co-transfected with the circular exchange vector containing the transgene and the recombinase pCAG-Flpe pA. The transfection was performed via lipofection with a commercially available kit. From day 2 onwards, the medium was replaced daily with medium containing the appropriate selection antibiotics. The recombinant clones were isolated using positive neomycin resistance selection. On day 7 after transfection, resistant ES cell colonies (ES clones) with a distinct morphology were isolated. The clones were expanded and frozen in liquid nitrogen after extensive molecular validation by Southern Blotting and/or PCR. Quality control of the ES cell line used for transfection was performed at Chrombios GmbH (Germany). Karyotype analysis was undertaken by multicolor fluorescence in situ hybridization with probes for all murine chromosomes (mFISH) to confirm that the cell line meets the quality standard for parental ES cell lines used for targeting experiments. To generate chimeras, superovulated BALB/c females were mated with BALB/c males following hormone administration. Blastocysts were isolated from the uterus at dpc 3.5. For microinjection, blastocysts were placed in a drop of DMEM with 15% FCS under mineral oil. A flat tip, piezo actuated microinjection-pipette with an internal diameter of 12–15 micrometer was used to inject 10–15 targeted C57BL/6NTac ES cells into each blastocyst. After recovery, eight injected blastocysts were transferred to each uterine horn of 2.5 days post coitum, pseudopregnant NMRI females. Chimerism was measured in chimeras (G0) by coat color contribution of ES cells to the BALB/c host (black/white). Germline transmission occurred during an IVF expansion using chimeric males and C57BL/6NTac oocyte donors. The colony is maintained by mating wildtype C57BL/6NTac females to heterozygous males and heterozygous females to wildtype C57BL/6NTac males.</p><!><p>Genotyping of mice was performed by the MRC genotyping team at the MRC-PPU, University of Dundee, by PCR using genomic DNA isolated from ear biopsies. For this purpose, Primer 1 (5′ CACACACATGGTACACAGATATACATGTAGG 3′) Primer 2 (5′ ACATCCATGACACGACTCTACTATAGAGAT 3′) and Primer 3 (5′ CTATCCCGACCGCCTTACTGC 3′) were used to distinguish between wildtype and Rab29 knock-out alleles (63°C annealing temp). The VPS35[D620N] knock-in mouse strain required Primer 1 (5′ TCATTCTGTGGTTAGTTCAGTTGAG 3′), Primer 2 (5′ CCTCTAACAACCAAGAGGAACC 3′) and Primer 3 (5′ ATTGCATCGCATTGTCTGAG 3′) to distinguish wildtype from D620N knock-in alleles (60°C annealing temp). The LRRK2[R1441C] knock-in mouse strain required Primer 1 (5′ CTGCAGGCTACTAGATGGTCAAGGT 3′) and Primer 2 (5′ CTAGATAGGACCGAGTGTCGCAGAG 3′) to identify wildtype and R1441C knock-in alleles (60°C annealing temp). To detect the constitutive KI allele in the transgenic Rab29 overexpression mouse, Primer 1 (5′ TTGGGTCCACTCAGTAGATGC 3′) and Primer 2 (5′ CATGTCTTTAATCTACCTCGATGG 3′) as well as internal PCR control Primer 1 (5′ GTGGCACGGAACTTCTAGTC 3′) and Primer 2 (5′ CTTGTCAAGTAGCAGGAAGA 3′) were used (58°C annealing temp). To detect the wildtype allele in the transgenic Rab29 overexpression model, Primer 1 (5′ CTCTTCCCTCGTGATCTGCAACTCC 3′) and Primer 2 (5′ CATGTCTTTAATCTACCTCGATGG 3′) and internal PCR control Primer 1 (5′ GAGACTCTGGCTACTCATCC 3′) and Primer 2 (5′ CCTTCAGCAAGAGCTGGGGAC 3′) were used (58°C annealing temp). All genotyping primers were used at a final concentration of 10 pmol/μl. PCR reactions were set up and run using KOD Hot Start Polymerase standard protocol. PCR bands were visualized on Qiaexcel (Qiagen) using the standard DNA screening kit cartridge.</p><!><p>Mouse tissues were collected and snap frozen in liquid nitrogen. Snap frozen tissues were weighed and quickly thawed on ice in a 10-fold volume excess of ice-cold lysis buffer containing 50 mM Tris–HCl pH 7.4, 1 mM EGTA, 10 mM 2-glycerophosphate, 50 mM sodium fluoride, 5 mM sodium pyrophosphate, 270 mM sucrose, supplemented with 1 μg/ml microcystin-LR, 1 mM sodium orthovanadate, complete EDTA-free protease inhibitor cocktail (Roche), and 1% (v/v) Triton X-100. Tissue was homogenized using a POLYTRON homogenizer (KINEMATICA), employing three rounds of 10 s homogenization with 10 s intervals on ice. Lysates were centrifuged at 20 800g for 30 min at 4°C and supernatant was collected for subsequent Bradford assay and immunoblot analysis.</p><!><p>Frozen tissue samples were ground to a fine powder in a vessel submerged in liquid nitrogen using a mallet. Powdered tissue (∼5 mg) was dissolved in lysis buffer provided by RNeasy micro kit (Qiagen), supplemented with 1% (v/v) β-mercaptoethanol. Tissue was homogenized in lysis buffer using IKA VIBRAX VXR basic orbital shaker for 5 min at 4°C at 1000 rpm and total RNA was extracted from tissue lysate following RNeasy micro kit instructions. cDNA was synthesized from total RNA extracts using Bio-Rad iScript cDNA synthesis kit (#170-8891), using a starting template of 150 ng total RNA. The Bio-Rad Sso EvaGreen Supermix (#1725201) was used to set up qPCR reactions in a 384-well plate format according to the manufacturer's instructions and 20 μl reactions were prepared in duplicate. Real-time quantitative PCR primers for mouse Rab29 were designed using NCBI Primer Blast and the sequences are as follows: 5′-AGGCCATGAGAGTCCTCGTT-3′ (forward) and 5′-GGGCTTGGCTTGGAGATTTGA-3′ (reverse). The β-actin internal control primers employed for real-time quantitative PCR analysis are described in [52]: 5′-CACTATCGGCAATGAGCGGTTCC-3′ (forward) and 5′-CAGCACTGTGTTGGCATAGAGGTC-3′ (reverse). Primers were ordered from Sigma as lyophilized and reconstituted in Milli-Q water to a stock concentration of 100 μM and further diluted to a 10 μM working stock. The PCR efficiency of the primers was validated using the relative standard curve method. The qPCR reactions were run using the Bio-Rad CFX384 Real-Time System C1000 Thermal Cycler, and raw data were collected for duplicate reactions from four biological replicates per genotype for three different tissues. The relative quantification of Rab29 and β-actin mRNA was undertaken using the comparative Ct (cycle threshold) method, which employs the formula RQ = 2(−ΔΔCt) [53].</p><!><p>pQE80L 2X 6-His LRRK2 1-552 and pET15D 6-His empty (MRC PPU Reagents and Services, DU 57719) were transformed into BL21 cells. Expression cultures were inoculated with 1% (v/v) of an overnight culture and were grown to OD600 of 0.3 at 37°C, shaking at 180 rpm. The bacterial cultures were then cooled to 18°C, induced at OD600 of 0.6–0.7 with 0.1 mM isopropyl-β-d-thiogalactoside and incubated at 18°C overnight. The following day, the cells were spun down at 4000g for 25 min at 4°C. Cell pellets were resuspended in lysis buffer containing 50 mM Tris–HCl pH 7.5, 150 mM NaCl, 5 mM MgCl2, 10% (v/v) glycerol, 0.5 mM TCEP (tris(2-carboxyethyl)phosphine), 10 mM Imidazole pH 8.0, 1 mM PMSF and 1 mM benzamidine. Cells were lysed using an Avestin Emulsiflex apparatus at 20 000 psi at 4°C. The lysate was clarified by centrifugation at 30 000g for 30 min at 4°C, and incubated with 200 μl of equilibrated nickel-NTA agarose (per 1 l culture) for 1 h rotating at 4°C. The resin was washed twice with 50 mM Tris–HCl pH 7.5, 300 mM NaCl, 5 mM MgCl2, 10% glycerol, 0.5 mM TCEP, 20 mM Imidazole (high salt buffer), a total of 15 ml per 200 μl of resin, and twice with 50 mM Tris–HCl pH 7.5, 150 mM NaCl, 5 mM MgCl2, 10% glycerol, 0.5 mM TCEP, 20 mM Imidazole (low salt buffer), a total of 20 ml per 200 μl of resin. A total of 1.5 mg of tissue lysate (prepared as described above) was diluted to 10 ml using low salt buffer to reduce Triton X-100 concentration to ∼0.03% and supplemented with GTP-γ-S at a final concentration of 100 μM. Tissue lysate was incubated with 200 μl nickel-NTA agarose with immobilized 6-His LRRK2 1-552 or 6-His for 2 h rotating at 4°C. The resin was washed three times with 5 ml low salt buffer. An equal volume of elution buffer containing 500 mM Imidazole and low salt buffer was added to the resin and the slurry was transferred to Corning Costar spin-X centrifuge tube filters (Corning #8161). The resin was incubated with elution buffer for 20 min rotating at 4°C. Protein was eluted in spin-X tubes by centrifugation at 500g for 5 min at 4°C. Protein was concentrated to 80 μl using Amicon Ultra centrifugal filters, 10 K (#UFC901024). 15% of the eluted protein was analyzed by immunoblotting.</p><!><p>Fractionation to detect LRRK2 auto-phosphorylation at Ser1292 in mouse tissues was described previously [54]. Briefly, snap frozen mouse lungs were homogenized on ice in 15% (w/v) sedimentation buffer containing 3 mM Tris–HCl pH 7.4, 250 mM sucrose, 0.5 mM EGTA, 10 mM 2-glycerophosphate, 50 mM NaF, 5 mM sodium pyrophosphate, 1 μg/ml microcystin-LR, 1 mM sodium orthovanadate and complete EDTA-free protease inhibitor cocktail (Roche). Homogenates were centrifuged at 3000g for 10 min at 4°C, and the supernatant was centrifuged again at 5000g for 10 min at 4°C to produce cleared homogenate. Two-hundred microliters of cleared homogenate was supplemented with 10X lysis buffer (200 mM Tris–HCl pH 7.4, 1.5 M NaCl, 10 mM EGTA, 25 mM sodium pyrophosphate, 10 mM 2-glycerophosphate, 10 mM sodium orthovanadate, 1 μg/ml microcystin-LR, protease inhibitor cocktail tablet and 10% Triton X-100) to a final concentration of 1X, and cleared homogenate was further supplemented with 0.1% (w/v) SDS and 0.5% (w/v) sodium deoxycholate. The cleared homogenate was incubated on ice for 1 h for complete lysis, and centrifuged at 17 000g for 20 min at 4°C. The supernatant from this centrifugation step was designated as the total fraction. The remainder of the cleared homogenate was centrifuged at 12 000g for 10 min at 4°C. The pellets were resuspended in 15% (v/v) sedimentation buffer supplemented with the 10X lysis buffer to a final concentration of 1X (as described above) to the volume of the original sample that was spun down. The resuspended pellets were termed crude mitochondrial fractions. The supernatant from the aforementioned centrifugation step was quantified using the Bradford method and 20 mg of supernatant was ultracentrifuged at 100 000g for 1 h at 4°C. The supernatant from this centrifugation step was designated the cytosol fraction. The pellets were washed twice with PBS and resuspended in 530 μl resuspension buffer (15% w/v sedimentation buffer supplemented with 10X lysis buffer). Resuspended pellets were sonicated three times for 15 s and designated as microsomal fractions. Forty micrograms of the total fractions and the equivalent volumes of the remaining fractions were analyzed by immunoblotting.</p><!><p>MEFs were cultured in Dulbecco's modified eagle medium (DMEM) supplemented with 20% (v/v) fetal calf serum, 2 mM l-glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin, non-essential amino acids and 1 mM sodium pyruvate. Primary lung fibroblasts were cultured in Dulbecco's modified eagle medium: nutrient mixture F-12 (DMEM/F-12) supplemented with 20% (v/v) fetal calf serum, 2 mM l-glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin, non-essential amino acids and 1 mM sodium pyruvate. Generation of A549 Rab29 knock-out cells was described previously [14], and A549 cells were cultured in DMEM supplemented with 10% (v/v) fetal calf serum, 2 mM l-glutamine, 100 U/ml penicillin and 100 μg/ml streptomycin. All cells were grown at 37°C and 5% CO2 in a humidified atmosphere. Cell lines utilized for this study were tested regularly for mycoplasma contamination and confirmed as negative prior to experimental analysis. Cells were lysed in ice-cold lysis buffer containing 50 mM Tris–HCl pH 7.4, 1 mM EGTA, 10 mM 2-glycerophosphate, 50 mM sodium fluoride, 5 mM sodium pyrophosphate, 270 mM sucrose, supplemented with 1 μg/ml microcystin-LR, 1 mM sodium orthovanadate, complete EDTA-free protease inhibitor cocktail (Roche) and 1% (v/v) Triton X-100. Lysates were clarified by centrifugation for 15 min at 15 000g at 4°C. Protein concentrations of cell lysates were determined using the Bradford assay. MLi-2 inhibitor was dissolved in sterile DMSO, and treatment of cells with MLi-2 was for 90 min at a final concentration of 100 nM, unless otherwise indicated. Nigericin and monensin were dissolved in absolute ethanol and chloroquine diphosphate salt was dissolved in sterile water. Cell treatments were added at a dilution of 0.1% to cells. LLOMe was prepared in DMSO at a working concentration of 100 mM and cells were treated with a 1% dilution of stimulant. An equivalent volume of diluent was added to vehicle control cells where appropriate.</p><!><p>Wildtype, heterozygous and homozygous Rab29 knock-out or transgenic Rab29 overexpressing MEFs were isolated from littermate-matched mouse embryos at day E12.5, as described in a previous study [55]. The resulting embryo genotypes were produced following crosses between Rab29 knock-out/wildtype (heterozygous) mice or between transgenic Rab29/wildtype (heterozygous) mice. Rab29 knock-out and LRRK2[R1441C] mice were bred to create doubly modified Rab29 knock-out/LRRK2[R1441C], and Rab29 knock-out and VPS35[D620N] mice were bred to create doubly modified Rab29 knock-out/VPS35[D620N] mice. To generate MEFs for these mouse models, the following crosses between homozygous mice of the following genotypes were set up: Rab29 wildtype/LRRK2 or VPS35 wildtype, Rab29 knock-out/LRRK2 or VPS35 wildtype, Rab29 wildtype/LRRK2[R1441C] or VPS35[D620N], and Rab29 knock-out/LRRK2[R1441C] or VPS35[D620N]. The resulting embryos from each litter were of the same genotype and MEFs were isolated at day E12.5. Genotypes of all aforementioned mouse models were verified via allelic sequencing and immunoblot. Primary MEFs between passage 2 and 8 were used for all experimental analyses, except Figure 8 where MEFs ranged from passage 8 to 12.</p><!><p>For siRNA knockdown of proteins of interest, ON-TARGETplus Mouse LRRK2 siRNA-SMARTpool (#L-049666-00-0005), ON-TARGETplus Mouse Rab32 siRNA-SMARTpool (#L-063539-01-0005) and ON-TARGETplus non-targeting pool (#D-001810-10-05) were purchased from Dharmacon. MEF cells were seeded in a six-well format at 400 000 cells/well for transfection the following day. Cells were transfected using Lipofectamine RNAiMAX according to the manufacturer's protocol. Briefly, 50 pmol siRNA was diluted in 150 μl opti-MEM and combined with 10 μl Lipofectamine RNAiMAX in 150 μl opti-MEM per well. The two mixtures were incubated together at room temperature for 5 min and 250 µl was added dropwise to cells, which were harvested 72 h after transfection.</p><!><p>Primary MEFs of the indicated genotypes in Figure 9 were seeded in a six-well format for treatment the following day. At 50–60% confluence, MEFs were treated with vehicle (DMSO) or 100 nM MLi-2 for 48 h. To remove the MLi-2 inhibitor, cells were washed three times with warm, complete media; 15–20 min following the initial washes, cells were washed an additional two times with complete media. Cells were harvested with complete lysis buffer 30–360 min following the initial washes.</p><!><p>Littermate-matched wildtype and transgenic Rab29 MEFs, and Rab29 knock-out MEFs were plated in a six-well format on VWR 22 × 22 mm cover slips (cat# 631-0125) that were soaked in absolute ethanol for 1 h prior to seeding 400 000 cells per well for each genotype. The following day, cells were fixed on coverslips with 4% paraformaldehyde in phosphate-buffered saline (PBS), pH 7.4, for 10 min. Cells were washed three times with 0.2% BSA diluted in PBS and permeabilized with 0.1% NP-40 diluted in PBS for 10 min. Cells were washed three times with 0.2% BSA and blocked with 1% BSA diluted in PBS for 1 h. Cells were washed three times with 0.2% BSA and incubated with primary antibodies against ACBD3 and Rab29 that detects mouse (MJF-30, clone 124), diluted to final concentrations of 10 μg/ml in 0.2% BSA, for 1 h. Cells were washed with 0.2% BSA three times for 5 min each and incubated with 1 μg/ml DAPI (Bisbenzimide Hoechst 33342 trihydrochloride, Sigma B2261) and secondary antibodies diluted 1 : 500 in 0.2% BSA for 1 h (Invitrogen donkey anti-rabbit IgG (H + L) Alexa Fluor 594 (cat# A-21207) and donkey anti-mouse IgG (H + L) Alexa Fluor 488 (cat# A21202)). Cells were washed three times with 0.2% BSA for 5 min each. The slides were rinsed in sterile water before mounting on VWR super-premium microscope slides (cat# 631-0117) using Vectashield antifade mounting media (H-1000). All incubation steps were carried out at room temperature. Images were acquired using a Carl Zeiss LSM710 laser scanning confocal microscope (Carl Zeiss) using the 63X Plan-Apochromat objective (NA 1.4) and a pinhole chosen to provide a uniform optical section thickness in all fluorescence channels. The images were processed as a batch using ImageJ and brightness and contrast adjustments were kept constant for the same fluorescent channel.</p><!><p>Primary lung fibroblasts were derived from adult mice as previously described [56]. Briefly, lung tissue was harvested and transferred to a sterile tissue culture dish, washed twice with PBS and minced with a scalpel. Tissue fragments were transferred to a 75 cm2 cell culture flask with suitable aeration and immersed in 10 ml DMEM/F12 supplemented with 2 mM l-glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin and 0.14 Wunsch units/ml collagenase (Liberase, Sigma–Aldrich 05401119001). The tissue fragments were digested with collagenase in a shaking incubator at 37°C and 5% CO2 for 1 h. Twenty milliliters of DMEM/F12 supplemented with 20% (v/v) fetal calf serum, 2 mM l-glutamine, 100 U/ml penicillin and 100 μg/ml streptomycin was added, and the cell/tissue suspension was centrifuged at room temperature at 525g for 5 min. The pellet was gently resuspended in fresh complete media and plated in a collagen-coated cell culture flask. To coat the cell culture flasks, Gibco Collagen I, rat tail (A10483-01) was diluted to a final concentration of 50 μg/ml in sterile-filtered 20 mM acetic acid. Tissue culture flasks were coated with diluted collagen according to the manufacturer's. Fibroblasts required ∼5 days to emerge from tissue fragments and regular media changes. Approximately 1.5 weeks following isolation, lung fibroblasts were passaged once, then seeded in six-well plates for experimental analysis.</p><!><p>Graphs were made using Graphpad Prism 7 and 8 software. Error bars indicate SD. Two-tailed unpaired t-test or one-way ANOVA with Tukey's or Dunnett's multiple comparisons test were used to determine statistical significance. P-values < 0.05 were considered statistically significant. Based on previous publications that monitor Rab10 Thr73 phosphorylation and LRRK2 Ser935 phosphorylation in various genotypes, following vehicle or MLi-2 administration, [9,21,49,51,54], we reasoned that N = 4 per genotype for the studies outlined in Figures S6B–E and S7B–E, gives >80% power to reject the null hypothesis at α = 0.05. For the study outlined in Figures 6B–E, post hoc power calculations derived from the standard deviations of wildtype and pathogenic mutant LRRK2[R1441C], and the difference between means of the four biological replicates for each genotype revealed that >99% power was achieved to reject the null hypothesis at α = 0.05 for Rab12 phosphorylation in Figure 6B–D and >90% power in Figure 6E. Similar analysis for Rab10 phosphorylation revealed that >10% power in Figure 6B, >70% power in Figure 6C, >90% power in Figure 6D and >99% power in Figure 6E was achieved in order to reject the null hypothesis at α = 0.05. For the study outlined in Figure 7B–E, post hoc power calculations derived from the standard deviations of wildtype and pathogenic mutant VPS35[D620N], and the difference between means of the four biological replicates for each genotype revealed that >99% power was achieved to reject the null hypothesis at α = 0.05 for Rab12 phosphorylation in Figure 7B–E. A similar analysis for Rab10 phosphorylation revealed that >40% power in Figure 7B and >99% power in Figure 7C–E was achieved in order to reject the null hypothesis at α = 0.05.</p><!><p>We raised two novel Rab29 monoclonal antibodies termed MJF-30-Clone-124 and MJF-30-Clone-104 that detect endogenous Rab29 in wildtype but not in Rab29 knock-out human A549 cells (Figure 1A). MJF-30-Clone-124 detected both mouse and human Rab29 whilst MJF-30-Clone-104 was human specific (Figure 1A). Immunoblotting of six mouse tissues (brain, spleen, lung, kidney, large intestine and spinal cord) and three primary mouse cell lines (MEFs, lung fibroblasts and bone marrow-derived macrophages) that all express endogenous LRRK2, revealed that Rab29 is expressed ubiquitously but levels vary significantly between tissues and cells (Figure 1B). The highest expression is observed in macrophages and spleen, whilst low expression is seen in brain and spinal cord, and intermediate expression observed in other tissues and cells. LRRK2 was proteolyzed into at least two bands in many extracts but the expression of the two major upper bands was also lower in brain and spinal cord, and significantly higher in other tissues and cells. This is consistent with substantial evidence that LRRK2 and Rab29 are co-expressed in the same cells (MEFs, A549 cells, macrophages, neutrophils) [14,15,43,57,58] (http://www.immprot.org/) as well as tissues (https://www.proteinatlas.org/).</p><!><p>(A) Thirty micrograms of the indicated cell and tissue extracts were subjected to quantitative immunoblot analysis with the indicated antibodies, diluted to 1 µg/ml. Membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. (B) Various cell and tissue extracts were analyzed for Rab29 and LRRK2 expression (upper panels). Total protein levels were visualized using the Bio-Rad Oriole Fluorescent Gel Stain and exposed using the Bio-Rad Chemidoc MP Imaging System (lower panel). Total protein levels were quantified using Bio-Rad Image Lab software. Total Rab29 or total LRRK2 was quantified using the Image Studio software. Quantified data are presented as ratios of Rab29 or LRRK2 expression divided by total protein levels, and values were normalized to the average of the respective protein expression observed in MEFs. Quantifications are representative of three independent experiments and shown as mean ± SD.</p><!><p>To investigate the role of endogenous Rab29 in regulating LRRK2 pathway activity, we obtained Rab29 knock-out mice made available through the Wellcome Trust Sanger Institute, Infrafrontier EMMA mouse repository and the Michael J. Fox Foundation (see Material and methods). These mice have also been deployed in other studies mentioned above [43,44,46]. As a readout for LRRK2 pathway activity, we measured phosphorylation of Rab10 at Thr73 [7], employing a well-characterized phospho-specific antibody [51]. Consistent with previous reports [44], the Rab29 knock-out mice were viable and displayed no overt phenotypes. We analyzed wildtype, heterozygous and Rab29 knock-out MEFs (Figure 2A) as well as wildtype and Rab29 knock-out lung (Figure 2B), spleen (Figure 2C), kidney (Figure 2D) and various brain sections (Supplementary Figure S1) derived from littermate 6-month-old mice treated ± MLi-2 LRRK2 inhibitor (30 mg/kg, 2 h). Results from numerous independent experiments demonstrated that there was no significant difference in levels of LRRK2-phosphorylated Rab10, quantitated as a ratio with total Rab10, in wildtype or Rab29 knock-out MEFs, lung, spleen or kidney. In MEFs, we also analyzed LRRK2-mediated phosphorylation of Rab12 at Ser105 using a previously characterized phospho-specific antibody [21], which was also shown to be unaffected by Rab29 knock-out (Figure 2A). Rab29 knock-out also had no impact on LRRK2 expression or phosphorylation of LRRK2 at Ser935 (Figure 2, Supplementary Figure S1). As expected, MLi-2 treatment markedly reduced Rab10 phosphorylation levels in both wildtype and Rab29 knock-out mice and was accompanied by a decrease in LRRK2 Ser935 phosphorylation. We found that although MLi-2 administration reduced Ser935 phosphorylation in brain, the low basal levels of pRab10 observed were not further decreased (Supplementary Figure S1), consistent with previous findings [51,59]."</p><!><p>(A) Two independent littermate-matched wildtype (WT), Rab29 knock-out heterozygous (+/−), or Rab29 knock-out homozygous (−/−) MEFs were treated with vehicle (DMSO) or 100 nM LRRK2 inhibitor MLi-2 for 90 min prior to harvest. Twenty micrograms of whole-cell extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. Technical replicates represent cell extract obtained from a different dish of cells. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the mean ± SD of phospho-Rab10/total Rab10 and phospho-Rab12/total Rab12 ratios, which were quantified using the Image Studio software. Values were normalized to the average of Litter 1 wildtype MEFs treated with DMSO. Similar results were obtained in three independent experiments. (B–D) 6-month-old, littermate-matched wildtype (WT) and Rab29 knock-out (−/−) mice were administered with vehicle (40% (w/v) (2-hydroxypropyl)-β-cyclodextrin) or 30 mg/kg MLi-2 dissolved in vehicle by subcutaneous injection 2 h prior to tissue collection. Forty micrograms of tissue extracts were analyzed by quantitative immunoblot as described in (A). Each lane represents tissue extract derived from a different mouse. Quantified data are presented as mean ± SD and values were normalized to the average of the wildtype, vehicle-treated mice. Data were analyzed using two-tailed unpaired t-test and there was no statistical significance between WT and Rab29 knock-out mice. The resulting P-values from the unpaired t-tests are (B) lungs P = 0.6585 (C) spleen P = 0.9318 (D) kidneys P = 0.4793.</p><!><p>As the human genetic data point toward variants within the PARK16 locus enhancing expression of Rab29 [15,38,39], we generated a transgenic mouse strain in which Rab29 is constitutively overexpressed in all tissues. The mouse Rab29 cDNA with no epitope tags was knocked-into the ROSA26 locus, which is frequently employed to constitutively express proteins in mouse tissues [60] (Figure 3A). The heterozygous and homozygous Rab29 transgenic mice displayed no overt phenotype at 6 months of age, which were the oldest animals studied. Rab29 protein levels in brain, spleen, lung, kidney, large intestine and spinal cord derived from wildtype and homozygous transgenic Rab29 mice were analyzed at 3.5 and 6 months of age. This revealed that the highest overexpression of Rab29 was observed in brain (7 to 9-fold), kidney (5 to 7-fold) and large intestine (23 to 25-fold), with lower levels of overexpression observed in lung (<1.5-fold), spleen (<2-fold) and spinal cord (4-fold) (Figure 3B). The levels of other Rab proteins measured by immunoblotting (Rab8A, Rab10, Rab12, Rab32 and Rab35) were not impacted by overexpression of Rab29 (Figure 3B). There was no marked difference in the relative levels of Rab29 expression between 3.5 and 6-month-old mice (Figure 3B). We also analyzed Rab29 mRNA levels in wildtype, heterozygous and homozygous brain, lung and kidney from 3.5-month-old mice (Figure 3C). Consistent with protein levels, brain displayed the highest increase in Rab29 mRNA levels, namely 2-fold in heterozygous and ∼4-fold in homozygous Rab29 transgenic mice (Figure 3C). In transgenic homozygous kidney and lung, Rab29 mRNA levels were increased ∼3 and 2-fold, respectively (Figure 3C).</p><!><p>(A) Schematic overview of design and the targeting strategy utilized to create the Rab29 transgenic mouse model. The illustration depicts the transgene containing a neo cassette, a Pgk promoter, the murine Rab29 open reading frame together with a Kozak sequence (GCCACC), the human growth hormone polyadenylation signal and an additional polyadenylation signal. These elements were inserted into the ROSA26 locus via recombinase-mediated cassette exchange. (B) The indicated tissues were collected from 3.5-month-old and 6-month-old wildtype (WT) and homozygous, transgenic Rab29 overexpressing (Tg Rab29) mice. Thirty micrograms of tissue extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as mean ± SD of total Rab29/GAPDH ratios, calculated using the Image Studio software. Values were normalized to the average of the 3.5-month-old wildtype mice. Each lane represents a tissue sample from a different animal. (C) The indicated tissue extracts from 3.5-month-old wildtype (WT), heterozygous (Tg Rab29 Het), and homozygous (Tg Rab29 Hom) transgenic Rab29 overexpressing mice were processed for total RNA extraction, cDNA synthesis, and subsequent quantitative real-time RT-PCR analysis. Rab29 mRNA levels were normalized to β-actin mRNA levels and further normalized to the wildtype of the appropriate tissue. Quantified data are presented as mean ± SD of four biological replicates per genotype.</p><!><p>To demonstrate that the overexpressed Rab29 was functional, we undertook immunofluorescence studies of Rab29 knock-out and littermate-matched wildtype and transgenic MEFs (Figure 4A). This revealed that the overexpressed transgenic Rab29 was correctly localized to the Golgi, similar to wildtype Rab29, and this was confirmed by co-staining with the ACBD3 Golgi marker. Consistent with our localization being specific, no Rab29 signal was observed in the Rab29 knock-out cells and enhanced levels of Rab29 were clearly observed in the transgenic cells (Figure 4A). Rab29 localization to the Golgi complex indicates that the protein is properly folded and active [30]. Rab29 binds to the N-terminus of LRRK2 and recent work suggests that the binding site is located within the first 552 residues of LRRK2 [41]. To obtain further evidence that the Rab29 expressed in the transgenic mouse was functional, we undertook affinity purification studies using a fragment of LRRK2 encompassing residues 1–552 in intestinal extracts that express the highest levels of Rab29. These studies confirmed that the transgenic Rab29 expressed in these extracts interacts with the LRRK2 N-terminal fragment, providing further evidence that the transgenic Rab29 is functionally competent (Figure 4B). Binding of endogenously expressed wildtype Rab29 to the LRRK2 N-terminal fragment was also observed in wildtype intestine extracts (Figure 4B).</p><!><p>(A) Littermate-matched wildtype and transgenic Rab29 overexpressing MEFs, and Rab29 knock-out MEFs were seeded on coverslips. The following day, cells were fixed with 4% (v/v) paraformaldehyde and Rab29 was visualized with rabbit Rab29 antibody and anti-rabbit Alexa Fluor 594 secondary. Golgi were stained with mouse anti-ACBD3 and anti-mouse Alexa Fluor 488 secondary, and nuclei using DAPI. Immunoblotting of MEFs of the indicated genotypes was undertaken in parallel. (B) Recombinant 6-His LRRK2 1-552 immobilized on nickel-NTA resin or immobilized 6-His, was incubated with intestinal tissue extracts supplemented with excess GTP-γ-S from two different wildtype or transgenic Rab29 overexpressing mice. Eluted protein was analyzed by immunoblotting with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Similar results were obtained in two independent experiments.</p><!><p>We examined LRRK2-mediated Rab10 and Rab12 phosphorylation in wildtype and homozygous transgenic Rab29 mouse brain (Figure 5A), large intestine (Figure 5B), kidney (Figure 5C), spinal cord (Figure 5D), spleen (Figure 5E) and lung (Figure 5F) from 6-month-old mice treated for 2 h ± MLi-2 LRRK2 inhibitor (30 mg/kg). As expected, phosphorylation of Rab10 and Rab12 were robustly detected in all tissues and were significantly lowered by MLi-2 treatment (Figure 5). Notably, in the brain extracts, Rab12 phosphorylation was more sensitive to MLi-2 administration than Rab10 phosphorylation (Figure 5A). No significant increases in LRRK2-mediated phosphorylation of Rab10 or Rab12 were observed in any of the tissues of the Rab29 transgenic mice. Levels of LRRK2 or phosphorylation at Ser935 were also not impacted by Rab29 overexpression. Similar results were also observed in 3.5-month-old animals (Supplementary Figure S2). We also studied MEFs and lung fibroblasts derived from wildtype and homozygous Rab29 transgenic mice in which Rab29 levels were increased ∼4-fold in both cell types, and here again observed no significant impact on LRRK2-mediated Rab10 or Rab12 phosphorylation (Supplementary Figure S3). As expected, MLi-2 reduced Rab10 and Rab12 phosphorylation (Supplementary Figure S3).</p><!><p>(A–F) 6-month-old littermate-matched wildtype (WT) and homozygous, transgenic Rab29 overexpressing (Tg Rab29 Hom) mice were administered with vehicle (40% (w/v) (2-hydroxypropyl)-β-cyclodextrin) or 30 mg/kg MLi-2 dissolved in the vehicle by subcutaneous injection 2 h prior to tissue collection. Forty micrograms of tissue extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10 and phospho-Rab12/total Rab12, calculated using the Image Studio software. Values were normalized to the average of the wildtype, vehicle-treated mice. Each lane represents a tissue sample from a different animal. Quantifications are presented as mean ± SD and data were analyzed using two-tailed unpaired t-test. There was no statistical significance in Rab10 phosphorylation between wildtype and homozygous, transgenic Rab29 overexpressing mice. The resulting P-values from the aforementioned statistical analyses of Rab10 phosphorylation between genotypes are as follows: (A) brain P = 0.0625 (B) large intestine P = 0.8026 (C) kidneys P = 0.7243 (D) spinal cord P = 0.3120 (E) spleen P = 0.7257 (F) lungs P = 0.1676. The resulting P-values from the statistical analyses of Rab12 phosphorylation between genotypes are: (A) brain P = 0.8545 (B) large intestine P = 0.1831 (C) kidneys *P = 0.0316 (D) spinal cord P = 0.3361.</p><!><p>To study whether endogenous Rab29 was necessary for the previously reported elevated Rab10 phosphorylation observed in LRRK2[R1441C] knock-in MEFs and mouse tissues [26,51], we generated LRRK2[R1441C] knock-in MEFs as well as 6-month-old LRRK2[R1441C] ± Rab29 knock-out mice. As a control, we also generated matched LRRK2 wildtype ± Rab29 knock-out MEFs for comparison. In MEFs, as reported previously [51], the LRRK2[R1441C] knock-in mutation enhanced Rab10 phosphorylation around 3-fold compared with wildtype (Figure 6A). Knock-out of Rab29 had no impact on Rab10 phosphorylation (Figure 6A). As reported previously [61], the R1441C mutation reduced Ser935 phosphorylation, which was also not impacted by Rab29 knock-out (Figure 6A). In mouse brain (Figure 6B), lung (Figure 6C), kidney (Figure 6D), spleen (Figure 6E), large intestine (Supplementary Figure S4A) and spinal cord (Supplementary Figure S4B), we also observed that knock-out of Rab29 in LRRK2[R1441C] knock-in mice had no significant impact on Rab10 phosphorylation. The LRRK2[R1441C] mutation enhanced Rab10 phosphorylation between 1.5 and 2-fold in the lung (Figure 6B), kidney (Figure 6C), spleen (Figure 6D) and large intestine (Supplementary Figure S4A). No significant increase in Rab10 phosphorylation was observed in the brain (Figure 6B) and spinal cord (Supplementary Figure S4B) of LRRK2[R1441C] knock-in mice. However, moderate sensitivity to MLi-2 was observed in the LRRK2[R1441C] knock-in mice, which was less apparent in wildtype animals (Figure 6B). Interestingly, pRab12 in the brain samples was more clearly regulated by LRRK2[R1441C] compared with Rab10 (Figure 6B). MLi-2 markedly decreased pRab12 levels 2.6-fold in the LRRK2[R1441C] and more modestly in wildtype brain samples, around 1.3-fold (Figure 6B). We observed ∼2-fold increase in pRab12 levels in LRRK2[R1441C] brain samples compared with wildtype (Figure 6B). In contrast, phosphorylation of Rab10 was not significantly impacted by the LRRK2[R1441C] mutation or by MLi-2 in the same extracts (Figure 6B). Similar results were also observed in the lung (Figure 6C), kidney (Figure 6D) and spleen (Figure 6E). Moreover, pRab10 or pRab12 levels were not significantly impacted by knock-out of Rab29 in these tissues.</p><!><p>(A) The indicated matched primary MEFs were treated with vehicle (DMSO) or 100 nM LRRK2 inhibitor MLi-2 for 90 min prior to harvest. Twenty micrograms of whole-cell extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. Technical replicates represent cell extract obtained from a different dish of cells. Cell extract derived from a wildtype MEF cell line (WT*) was added to each gel in order to accurately compare the Rab10 pThr73/Rab10 total ratios between genotypes. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10, calculated using the Image Studio software. Values were normalized to the average of wildtype MEFs treated with DMSO. Similar results were obtained in two separate experiments. Quantifications are presented as mean ± SD. Data were analyzed by one-way ANOVA with Tukey's multiple comparisons test and there was a statistically significant difference between wildtype and LRRK2[R1441C] knock-in MEFs (****P < 0.0001) but not between wildtype and Rab29 knock-out MEFs (P = 0.8351) or between LRRK2[R1441C] knock-in and Rab29 knock-out LRRK2[R1441C] knock-in MEFs (P = 0.9452). (B–D) The indicated 6-month-old matched mice were administered with vehicle (40% (w/v) (2-hydroxypropyl)-β-cyclodextrin) or 30 mg/kg MLi-2 dissolved in vehicle by subcutaneous injection 2 h prior to tissue collection. Forty micrograms of tissue extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10 and phospho-Rab12/total Rab12, which were calculated using the Image Studio software. Quantifications are presented as mean ± SD, normalized to vehicle treated, wildtype animals. Each lane represents a tissue sample from a different animal. Data were analyzed by one-way ANOVA with Tukey's multiple comparisons test and there was a statistically significant difference in Rab10 phosphorylation between wildtype and LRRK2[R1441C] spleen samples (**P = 0.0093 (E)). All other phospho-Rab10 comparisons were not statistically significant. Wildtype vs LRRK2[R1441C]: P = 0.7169 (B), P = 0.2792 (C), P = 0.1555 (D). Wildtype vs Rab29 knock-out: P = 0.2594 (B), P = 0.8942 (C), P = 0.9372 (D), P = 0.3964 (E). LRRK2[R1441C] vs Rab29 knock-out LRRK2[R1441C]: P = 0.6629 (B), P = 0.9955 (C), P = 0.9962 (D), P = 0.4184 (E). There was a statistically significant difference in Rab12 phosphorylation between wildtype and LRRK2[R1441C] tissue samples: brain ****P < 0.0001 (B), lungs *P = 0.0438 (C), kidneys **P = 0.0041 (D) and spleen *P = 0.0390 (E). All other phospho-Rab12 comparisons were not statistically significant. Wildtype vs Rab29 knock-out: P = 0.3057 (B), P = 0.8915 (C), P = 0.9595 (D), P = 0.2078 (E). LRRK2[R1441C] vs Rab29 knock-out LRRK2[R1441C]: P = 0.7791 (B), P = 0.9747 (C), 0.6681 (D), P = 0.4093 (E).</p><!><p>We also immunoblotted for the pRab specific phosphatase PPM1H [33], and found that this was most highly expressed in the brain tissue, but found that its levels were not impacted by loss of Rab29 in multiple tissues (Figure 6B–E). In addition, we immunoblotted kidney tissue for the M6PR that had previously been reported to be more highly expressed in Rab29 knock-out mice [46]. We confirm this finding and found that M6PR was expressed at ∼2.5 fold higher levels in the Rab29 knock-out kidney, but the expression was not significantly affected by the LRRK2[R1441C] mutation or MLi-2 administration (Figure 6D). M6PR is often overexpressed when its trafficking is compromised.</p><p>We also attempted to measure endogenous phosphorylation of LRRK2 at Ser1292, an autophosphorylation site, using a commercially available antibody [10,54]. This site is challenging to detect, as the stoichiometry of phosphorylation at this site is believed to be low. In addition to attempting to measure endogenous LRRK2 Ser1292 phosphorylation in total extracts, we also purified microsomal enriched fractions from lungs (that express the highest levels of LRRK2), a method that was reported to facilitate detection of endogenous Ser1292 [54]. We were unable to robustly detect and quantify LRRK2 Ser1292 phosphorylation in either the total or microsome enriched fractions under conditions in which pRab10 levels were strongly detected (Supplementary Figure S5).</p><!><p>To investigate whether endogenous Rab29 was necessary for the elevated Rab10 phosphorylation observed in VPS35[D620N] MEFs and mouse tissues [21], we generated VPS35[D620N] knock-in MEFs and 6-month-old VPS35[D620N] ± Rab29 knock-out mice. As a control, we also generated matched VPS35 wildtype ± Rab29 knock-out animals. As reported previously [21], VPS35[D620N] knock-in mutation enhanced Rab10 and Rab12 phosphorylation to a greater extent than is observed with the LRRK2[R1441C] pathogenic mutation (compare Figure 6 with Figure 7). The knock-out of Rab29 had no significant impact on the elevated Rab10 phosphorylation in the VPS35[D620N] knock-in MEFs (Figure 7A) or in mouse brain (Figure 7B), lung (Figure 7C), kidney (Figure 7D), spleen (Figure 7E), large intestine (Supplementary Figure S6A) and spinal cord (Supplementary Figure S6B). In brain extracts derived from VPS35[D620N] mice, a moderate 1.5-fold increase in Rab10 phosphorylation was observed, which decreased with MLi-2 administration, but was also not significantly impacted by Rab29 knock-out (Figure 7B). In contrast, the VPS35[D620N] mutation increased Rab12 phosphorylation ∼3-fold in brain extracts, which was suppressed by MLi-2 administration (Figure 7B). The VPS35[D620N] mutation also enhanced Rab10 and Rab12 phosphorylation in the lung (Figure 7C), kidney (Figure 7D) and spleen (Figure 7E). Here again, knock-out of Rab29 had no impact on Rab10 or Rab12 phosphorylation in any tissue studied. Consistent with previous results [21], the phosphorylation of Ser935 was not impacted by the VPS35[D620N] mutation. Knock-out of Rab29 had no impact on Ser935 phosphorylation in these MEFs and mouse tissues (Figure 7). We also found that M6PR was expressed at 2.5-fold higher levels in the Rab29 knock-out kidney and are increased ∼1.7-fold in the VPS35[D620N] mice (Figure 7D).</p><!><p>(A) The indicated matched MEFs were treated with vehicle (DMSO) or 100 nM LRRK2 inhibitor MLi-2 for 90 min prior to harvest. Fifteen micrograms of whole-cell extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. Technical replicates represent cell extract obtained from a different dish of cells. Cell extract derived from a wildtype MEF cell line (WT*) was added to each gel in order to accurately compare the Rab10 pThr73/Rab10 total ratios between genotypes. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10 and phospho-Rab12/total Rab12, calculated using the Image Studio software. Values were normalized to the average of wildtype MEFs treated with DMSO. Similar results were obtained in two separate experiments. Quantifications are presented as mean ± SD. Data were analyzed by one-way ANOVA with Tukey's multiple comparisons test and there was a statistically significant difference between wildtype and VPS35[D620N] knock-in MEFs (****P < 0.0001) but not between wildtype and Rab29 knock-out MEFs (P = 0.9792) or between VPS35[D620N] knock-in and Rab29 knock-out VPS35[D620N] knock-in MEFs (P = 0.6952). (B–D) The indicated 6-month-old matched mice were administered with vehicle (40% (w/v) (2-hydroxypropyl)-β-cyclodextrin) or 30 mg/kg MLi-2 dissolved in vehicle by subcutaneous injection 2 h prior to tissue collection. Forty micrograms of tissue extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10 and phospho-Rab12/total Rab12, calculated using the Image Studio software. Quantifications are presented as mean ± SD, normalized to vehicle treated, wildtype animals. Each lane represents a tissue sample from a different animal. Data were analyzed by one-way ANOVA with Tukey's multiple comparisons test and there was a statistically significant difference in Rab10 phosphorylation between wildtype and VPS35[D620N] lungs **P = 0.0094 (C), kidneys ****P < 0.0001 (D), spleen ***P = 0.0001 (E), but not brain (P = 0.0738 (B)). All other phospho-Rab10 comparisons were not statistically significant. Wildtype vs Rab29 knock-out: P = 0.6120 (B), P = 0.9270 (C), P = 0.7648 (D), P = 0.1233 (E). VPS35[D620N] vs Rab29 knock-out VPS35[D620N]: P = 0.5654 (B), P = 0.1329 (C), P = 0.5075 (D). There was a statistically significant difference in Rab12 phosphorylation between wildtype and VPS35[D620N] tissue samples: brain **** P < 0.0001 (B), lungs *** P = 0.0002 (C), kidneys **** P < 0.0001 (D) and spleen **** P < 0.0001 (E). There was a statistically significant difference in Rab12 phosphorylation between VPS35[D620N] and Rab29 knock-out VPS35[D620N] brain samples, *P = 0.0346. All other phospho-Rab12 comparisons were not statistically significant. Wildtype vs Rab29 knock-out: P = 0.5995 (B), P = 0.9988 (C), P = 0.9400 (D), P = 0.8677 (E). VPS35[D620N] vs Rab29 knock-out VPS35[D620N]: P = 0.6015 (B), P = 0.8935 (C), P = 0.7533 (D), P = 0.1332 (E).</p><!><p>We next investigated whether we could identify agonists that stimulate LRRK2 pathway activity. We profiled a panel of agonists and stressors, which led to the finding that structurally related antibiotics nigericin (2 μM) and monensin (10 μM) markedly enhanced phosphorylation of Rab10 and Rab12 in wildtype MEFs (Figure 8A,B). This was blocked by treatment with the inhibitor MLi-2, indicating that nigericin and monensin stimulated Rab10 and Rab12 phosphorylation via LRRK2. Nigericin is derived from Streptomyces hygroscopicus [62], and monensin from Streptomyces cinnamonensis [63]. These agents function as monovalent cation ionophores inducing pleiotropic effects on vesicle trafficking responses [63]. We found that treatment of MEFs with 2 μM nigericin, over a 2–8 h time course, enhanced Rab10 phosphorylation 3.5 to ∼6-fold and Rab12 phosphorylation ∼6 to 9-fold (Figure 8A). 10 µM monensin over this period enhanced Rab10 phosphorylation up to ∼2.3-fold and Rab12 phosphorylation up to ∼3.5-fold in MEFs (Figure 8B). The knock-out of Rab29 had no significant impact on the stimulation of Rab10 and Rab12 phosphorylation observed with nigericin or monensin (Figure 8A,B). We also found that nigericin and monensin significantly stimulated Rab10 phosphorylation in A549 cells in a manner that was also unaffected by CRISPR knock-out of Rab29 (Supplementary Figure S7).</p><!><p>(A–D) Littermate-matched wildtype and Rab29 knock-out MEFs were treated with vehicle or (A) 2 μM nigericin, (B) 10 μM monensin, (C) 50 μM chloroquine, or (D) 1 mM LLOMe for the indicated periods of time. Cells were treated with DMSO or 100 nM LRRK2 inhibitor MLi-2 for 2 h prior to harvest. 15–20 μg of cell extract was subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10 and phospho-Rab12/total Rab12, which were calculated using the Image Studio software. Values were normalized to the average of the vehicle-treated cells for each respective genotype. Similar results were obtained in a second independent trial for each stimulus, and data for this including a 100 μM chloroquine experiment is shown in Supplementary Figure S8.</p><!><p>Recent work has reported that lysosomotropic agents including chloroquine [64] and the peptide LLOMe (l-leucyl-l-leucine methyl ester) [65] enhance Rab10 phosphorylation [57,66–68]. We confirmed that both 50 µM chloroquine and 1 mM LLOMe (concentrations used in previous studies) enhance Rab10 as well as Rab12 phosphorylation in manner that was suppressed by MLi-2 (Figure 8C,D). The enhancement of Rab10 and Rab12 phosphorylation by 50 μM chloroquine over an 8-h time period was up to ∼3.5 and 4-fold, respectively (Figure 8C). Increasing the chloroquine concentration to 100 μM resulted in a 4 to 4.5-fold increase in pRab10 and pRab12 over 8 h (Supplementary Figure S8D). The increase in Rab10 and Rab12 phosphorylation upon 1 mM LLOMe stimulation approached ∼2-fold in MEFs (Figure 8D). The knock-out of Rab29 had no significant effect on Rab10 or Rab12 phosphorylation induced by chloroquine or LLOMe (Figure 8C,D). For the 1 mM LLOMe stimulation, we limited our analysis to 2 h, because MEF cells started to detach from tissue culture plates by 4 h. Similar results for Nigericin, Monensin, Chloroquine and LLOMe were obtained in an independent experiment with each condition undertaken in duplicate (Supplementary Figure S8). Statistical analysis of data from both sets of experiments (n = 4 datapoints for each condition-MLi-2) are included in Supplementary Figure S8.</p><!><p>We next investigated whether endogenous Rab29 affected the rate at which Rab10 was re-phosphorylated following washout of MLi-2 in MEFs. We treated wildtype (Figure 9A), LRRK2[R1441C] (Figure 9B) or VPS35[D620N] (Figure 9C) ± Rab29 knock-out MEFs with MLi-2 to reduce pRab10 to undetectable levels (100 nM, 48 h). MLi-2 was removed by sequential changes of medium over a 15 min period, and phosphorylation of Rab10 quantified at time points up to 6 h. Under these conditions, we observed that the rate of recovery in the three cell lines was not affected by Rab29 knock-out. For the wildtype and VPS35[D620N] MEFs we observed 60–70% recovery of Rab10 phosphorylation within 6 h. However, in the LRRK2[R1441C] MEFs, recovery of pRab10 was only ∼30% after 6 h, and it is possible that the higher affinity of MLi-2 for this pathogenic mutant might account for this.</p><!><p>(A–C) The indicated matched MEFs were treated with vehicle (DMSO) or 100 nM LRRK2 inhibitor MLi-2 for 48 h. The MLi-2 inhibitor was removed from cells through multiple washes with complete media for the indicated periods prior to cell lysis. Twenty micrograms of whole-cell extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/total Rab10, which were calculated using the Image Studio software. Values were normalized to the average of (A) wildtype MEFs treated with DMSO, (B) LRRK2[R1441C] MEFs treated with DMSO, or (C) VPS35[D620N] MEFs treated with DMSO. Cell extract derived from a wildtype MEF cell line (**) was added to each gel in order to accurately compare the Rab10 pThr73/Rab10 total ratios between genotypes in each panel. Data quantifications are presented as mean ± SD. Similar results were obtained in two separate experiments.</p><!><p>Finally, we explored whether Rab32, which is closely related to Rab29 and reported to interact with LRRK2 [41,69], could contribute to the regulation of LRRK2 activity in Rab29 knock-out MEFs. siRNA knockdown reduced Rab32 expression by 70–80%, however, this had no impact on Rab10 phosphorylation in Rab29 knock-out wildtype LRRK2 or LRRK2[R1441C] knock-in cells (Figure 10). Knockdown of LRRK2 in parallel experiments, as expected, markedly reduced Rab10 phosphorylation (Figure 10). By immunoblotting analysis of wildtype and Rab29 knock-out MEFs we were unable to detect Rab38, which is also related to Rab29 and Rab32. This is consistent with previous high-resolution proteomic analysis of MEFs in which Rab38 was not detected [7].</p><!><p>The indicated matched primary MEFs were transfected with Dharmacon smartPOOL siRNA targeting either LRRK2, Rab32, or control scrambled non-targeting siRNA. The cells were lysed 72 h post-transfection. 20 µg of whole-cell extracts were subjected to quantitative immunoblot analysis with the indicated antibodies. The membranes were developed using the LI-COR Odyssey CLx Western Blot imaging system. Quantified data are presented as the ratios of phospho-Rab10/Total Rab10 and were calculated using the Image Studio software. Values were normalized to the average of Rab29 knock-out MEFs treated with scrambled siRNA. The ratio of LRRK2 or Rab32 expression divided by the loading control was used to determine siRNA knockdown efficiency, and values were normalized to the average of the scrambled siRNA treated MEFs. Data quantifications are represented as mean ± SD. Similar results were obtained in three separate experiments.</p><!><p>As outlined in the introduction, considerable evidence supports the view that transient overexpression of Rab29 recruits the bulk of cellular LRRK2 to the Golgi surface, leading to its activation. In overexpression studies, the LRRK2[R1441C/G] mutants are more readily activated by Rab29, which could explain why this mutation elevates LRRK2 activity. However, our results suggest that knock-out of endogenous Rab29 has no significant impact on endogenous LRRK2 activity, assessed by monitoring pRab10 and pRab12 levels in six mouse tissues as well as MEFs and lung derived fibroblasts. Moreover, we also found that knock-out of Rab29 does not impact elevated Rab10 or Rab12 phosphorylation observed in the LRRK2[R1441C] knock-in MEFs or mouse tissues. This would suggest that endogenous Rab29 is not sufficient to explain the elevated activity of the LRRK2[R1441C] pathogenic mutant. We also found that Rab29 knock-out had no effect on the elevated LRRK2-mediated Rab10 or Rab12 phosphorylation observed in VPS35[D620N] knock-in MEFs and mouse tissues. To our knowledge, there is no evidence implicating Rab29 in mediating the effects of the VPS35[D620N] mutation. We also find that in brain extracts, Rab12 phosphorylation appears to be more robustly impacted by LRRK2 inhibitors and pathogenic mutations than Rab10 phosphorylation, consistent with a recent study [70].</p><p>In this study, we also report that agents that induce endolysosomal pathway stress including nigericin, monensin, chloroquine and LLOMe significantly enhance Rab10 and Rab12 phosphorylation in MEFs and A549 cells, in a manner that is blocked by LRRK2 inhibitors. Out of the 4 agents tested, nigericin was the most potent in enhancing Rab10 and Rab12 phosphorylation and increases the basal phosphorylation of these substrates 5 to 9-fold (Figure 8, Supplementary Figure S8). Nigericin and monensin function as broad monovalent cation ionophores, and have been reported to have pleiotropic effects on vesicular trafficking pathways [63]. Recent reports have also shown that chloroquine and LLOMe enhance Rab10 phosphorylation [57,66–68], and we find that these agents also promote Rab12 phosphorylation (Figure 8C,D, Supplementary Figure S8). We find that in MEFs, monensin, chloroquine and LLOMe induce pRab10 and pRab12 around 2 to 4-fold, compared with 5 to 9-fold effects observed with nigericin. A recent report suggested that chloroquine induced phosphorylation of Rab10 in RAW264.7 macrophages in a manner that was largely blocked by siRNA knockdown of Rab29 [67]. In contrast, we find that in MEFs, knock-out of Rab29 does not impact moderate Rab10 or Rab12 phosphorylation induced by chloroquine as well as the other agents we have tested (nigericin, monensin, LLOMe). It should be noted that Rab29 is highly expressed in macrophages [47] and in future work, it would be important to utilize Rab29 knock-out models to verify whether Rab29 plays a role in regulating LRRK2 pathway activity through agents such as chloroquine in primary macrophages. Further work is required to understand the mechanism by which nigericin, monensin and lysosomotropic agents promote LRRK2-mediated Rab protein phosphorylation. It would be interesting to explore whether these agonists promote the recruitment of LRRK2 to particular membrane compartments, thereby activating LRRK2 and promoting Rab10 and Rab12 phosphorylation at that location. Recruitment of LRRK2 to membranes has been proposed previously to be a key mechanism by which LRRK2 activity is regulated [29,57,68].</p><p>It is possible that other Rab proteins, or even other regulators that have not yet been characterized, could also interact with and activate LRRK2 in a similar manner to Rab29 by recruiting LRRK2 to a variety of cellular membranes. In the absence of Rab29 overexpression, LRRK2 is widely distributed in cells with ∼90% cytosolic localization and ∼10% localization on a variety of cellular membranes [14,57,71,72]. A small fraction of LRRK2 appears to be localized in the Golgi region without Rab29 overexpression [14–17,73], which may explain why Rab29 knock-out does not have a noticeable impact on Rab10 or Rab12 protein phosphorylation when measured in a whole cell or tissue extract. In future work, it will be important to develop assays in which the pool of endogenous LRRK2 that resides at the Golgi could be specifically assessed. Since LRRK2 is likely in equilibrium between membranes and the cytosol [29], such interactions may be transient and more challenging to capture quantitatively. Indeed, by elevating the local concentration of Rab29 on the Golgi by exogenous expression, this pool was more readily detected. It will be important to define whether the activity and localization of the endogenous pool of Golgi-resident LRRK2 is dependent upon Rab29. It will also be necessary to further study whether endogenous LRRK2 located on other specific membrane compartments relies on other Rab proteins or regulators for this localization, and whether this contributes to the total cellular LRRK2 activity measured in cell extracts. It would also be important to define more precisely the residues in LRRK2 that bind Rab29 and investigate how subtle mutations that prevent Rab29 binding, impact cellular LRRK2 activity. Whether other Rab proteins bind to the same or different sites in LRRK2 should also be investigated.</p><p>The ability of exogenous Rab29 to recruit LRRK2 to the Golgi (or other compartments to which it is targeted) confirms the ability of Rab29 to bind LRRK2 in cells. Yet our knock-in and knock-out models failed to reveal clues regarding the functional significance of this interaction. Rab29 is a relatively poorly abundant Rab and may play a specific role in macrophages and dendritic cells where it is most abundant. Indeed, LRRK2 activation triggered by Rab29 could occur in a specific cell type or tissue, or following a physiological stimulus, stress or infection that we have not investigated. Our data do not rule out the possibility that Rab29 knock-out is compensated by another cellular protein(s) other than Rab32. However, our findings with transgenic mice that overexpress Rab29 from 1.5 to 25-fold, without enhancing LRRK2-mediated Rab10 or Rab12 phosphorylation, reveal that increasing Rab29 expression is not sufficient to stimulate the activity of endogenous LRRK2.</p><p>We have previously shown that Rab3, Rab8A, Rab10 Rab12, Rab35 and Rab43 are the main substrates of LRRK2 [7,26,74], and have herein monitored changes in phosphorylation of Rab10 and Rab12. We, therefore, cannot exclude the possibility that Rab29 preferentially activates phosphorylation of the Rab proteins we have not assayed, but we consider this unlikely because this set of Rab proteins appear to be co-ordinately phosphorylated in all cultured cell experiments that we have carried out to date [26,33,51]. It has also been suggested that screens could be undertaken to identify potentially therapeutic compounds that block Rab29 binding to LRRK2, however, our data suggest that such agents may not be effective at reducing basal LRRK2 activity, unless these chemicals also block LRRK2 binding to other regulators that transport it to cellular membranes. Finally, we propose that the new Rab29 monoclonal antibodies we have developed could be exploited to better understand how Parkinson's mutations within the PARK16 locus impact Rab29 protein expression.</p>

PubMed Open Access

Generating ampicillin-level antimicrobial peptides with activity-aware generative adversarial networks

Antimicrobial peptides are a potential solution to the threat of multidrug-resistant bacterial pathogens. Recently, deep generative models including generative adversarial networks (GANs) have been shown to be capable of designing new antimicrobial peptides. Intuitively, a GAN controls the probability distribution of generated sequences to cover active peptides as much as possible. This paper presents a peptide-specialized model called PepGAN that takes the balance between covering active peptides and dodging non-active peptides. As a result, PepGAN has superior statistical fidelity with respect to physicochemical descriptors including charge, hydrophobicity and weight.Top six peptides were synthesized and one of them was confirmed to be highly antimicrobial. The minimum inhibitory concentration was 3.1µg/mL, indicating that the peptide is twice as strong as ampicillin.

generating_ampicillin-level_antimicrobial_peptides_with_activity-aware_generative_adversarial_networ

Introduction<!>Generative Model<!>Statistical Fidelity<!>Experimental Validation<!>Conclusion<!>Peptide Synthesis<!>MIC determination

<p>Antibiotic resistance is a serious and immediate threat against humanity, as currently available antibiotics become increasingly obsolete. The annual deaths due to antimicrobial resistance are expected to exceed 10 million by 2050. 1 Antimicrobial peptides (AMPs) are a possible solution to this problem. 2 They are considered as less prone to resistance, because microbes have been exposed to natural AMPs for millions of years, but widespread resistance against them has not been reported. Human experts have been developing successful AMPs by using simple hydrophilic/hydrophobic repeats, 3 or modifying an existing AMP. 4 Given the huge peptide space, however, it is very likely that numerous AMPs are yet to be found.</p><p>Deep generative models 5 are one of the viable ways to boost the speed of AMP discovery, and several studies have been reported so far. Purely computational studies employing recurrent neural networks (RNN), 6 variational auto encoders (VAE) 7 and GAN 8 showed promising results in statistical terms, but experimental validation is yet to be done. Nagarajan et al. 3 were the first to show that a recurrent neural network can generate AMPs that works in vitro. They identified two peptides with minimum inhibitory concentration (MIC) 4µg/mL against E.coli. The potency of these peptides is at ampicilin-level, because their MIC is comparable to that of ampicilin (6.25µg/mL), a widely used antibiotic. Their neural network model has two parts. First, a recurrent neural network (i.e., generator) trained with known antimicrobial peptides generates a large number of peptides. Next, a classifier neural network trained with peptide-MIC pairs ranks the generated sequences, and top-ranked peptides are subject to experimental validation. Drawbacks of the model by Nagarajan et al. 3 are as follows. 1) LSTM is an obsolete model that is often outperformed by GANs. 9 2) The generator is trained only with positive examples (i.e., AMPs), despite the fact that a plenty of negative examples (i.e., non-AMPs) are available. Aiming to solve the drawbacks, we develop a specialized model called Pep-GAN by engineering LeakGAN, one of the state-of-the-art sequence generators. 10 PepGAN enhances the performance of LeakGAN with the help of activity predictor that is trained separately with positive and negative examples together (Figure 1).</p><p>Another challenge in deep-learning-based AMP design is how to incorporate physicochemical properties such as charge, hydrophobicity, normalized van der Waals volume and polarity. Deep learning models are essentially a language model and it is not clear how to incorporate such information. To this aim, Nagarajan et al. 3 included several filtering steps in the model. Instead of complicating our model further, we simply chose to rerank PepGAN-generated peptides with an external AMP prediction tool (i.e., CAMP server 11 ) trained with various physicochemical features. As a result of our experimental validation, the MIC of the best peptide was as low as 3.1µg/mL, i.e., twice as strong as ampicilin. We made a python library of PepGAN publicly available at https://github.com/tucs7/PepGAN to contribute in the developing open-source ecosystem of peptide design. The generator samples a number of sequences stochastically. The reward for the sequences is evaluated by the discriminator, and transmitted back to the generator to update the parameters. In normal GANs, the reward function represents fidelity, i.e., how the sequences are similar to AMPs. In PepGAN, an activity predictor (shown in red) is incorporated in reward computation. Finally, top peptides are subject to experimental validation.</p><!><p>In various tasks including scheduling and maze solving, reinforcement learning has been used to generate a sequence of actions that maximizes a reward function. 12 A reward function represents the quality of a generated sequence. In traditional settings, it is given a priori and stays unchanged during training. When optimizing multiple reward functions at once, a linear combination of them is used in many cases. 13,14 Recently, Yu et al. 15 introduced SeqGAN that employs a machine-learned reward function for generating texts that resembles real sentences. A deep neural network called discriminator is trained to discriminate generated ones against real ones, and the training loss is adopted as the reward function. High reward implies high statistical fidelity: generated sequences are statistically indistinguishable from real ones. Later, SeqGAN is extended to LeakGAN 10 by introducing the ideas of hierarchical reinforcement learning. 16 In LeakGAN, the reward function for a sequence Y is designated as the output of the discriminator D(Y ), i.e., the probability of Y being real. The reward function of our model, PepGAN, is described as</p><p>where F (Y ) is a separately-trained activity predictor, and λ denotes the mixing constant.</p><p>The activity predictor has a GRU (Gated Recurrent Unit) 17 with 256 hidden variables.</p><p>Given a sequence Y , it computes a hidden vector at each position. The hidden vector is fed to a one-layer dense neural network to yield a partial score at each position.</p><!><p>As training examples, we collect sequences not longer than 52 amino acids from the following databases: APD, 18 CAMP, 19 LAMP 20 and DBAASP. 21 Redundant sequences are removed via multiple sequence alignment with cut-off ratio 0.35. The final dataset contains 16648 positive sequences (i.e., AMPs) and 5583 negative sequences (i.e., non-AMPs). The activity predictor is first trained with all sequences and later the rest of PepGAN is trained only with positive sequences. PepGAN is used with three different parameter settings λ = 0, 0.5 and 1. Notice that LeakGAN corresponds to the case λ = 1. For each setting, 10000 peptide sequences are generated.</p><p>We investigate the statistical fidelity of generated sequences from multiple viewpoints.</p><p>The generated sequences are regarded as high-quality, if their statistics match well with those of the positive sequence set. First, we investigate the following physicochemical properties: length, molar weight, charge, charge density, isoelectric point, aromaticity, global hydrophobicity and hydrophobic moment. ModlAMP package 6 was used to compute these properties.</p><p>Obtained statistics are summarized in Table 1. With respect to seven in eight properties, PepGAN with the activity predictor (λ = 0 and 0.5) were better than LeakGAN (λ = 1).</p><p>This result shows that the activity predictor has a favorable impact in statistical fidelity. In the following experiments, λ = 0.5 is adopted, because it achieved the best result here. It is reported that samples generated by GANs tend to lose diversity due to mode collapse. 9 To check if mode collapse happened or not, the diversity of PepGAN-generated sequences is measured as follows. For each sequence, a BLEU score between that and all the other sequences is computed. The diversity score called self-BLEU is then computed as the average of all the BLEU scores. Table 3 shows self-BLEU scores for the positive sequence set (i.e., AMPs) and the generated sequences sets of PepGAN variations. In all cases, generated sequences were as diverse as the positive set, and mode collapse did not happen.</p><p>Table 3: Self-BLEU scores based on k-grams (k = 2, 3, 4, 5) for three variants of PepGAN (λ = 0, 0.5, 1) and the positive sequence set (AMPs).</p><p>AMPs λ = 0 λ = 0.5 λ = 1 Self-BLEU-2 0.965 0.969 0.970 0.970 Self-BLEU-3 0.802 0.835 0.842 0.846 Self-BLEU-4 0.550 0.592 0.608 0.621 Self-BLEU-5 0.393 0.372 0.381 0.405</p><!><p>Fo experimental validation, generated peptides are prioritized according to the AMP likehood computed by the CAMP server. 11 Top six peptides are shown in Table 4. In addition, the worst four sequences are chosen as negative controls. Figure 2 shows helical wheel plots of these peptides 22 together with their hydrophobic moments. 23 Cell penetrating peptides tend to have a high relative abundance of positively charged amino acids, and contain an alternating pattern of polar and hydrophobic amino acids (i.e., amphiphilicity). 2 Our top peptides are observed as highly cationic and amphiphilic, because they contain a large number of positively charged amino acids and no negatively charged ones, and their hydrophobic moments are high (0.58±0.048). In comparison, negative controls are neither cationic nor amphiphilic.</p><p>The potency of the peptides are evaluated based on minimum inhibitory concentration (MIC) against E.coli. MIC is determined as the minimum concentration of an antimicrobial at which the growth of a target microbe is suppressed. We found that as many as five out of six AMP peptides exhibited effective antimicrobial activity. Among them, AMP4 exhibited the best antimicrobial performance, 3.1 µg/mL, which is better than a well-known antimicrobial, ampicillin (6.25 µg/mL). The high production ratio, 5/6, and the sufficiently low MIC of AMP4 validate PepGAN's ability to generate industry-level peptides. In contrast, all four negative control peptides did not exhibit effective antimicrobial activity.</p><!><p>We presented PepGAN, a generative model for designing peptides, and demonstrated its statistical and in vitro success in AMP design. AMP-specific tricks are intentionally left out of our python library. Thus, our library can directly be applicable in development of other kinds of peptides such as drug-delivery peptides 24 and anti-cancer peptides. 25 To achieve our goal of boosting the speed of peptide development, experimental researchers, who are not necessarily familiar with machine learning, should be able to use computational tools such as PepGAN. Although we made our code public, we have not reached this level of utility. Open-source ecosystems in machine translation and computer vision are well-developed to the point that non-experts can use them without difficulty. In future work, we continue to develop PepGAN with an aim to make it a core of the emerging ecosystem of peptide design tools.</p><!><p>We synthesized all peptides on rink amide resin (ProTide, CEM corporation, NC, USA) using an automated microwave peptide synthesizer (Liberty Blue, CEM corporation). Each peptides were cleaved from resin and purified by reversed-phase HPLC using a C18 column (COSMOSIL 5C18-AR-II, Nacalai tesque, Japan) at 25 • C for 60 min with a linear gradient of acetonitrile in water containing 0.1% trifluoroacetic acid (v/v) at a flow rate of 1 mL/min.</p><p>We confirmed the purified peptides using a MALDI-TOF MS (microflex, Bruker, MA, USA).</p><!><p>The MICs of the peptides were determined using the micro-dilution test with some modifications. We used em E.coli TOP10 (Thermo scientific, MA, USA) in the late-log phase for this test. The colony forming unit of E.coli was determined using optical density at 600nm.</p><p>For each peptide we prepared 11 wells containing 150 µL of 5×10 5 CFU/ml of E.coli and the series of concentration of each peptide from 10 to 0.01 µg/ml (2-fold dilution for 10 times).</p><p>We also prepared 1 well containing only 150 µL of 5 × 10 5 CFU/ml of E.coli without the peptide. Similarly, we prepared 11 wells for ampicillin in the same well-plate. We incubate the plates for 26 hours at 37 • C for the growth of E.coli. To read optical density for each well, we set the plates in a plate reader (EnSpire 2300, Perkin Elmer). After shaking the plate for 10 s at 300 rpm in double-orbital motion (diameter 1mm), we measured the optical density of each solutions (600 nm).</p>

ChemRxiv

Active Site Ring-Opening of a Thiirane Moiety and Picomolar Inhibition of Gelatinases

(\xc2\xb1)-2-[(4-Phenoxyphenylsulfonyl)methyl]thiirane 1 is a potent and selective mechanism-based inhibitor of the gelatinase sub-class of the zinc-dependent matrix metalloproteinase (MMP) family. Inhibitor 1 has excellent activity in in vivo models of gelatinase-dependent disease. We demonstrate that the mechanism of inhibition is a rate-limiting gelatinase-catalyzed thiolate generation via deprotonation adjacent to the thiirane, with concomitant thiirane opening. A corollary to this mechanism is the prediction that thiol-containing structures, related to thiirane\xe2\x80\x93opened 1, will possess potent MMP inhibitory activity. This prediction was validated by the synthesis of the product of this enzyme-catalyzed reaction on 1, which exhibited a remarkable Ki of 530 pM against MMP-2. Thiirane 1 acts as a caged thiol, unmasked selectively in the active sites of gelatinases. This mechanism is unprecedented in the substantial literature on inhibition of zinc-dependent hydrolases.

active_site_ring-opening_of_a_thiirane_moiety_and_picomolar_inhibition_of_gelatinases

<!>Restoration of Activity to MMP-2 Inhibited by Thiirane 1<!>Solvolytic Chemistry of Thirane 1 and Key Analogues<!>A Kinetic Isotope Effect for MMP-2 Inhibition by Thiirane 1<!>Potent MMP-2 Inhibition by Thiol 7<!>Discussion

<p>The central position of the epoxide ring in organic synthesis derives from the ease of its synthesis, and the ability of Brønsted or Lewis acids to control its opening by nucleophiles. Thiiranes, three-membered rings containing a sulfur atom, are typically less reactive than epoxides. Due to their latent reactivity toward nucleophiles, the aziridines, epoxides and thiiranes all have been used as irreversible enzyme inhibitors (1–3). In the pioneering work of Kim et al., epoxybutanoic acid covalently modified the carboxylate of the glutamate in the active site of the zinc protease, carboxypeptidase A (4). The catalytic zinc ion of this protease, which activates the scissile amide bond of the substrate during normal turnover, here functions as a Lewis acid for epoxide O-alkylation of this glutamate (5). The conceptual extension of this principle to the creation of efficacious matrix metalloproteinase inhibitors, zinc proteases involved in the pathophysiology of inter alia human inflammation and tumor metastasis, is an objective of this laboratory (6). We previously reported the discovery, the core SAR, and initial computational and experimental mechanistic studies with the thiirane-containing structure 1 (7–12). Thiirane 1 (also known as SB-3CT) exerts potent (nanomolar) and time-dependent inhibitory activity with high selectivity toward the gelatinase MMP sub-class (13). The selectivity of 1 for the gelatinases (MMP-2 and MMP-9) has provided experimental evidence for gelatinase activation in cell culture models of breast cancer metastasis (14–16), axon guidance (17), beta-adrenergic receptor stimulated apoptosis (18,19) and amyloid precursor protein processing (20). Compound 1 is active in an animal model of testosterone-induced neurogenesis (21) as well as in several rodent models of human disease, including laminin degradation following cerebral ischemia (22), prostate cancer metastasis to the bone (23), breast cancer metastasis to the lungs (24), blood-brain barrier integrity (25), and T-cell lymphoma metastasis to the liver (26). In contrast, the lack of efficacy of 1 in cell culture models of ovarian cancer cell metastasis implicates the activity of other MMPs during collagen degradation in this cancer (27). The favorable biological outcome in MMP-dependent disease models using 1 as a gelatinase MMP sub-class inhibitor stimulated this further mechanistic study of MMP-2 inhibition by 1.</p><p>The design of inhibitor 1 was based on the precedent of Kim's oxirane inhibitors of carboxypeptidase A. Kim documented by X-ray crystallography that interactions of the oxirane with the zinc ion led to covalent modification of the active site glutamate common to all zinc proteases (28). This same chemistry appeared plausible for gelatinases (29). This conception led to a computer-aided design effort, resulting in the synthesis of over 100 compounds, and culminating in the discovery of 1. Compound 1 proved to be a potent inhibitor of gelatinases having time-dependent kinetics for this inhibition, a hallmark of both covalent inhibition as well as slow-binding inhibition of enzymes. In contrast, the epoxide analogue of 1 was a much weaker inhibitor, and its inhibition lacked time-dependence (7). This difference emphasized the special ability of 1 to exploit the Lewis acidity of the active site zinc. Based on the Kim precedent, we favored the glutamate alkylation mechanism, notwithstanding the observation that the enzyme activity recovered gradually. This recovery was thought to reflect hydrolytic lability of the ester linkage between the glutamate and the inhibitor. Three separate crystallographic efforts to confirm this mechanism were without success.</p><p>However, in the course of further synthesis we noted that the thiirane ring of 1 was not stable in the presence of base. A retrospective look at the chemistry of zinc proteases alerted us to the observation by Sugimoto and Kaiser that Glu270 of carboxypeptidase A promoted enolization of a ketone (30). As stable thiol coordination of the MMP zinc is used to suppress protease activity in MMP pro-enzymes (that is, the inactive zymogen), the possibility that proper presentation of a thiol to the MMP catalytic zinc would coincide with potent inhibition of the enzyme was credible. Moreover, the thiol and thioether functional groups are key zinc-interacting functional groups in several well-studied MMP inhibitor classes (31–33). Hence, we were compelled to consider two limiting mechanisms for gelatinase inhibition by 1. Each uses the Lewis acidity of the active site zinc ion to activate the thiirane. The first mechanism is covalent O-alkylation of the cognate glutamate to the Glu270 of carboxypeptidase A, which is also present in the MMP active site (Mechanism A of Scheme 1). The second mechanism is base-catalysis— presumably by Glu404 or Glu404-activated water—removal of a proton from the relatively acidic carbon that is adjacent to the sulfone. This deprotonation initiates opening of the thiirane to an allylthiolate (Mechanism B of Scheme 1). In this mechanism, the thiirane ring acts as a caged thiol, unmasked only within the gelatinase active site. The experiments used to differentiate the two mechanisms are described.</p><!><p>Following incubation of MMP-2 with a 1000-fold excess of 1 (reaction of 10 nM MMP-2 with 10 µM 1 for 3 h in pH 7.5 buffer at ambient temperature), the catalytic activity of MMP-2 was 0% of the control (MMP-2 activity in the absence of 1). Two methods were used to remove the excess inhibitor from this inhibited MMP-2 enzyme. The first method was gel filtration. The inhibited enzyme was separated from excess inhibitor using a centrifugal gel filtration column, recovering 97% of the activitiy of the control (enzyme incubated without inhibitor and filtered separately). The activity recovered from the control was >95% of the total activity at the start of the incubation. This result shows that MMP-2 regains activity following separation from 1. The kinetic behavior of the recovered MMP-2 with respect to the assay substrate was identical to the enzyme from the no inhibitor control. This observation suggests that 1 left no residual modification of the enzyme. Mechanism A of Scheme 1 postulates covalent modification of the catalytically essential active site glutamate. If this mechanism were operative, full recovery of MMP-2 activity would be an improbable observation following separation of the inhibitor from the MMP-2 enzyme.</p><p>MMPs are synthesized in vivo as zymogens (34,35). The molecular basis for suppression of catalytic activity in the zymogen is the presence of a pro domain, containing a cysteine residue that engages the active site zinc ion as a thiolate ligand (36). Enzyme activity is suppressed by this stable zinc coordination (37) and by the body of the pro-domain, blocking substrate access to the active site (38,39). Transformation of the zymogen to the mature MMP occurs by proteolytic removal of the pro-domain. Efficient in vitro initiation of the proteolytic removal of the prodomain is accomplished with the organomercurial reagent APMA (40). This reagent traps the prodomain cysteine thiolate that coordinates to the active site zinc, thereby displacing the prodomain from the active site. The possibility that APMA would exert a similar effect on MMP-2 inhibited by 1—which is also characterized by direct zinc-thiolate coordination (8,38)—was evaluated as a second method. Inactivation of a 1 nM solution of MMP-2 using excess 1 (1.5 µM) for 4 h gave complete loss of enzyme activity. Addition of a solution of APMA (to 1 mM final concentration) restored 90% of the total enzyme activity that was initially present. Again, this result is improbable for a covalent mechanism of inhibition. In contrast, if the mechanism for loss of MMP-2 catalytic activity by 1 is formation of a stable zinc thiolate coordination complex, then restoration of activity by APMA (analogous to its role in MMP zymogen activation) is expected.</p><!><p>The possibility that a base-catalyzed deprotonation mechanism (Scheme 1, Pathway B) might better account for the ability of 1 to effect inhibition of MMP-2 catalytic activity prompted further experiment. In particular, we were curious as to its intrinsic reactivity. Accordingly, a solution of 1 in toluene in the presence of 1.1 equiv of 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU, pKa = 12) and iodomethane (10 equivalents) showed rapid and complete (within 30 min) transformation of 1 to the vinylsulfide 2, isolated as a 2:1 Z,E-diasteromeric mixture (Scheme 2). A solution of 1 in MeOH in the presence of a DBU buffer (1.1 equivalents of DBU, 1.1 equivalents of DBU·HCl) and iodomethane (10 equivalents) also showed complete loss of 1 within 3 h at rt. In contrast, the identity of the major product (80%) of this reaction was the S-methylated vinylsulfone 3, with the S-methylated vinylsulfides 2 (here also as the 2:1 Z,E-mixture) as minor products (20% total).</p><p>The solvolytic behavior of 1 parallels previous mechanistic study with structurally very closely related thiiranes and epoxides (41). In this study, Piras and Stirling demonstrated that (sulfonyl)methyl-substituted thiiranes (and epoxides) open by base-mediated deprotonation at the carbon adjacent to the sulfone, giving vinylsulfone products. Kinetic study indicated proton abstraction, alkene formation, and thiirane opening to coincide within a single transition state. Deuterium substitution adjacent to the sulfone gave a primary kinetic isotope effect of 3.2 for thiirane opening (41). Following vinylsulfone formation, further proton exchange equilibrates the vinylsulfone with its thermodynamically more stable vinylsulfide isomer 2 (42–44). The difference in product outcome between the conditions of DBU in toluene, and DBU/DBU·HCl in MeOH, may be understood in terms of the preservation of the basicity of DBU under the former reaction conditions. The kinetic vinylsulfone product is favored by the lower basicity of the DBU·HCl reaction conditions. Significantly, yet milder reaction conditions using a mixture of NaOAc and Zn(OAc)2 in MeOH as a simple mimetic of the conserved glutamate carboxylate and Zn(II) ion of the MMP active site, gave a similar outcome to the DBU·HCl reaction conditions. After one month at room temperature, the reaction mixture consisted of 40% unreacted 1 and ≥55% 3, with small amounts (≤5%, all yields by NMR) of the vinylsulfides 2.</p><p>Further evidence in support of this mechanism was obtained with a derivative of 1 having reduced carbon acidity. The acidity of alkylarylsulfoxides (approximate pKa = 33) is significantly weaker than that of the corresponding sulfone (approximate pKa = 29). Accordingly, it was anticipated that the sulfoxide analog of 1 would be more stable in solution. Indeed, sulfoxide 4 (prepared as a 1:1 diastereomeric mixture by adaptation of the routes used previously in this laboratory to prepare derivatives of 1, as fully described in the Supporting Information) was stable to DBU (3 d, rt). Sulfoxide 4 was evaluated as an MMP-2 inhibitor. Poor linear competitive inhibition of substrate hydrolysis (Ki = 2.1 µM) was seen for 4 without any evidence of time-dependent inhibition (Table 1). The pronounced difference in the kinetics behavior between 4 and 1 indicates different mechanisms for the two. Sulfoxide 4 is a linear competitive inhibitor, whereas sulfone 1 is a slow-binding inhibitor (7,13).</p><!><p>The catalytic velocity of substrate hydrolysis by MMP-2 in the presence of 1 progressively diminishes, as a result of the time-dependence inherent to slow-binding inhibition by 1. Classically, slow-binding behavior involves non-covalent chemistry, wherein the slow-binding event correlates to a conformational shift to a more stable enzyme-inhibitor complex. Deuterium incorporation into the inhibitor allows inquiry as to whether a kinetic isotope effect is expressed on any phase of the slow-binding kinetics. The progress curve for 1-d2 showed a five-fold decrease in the rate constant for the onset of the slow-binding transition (kon) and no difference in the rate constant for dissociation (koff). This kinetic isotope effect results in a five-fold increase in the apparent Ki, (a ratio of koff/kon). This result indicates that the entire isotopic effect is on the rate constant for the onset of inhibition (kon) and not on the rate constant for the offset (koff). It is logical that the koff values measured with 1 and 1-d2 are equal, as dissociation occurs after the deprotonation event in which the kinetic isotope effect is expressed. The appearance of this kinetic isotope effect implicates deprotonation at the α-carbon as the step that precipitates the onset of slow-binding process, leading to the more tightly bound state.</p><p>Two dimethyl-substituted derivatives of 1 were made. The α,α-dimethyl derivative 5, which is incapable of thiirane opening by deprotonation adjacent to the sulfone, shows no detectable inhibition of MMP-2 up to its solubility limit of 40 µM. The γ,γ-dimethyl derivative 6, which is capable of thiirane opening but is sterically encumbered compared to 1, is a linear competitive inhibitor with decreased affinity compared to 1. The dramatic difference between 1 and these two derivatives emphasizes the importance of the spare structure of 1 to the mechanistically important criteria of nanomolar potency and slow-binding onset of potent inhibition.</p><!><p>Vinylsulfone 7 is the kinetic product of base-mediated solvolysis of 1 and is also the presumed product of MMP-catalyzed action upon 1. The mechanism-dependent release of a latent thiolate by 1 coincides with the onset of the more stable inhibited state. Compound 7 was synthesized, and upon evaluation as an inhibitor of MMP-2 showed competitive inhibition with no evidence of a slow-binding kinetic transition. Its Ki value of 530 ± 70 pM is noteworthy. As this value is below the assay concentration of the enzyme, it was calculated using Morrison's equation for analysis of tight-binding inhibition (45,46).</p><p>Thiirane 1 is a selective inhibitor of the gelatinases by a mechanism that ultimately results in thiolate ligand presentation to the active site zinc. The plausibility of thiirane opening by general base-catalyzed deprotonation at the carbon adjacent to the sulfone thiolate, when 1 is bound within the active site of MMP-2, was assessed computationally (Fig. 2). This assessment was made firstly by examination of the computationally predicted structure of the MMP-2·1 complexes (as 1 is racemic, and as both enantiomers of 1 are competent inhibitors, both the R-1 and S-1 complexes with the MMP require evaluation). Recognition by the gelatinase active site of inhibitor stereoisomers is precedented. The crystal structure of MMP-2 (PDB code: 1CK7) was transformed to that of the active enzyme by removal of the pro-domain in silico. Using the program DOCK, the R-enantiomer of 1 was computationally inserted into the active site, so as to allow coordination of the thiirane sulfur to the active site Zn(II). The structure of the S-enantiomer of 1 bound to the active site was generated from that of the R-enantiomer by inversion of configuration. Each complex was computationally equilibrated by dynamics simulation to bring the thiirane sulfur into the coordination sphere of the zinc ion. Further dynamics simulations (2 ns duration) of each complex (of the two enantiomers) were performed individually. We focused on the proximity of the carboxylate of Glu404 to the methylene hydrogens adjacent to the sulfone. As is shown in Figure 2, both enantiomer complexes show the approach of one oxygen atom of the carboxylate to within 2.4 Å of one of these hydrogens. This proximity is necessary for a proton abstraction initiating the thiirane ring-opening step. For the R-1 enantiomer, the pro-S hydrogen is in close contact to a Glu404 oxygen, while the pro-R hydrogen makes closer contact for S-1. While the time scale for these bond-making and bond-breaking events is much longer than this dynamic simulation, the calculated transition state for the non-enzymatic solvolysis of 1 fully substantiates this proposed mechanism (47). These simulations support C–H proton abstraction within the enzyme-inhibitor complex as the critical event leading to the tight-binding inhibition.</p><!><p>The departure of the cysteine thiol ligand from the active site zinc is a key event in pro-MMP maturation (38,39). In addition, the ability of endogenous thiols to suppress the cellular activity of the mature MMP enzyme (wherein the inhibitory cysteine ligand has been removed proteolytically), by engagement of the active site zinc, is well known. It is therefore hardly surprising that appropriate incorporation of the thiol functional group into precedented MMP inhibitor motifs attains exceptional inhibitory potency, as shown by Freskos et al. (48,49) with a structural motif related to 7, by our group with dithiol structures also related to 7 (8), and by others exploiting other thiol MMP/TACE inhibitor classes (32). However, application of the thiol as the zinc-binding group within a practical MMP inhibitor is challenging, due to the promiscuity of the thiol for metal binding and due to the ease of its oxidative and metabolic transformations (32). These challenges underscore the virtues of thiirane 1 as an MMP inhibitor. Its thiol is masked within the three-membered thiirane, with liberation of its latent thiol dependent on the base-catalysis machinery unique to the gelatinases. Moreover, the chemical structure of 1 is found by experiment to uniquely complement the machinery of the MMP-2 and MMP-9 gelatinase active sites. Inhibitor 1 yields a monodentate ligand for presentation to the active site zinc. X-ray absorption spectroscopy (XAS) comparison of the zinc-sulfur bond of MMP-2 inhibited by 1 to the cysteine-liganded zinc of pro-MMP-2 shows remarkable similarities in Zn—S bond length, ligation, and coordination geometry (8,50).</p><p>Thiirane 1 integrates three complementary structural components. The phenoxyphenyl moiety is a proven structural complement to the hydrophobic tunnel within the gelatinase active sites (51). The sulfone makes a key hydrogen bond to Leu-191 (MMP-2 numbering) in the active site (51) and the sulfone activates the adjacent methylene hydrogens for the deprotonation step that fragments the thiirane (41). The MD simulations indicate spatial feasibility for the Glu404 carboxylate to serve as the general base in this reaction. The third structural aspect of 1 is the thiirane, which first coordinates to the active site zinc (and is thus activated for fragmentation), and which is transformed to a thiolate anion upon thiirane ring opening. The transformation of the ligand from thioether (thiirane) to thiolate strengthens the inhibitor coordination to the zinc, mimicking the behavior of the cysteine of the pro-domain. The tight integration of these structural components is emphasized by the dramatic loss of inhibitory competence for many closely related structures to 1 (7).</p><p>The kinetics of MMP-2 (and MMP-9) inhibition by 1 indicate time dependence for loss of activity (13), and the electronic coordination environment of the inhibited enzyme implicates a thiirane opening event (50). Although 1 generates (and 7 has) a vinyl sulfone functional group, also well applied as a latent electrophile for protease inhibition, we have no evidence supporting covalent reaction of these vinyl sulfones with MMP-2. All of the experimental observations support the mechanism for gelatinase inhibition by 1 to be the thiirane-opening pathway B of Scheme 1. The salient question that follows this conclusion is the structural basis for the selectivity that 1 exhibits for gelatinase inhibition (7). The other members of the MMP family are either not inhibited by 1 at all, or are inhibited poorly. The success of this inhibitor in selective inhibition of gelatinases both in in vivo and in vitro experiments is impressive, and is a unique aspect of the inhibitor class. As our experiments reveal, the onset of inhibition is initiated by the rate-limiting deprotonation α to the sulfone function. This event is the likely step that initiates the time-dependence for inhibition, slow-binding behavior of the inhibitor, which leads to the formation of the thiolate. Its strong coordination to the zinc ion leads to tight-binding chemistry for the enzyme-inhibitor complex. Since the active sites of MMPs are very similar to each other, it is likely that 1 would interact relatively poorly with the active site zinc ions of MMPs, but in the cases of gelatinases, the complex is able to proceed via the requisite deprotonation event to tight-binding inhibition at picomolar level of potency. In essence, the thiirane is a caged entity that leads to the formation of the thiolate only in the active site of gelatinases. This chemistry for the mechanism of action is entirely unprecedented in the substantial literature of zinc protease (including MMP) inhibition. Compound 1 and its structural congeners have considerable promise for applications to diseases that are gelatinase-dependent.</p>

PubMed Author Manuscript

[Ag]2[B12Cl12] as a Catalyst in PhICl2 Mediated Chlorination

The weakly coordinating [B12Cl12] 2originates from a family of carboranes typically reserved for application in coordination chemistry. Here, we show its readily accessible Ag(I) salt, [Ag]2[B12Cl12], can be used as a catalyst in the PhICl2 mediated chlorination of arenes, alkenes, and alkynes. The promising activity displayed by [Ag]2[B12Cl12] over a variety of commercially available Ag(I) sources merits its incorporation to the toolkit of commonly screened silver catalysts in synthesis.

[ag]2[b12cl12]_as_a_catalyst_in_phicl2_mediated_chlorination

<p>PhICl2, the first reported λ 3 -iodane compound, [1] is a versatile oxidant, primarily acting as a chlorinating agent representing a convenient substitute for Cl2. Cl2 is a highly corrosive, toxic gas, which in addition to being hazardous, is challenging to deliver in a stoichiometric fashion. Conversely, PhICl2 is an easily weighed solid which is readily accessible from PhI, HCl, and H2O2, [2] can be used without the need for rigorously anhydrous conditions, and has been used widely in the oxidation of organic and inorganic compounds. [3] PhICl2, which can also be generated from a combination of PhI and Cl2, is not without limitation. It is necessarily a weaker oxidizing agent than the Cl2 it replaces and is unreactive towards many substrates. Activation of PhICl2 can be accomplished using Lewis acids with a handful of reports over the years, including by stoichiometric AgBF4 and SbCl5 in chlorination of norbornene derivatives, [4] and by catalytic AlCl3 in the replacement of diazo groups with chlorines. [5] Lewis acids such as BF3 have also been shown to increase the activity of the related oxidant PhI(OAc)2. [6] Numerous groups over the years have used TMS-OTf to generate purported PhI(OTf)2 from PhI(OAc)2 as a stronger oxidant, [7] however this has recently been shown to actually be PhI(OTf)(OAc). [8] A recent paper by Nagib [9] described the activation of PhI(OAc)2 using either HCl or acid chloride, or of PhICl2 using acetic anhydride, in each case giving a mixed PhI(OAc)(Cl) species capable of chlorinating the C-H bonds of a variety of (hetero)arenes in a few hours at 50 °C. Lupton [10] employed the same concept a decade earlier using excess pyridinium chloride as the chloride source in concert with PhI(OAc)2 to chlorinate α,β-unsaturated carbonyls and alkenes (Scheme 1). Scheme 1. General classes of reported halogenation reaction using λ 3 -iodanes.</p><p>In this report we show that abstraction of chloride from PhICl2 using catalytic amounts of silver salts of the weakly coordinating anion [B12Cl12] 2increases the activity of PhICl2 such that substrates unreactive or poorly reactive to PhICl2 can be rapidly chlorinated at room temperature.</p><p>Our initial goal in this study was generation of the [Ph-I] 2+ dication, likely a highly reactive species. To achieve this we aimed to generate the [Ph-I][B12Cl12] salt, using the weakly coordinating and highly robust nature of the [B12Cl12] 2dianion to allow for an isolable or at least observable species. [11] To this end, PhICl2 was reacted with stoichiometric [Ag]2[B12Cl12] in CHCl3. A 1 H-NMR spectrum of an aliquot of the reaction mixture revealed the presence of several species. Notably, similar reactivity was observed in the presence of catalytic (10 mol%) We have previously observed electrophilic aromatic substitution processes in reactions with electron poor λ 3 -iodane species, [12] and therefore surmised that residual PhI generated from the decomposition of PhICl2 was undergoing electrophilic aromatic chlorination. [Ag]2[B12Cl12] was essential for the reaction to suggestive of an "iodonium" type mechanism, in which Ag(I) abstracts chloride from PhICl2 resulting in a in an [PhICl] + species, which is presumably stabilised by the weakly coordinating [B12Cl12] 2anion (Scheme 3). As discussed, attempts to isolate [PhICl] + or similar were unsuccessful. Scheme 3. Proposed [Ag]2[B12Cl12] mediated "iodonium" mechanism for electrophilic aromatic chlorination of iodobenzene.</p><p>Encouraged by this preliminary reactivity, we decided to explore the efficacy of a number of other Ag(I) sources as mediators of electrophilic aromatic chlorination with PhICl2 using the electron rich arene, anisole (1), as an exemplar substrate (Table 1). Only minor conversion to 4-chloroanisole (2) was observed in the absence of any catalyst (entry 1). As expected, addition of 5 mol% [Ag]2[B12Cl12] resulted in substantially greater reactivity, which was further improved to a conversion of 67% upon doubling catalyst loading to 10 mol% (entries 2 & 3). Pleasingly, conversion was rapid (20 minutes) and occurred readily at room temperature. Changing solvent to acetonitrile (entry 4), or altering the nature of the counteranion and cation (entries 5 & 6) were all detrimental. AgCl, potentially generated in quantities up to 20 mol% during the catalytic cycle with [Ag]2[B12Cl12], was also investigated as a potential catalyst, and resulted little conversion at 20% loading (entry 7). [Ag]2[B12Cl12] is synthesized from relatively inexpensive and non-toxic precursors, primarily NaBH4, I2, and SO2Cl2. The Ag(I) salt is most conveniently obtained by metathesis using AgNO3 from a Cs salt. Unlike a number of related carborane reagents, which require the use of highly toxic and expensive reagents (i.e. B10H14), [13] and are extremely time consuming to make, [14] synthesis of [Ag]2[B12Cl12] is relatively straightforward, and can be delivered on a decagram scale in a few days in a typically equipped academic laboratory. [15] Nonetheless, it was considered prudent to investigate several commercially available Ag(I) sources as alternative activators of PhICl2. Some conversion was observed in all cases, however activity was on the whole worse than [Ag]2[B12Cl12]. Reactions with AgOTf, AgBF4, and AgSbF6 (traditionally considered weakly coordinating), displayed similar levels of activity only when stoichiometric quantities of Ag(I) were used (entries 9, 11, & 13, respectively). Lower loadings resulted in activity comparable to the use of no Ag(I) at all. AgNO3 was the worst activator investigated, resulting in only minimal conversion even when deployed stoichiometrically (entry 14).</p><p>The optimum conditions (i.e. entry 3) were then applied to a range of substituted arenes in order to investigate the scope of the system. For each substrate, a control reaction (% yield in brackets) was also performed in the absence of [Ag]2[B12Cl12] to probe its innate propensity to react with PhICl2 (Table 2). Anisole translated well to scale, with 4-chloroanisole (2) isolated as the sole isomer in 55% yield. 2,6-Dimethyl phenol was also isolated exclusively as the 4-chloro isomer (3), and performed much better in the presence of catalyst (i.e. 76% vs. 30%). Selectivity and yields were lower for unsubstituted phenol, with the 2,4-dichloro isomer (4) isolated in higher proportions in the presence of catalyst. Incorporation of an electron withdrawing group to the phenol ring was well tolerated, as demonstrated by ethyl salicylate, which was chlorinated in the 4-position relative to the hydroxyl group (6). Notably, this reaction did not proceed at all in the absence of catalyst. Napthalen-1-ol proved problematic, with a range of isomers (7-10) isolated in either event, although the 4-chloro isomer (10) was the major in each case. Rerunning the reaction at 0 ºC gave similar results and did not afford any improvement in selectivity. Using a phenol in which the 4position was blocked gave a mixture of 2-chloro isomers (i.e. 11 and 12). Interestingly, moving to propiophenone, an electron deficient arene, resulted exclusively in chlorination alpha to the ketone (13 and 14), with the aromatic ring left untouched. Introduction of an electron donating substituent marked a complete reversal in chemoselectivity (15). Neither substrate showed reactivity in a control reaction. 3,4,5-Trimethoxybenzoic acid, the most electron rich arene in the series, was the only member to display superior reactivity in the absence of catalyst, giving chloride 16 in 84% yield in a control experiment, but only 64% in the presence of [Ag]2[B12Cl12]. The reason for this remains unclear, but may be explained, in part, by the propensity of residual PhI (generated as a byproduct of successful SEAr) to undergo chlorination (as depicted in Scheme 2), thereby reducing the amount of PhICl2 available for productive pathways. The conditions were also successful in delivering chlorinated oxazolidinone 18 as a single isomer, as confirmed by HSQC and subsequently X-ray crystallography. Compound 18 is a structural analogue of the commercially available antibiotic Linezolid, [16] and highlights the utility of this approach in late stage chlorination, an attractive strategy in drug design. [17] Finally, heteroarenes were investigated, and unfortunately proved to be a limitation. Quinoline was not amenable to chlorination (19). 4-Dimethylaminopyridine, which is contrast is electron rich and activated towards SEAr, we have previously found is readily chlorinated without added Ag(I). [18] Pyridine gave a mixture of species for which only pyridnium chloride could be identified.</p><p>Given related methods (i.e. Nagib and Lupton) have both capitalised on PhI(OAc)(Cl), an active intermediate capable of delivering a single chlorine atom, and recent reports of the enantioselective dichlorination of alkenes, [19] we speculated whether our methodology would be capable of activating PhICl2 to formally deliver a unit of molecular Cl2. To this end, the chlorination of several alkenes/alkynes was investigated (Table 3). Gratifyingly, this approach proved fruitful. Styrene delivered 1,2-dichloro styrene (20), albeit in modest yield. Methyl cinnamate was also readily chlorinated, giving the corresponding dichlorides (21 and 22) in a combined yield of 56% and a 2:1 d.r. in favour of the anti-isomer. [20] Minor amounts of the elimination product, methyl β-chlorocinnamate (23), were also isolated. Diphenylacetylene gave the corresponding trans-dichloride, 24, as well as minor amounts of compound 25, presumably arising as a result of nucleophilic attack of residual PhI to the less hindered side of the transient vinyl cation. [21] The structure of both compounds were confirmed by X-ray crystallography, with the trans-dichloride having been previously reported. [22] In all examples, the presence of [Ag]2[B12Cl12] was essential, and reactions were completely chemoselective for exocyclic π-bonds over arenes. The electron poor dimethyl acetylenedicarboxylate (DMAD), was not tolerated under these conditions, under which no chlorinated adducts (26) were observed.</p><p>In summary, we have demonstrated that catalytic [Ag]2[B12Cl12] can activate PhICl2 to act as a source of Cl + in the electrophilic aromatic substitution of arenes, and also to deliver a full equivalent of Cl2 in the chlorination of alkenes and alkynes. The reactions discussed herein likely proceed through the intermediacy of [PhICl] + via an "iodonium" mechanism, as opposed to a radical cation mechanism observed by others in related systems, and thereby present an attractive complimentary reactivity manifold. [9] Further evidence for this comes from the fact that electron rich arenes outperformed their electron poor counterparts, and that chlorination was generally selective for positions on which the greatest delocalisation of partial negative charge would be expected. Whilst innate reactivity was observed with some arenes, in all but one substrate surveyed, [Ag]2[B12Cl12] resulted in enhanced reactivity. Presence of the Ag(I) salt was essential for the chlorination of alkenes and alkynes.</p><p>Current usage of the [B12Cl12] 2dianion is largely limited to the inorganic community, where it enjoys a position amongst several related carborane reagents which act as superacids, [11] an unparalleled source of strong electrophiles, [23] and can be used in the isolation and X-ray crystallography of exotic carbocations. [24] It is our hope that in demonstrating the superior activity of [Ag]2[B12Cl12] over several commonly used silver salts as a source of Ag(I), other practitioners will be encouraged to further investigate its application in related areas of organic synthesis.</p>

ChemRxiv

Superoxide Inhibits Guanine Nucleotide Exchange Factor (GEF) Action on Ras, but not on Rho, through Desensitization of Ras to GEF

Ras and Rho GTPases are molecular switches for various vital cellular signaling pathways. Overactivation of these GTPases often causes development of cancer. Guanine nucleotide exchange factors (GEFs) and oxidants function to upregulate these GTPases through facilitation of guanine nucleotide exchange (GNE) of these GTPases. However, the effect of oxidants on GEF functions, or vice versa, has not been known. We show that, via targeting Ras Cys51, an oxidant inhibits the catalytic action of Cdc25\xe2\x80\x94the catalytic domain of RasGEFs\xe2\x80\x94on Ras. However, the enhancement of Ras GNE by an oxidant continues regardless of the presence of Cdc25. Limiting RasGEF action by an oxidant may function to prevent the pathophysiological overactivation of Ras in the presence of both RasGEFs and oxidants. The continuous exposure of Ras to nitric oxide and its derivatives can form S-nitrosated Ras (Ras-SNO). This study also shows that an oxidant not only inhibits the catalytic action of Cdc25 on Ras-SNO but also fails to enhance Ras-SNO GNE. This lack of enhancement then populates the biologically inactive Ras-SNO in cells, which may function to prevent the continued redox signaling of the Ras pathophysiological response. Finally, this study also demonstrates that, unlike the case with RasGEFs, an oxidant does not inhibit the catalytic action of RhoGEF\xe2\x80\x94Vav or Dbs\xe2\x80\x94on Rho GTPases such as Rac1, RhoA, RhoC, and Cdc42. This result explains the results of the previous study in which, despite the presence of an oxidant, the catalytic action of Dbs in cells continued to enhance RhoC GNE.

superoxide_inhibits_guanine_nucleotide_exchange_factor_(gef)_action_on_ras,_but_not_on_rho,_through_

<!>Experimental Conditions<!>Generation and Quantification of O2\xe2\x80\xa2\xe2\x88\x92<!>Protein Sample Preparations<!>Kinetic Assay<!>DATA ANALYSES<!>RESULTS<!>Apparent Inhibition of the Oxidant-Mediated Catalytic Action of Cdc25 on wt Ras GTPase<!>Deconvolution of the Oxidant-Mediated Inhibition of the Catalytic Action of Cdc25 on wt Ras GTPase<!>Role of Ras Cys51 in the Oxidant-Dependent Inhibition of the Cdc25-Mediated wt Ras GDP Dissociation<!>Role of Cysteines of Cdc25 in the Oxidant-Dependent Inhibition of the Cdc25-Mediated wt Ras GDP Dissociation<!>The O2\xe2\x80\xa2\xe2\x88\x92-Mediated Perturbation of the Binding Interaction between wt Ras and Cdc25<!>Lack of the Oxidant-Mediated Inhibition of the RhoGEF-Mediated GDP Dissociation from Rac1 and RhoC<!>DISCUSSION<!>Implication of the Oxidant-Mediated Inhibition of the RasGEF Actions on wt Ras<!>Kinetic Mechanism of the Oxidant-Mediated Inhibition of the Catalytic Activity of RasGEFs on wt Ras<!>Potential Role of Ras Cys51 in the Oxidant-Mediated Inhibition of the Catalytic Activity of RasGEFs by the Perturbation the wt Ras\xe2\x80\x93Cdc25 Binding Interaction<!>Redox Regulation of wt Rho GTPases with RhoGEFs<!>

<p>The Ras and Rho families of small GTPases are subfamilies of the Ras superfamily.1 The Ras family of small GTPases includes Harvey Ras (HRas), Neuroblastoma Ras, and Kirsten Ras.2 Ras-dependent cellular signals control cell growth and division.3,4 Rac1 and other proteins, such as RhoA, RhoC, and Cdc42, belong to the Rho family of small GTPases.5 These Rho proteins modulate various cellular functions, including cell polarity, vesicular trafficking, and the cell cycle.5,6 Various diseases, including cancer, are linked to misregulation of the cellular signaling events associated with Ras and Rho GTPases.4,7–9</p><p>A variety of regulators govern the cycle between the biologically active GTP- and inactive GDP-bound forms of these small GTPase proteins. These regulators include guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs).10 GAPs downregulate the level of activity of small GTPases by stimulating the intrinsically slow rate of GTP hydrolysis, populating small GTPases in their inactive GDP-bound form. Conversely, GEFs upregulate the function of small GTPases by promoting the dissociation of the bound GDP from small GTPases. This dissociation allows small GTPases to bind with cellularly abundant GTP to generate the active GTP-bound state of small GTPases in vivo.</p><p>A number of Ras-specific GEF (RasGEF) proteins have been identified. These include Son of Sevenless (SOS, originally named the Drosophila gene product of Son of Sevenless),11 Ras protein-specific guanine nucleotide-releasing factor (RasGRF),12 and Ras guanyl nucleotide-releasing protein (RasGRP).13 The general architecture of these related RasGEFs is conserved sequentially and structurally within the catalytic core domain Cdc25.14 Nevertheless, both SOS and RasGRF also possess the noncatalytic regulatory domains of Dbl homology (DH) and the Pleckstrin homology (PH). However, RasGRP lacks these regulatory domains.15 The DH domains of these RasGEFs are homologuous to the catalytic domain of the Rho-specific GEF (RhoGEF) proteins that may endow these RasGEFs with Rho-specific GEF activity in addition to the RasGEF function.16 A PH domain that connects directly to a DH domain interacts with the plasma membrane.17 The current model of the mechanism for the activation of RasGEF is that, by the binding of the RasGEF to the plasma membrane, the PH/DH domain-mediated allosteric inhibition of RasGEF is released, resulting in activation of the RasGEF.18</p><p>Dbl's big sister (Dbs) that possesses DH and PH domains is known as a RhoGEF specific to RhoA and RhoC19 as well as to Cdc42.20 Vav, another RhoGEF composed of several domains that have been implicated in protein-protein interactions in addition to the DH and PH domains, has been shown to be broadly active with several Rho GTPases, such as Rac, RhoA, and Cdc42. However, it is most active with Rac1.21</p><p>Biologically important oxidants include the superoxide anion radical (O2•−), hydrogen peroxide (H2O2), the hydroxyl radical, nitric oxide (NO), and nitrogen dioxide (•NO2).9 Among them, O2•− and •NO2 are capable of enhancing the dissociation of GDP from redox-sensitive Ras and Rho proteins.22,23 In Ras proteins, these oxidants target the site of the Cys118 (HRas numbering) in the NKCD motif.24 In Rho GTPases, the Cys18 (Rac1 numbering) in the GXXXXGK(S/T)C motif serves as their target site.23 Intriguingly, the redox-mediated enhancement of Ras GDP dissociation is often coupled with S-nitrosation at the Cys118 side chain of Ras (Ras-SNO).24,25 Despite the lack of clarity about the cellular conditions necessary to produce Ras-SNO, it is easily formed when Ras is continuously exposed to oxidants such as •NO2 in the presence of NO.26 Nonetheless, because Ras-SNO does not react with oxidants such as O2•− and •NO2, some researchers have speculated that Ras-SNO formation terminates the redox regulation of Ras GTPases.9</p><p>The mechanisms of the regulation of Ras and Rho GTPases by their GEF alone or by an oxidant alone are well-established.9 However, it is less clear how redox sensitive Ras and Rho GTPases are regulated when a GEF and oxidants are both present at the same time. Although the sensitivity of the catalytic action of Cdc25 to oxidants has been reported,27 the biological significance of the kinetic and mechanistic features of this sensitivity remains unclear. No report exists of the redox sensitivity of the catalytic action of RhoGEFs. This study examined the redox properties of the catalytic core domain Cdc25 of RasGEFs as well as those of RhoGEFs Vav2 with the DH and PH domains and of the cysteine-rich domains (Vav2 DPC) and those of the Dbs with the DH and PH domains (Dbs DH/PH). The result clarifies the regulation of Ras activity by RasGEFs associated with Ras Cys51 in the presence of an oxidant. Moreover, this study also explains some earlier enigmatic findings about the inhibitory effect of the oxidant NO in regulating the cellular activity of Ras28–30 in which NO typically upregulates the cellular activity of Ras.31–34 Finally, this study notes the redox inert features of Vav2 DPC and Dbs DH/PH.</p><!><p>The presence of transition metals in an assay mixture often converts biologically relevant oxidants into other molecules via the Haber–Weiss reaction and the Fenton reaction.35,36 Removal of transition metals from the assay mixture to prevent these Haber–Weiss and Fenton reactions ensures the desired oxidant concentrations and also blocks generation of byproducts.22 Moreover, most of the biologically relevant oxidants are highly reactive with O2. The reaction of oxidants with O2 not only depletes the effective oxidant concentrations but also often generates unwanted byproducts.9 However, despite the aerobic conditions of this cellular reaction, the cellularly produced oxidant effectively targets redox-sensitive proteins such as Ras.37–39 The spatial proximity between the redox-sensitive proteins and the oxidant-producing proteins (e.g., nitric oxide synthase)40 is one of the cellular features that may be responsible for directing the oxidant to target redox-sensitive proteins while minimizing its side reaction with O2. However, such a cellular proximity feature cannot be easily mimicked in in vitro assay approaches.</p><p>Although an anaerobic experimental condition—an experimental condition that lacks O2—is apparently atypical in biologically relevant kinetic studies, it is nevertheless one recourse for the mimicking of cellular reaction conditions. This is because the anaerobic condition minimizes the reaction of an oxidant with O2 during the course of in vitro assays.22 To prevent undesirable decay or conversions of oxidants during the time periods of the experiments, all experiments were performed under transition metal-free anaerobic experimental conditions. Residual transition metals on the surface of all assay equipment, including vials and cuvettes used in experiments, were removed by soaking them in 1 N HCl for 1 day and then thoroughly rinsing them with double-distilled water. A transition metal-free assay buffer was prepared by passing a solution containing 50 mM NaCl, 0.1 mM diethylenetriamine-pentaacetate, and 10 mM TrisHCl (pH 7.4) through a column packed with Bio-Rad Chelex-100 cation exchange resin. The highest grade of pure MgCl2 (5 mM) was then added to the transition metal-free solution. All purified protein samples (see below) were dialyzed with the transition metal-free assay buffer to produce transition metal-free protein samples.</p><p>O2-free rubber serum stopper-sealed assay vials containing the transition metal-free buffer and small GTPase protein samples were prepared in an N2-filled anaerobic glovebox (O2 concentrations <3 PPM). GEF protein samples (Cdc25, Vav2 DPC, and Dbs DH/PH) as well as the fluorescence-tagged Ras proteins complexed with Cdc25 stocks in O2-free rubber serum stopper-sealed assay vials were also prepared in this N2-filled anaerobic glovebox. All syringes were flushed with N2 before being used to transfer buffer, reagents, or proteins from the stock vials to the assay cuvettes.</p><!><p>KO2 was used as a source for the generation of O2•−. The KO2 stock solution (~3.6 mM) was prepared in anhydrous dimethyl sulfoxide essentially as described in the previous study.41 Anaerobic KO2 and H2O2 stock solutions were prepared by placing the KO2 and H2O2 solutions in a sealed vial, applying a vacuum, and then using a vacuum manifold to flush them three times with N2. A fraction of the KO2 solution (e.g., ~1–2 µL) was transferred to an anaerobically sealed assay vial that contained an assay buffer (1 mL). The O2•− concentration in the assay vial was then measured using unmodified ferricytochrome c as described in the previous study.42 In brief, a fraction of the assay solution containing KO2 was transferred to an anaerobically sealed vial that contained oxidized ferricytochrome c (10 µL). The change in wavelength of 550 nm against 557 nm that occurred because of the reduction of ferricytochrome c was then monitored with a spectrophotometer. The value of the spectra of cytochrome c (550 nm minus 557 nm) provided the concentration of O2•− derived from KO2 in the assay solution. The cytochrome c concentrations were calculated from the absorption coefficient of 21 mM−1 cm−1.43</p><!><p>Except for the commercially available superoxide dismutase (SOD, from bovine erythrocytes, Sigma), all protein samples used were prepared using human origin constructs. The C-terminus truncated version of wild type (wt) HRas (1–166) conserves the structural features of the full-length wt Ras (i.e., Switches I and II) necessary for the binding interactions with the full-length wt HRas effectors and regulators.44–46 This C-terminus truncated wt HRas construct also is stably and abundantly expressed in Escherichia coli and thus is widely used for various in vitro studies. Within this study, unless otherwise specified, all experiments were conducted with the C-terminus truncated wt HRas. Also, in all experiments, unless otherwise specified, the term "wt Ras" describes the C-terminus truncated version of wt HRas (1–166). As with wt Ras, single cysteine mutant Ras proteins—C51S, C80S, and C118S—as well as a double cysteine mutant—C51S/C118S Ras—that were constructed using the wt HRas (1–166) were stably and abundantly expressed in E. coli. Therefore, these cysteine mutants represent versions of C-terminus truncated HRas. However, the C-terminus double cysteine mutant—C181S/C184S—was constructed using full-length wt HRas (1 – 189). Therefore, C181S/C184S Ras protein represents a full-length HRas mutant protein, whereas the full-length wt Ras denotes the full-length wt HRas. The expressions of the full-length wt and C181S/C184S HRas proteins in E. coli were not as abundant as in these C-terminus truncated versions; this may have been because of the instability of these C-terminus HRas residues (167–189). Nevertheless, their expressions were sufficient for the planned experiments. When necessary, the control of C181S/C184S Ras, the full-length wt Ras, is noted as it is. A Cdc25 construct of human RasGRF1 (564–1049) was used with this study. The advantage in using Cdc25, instead of the whole RasGEF (such as SOS), was to pinpoint whether the target action of the oxidant is linked directly to the catalytic action of RasGEFs. Moreover, because Cdc25 represents the catalytic core domain of these RasGEFs, the result associated with Cdc25 generally applies as well to the catalytic action of these RasGEF proteins.</p><p>All Ras constructs, as well as the Cdc25 construct, were expressed as a maltose-binding protein (MBP)-fusion protein from the pMAL vector (New England Biolabs). They were purified from E. coli as described by the vendor. Ras and Cdc25 proteins were isolated by using a Q-Sepharose column after cleavage of the fusion proteins by using the protease supplied by the manufacturer. To produce a Ras-SNO, wt Ras (10 mL of ~10 µM) was transferred for 30 min into a sealed vial (100 mL) containing a mixture of NO and O2. The mixture of NO and O2 in a sealed vial was prepared by purging NO gas for 5 min, followed by an injection of air (50 mL) into the NO-filled sealed vial while simultaneously venting the vial to release the increased air pressure that resulted. The NO/O2-treated Ras was passed through a G-25 size exclusion column (1.5 × 7 cm) to remove denatured Ras proteins. An estimation of the Ras-SNO characteristic peak at 542 nm (an extinction coefficient (ε) of 0.020 cm−1 mM−1)22 gave the fraction of Ras-SNO in the NO/O2-treated Ras sample as ~0.7. As this fraction indicated, not all of the Ras was S-nitrosated. This was likely because a certain fraction (0.2–0.3) of the sulfur atom of the Cys118 side chain of the as-purified Ras exists in various oxidized states, such as sulfinate and sulfonate.47 These oxidized forms of Ras are redox inert; thus, they did not affect the experiment results. The Ras-SNO is stable unless otherwise illuminated by high energy UV light (i.e., >260 nm).47,48 Given that Ras-SNO was not exposed to UV light during the experiments, the decomposition of Ras-SNO was not expected.</p><p>wt Ras and its mutant proteins were tagged with rhodamine fluorescence as described in the previous study.47 The fluorescence-tagged Ras proteins complexed with Cdc25 were generated essentially as described in the previous study.49</p><p>Glutathione S-transferase (GST)-tagged wt Rho GTPases— such as Rac1 (1–177), RhoA (1–181), RhoC (1–193) in the pGEX vector—were expressed in and purified from E. coli by using the GST gene fusion system supplied by the manufacturer (GE Healthcare). Rho GTPases were isolated by using the factory-provided GSTrap followed by thrombin digestion as indicated in the vendor's protocol. The Vav2 DPC (1–573) and The Dbs DH/PH (525–1097) construct, expression, and purification were essentially the same as described in the previous studies.19 Tritium-labeled guanosine diphosphate ([3H]GDP) was diluted with unlabeled GDP, giving ~4000 dpm/µM [3H]GDP. When necessary, [3H]GDP was loaded on Ras and Rho GTPases as described previously.23</p><!><p>A syringe flushed with N2 was used to add an anaerobically prepared oxidant or GEF protein (e.g., Cdc25) to the anaerobically sealed assay cuvettes that contained small GTPase loaded with [3H]GDP in the presence and absence of SOD in the transition metal-free assay buffer. Simultaneous treatment with GEF and an oxidant was done by introducing GEF, followed immediately by an oxidant, into the assay cuvettes containing [3H]GDP-loaded small GTPase in an assay buffer. When necessary, this sequence was reversed, first introducing an oxidant, followed immediately by GEF. Aliquots of the assay sample were then withdrawn with a syringe at specific times and spotted onto nitrocellulose membrane filters. These filters were then washed three times with an assay buffer. The radioactivity of the nitrocellulose membrane filters was measured with a scintillation counter (Beckman). When necessary to perturb any potential binding interaction between GEF and GTPase, GEF (50 nM) was pretreated with an oxidant (e.g., O2•−, 5 µM) in the presence of GTPase (1 µM) under anaerobic conditions, quenched with excess ascorbic acid (1 mM), and then treated with 100 mM (NH4)2SO4. The (NH4)2SO4-treated protein sample was concentrated with an Amicon centrifugal filter (10 kDa cut off). To isolate GTPase from GEF protein and chemicals, the concentrated protein sample was then passed through a gel filtration column (2.5 × 20 cm packed with Sephadex 75).</p><p>Depending on the assay involved, a certain fraction of [3H]GDP was dissociated from small GTPases by treatment with an oxidant and/or GEF. However, complete dissociation did not occur, even over an extended period (e.g., 1 h). One possible reason for this incomplete dissociation is that, although the GTPase protein samples used were more than 95% pure (judged by SDS-PAGE), the structure and/or redox-sensitive motif of the used GTPase samples was not entirely homogeneous. For example, a certain fraction of the redox-sensitive cysteine residues of Ras proteins that are coupled with the Ras GDP dissociation was in a redox inert oxidation state (sulfenic acid, sulfinate, and/or sulfonate states). A Ras-specific redox enzyme has not been reported; however, it is possible that in cells these redox inert states can be reversed by the action of various redox enzymes such as thioredoxin, peroxiredoxin, and sulfiredoxin. However, the in vitro assay used for this study lacked such redox enzymes. Therefore, the presence of a desensitized fraction of Ras in an assay mixture reduced the quantity of the redox-mediated dissociation of the bound [3H]GDP from Ras. It is not unprecedented for a fraction of GDP to remain unassociated from Ras when treated with an oxidant.47 Another possible explanation is that a fraction of the oxidation reaction of the redox-sensitive residue of Ras does not always couple with the mechanical perturbation of the Ras nucleotide-binding interaction. For example, a fraction of the thiyl radical generated by the reaction of a redox-sensitive cysteine of Ras with an oxidant (e.g., O2•−) reacts instead with another O2•− to produce a redox inert oxidized form of Ras. This cysteine oxidation does not couple with the dissociation of [3H]GDP from Ras.</p><p>The fluorescence-based binding assays under anaerobic conditions were performed by titration of the rhodamine-tagged Ras Cdc25 binary complex with KO2. This was described in the previous study,47 except that Cdc25 was used instead of Raf-RBD. KO2 was repeatedly injected into the anaerobically sealed assay cuvettes containing the rhodamine-tagged Ras complexed with Cdc25. The change in fluorescence emission intensity at 545 nm, followed by excitation at 490 nm because of the dissociation by KO2 of Cdc25 from the rhodamine-tagged Ras, was then monitored with a Perkin-Elmer LS 55 Fluorescence spectrometer.</p><!><p>Three independent measurements were performed for each set of experiments (e.g., wt Ras). When necessary, the values were normalized against the value of the initial untreated sample that was set at 1.0. For purposes of graphic presentation, the mean values of each data point were then calculated, along with the corresponding standard deviations (SD) from these independent triple measurements. Depending on the experimental set, the values were plotted against either time (e.g., s) or concentration of an effector(s) (e.g., KO2). The plot was further fitted to a proper kinetic model—the one-phase exponential decay or the one-site binding (hyperbola)—to statistically analyze and then estimate various kinetic parameters. Briefly, for each data set of the triple independent measurements, Prism software was used to perform a two-tailed variance ratio test (F test) for a null hypothesis (H0) "one curve is for all data sets" and an alternative hypothesis (HA) "one curve is not for all data sets" with a P value < 0.05. This test evaluates whether the individual curves are statistically distinguishable with a 95% confidence interval. Once the result of the F test does not reject the null hypothesis, Prism software was used to find the global fit, finding one shared (among data sets) best-fit value for all triple independent measurements for each parameter. These values include the rate constant, the apparent inhibition constant (appKI), or the dissociation constant (KD). The fittings also provide the SD of each of the determined parameters as well as the regression values (r2) of the global fits.</p><p>To test the difference between the kinetic parameters obtained from each set of experiments (e.g., wt Ras versus C118S Ras), Prism software was used to perform a two-sample t test for a two-tailed H0 "one parameter is for all data sets" and an HA "one parameter is not for all data sets" with a P value < 0.05.</p><p>Kinetic parameters of reactions include the rate constant and the span. Such parameters can be obtained by fitting the reaction data to the kinetic model "one phase exponential decay" (see above). However, unlike their rate constants, spans are often omitted in the description of reactions. This is because, in the absence of any other reaction limitation, the span of the complete reaction asymptotically reaches 1 (in terms of the fraction of the total reaction substrate). The span within this study is defined as the total quantity GTPase GDP dissociation in the time period for a given reaction. Under optimal conditions, the quantity of the usage of GEF does not control the span of the GEF-mediated Ras GDP dissociation— which is expected to be near 1. This is because, up until the reaction is completed to reach span 1, the presence of any amount of whatsoever of the enzyme GEF will be continuously recycled. However, how much of an oxidant is used determines the span of the oxidant-mediated Ras GDP dissociation, which is expected to vary. This is because, unlike GEFs, the inorganic oxidant cannot be recycled but is consumed in the course of the turnover of the facilitation of the GTPase GDP dissociation. Adding more of the oxidant generates more of the GTPase GDP dissociation and thus yields a bigger span. For example, the span of the wt Ras GDP dissociation by O2•− can be further increased by multiple additions of O2•− during the assay time period or by using the xanthine oxidase system that continuously generates O2•− over the assay time period (not shown).</p><p>However, characterization of the completion of the oxidant-mediated Ras GDP dissociation is outside the scope of this study, which aims instead to clarify the effect an oxidant has on the catalytic action of GEFs on these GTPases. Nonetheless, when the quantity of oxidant to be used for assays is set, the span—an indicator of the amount of the GTPase GDP dissociation by the oxidant—can be used as a signature feature of the oxidant-mediated GTPase GDP dissociation. Accordingly, this study used a fixed concentration of an oxidant, rather than multiple additions of oxidants or of the xanthine oxidase system. A certain fraction of Ras and Rho GTPases was denatured in the presence of oxidant concentrations higher than 10 µM (see Figure 3 in Results). To minimize denaturation of these GTPases during the assay time, ~3 µM of oxidant was uniformly used for all assays unless otherwise noted.</p><p>When the oxidant concentration is fixed, not only the rate constant but also the span of the oxidant-mediated GTPase GDP dissociation may differ from the rate constant and the span of the GEF-mediated GTPase GDP dissociation. If the spans between one reaction and another differ, visual comparison of the reaction rates (expressed as rate constants) between these two reactions is confusing. As illustrated in Figure 1, reaction 1 appears slower than reaction 3. In fact, however, these rates are the same. This illusion of difference is because of the 2-fold smaller span of reaction 1 compared with the span of reaction 3. Furthermore, reaction 2 appears slower than reaction 3. This apparent difference also is misleading. In fact, the rate of reaction 2 is 2-fold faster than the rate of reaction 3, yet the span of reaction 2 is 2-fold smaller than the span of reaction 3. Similarly, reaction 2 appears much slower than reaction 4. However, their rates are actually the same; nonetheless, the span of reaction 2 is simply 2-fold smaller than the span of reaction 4. To avoid such confusion, we provide not only the rate constant values but also the span values of the oxidant- and the GEF-mediated GTPase GDP dissociations, along with their corresponding figures.</p><!><p>To assess any potential effect of oxidants on the catalytic function of the GEF proteins of Ras and Rho GTPases, two kinetic parameters—a rate constant and a span—were determined and analyzed for the GDP dissociation from Ras and Rho GTPases in the presence and absence of GEFs and/or various oxidants. When necessary, values were determined for the oxidant concentration that gives the maximal inhibition of the catalytic action of GEFs on small GTPases. This is equivalent to the minimal velocity (appVmin) of the GEF-mediated GDP dissociation from small GTPases. Values also were determined for appKI of an oxidant in its effect on the catalytic action of GEF on GTPases as well as for KD of an oxidant for small GTPases complexed with GEF. These parameters also aid evaluation of the potential effect of oxidants on the catalytic function of the GEF proteins of Ras and Rho GTPases. wt Ras and various Ras mutants as well as wt Rac1 and wt RhoC were used for this study. Cdc25 was used as a Ras GEF. Vav2 DPC and Dbs DH/PH were used for Rho GEFs.</p><!><p>wt Ras GDP dissociation was enhanced by Cdc25, which is consistent with previous reports.49 wt Ras GDP dissociation also was enhanced by KO2 alone (Figure 2). The KO2-mediated wt Ras GDP dissociation was abolished by treatment with SOD (Table 1), suggesting that O2•−—derived from KO2—is the active species to facilitate wt Ras GDP dissociation. The effect of O2•− and its nullification by SOD are consistent with the previous result.23 The values of the rate constant and the span of the Cdc25-mediated wt Ras GDP dissociation are, respectively, 5.4-fold smaller and 1.2-fold larger than the values of the rate constant and the span of the O2•− -mediated wt Ras GDP dissociation (Table 1). These rate constants indicate that, under experimental conditions, the rate of wt Ras GDP dissociation by Cdc25 is slower than the rate of wt Ras GDP dissociation by O2•−. The span values indicate that, under experimental conditions, the quantity of the wt Ras GDP dissociation by Cdc25 exceeds that by O2•−. Unlike the dissociation rate constant, the reaction span is not an intrinsic kinetic characteristic of each reaction. Nevertheless, such a span difference occurred. This occurrence is because, as detailed in the kinetic analysis section of Materials and Methods, the total treated quantity of KO2 (i.e., ~3 µM) that produces the active radical species O2•− for the wt Ras GDP dissociation was simply insufficient to complete the wt Ras GDP dissociation. In contrast, a relatively small amount of the enzyme, Cdc25 (50 nM), was recycled during the assay time period to reach the maximal span.</p><p>Facilitation of wt Ras GDP dissociation also was observed in the presence of both Cdc25 and O2•− together (Figure 2). If O2•− does not affect the catalytic action of the Ras GEF Cdc25 on wt Ras or vice versa, the values of the rate constant and the span of the wt Ras GDP dissociation in the presence of Cdc25 and O2•− together will be a numerical sum. This sum is the total of the rate constant and the span values of the Cdc25-mediated wt Ras GDP dissociation and the O2•−-mediated wt Ras GDP dissociation. However, the values of the rate constant and the span of the Cdc25/O2•−-mediated wt Ras GDP dissociation approximate the values of the rate constant and the span of the O2•−-mediated wt Ras GDP dissociation. Nevertheless, they are not equivalent to the sum of the values of the rate constant and the span of the Cdc25-mediated wt Ras GDP dissociation and the O2•−-mediated wt Ras GDP dissociation (Table 1).</p><p>The O2•−-dominant kinetic features can be quenched by addition to the assay of the O2•−-scavenger SOD containing both Cdc25 and O2•−. In this assay, the values of the kinetic constant and the span of the Cdc25/O2•−-mediated wt Ras GDP dissociation in the presence of SOD were similar to the values of the kinetic constant and the span of the Cdc25- mediated wt Ras GDP dissociation (Table 1). The best explanations for these results are (i) O2•− interferes with the catalytic action of Cdc25 on the wt Ras GDP dissociation, so that the kinetic characteristics of the Cdc25-mediated wt Ras GDP dissociation were fated; and (ii) O2•− continuously facilitates wt Ras GDP dissociation in the presence of Cdc25 that exhibits the signatures of the O2•−-mediated wt Ras GDP dissociation. Accordingly, we hypothesize that O2•− inhibits the Cdc25-mediated wt Ras GDP dissociation. However, Cdc25 has no effect on the O2•−-mediated wt Ras GDP dissociation.</p><p>The wt Ras GDP dissociation was not facilitated by H2O2 (Table 1), which is consistent with the previous result.23 The Cdc25-mediated wt Ras GDP dissociation also was unaffected by other oxidants, such as H2O2 (Table 1). The result suggests that both the intrinsic and the Cdc25-mediated wt Ras GDP dissociation are insensitive to H2O2. Nonetheless, the inability of H2O2 to inhibit the Cdc25-mediated wt Ras GDP dissociation clarifies that the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras is O2•− specific.</p><!><p>It would be challenging to validate the effect of O2•− on the Cdc25-mediated facilitation of the wt Ras GDP dissociation through monitoring of the GDP dissociation from wt Ras. This is because, although O2•− apparently inhibits the Cdc25-mediated wt Ras GDP dissociation, it directly facilitates the wt Ras GDP dissociation.</p><p>To isolate the effect of O2•− on the Cdc25-mediated wt Ras GDP dissociation from the direct effect of O2•− on the wt Ras GDP dissociation, the C118S Ras mutant and the S-nitrosated wt Ras on Cys118 side chain (wt Ras-SNO) were used instead of wt Ras. This substitution was made because O2•− is unable to facilitate the GDP dissociation from C118S Ras and wt Ras-SNO (Figure 2B and Table 1). This inability is because C118S Ras lacks the redox-sensitive Cys118, whereas the SNO moiety of wt Ras-SNO is redox inert against O2•−.47 Moreover, the values of the rate constant and span of the Cdc25-mediated GDP dissociation from C118S Ras and wt Ras-SNO were similar to those of the rate constant and span of the Cdc25-mediated wt Ras GDP dissociation (Figure 2B and Table 1). The results suggest that the mutated Ser residue in C118S Ras and the SNO moiety of the Cys118 side chain of wt Ras do not alter the catalytic function of Cdc25 on Ras. Collectively, kinetic data of C118S Ras and wt Ras-SNO can be used to deconvolute the sole potential inhibition effect of O2•− on the Cdc25-mediated wt Ras GDP dissociation from the O2•−-mediated wt Ras GDP dissociation.</p><p>The values of the rate constant and the span of the Cdc25-mediated C118S Ras GDP dissociation in the presence of O2•− were 2.6- and 1.3-fold smaller than the rate constant and span of the Cdc25-mediated C118S Ras GDP dissociation in the absence of O2•− (Figure 2B and Table 1). However, treatment with SOD abolished the decreases in the rate constant and the span of the Cdc25-mediated C118S Ras GDP dissociation by O2•− (Table 1). Identical biochemical results were obtained by using wt Ras-SNO instead of C118S Ras (Table 1). These results suggest that O2•− perturbs the catalytic function of Cdc25 on C118S Ras and wt Ras-SNO. This supports a hypothesis that O2•− inhibits the catalytic action of Cdc25 on wt Ras.</p><p>The inhibition of the rate constant and span of the Cdc25-mediated C118S Ras GDP dissociation by O2•− was hardly significant (Table 1). To determine the effective inhibition concentrations of O2•− on the catalytic action of Cdc25 on C118S Ras, the mixture of C118S Ras and Cdc25 was titrated with various concentrations of O2•−. The appVmin value— equivalent to the value of the maximal O2•−-mediated inhibition—of the catalytic action of Cdc25 on C118S Ras was determined to occur at an O2•− concentration of 27 µM (Figure 3). The appKI value of O2•− for C118S Ras in the presence of Cdc25 was estimated to be 2.3 µM (Figure 3). This result explains why the default O2•− concentration (~3 µM, see the Materials and Methods section) caused only partial inhibition of the catalytic action of Cdc25 on C118S Ras.</p><p>Intriguingly, although C118S Ras lacks Cys118 and wt Ras-SNO possesses the chemically modified redox inert Cys118 side chain, O2•− was able to perturb the Cdc25-mediated GDP dissociation from C118S Ras and wt Ras-SNO. Therefore, these results constitute another piece of critical evidence that the residue associated with the redox feature of Ras Cys118 is not involved in the O2•−-mediated inhibition of the Cdc25-mediated catalysis of the wt Ras GDP dissociation.</p><!><p>Full-length HRas has a total of five cysteines: Cys51, Cys80, Cys118 , Cys181 , and Cys184 . As noted elsewhere, Ras Cys118 is well-known as a direct target of an oxidant such as O2•−, resulting in enhancement of the GDP dissociation from Ras.23,24 However, it is unclear if any of these Ras cysteines play a role in how O2•− inhibits the catalytic action of Cdc25.</p><p>To determine if Ras Cys51 has a role in the O2•−-mediated inhibition of the catalytic action of Cdc25 on wt Ras, we examined the kinetic properties of the Ras mutant C51S in the presence and absence of Cdc25 and/or O2•−. In contrast to the results associated with wt Ras (Figure 2A and Table 1), the rate constant and the span of the GDP dissociation from C51S Ras by Cdc25 and O2•− together approximated the sum of the individual rate constants and the spans of the GDP dissociation from C51S Ras by Cdc25 and by O2•− (Figure 4A and Table 2). Nevertheless, the values of the rate constants and the spans of the intrinsic, the Cdc25-mediated, and the O2•−-mediated C51Ras GDP dissociation (Figure 4A) were, respectively, similar to those of the values of the intrinsic, Cdc25-mediated, and O2•−-mediated wt Ras GDP dissociation. These results suggest that, although Ras Cys51 has no role in either the wt Ras GDP binding interaction or in the O2•−- and Cdc25-mediated wt Ras GDP dissociation, the Ras residue Cys51 is involved in the O2•−-mediated inhibition of the catalytic action of Cdc25 on Ras. Given that O2•− targets Ras Cys51 rather than Cdc25 to inhibit the catalytic action of Cdc25 on wt Ras, it follows that the mechanism of the O2•−-mediated inhibition of the catalytic action of Cdc25 on wt Ras is that O2•− targets Ras Cys51, which in turn renders Ras insensitive to Cdc25.</p><p>A double mutant Ras C51S/C118S was introduced to further verify the potential O2•−-mediated desensitizing role that Ras Cys51 plays in the catalytic action of Cdc25 on wt Ras. The rate constant and the span of the intrinsic and the Cdc25-mediated GDP dissociation from C51S/C118S Ras (Figure 4B and Table 2) were similar to that of the intrinsic and the Cdc25-mediated GDP dissociation from wt Ras (Figure 2A and Table 1). This result suggests that the Cys51 and Cys118 residues of wt Ras are unnecessary in the Ras nucleotide binding interaction and also in the catalytic action of Cdc25. This is not unusual because the Ras nucleotide binding interaction and the catalytic action of Cdc25 were unaffected by the absence, either separately or in combination, of the Cys51 and Cys118 residue of Ras (see above). Furthermore, the rate constant and the span of the Ras C51S/C118S GDP dissociation by Cdc25 and O2•− together were similar to the rate and the span of the C51S/C118S Ras GDP dissociation by Cdc25 alone (Figure 4B and Table 2). This similarity was unchanged even in the presence of higher concentrations of O2•− (up to 20 µM) (Figure 3). These results indicate that O2•− was unable to desensitize C51S/C118S Ras to Cdc25. Given that the Ras mutant C51S/C118S lacks the Cys118 residue responsible for the direct O2•−-mediated wt Ras GDP dissociation, whatever effect O2•− has on the GDP dissociation from C51S/C118S Ras can be attributed solely to the absence of the Ras residue Cys51. Accordingly, the failure to desensitize C51S/C118S Ras to Cdc25 in the presence of O2•− appears to be caused by the absence of Cys51 in C51S/C118S Ras. These analytical results also support a hypothesis that Ras Cys51 plays a role in the O2•−-mediated desensitization of wt Ras to the catalytic action Cdc25.</p><p>Unlike Ras Cys51, Ras Cys118 was shown to be unaffected by the O2•−-mediated inhibition of the catalytic action of Cdc25 (see the section on the deconvolution of the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras GTPase). This result suggests that Ras Cys118 is not involved in the O2•−-mediated desensitization of wt Ras to Cdc25. However, the potential role(s) of other Ras cysteine residues—including Cys80, Cys181, and Cys184—in the O2•−-mediated desensitization of wt Ras to Cdc25 was unclear. The kinetic and redox properties associated with C80S Ras GDP dissociation were exactly the same as those with wt Ras (Table 2). The result suggests that the Cys80 of Ras has no role in the O2•−-mediated desensitization of wt Ras to Cdc25. As noted in the Materials and Methods section, the construction of C51S, C80S, and C118S Ras (1–166) excluded the Ras C-terminus. However, because Cys181 and Cys184 are located at the end of the C-terminus of the full-length wt Ras, C181S/C184S Ras was constructed with the full-length wt Ras (1—189). Therefore, full-length wt Ras serves as a control for C181S/C184S Ras. The kinetic and redox properties of C181S/C184S Ras were similar to the kinetic and redox properties of the full-length wt Ras (Table 2). It is also noteworthy that the kinetic and redox properties of the full-length wt Ras were similar to the kinetic and redox properties of the C-terminal truncated version of wt Ras (Tables 1 and 2). The results suggest that the portion of the N-terminus of the full-length wt Ras that includes the Cys181 and Cys184 residues is unnecessary for the O2•−-mediated desensitization of wt Ras to Cdc25. Taken as a whole, it appears that, as far as these five Ras cysteines are concerned, only Ras Cys51 is involved in the O2•−-mediated desensitization of the action of Cdc25 on wt Ras.</p><!><p>There are seven cysteine residues in Cdc25. None has been investigated for a potential redox role(s) of any of these Cdc25 cysteines. Given that the oxidant-dependent inhibition of the action of Cdc25 on wt Ras depends entirely on the presence of Ras Cys51 , these Cdc25 cysteines are unlikely to participate in the oxidant-dependent inhibition of the Cdc25-mediated wt Ras GDP dissociation. However, the possibility that these Cdc25 cysteines have other roles, such as modulation of the activity of Cdc25, cannot be dismissed. More studies are necessary to examine this possibility.</p><!><p>Typically, enzymes must bind with their substrates as a prerequisite for their catalytic action.50 In accounting for the kinetic results showing that Ras Cys51 is a central element in the O2•−-mediated desensitization of wt Ras to Cdc25, we hypothesize that the Ras Cys51-targeting action of O2•− is implicated in the perturbation of the binding interaction between Cdc25 and wt Ras that results in desensitization of wt Ras to Cdc25.</p><p>To examine the potential O2•−-mediated perturbation of the binding interaction between Cdc25 and Ras via the targeting of Ras Cys51, a binary complex of Cdc25 with the rhodamine fluorescence-tagged wt Ras and all available cysteine mutants was titrated with O2•− in the absence of free GDP. Figure 5A shows that the rhodamine fluorescence intensity of Cdc25 complexed with wt Ras decreased hyperbolically with increases in the concentration of O2•−. This is an indicator of the dissociation of Cdc25 from wt Ras; it suggests that O2•− interferes with the binding of Cdc25 to wt Ras. The rhodamine fluorescence intensity of Cdc25 complexed with C118S Ras also decreased hyperbolically after treatment with O2•− (Figure 5A). This result suggests that Ras Cys118 is not involved in the O2•−-mediated interference with the binding interaction between Cdc25 and Ras. Identical results were obtained with other Ras cysteine mutants C80S and C181S/C184S Ras (not shown). However, the O2•−-dependent decrease in rhodamine fluorescence was not observed when either C51S or C51S/ C118S Ras was used instead of wt Ras or C118S Ras (Figure 5A). This result indicates that treatment with O2•− did not enhance dissociation of Cdc25 from C51S or C51S/C118S Ras. Accordingly, this result suggests that the targeting action of O2•− on Ras Cys51, but not on Ras Cys80, Cys118, Cys181, and Cys184, is linked to the perturbation of the binding interaction between Cdc25 and wt Ras.</p><p>Unlike the slow pace of the O2•−-mediated wt Ras nucleotide dissociation (Figure 2A), the O2•−-mediated wt Ras Cdc25 dissociation is more likely to be immediate (Figure 5A). This is possibly because the Ras Cdc25 binding interactions are not multilayered. Also, an increase in fluorescence intensity was observed after addition of either a radical quencher 5,5-dimethyl-1-pyrroline N-oxide (DMPO) to the O2•−-treated Cdc25 complexed with the rhodamine fluorescence-tagged wt Ras or C118S Ras (Figure 5A). Treatment with ascorbic acid (1 mM), instead of DMPO, showed the same result (not shown). The thiyl radical can be quenched by DMPO and ascorbic acid.51,52 Therefore, this result supports the involvement of a thiyl radical in the O2•−-mediated perturbation of the binding interaction between Cdc25 and wt Ras or C118S Ras. Given that Ras Cys51 is the target site of the oxidant that couples with the O2•−-mediated perturbation of this binding interaction, the thiyl radical is likely formed on the Ras Cys51 side chain. This result, therefore, discloses a radical formation as an essential step involved in the O2•−-mediated perturbation of the wt Ras Cdc25 binding interaction. In addition, the fact that both DMPO and ascorbic acid reverse the effect of O2•− on the wt Ras or C118S Ras Cdc25 complex raises the possibility of the reversability of the O2•−-mediated perturbation of the binding interaction between Cdc25 and Ras.</p><p>The values of the KD of O2•− for wt Ras and C118S Ras complexed with Cdc25, respectively, were determined to be 2.3 and 2.2 µM (Figure 5B). The O2•−-dependent changes in the rhodamine fluorescence intensity of C51S and C51S/C118S Ras complexed with Cdc25 were nevertheless negligible (Figure 5B). In light of these minimal changes, the values determined for the KD of O2•− for Ras and for C118S Ras complexed with Cdc25 may represent the sensitivity of the targeting action of O2•− on Ras Cys51 that interferes with both the Ras and C118S Ras binding interaction with Cdc25. Intriguingly, these KD values of O2•− for wt Ras and for C118S Ras complexed with Cdc25 are similar to those of the appKI values of O2•− for wt Ras and for C118S Ras in the presence of Cdc25 (Figure 3). This similarity suggests a hypothesis that the Ras Cys51-targeting action of O2•− interferes with the binding interaction of Cdc25 with Ras and that this interference is linked to the O2•−-mediated desensitization of wt Ras for Cdc25.</p><!><p>To determine the effect of oxidants on the catalytic function of the RhoGEFs, including Vav2 DPC and Dbs DH/ PH or vice versa, we examined the rate of Rac1 and RhoC GDP dissociation in the presence and absence of these GEFs and/or H2O2 and O2•−.</p><p>wt Rac1 GDP dissociation was enhanced by its GEF Vav2 DPC or KO2 alone (Figure 6). Treatment with SOD ended the KO2-mediated wt Rac1 GDP dissociation (Figure 6). These results suggest that either Vav2 DPC or O2•− derived from KO2 enables facilitation of the wt Rac1 GDP dissociation, which is consistent with previous results.23 The values of the rate constant and the span of the Vav2 DPC-mediated wt Rac1 GDP dissociation are, respectively, 6.9-fold smaller and 1.2-fold larger than the values of the rate constant and the span of the O2•−-mediated wt Rac1 GDP dissociation (Table 3). The difference in the rate constant values indicates that, under our experimental conditions, the rate of the wt Rac1 GDP dissociation by Vav2 DPC is much slower than the rate of dissociation of wt Rac1 GDP by O2•−. The difference in the span values indicates that, under these experimental conditions, the quantity of the wt Rac1 GDP dissociation by Vav2 DPC exceeds that by O2•−. However, as noted in Materials and Methods, this is simply because the quantity of concentration treated with O2•− (~3 µM) is insufficient to complete the wt Rac1 GDP dissociation.</p><p>wt Rac1 GDP dissociation was significantly enhanced by a combination of Vav2 DPC and O2•− (Figure 6 and Table 3). In contrast to what occurred with wt Ras with a combination of Cdc25 and O2•− (Table 1), the values of the rate constant and the span of the Vav2 DPC/O2•−-mediated wt Rac1 GDP dissociation were almost the sum of the values of the rate constant and the span of the Vav2 DPC-mediated wt Rac1 GDP dissociation plus the O2•−-mediated wt Ras GDP dissociation (Table 3). For such an approximation of the total sum to occur means neither O2•− nor Vav2 DPC, respectively, interferes with the catalytic action of Vav2 DPC or of O2•− on wt Rac1. These results, therefore, suggest that the catalytic action of Vav2 DPC and O2•− on the wt Rac1 GDP dissociation is preserved even if both Vav2 DPC and O2•− are present simultaneously.</p><p>The catalytic action of another GEF, Dbs DH/PH, on another redox-sensitive wt Rho GTPase, wt RhoC, was unperturbed by O2•− (Table 3). O2•− also failed to perturb the catalytic action of Dbs DH/PH on wt RhoA and on wt Cdc42 (not shown). Therefore, this conclusion concerning the action of Vav2 DPC on wt Rac1 GDP dissociation with the oxidant O2•− is also applicable to the catalytic action of Dbs DH/PH on the dissociation of GDP from wt RhoA, RhoC, and Cdc42 with O2•−.</p><p>The GDP dissociation from wt Rac1, wt RhoC, wt RhoA, and wt Cdc42 was not facilitated by H2O2 (not shown), which is consistent with the previous result.23 Similarly, H2O2 did not affect the Vav2 DPC or Dbs DH/PH-mediated GDP dissociation from these redox-sensitive wt Rho proteins (not shown). Taken together, these results suggest that the GDP dissociation from these redox-sensitive Rho proteins as well as the catalytic function of Vav2 DPC and Dbs DH/PH on these redox-sensitive Rho proteins are insensitive to H2O2.</p><!><p>This study shows that an oxidant, O2•−, inhibits the catalytic action of Cdc25—the catalytic core domain of RasGEFs—on wt Ras. Although not shown for clarity of presentation, •NO2 can be used to mimic this inhibitory effect of O2•− on the catalytic action of Cdc25 with wt Ras and its cysteine mutants. This function of O2•− or •NO2 is an intriguing addition to the previously known role of oxidants in regulating wt Ras activity.23,24 Because the use of Ras C51S as the substrate of Cdc25 nullified the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras, the apparent mechanism of this inhibitory effect lies in the Ras Cys51-targeting action of the oxidant. This action appears to cause wt Ras insensitivity to the Cdc25 of RasGEFs.</p><p>Unlike with O2•− and •NO2, H2O2 did not inhibit the catalytic action of Cdc25 on wt Ras. Taking into account that Ras Cys51 is a target site of the oxidant, this is consistent with the chemistry in which the side chain of Ras Cys51 that contains the sulfur atom does not react with H2O2 but does react with O2•− or •NO2. However, this result does not necessarily eliminate the role of H2O2 as a redox agent that modulates wt Ras activity with RasGEFs in cells. This is because H2O2 in cells can be converted into other oxidants such as a hydroxyl radical and a hydroxyl anion through the transition metal-mediated Fenton reaction.35 These free radicals from the Fenton reaction also are known to react with sulfur.9 Therefore, H2O2— through its derivation products but not in its original form— can function as an oxidant that can inhibit the catalytic action of Cdc25 on wt Ras.</p><p>Because Cdc25 is the catalytic core domain of many RasGEFs, including SOS, RasGRF, and RasGRP, the observed desensitization of wt Ras to Cdc25 by an oxidant represents the fundamental trait of the oxidant-dependent regulation of wt Ras activity associated with these RasGEFs. However, it is unclear if the oxidant has other effects on the catalytic action of Cdc25 on wt Ras through unexamined noncatalytic RasGEF domains. For example, it is uncertain whether the oxidant affects the function of the noncatalytic domain(s) of RasGEFs (e.g., SOS), such as the DH and PH domains. This study shows that, as a RhoGEF catalysis, the function of the DH domain in combination with the PH domain is unaffected by the oxidant (see the discussion below). However, this result does not necessarily indicate that an oxidant has no effect on the regulatory role of these noncatalytic domains in RasGEFs. The roles of these noncatalytic domains of RasGEFs in the current model are linked to the membrane anchorage of RasGEFs that is accompanied by RasGEF activation.18 Nevertheless, in assessing this current model, the apparent uncertainties about the oxidant-dependent regulation of the activity of RasGEFs via these noncatalytic domains of RasGEFs is not enough to overshadow the significance of the finding of the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras. This is because of the expected conservation of this inhibition feature regardless of any potential effects of the oxidant on these noncatalytic domains of RasGEFs. For example, if the oxidant does not perturb the functions of the noncatalytic domains of RasGEFs, the oxidant will continue to inhibit the catalytic action of Cdc25 on wt Ras. If the oxidant serves as a negative heterotropic effector by perturbing the membrane-anchorage functions of the noncatalytic domains of RasGEFs, RasGEFs cannot be recruited for the plasma membrane and activated. In this case, the oxidant inhibits the RasGEF activation before inhibition of RasGEFs' catalytic function. Therefore, the oxidant will continue to inhibit the catalytic action of Cdc25 on wt Ras. Finally, even if the oxidant serves as a positive heterotropic effector by enhancing functions of the noncatalytic domains of RasGEFs so as to enhance RasGEF membrane binding and RasGEF activation, the oxidant ultimately counteracts the RasGEF activation by inhibiting the catalytic action of RasGEFs on wt Ras. Therefore, RasGEFs will remain in an inactive state. In summary, regardless of any instances of the action of the oxidant on the noncatalytic domains of RasGEFs, no alteration would occur in the inhibitory effect of the oxidant on the catalytic action of RasGEFs. Therefore, although the roles of the oxidant in these noncatalytic domains of RasGEFs are yet to be investigated, the observed desensitization of wt Ras to Cdc25 by an oxidant is sufficient for it to be considered a factor in regulating the wt Ras activity associated with these RasGEFs, thereby controlling the Ras-dependent cell signaling cascades.</p><!><p>Although the oxidant can directly activate wt Ras via an enhancement of wt Ras GDP dissociation,23,24 the oxidant also can indirectly inhibit the RasGEF-mediated wt Ras activation through desensitization of wt Ras to the catalytic core domain Cdc25 of RasGEFs (this study). This redox regulation of wt Ras activity is more complicated than previously thought,9 but the result of this complexity in terms of wt Ras GDP dissociation is rather straightforward: The RasGEF-mediated enhancement of the GDP dissociation from wt Ras will only occur in the presence of RasGEFs when the oxidant is absent. When both the oxidant and RasGEFs are present, the oxidant desensitizes wt Ras to the catalytic core domains of RasGEFs to perturb the catalytic action of RasGEFs. At the same time, the oxidant retains its capability to enhance the dissociation of wt Ras GDP, thereby only continuing the oxidant-mediated enhancement of wt Ras GDP dissociation. These analyses infer that, even if there are two unrelated signaling events such as the nonredox and redox stimuli—for example, hormone- and oxidative stress-dependent, respectively—toward wt Ras, the Ras-dependent cellular signaling would not be overly upregulated. This would prevent the overresponse of the Ras-dependent cellular signaling cascades from multiple-signaling stimuli toward the wt Ras. Failure of the mechanism of the oxidant-mediated inhibition of the catalytic action on Ras (i.e., by Ras Cys51 mutation) triggers the two simultaneous, but unrelated, signaling events that result in overactivation of wt Ras. An overactivated wt Ras may possibly alter various Ras-dependent cellular effects, including cell survival, proliferation, and differentiation, in ways so as to produce certain diseases such as cancer.53 This analysis introduces the potential significance of the oxidant-mediated inhibition of the function of RasGEFs on wt Ras as a regulatory outlet that prevents overactivation of wt Ras as a cause of pathophysiological responses. Also, the dominant feature of the redox-dependent response of wt Ras compared with the nonredox-dependent response of wt Ras suggests that, where wt Ras-dependent cellular signaling cascades are concerned, the redox stimulus is somehow given more weight than the nonredox stimulus. The cellular meaning of this dominancy in regulating the wt Ras activity remains to be clarified.</p><p>The redox aspect of the intrinsic catalytic action of RasGEFs on the chemically modified form of wt Ras—such as wt Ras-SNO—is intriguing. The reason for this interest is because the oxidant was unable to enhance the GDP dissociation from wt Ras-SNO but nevertheless was able to desensitize wt Ras-SNO to the catalytic core domains of RasGEFs, resulting in inhibition of the RasGEF-mediated dissociation of GDP from wt Ras-SNO. Consequently, when an oxidant and RasGEFs are present simultaneously, the GDP dissociation from wt Ras-SNO cannot be accelerated. This notion implies that the oxidant can downregulate Ras-SNO regardless of the presence of RasGEFs. However, the appVmin value of the catalytic action of Cdc25 on C118S Ras occurs at a significantly high concentration of O2•− (near 30 µM). This suggests that a significantly high concentration of O2•− is required for it to complete the inhibition of the RasGEF action on wt Ras-SNO. Such a high concentration of O2•− occurs only in special cases, such as stimulated macrophages.54 Therefore, O2•− may not be completely inhibiting RasGEFs on wt Ras-SNO in the typical oxidative stress conditions of cells. However, although it could depend on cellular conditions, a complete inhibition of the RasGEF action on wt Ras is not necessary to achieve the minimal level of the cellular fraction of the GTP-bound form of wt Ras.55 Therefore, incomplete inhibition of RasGEFs by an oxidant that spurs a certain minimal level of activity by RasGEFs is sufficient to generate a basal level of cellular activity of wt Ras-SNO.</p><p>Although the cellular conditions necessary to produce wt Ras-SNO are yet to be clarified, we have found that a continuous treatment of bladder carcinoma (T24) and fibrosarcoma (HT1080) cells with the oxidant NO for at least 2 h produces wt Ras-SNO (unpublished results). Maximization of the formation of wt Ras-SNO can also be achieved by long-term treatment of NO (e.g., at least 1 day). Intriguingly, wt Ras-SNO was formed in 15 min by treatment of NIH 3T3 and PC12 cells with S-nitrosocysteine—another Ras S-nitrosation agent.56 This result in conjunction with our result suggests that, compared with the formation of wt Ras-SNO by NO, the formation of wt Ras-SNO by S-nitrosocysteine is likely effective in generating wt Ras-SNO. It is thus possible that the degree of efficiency in the formation of wt Ras-SNO depends on the type of oxidant. Nonetheless, when these findings are taken together, it can be postulated that the continuous presence of the oxidant not only results in the formation of wt Ras-SNO but also blocks GDP dissociation from the newly formed wt Ras-SNO. The outcome of this formation and blockage is production of a GDP-bound biologically inactive wt Ras-SNO. This postulation explains the enigmatic result of wt Ras inactivation by a long-term treatment of cells (>1 day) with NO.28–30 Accordingly, although a definitive finding awaits further studies, it is tempting to speculate that the extensive and continuous presence of the oxidant leads to severe oxidative stress that results in inactivation of wt Ras and shuts down wt Ras-mediated cellular signaling events. Failure to prevent prolonged oxidant-mediated wt Ras activation could result in continuation of the upregulation of the Ras-dependent cellular signaling events. Such deregulation could result in certain diseases such as cancer. Therefore, the pathophysiological significance of the formation of wt Ras-SNO and its inactivation mechanism may be to prevent continuous oxidative stress from overactivating Ras. This notion is supported by the relatively higher fraction of the GDP-bound form of wt Ras-SNO, compared with that of wt Ras, in NIH 3T3 and PC12 cells.56</p><p>Oxidant-mediated wt Ras inactivation may not occur when oxidative stress is not continuous. For example, a short burst of oxidative stress activated wt Ras instead of inhibiting it.57 In fact, a short-term treatment of cells with NO did not generate wt Ras-SNO (unpublished results). Therefore, a short and/or a one-time treatment of cells with H2O2 or other oxidants may be insufficient to generate an oxidized form of wt Ras (e.g., wt Ras-SNO) but may be sufficient to activate wt Ras via the redox-mediated wt Ras activation mechanism.9</p><!><p>This study shows that, among other Ras cysteines, the Ras Cys51 is involved in the oxidant-mediated interference with the wt Ras binding interaction with Cdc25. This interference results in desensitization of wt Ras to Cdc25. Such desensitization apparently inhibits the catalytic action of Cdc25 on wt Ras.</p><p>Figure 7 shows that two mechanistic steps are among the essential features of the process by which Cdc25 enhances the nucleotide exchange of wt Ras GTP ase.49,58 The first of these is the binding of Cdc25 to the GDP-bound wt Ras to produce the ternary wt Ras–GDP–Cdc25 complex. The formation of the ternary complex disrupts the binding interaction between wt Ras and GDP, resulting in release of the bound GDP to produce the wt Ras Cdc25 binary complex. The second step is the binding of the cellularly abundant GTP to the wt Ras complexed with Cdc25; this binding expels the bound Cdc25 from wt Ras to produce GTP-bound wt Ras. Given that an oxidant inhibits the catalytic action of Cdc25 on wt Ras that is an enhancement of the wt Ras-bound GDP, the oxidant evidently targets the ternary complex (Figure 7). Accordingly, the pattern of the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras can be classified as apparent uncompetitive. This apparent uncompetitive kinetic pattern suggests that the reaction of the oxidant with the ternary complex produces the radicalized wt Ras–GDP–Cdc25 ternary complex (wt Ras*–GDP–Cdc25) through the kinetic step of KI. Formation of wt Ras*–GDP–Cdc25 dodges the k2 step— the key catalytic step of the catalytic action of Cdc25 on wt Ras (Figure 7). This kinetic scheme also suggests that the more the oxidant is proportionate to the production of the radicalized wt Ras–GDP–Cdc25 complex, but the lesser the oxidant is proportionate to the turnover of the Cdc25-mediated wt Ras GDP dissociation via the k2 step. This relation defines the disproportionate feature of the KI value over the k2 value. Notably, the appKI value (2.3 µM [KO2], Figure 3) was determined by monitoring the value of the C118S Ras GDP dissociation (the k2 value) in the presence of the oxidant. Therefore, the appKI value that was determined essentially represents the value of KI of the oxidant for wt Ras–GDP– Cdc25 to produce wt Ras*–GDP–Cdc25.</p><!><p>Although the pattern of the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras can be defined as apparent uncompetitive, details of the role of Cys51 in this inhibition are unclear. As a target of the oxidant, the side chain of the Ras Cys51 in the ternary wt Ras–GDP–Cdc25 complex must be accessible to solvents. This possibility cannot be inspected because the structure of the ternary complex is unknown. However, the features of the available crystal structures before and after the ternary wt Ras–GDP–Cdc25 complex (wt Ras– GDP complex) and (wt Ras–Cdc25 complex) (Figure 7), respectively, suggest that the binding interaction of wt Ras with Cdc25 exposes the side chain of the Ras Cys51 to solvents. Such binding interaction is the key to the catalytic action of Cdc25 on wt Ras. Accordingly, it can be postulated that the oxidant, via targeting Ras Cys51, interferes with the wt Ras Cdc25 binding interaction and consequently restricts the catalytic action of Cdc25 on wt Ras. Furthermore, given the similarity of the value of the KD of the oxidant for the wt Ras-Cdc25 complex and that of the appKI of the oxidant for the ternary complex, the perturbation of the wt Ras Cdc25 binding interaction is likely the main factor that determines the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras.</p><p>Mechanically, the oxidant-dependent protein–protein binding interaction can be perturbed by either the state- or the process-based route. The mechanism associated with the state-based route herein refers to an outcome in which a chemical modification of the redox-sensitive cysteine and/or its relevant residue results in the alteration of a protein structure. This protein structural change perturbs its protein binding interaction with its counterpart. The mechanism of the process-based route within this article denotes that the reaction process between the oxidant and the redox-sensitive cysteine associated with its relevant residue(s) perturbs the protein binding interaction with its counterpart. In this mechanism, the chemical modification of the redox-sensitive cysteine and/or its relevant residue(s) occurs at the end of the process of the perturbation of the binding interactions between the protein and its counterpart. As for the redox regulation of wt Ras, the state-based mechanism was initially postulated for the oxidant-mediated enhancement of the wt Ras GDP dissociation coupled with the Ras-SNO formation. Similarly, the process-based mechanism was postulated as an alternative of the state-based mechanism to explain the oxidant-mediated enhancement of the wt Ras and wt Rho GDP dissociation without formation of the wt Ras-SNO.59 Nonetheless, based upon the currently available data, it is difficult to predict which of these routes best describes the mechanism of the oxidant-mediated inhibition of the catalytic action of Cdc25 on wt Ras.</p><p>The chemical modification and/or oxidation state of the Ras Cys51 side chain is of interest because it could directly support the involvement of Ras Cys51 with an oxidant in the perturbation of the wt Ras–Cdc25 binding interaction. However, our mass spectrometric analyses, which used both electrospray ionization and matrix-assisted laser desorption/ ionization time-of-flight approaches, did not detect any of the chemical modification/oxidation of the Ras Cys51 side chain under our experimental conditions. Nevertheless, this failure does not disprove the involvement of Ras Cys51 in the oxidant-mediated perturbation of the wt Ras–Cdc25 binding interaction. There is a precedent for this situation in which, although Ras Cys118 is typically a target of an oxidant to enhance the wt Ras GDP dissociation (which means Ras Cys118 is certainly involved in the oxidant-mediated enhancement of the wt Ras GDP dissociation), Ras Cys118 was not chemically modified/oxidized by the oxidant after the completion of the oxidant-mediated wt Ras GNE.59 It also is noteworthy that the lack of chemical modification/oxidation of the Ras Cys51 side chain does not necessarily indicate that any of these potential mechanisms fit the case of the oxidant-mediated perturbation of the wt Ras–Cdc25 binding interaction. To the contrary, the potential chemical modification/oxidation of the Ras Cys51 side chain does not support any of these mechanisms. This is because the state of the features of the chemical modification/ oxidation of the Ras Cys51 side chain does not necessarily couple with the structural change in wt Ras and/or Cdc25 nor does it necessarily couple with the mechanistic perturbation of the binding interaction between wt Ras and Cdc25. This argument is again based upon the case of the oxidant-mediated enhancement of the wt Ras GDP dissociation in which the oxidant-mediated Ras chemical modification—Ras-SNO formation—couples with neither the Ras structural change nor with the mechanistic perturbation of the binding interaction between wt Ras and a nucleotide.9</p><!><p>Studies show that the GDP binding interactions of certain wt Rho GTPases, including wt Rac1 as well as wt RhoC, wt RhoA, and wt Cdc42, are redox sensitive.9,23 This study shows that, in contrast to the effect of O2•− or •NO2 on Cdc25 with wt Ras, O2•− or •NO2 is unable to inhibit the catalytic action of Vav2 DPC on wt Rac1. Vav2 DPC is the wt Rac-specific RhoGEF that possesses a catalytic domain as well as the regulatory domains of Vav. Hence, regulation of the catalytic activity of Vav associated with its regulatory domains is likely to be insensitive to O2•− and •NO2.</p><p>This study also shows that neither O2•− nor •NO2 inhibits the catalytic action of Dbs DH/PH on wt RhoC or wt RhoA. Dbs DH/PH is the catalytic domain of Dbs that is a wt RhoA-and wt RhoC-specific RhoGEF. Hence, although it is clear that the catalytic function of Dbs is unaffected by O2•− or •NO2, the potential redox role of other known or unknown regulatory domains of Dbs is of interest because the Dbs regulatory domain(s) can influence the catalytic activity of Dbs. A previous study showed that using oxidant NO in the long term treatment of SUM and wt RhoC-overexpressed primary human mammary epithelial cells did not block the loading of a nucleotide analog, 6-thioguanine nucleotide, to wt RhoC.9 Notably, these SUM cells treated with NO were exposed to O2,9 and thus, it can be safely assumed that at least some portion of the treated NO reacts with O2 to produce •NO2 and higher oxides.9 Accordingly, the generation of the 6-thioguanine nucleotide-bound wt RhoC in these cells likely was solely because the catalytic action of Dbs was uninhibited despite the presence of the oxidant •NO2. Taking into account that the Dbs expressed constitutively in these cells is a full construct that contains catalytic and regulatory domains, the results and analysis together suggest that the catalytic function of Dbs was not inhibited by an oxidant despite the presence of the Dbs regulatory domains. Hence, it can be postulated that, as with Vav, an oxidant such as O2•− or •NO2 does not influence the catalytic function of Dbs in association with its regulatory domains.</p><!><p> Notes </p><p>The authors declare no competing financial interest.</p><p>5,5-dimethyl-1-pyrroline N-oxide</p><p>Dbl homology</p><p>Dbl's big sister</p><p>Dbs with DH and PH domains</p><p>GTPase activating proteins</p><p>guanine nucleotide exchange factors</p><p>Harvey Ras</p><p>Pleckstrin homology</p><p>Ras-specific GEFs</p><p>Rho-specific GEFs</p><p>S-nitrosated Ras</p><p>superoxide dismutase</p><p>the regression values</p><p>tritium-labeled guanosine diphosphate and</p><p>Vav2 with DH, PH, and cysteine-rich domains</p><p>Evaluation of the kinetic rate constant associated with the span of the reaction. Each line represents a reaction with (a) a 0.5 rate constant and a 0.5 span; (b) a 1.0 rate constant and a 0.5 span; (c) a 0.5 rate constant and a 1.0 span; and (d) a 1.0 rate constant and a 1.0 span.</p><p>Effect of oxidants on the Cdc25-mediated GDP dissociation from wt Ras and C118S Ras. (A) Independent triple filter-binding assays were performed to measure the radioactivity of the [ H]GDP that remained to bind to Ras after treatment of the [3H]GDP-loaded wt Ras (1 µM) with or without a regulator(s), including Cdc25 (50 nM) and/or KO2 (~3 µM), for the times given in Materials and Methods. (B) The identical independent triple filter-binding assays with or without the regulator(s), as described for panel A, also were performed for the [ H]GDP-loaded C118S Ras (1 µM). All of these triple measurements of radioactivity values measured at different times were normalized against the radioactivity value of the initial sample mixture (time = 0 s), which was set at 1.0. The one-phase exponential decay model (P < 0.05) was used to perform F tests on each data set of the triple measurements. The F tests indicated there was no significant curve difference within any data set of the triple measurements. Accordingly, mean values and their corresponding SD from each of the triple measurements are represented in panels A and B of this figure. The one-phase exponential decay model (P < 0.05) was used to obtain kinetic values, including kinetic rate constants and spans from the plots, for global fits for each of the triple data sets. Global fits give kinetic values and SD with r2 of fit of >0.9050. These values are summarized in Table 1.</p><p>Determination of the apparent inhibition constant of KO2 for C118S and C51S/C118S Ras in the presence and absence of Cdc25. Independent triple equilibrium titrations of [ 3H]GDP-loaded C118S and C51S/C118S Ras (1 µM) with various concentrations of KO2 (between 0 and 20 µM) were performed in the presence and absence of Cdc25 (50 nM). The KO2-treated samples were then incubated for 250 s, and their radioactivity values associated with the Ras-bound [3H]GDP were determined as described in Figure 2. All radioactivity values measured were normalized against the radioactivity value of the Ras sample without treatment of KO2. This radioactivity value was set at 1.0. The F tests with a linear regression model (P < 0.05), but not the hyperbola model (P < 0.05), support one curve for each set of the triple data of C118S and C51S/C118S Ras with KO2 in the absence of Cdc25. Mean values and the SD from each of the triple measurements of C118S and C51S/C118S Ras with KO2 in the absence of Cdc25 are shown in this figure. The F tests (P < 0.05) for each data set of the triple measurements of C118S and C51S/C118S Ras with KO2 in the presence of Cdc25 indicate the insignificant curve difference within each of these triple measurements. The global fits for each of these triple data with the hyperbola model (P < 0.05) determined the KO2 concentrations that give appVmin values of the catalytic action of Cdc25 on C118S and C51S/C118S Ras, respectively, to be 27 ± 7 and 6 ± 2 µM. The global fitting also gave appKI values of KO2 for C118S and C51S/C118S Ras in the presence of Cdc25, respectively, of 2.3 ± 1 and >100.7 ± 34 µM [KO2]. The r2 values associated with fit were >0.9065. Note that when the O2•− concentrations were higher than ~10 µM, these Ras proteins were partly denatured. This Ras denaturation complicates fitting these values to a curve. Therefore, kinetic values beyond O2•− concentrations higher than ~10 µM were ignored for ease of fit to the curve. However, as a way to present the original data, the kinetic values associated with O2•− concentrations beyond 10 µM, including 20 µM, are shown in this figure.</p><p>Effect of KO2 on the Cdc25-mediated GDP dissociation from C51S and C51S/C118S Ras. (A) All experimental methods and data analysis procedures were identical to those described in Figure 2, except that C51S Ras was used instead of wt Ras and C118S Ras. (B) The same experiments and analyses that are described for panel A also were performed for C51S/C118S Ras instead of C51S Ras. The F tests indicate that the curve differences are insignificant within the curve of each of the triple measurements associated with C51S and C51S/ C118S Ras in the presence and absence of an effector(s). Therefore, all values within this figure are shown with mean values and the SD from the independent triple measurements. Global fits for all triple data with the one-phase exponential decay model (P < 0.05) also were performed that gave kinetic values and their corresponding SD. All kinetic values determined are summarized in Table 2. The r2 values of fit were >0.9015.</p><p>Determination of the KO2-mediated perturbation of Cdc25 binding interaction with wt Ras, C118S Ras, and C51S/C118S Ras. (A) Cdc25 complexed with rhodamine fluorescence tagged-wt Ras, -C118S Ras, and -C51S/C118S Ras (1 µM) was treated with various concentrations of KO2 (between 0 and 20 µM), as indicated by the arrows. The corresponding changes in fluorescence intensity were monitored. When necessary, a radical quencher DMPO (1 mM) or ascorbic acid (1 mM; not shown) was added after treatment with KO2, as indicated by the arrows. (B) To ensure confidence in the results, the experiments shown in panel A were repeated two more times. The changes in fluorescence intensities of these triple measurement data sets were plotted against the KO2 concentrations. The F tests with a hyperbola model (P < 0.05) support one curve for each of triple data sets. Hence, the fluorescence values are shown in this figure with mean values and the SD from independent triplicate measurements. The global fits with a hyperbola model (P < 0.05) gave the apparent dissociation constants of KO2 for the wt Ras—Cdc25, C118S Ras— Cdc25, C51S/C118S Ras—Cdc25, and C51S Ras—Cdc25 binary complexes. These constants are, respectively, 2.3 ± 0.1, 2.2 ± 0.1, >20.6 ± 0.9, and >20.6 ± 0.8 µM [KO2] with r2> 0.9095.</p><p>Effect of KO2 on the Rho GEF-mediated GDP dissociation from wt Rac1. The experimental and analytical methods were identical to those used in Figure 2, except that wt Rac1 (1 µM) and its GEF, Vav2 DPC (100 nM), were used instead of wt Ras and Cdc25. The F tests with a hyperbola model (P < 0.05) indicate that the curve differences within each of the triple data sets are insignificant. Therefore, mean values and the SD from each of the independent triple measurements are presented in this figure. The global fits for each of these triplicate data with the hyperbola model (P < 0.05) gave kinetic values and their corresponding SD. The values determined for the apparent GDP dissociation rates of Rho proteins in the presence and absence of a regulator(s) are summarized in Table 3. The r2 values of all analyses were >0.9065.</p><p>Proposed kinetic mechanism of the oxidant-mediated inhibition of the RasGEF action on Ras. An apparent uncompetitive inhibition of the oxidant for the catalytic action of Cdc25 on wt Ras is shown with several kinetic constants. The binary wt Ras-GDP complex binds Cdc25 to produce the ternary wt Ras–GDP–Cdc25 complex, and this step couples with an equilibrium association constant K1. The step represented by the rate constant k2 that produces the Ras–Cdc25 binary complex is the rate limiting step for the catalytic action of Cdc25 on wt Ras. The cellularly abundant GTP displaces the wt Ras bound Cdc25 to produce the GTP-bound wt Ras. When the inhibitor—an oxidant—exists, through the step of KI, the ternary wt Ras–GDP–Cdc25 complex reacts with the oxidant to produce the radicalized ternary wt Ras–GDP–Cdc25 complex (ternary wt Ras*–GDP–Cdc25 complex). The buried Ras Cys51 side chain in the cartoon figure of the binary wt Ras–GDP complex (PDB 1AGP) is shown with a dotted arrow (left). The solvent-exposed Ras Cys51 side chain in the cartoon figure of the binary wt Ras–Cdc25 complex (PDB 1BKD) is indicated with a dotted arrow (right). These figures were generated using The PyMOL Molecular Graphics System, Version 1.6 Schrödinger, LLC.</p><p>Kinetic Parameters for the GDP Dissociation from wt Ras, C118S Ras, and wt Ras-SNO in the Presence and Absence of Cdc25, KO2, SOD, and/or and H2O2a</p><p>The values with SD of the rate constant and the span of GDP dissociation from wt Ras and C118S Ras with and without Cdc25 and/or KO2 were taken from Figure 2. The values with SD of the rate constant and the span of GDP dissociation from wt Ras and C118S Ras, with and without Cdc25 in the presence of KO2 and SOD, were obtained, with one exception, as described in Figure 2. The exception is that the Ras-containing assay vial was pretreated with SOD (5000 units), as noted in Materials and Methods. The values with SD of the rate constant and the span of GDP dissociation from wt Ras and C118S Ras, with and without Cdc25 in the presence of H2O2, were obtained as described in Figure 2, except that H2O2 (10 µM) was used instead of KO2. All listed values with SD of the rate constant and the span of GDP dissociation from wt Ras-SNO, with and without Cdc25, KO2, and/or H2O2 in the presence and absence of SOD, also were determined, with one exception, as described in Figure 2 and in this Table 2; the exception was the use of wt Ras-SNO instead of C118S Ras. To examine the significance of the potential similarity or difference among these rate constant values listed in Table 1, t tests with P < 0.05 were performed as described in Materials and Methods. Briefly, any values denoted by the letter "a" correspond to other values denoted with "a". The same is true for the values denoted with the letters "b", "c", "d", and "e". However, any values denoted with "a" differ from the values denoted by "b", "c", "d", and "e". The same applies for "b" with "c", "d", and "e"; and for "c" with "d" and "e"; and for "d" with "e". All of the t test results associated with the rate constants were exactly the same with the t test results for the corresponding span values. Therefore, for clarity of presentation, the t tests for the span value analyses are not shown. ND, not determined.</p><p>Kinetic Parameters for the GDP Dissociation from Full-Length wt Ras and Various Ras Cysteine Mutants in the Presence and Absence of Cdc25 and/or K02a</p><p>Data for the rate constants and the spans of GDP dissociation with the SD from CS1S and CS1/C118S Ras mutants were taken from Figure 4. The values with SD of the rate constants and the spans of GDP dissociation from C80S and C181S/C184S Ras mutants were obtained as described in Figure 4, except that C80S and C181S/C184S Ras mutants were used instead of CS1S and CS1/C118S Ras mutants. As with the values in Table 1, t tests with P < 0.05 were performed to evaluate the potential similarities or differences among the kinetic values. Table 2 is a continuation of Table 1. Therefore, the letters adopted in Table 1 continue to be used in Table 2. Also, the implications of the letters in Table 2 are exactly the same as in Table 1. For example, data denoted by the letter "a" in Table 2 are the same as the values denoted with "a" in Tables 1 and 2. Conversely, data denoted with a letter "a" in both Tables 1 and 2 differ from other values denoted with other letters, such as "b", in both Tables 1 and 2. This also applies to other letters in Tables 1 and 2. Notice that the letter "e" in Table 1 does not occur in Table 2. This is because Table 2 contains no equivalent value associated with the letter "e" of Table 1. Finally, there is no comparable value in Tables 1 and 2 for the value with the letter "f of Table 2 within Tables 1 and 2.</p><p>Kinetic Parameters for the GDP Dissociation from wt Rac1 and wt RhoC in the Presence and Absence of Vav2 DPC or Dbs DH/PH and/or KO2a</p><p>The kinetic values of the rate constants and the spans for GDP dissociation from wt Rac1, in the presence and absence of Vav2 DPC and KO2, were taken from Figure 6. The kinetic values of the rate constants and the spans for GDP dissociation from wt RhoC in the presence and absence of Dbs DH/PH and KO2 also were obtained as described in Figure 6, except that wt RhoC was used instead of wt Rac1. To evaluate the significance of the potential similarities and differences among the rate constant values listed within Table 3, t tests with P < 0.05 were performed as described in Materials and Methods. Any rate constant values that refer to the letter "a" are the same as other values coupled with the same letter "a". This also applies to all other letters used within Table 3. However, any values denoted with "a" differ from the values denoted with "b" and "c". The values denoted by "b" also differ from the values associated with the letter "c". For presentation clarity, only the t tests for the rate constants are shown. However, all of the t test results associated with the rate constants were exactly the same as the t test results for the span values that correspond to the rate constants. ND, not determined.</p>

PubMed Author Manuscript

Chiroptical inversion of a planar chiral redox-switchable rotaxane

A tetrathiafulvalene (TTF)-containing crown ether macrocycle with C s symmetry was designed to implement planar chirality into a redox-active [2]rotaxane. The directionality of the macrocycle atom sequence together with the non-symmetric axle renders the corresponding [2]rotaxane mechanically planar chiral. Enantiomeric separation of the [2]rotaxane was achieved by chiral HPLC. The electrochemical propertiescaused by the reversible oxidation of the TTFare similar to a non-chiral control. Reversible inversion of the main band in the ECD spectra for the individual enantiomers was observed after oxidation. Experimental evidence, conformational analysis and DFT calculations of the neutral and doubly oxidised species indicate that mainly electronic effects of the oxidation are responsible for the chiroptical switching. This is the first electrochemically switchable rotaxane with a reversible inversion of the main ECD band.

chiroptical_inversion_of_a_planar_chiral_redox-switchable_rotaxane

Introduction<!>Synthesis and characterisation<!>Optoelectronic properties<!>Enantiomer separation on chiral HPLC and CD spectroscopy<!>Conclusions

<p>Evidenced by the homochirality in our biosphere, [1][2][3] chirality is a fundamental principle, which governs the molecular recognition and activity of virtually all biomolecules. Therefore, gaining control over the preferred isomer of a molecule or an assembly by carefully designing a molecular system is a worthwhile endeavour.</p><p>The term "chiroptical switch" has been used by Canary to refer to molecules, which are capable of "changes in their interaction with polarized light". 4 Potential applications are information processing, data storage and sensing. In this context, the ground breaking work of Feringa and co-workers [5][6][7] on overcrowded alkenes, which act as light triggered chiroptical switches was awarded with the Nobel Prize in chemistry 2016 "for the design and synthesis of molecular machines" 8 and underlines the general interest in this topic.</p><p>Mechanically interlocked molecules (MIMs) [9][10][11][12] consist of parts that can move relative to each other guided by intramolecular forces. Therefore, we envisioned them to be ideal candidates for chiroptical switches in which coconformational or even congurational changes in the MIM occur.</p><p>An achiral wheel with directionality in its atom sequence forms a chiral [2]rotaxane, when threaded onto a directional Scheme 1 (a) Reversible one-electron oxidations of the TTF moiety, (b) reversible oxidation of a directional crown ether wheel bearing a TTF unit, (c) chiroptical switching of the planar chiral [2]rotaxane enantiomers.</p><p>axle (Scheme 1). In 1997, Vögtle et al. reported on the rst resolution of a racemate of such mechanically planar chiral rotaxanes. 13 Chiral rotaxanes may be chiral from inclusion of classical stereogenic elements or by virtue of being mechanically planar chiral. Since then, several examples followed, [14][15][16][17][18][19][20][21][22][23][24][25] in which the mechanically interlocked structure was used to induce directionality in polymers, [26][27][28] for sensing, [29][30][31] and to act as an enantioselective catalyst. 32 Today, sophisticated synthetic protocols allow an efficient enantioselective synthesis. For example, Goldup and co-workers 33,34 described elegant protocols to synthesise planar chiral enantiopure [2] rotaxanes using readily available chiral auxiliaries. However, switchable planar chiral rotaxanes remain rare. So far, the modulation of chirality relies on heat, 21 the choice of solvent, anion exchange, 35 or pH. 36 Recently, we described redox-switchable rotaxanes, in which the wheels are decorated with tetrathiafulvalenes (TTF). [37][38][39][40][41] TTF can be reversibly oxidised to the TTFc + and TTF 2+ states (Scheme 1). Large-amplitude motion and co-conformational changes in (oligo)rotaxanes were triggered by redox chemistry. 38,[42][43][44][45][46][47][48][49][50] Apart from rotaxanes, TTF derivatives with covalently bound chiral substituents exhibited a chiroptical response to a change of their redox-state. [51][52][53][54][55][56][57] Hence, our switchable rotaxanes display ideal optoelectronic properties since they are air stable in their neutral and oxidised form and show a clear-cut optical output, 37 which is even visible by the naked eye.</p><p>In this paper, we report the synthesis, characterisation and optical resolution of a new mechanically planar chiral tristable [2]rotaxane based on the 24-crown-8/secondary ammonium binding motif. 58 The rotaxane consists of the directional wheel dTTFC8 (Scheme 2), which is derived from a C 2v -symmetric TTF-decorated crown ether TTFC8 (Scheme 2) published by our group recently. 38 ECD measurements show reversible chiroptical switching, which can be explained mainly by electronic changes. The measurements are supported by quantum chemical calculations, which were also used to determine the absolute conguration. To the best of our knowledge, this is the rst example of a chiroptical switch with a complete sign reversal of the main band in the ECD spectra based on electronic changes in a mechanically bound assembly.</p><!><p>The prerequisite for rotaxane formation is a sufficiently high binding constant between the crown ether and the ammonium axle. ITC experiments revealed an association constant of K a ¼ (3.6 AE 0.3) 10 5 M À1 and a 1 : 1 stoichiometry for pseudorotaxane formation from dTTFC8 and axle A1 (Scheme 2). The binding constant is very similar to that of our previous non-directional TTF-decorated wheel TTFC8 (K a ¼ (4.4 AE 0.4) 10 5 M À1 , for thermodynamic parameters see ESI, † Section 4), 38 which indicates the positional change of the TTF unit not to signicantly affect the binding properties of the wheel.</p><p>As for the non-chiral [2]rotaxane 1, rotaxane formation was achieved with nitrile-oxide stopper St1 using a catalyst-free end-capping protocol established by Takata and co-workers 59 yielding a racemic mixture of rotaxane (rac)-2 (73%). The nonionic version (rac)-2Ac (95%) was obtained through N-acylation with Ac 2 O 60 (Scheme 2). The 1 H NMR spectra of (rac)-2 and (rac)-2Ac (Fig. 1) reveal a diastereotopic splitting of the macrocycle's methylene protons as well as of the axle methylene protons H h . 37,38 The splitting of both macrocycle and axle protons is characteristic for the formation of a chiral, yet racemic [2]rotaxane. Isoxazole formation during stopper attachment leads to a strong downeld shi of 3.88 ppm for proton H i .</p><p>In (rac)-2, the S-methyl protons on dTTFC8 split into two singlets of the same intensity. Comparable rotaxanes also showed this behaviour on the same position. 27,28 HR-ESI mass and tandem MS experiments support the interlocked architecture (Fig. S1 †).</p><p>For non-ionic (rac)-2Ac, the shi of H i (Dd ¼ +0.28 ppm) and H h (Dd ¼ +0.76 ppm) relative to (rac)-2 suggests that the wheel translates towards the isoxazole moiety in the absence of attractive interactions with the ammonium ion. Two sets of signals are observed due to the cis-trans isomerism of the amide bond in (rac)-2Ac. Variable temperature NMR experiments (Fig. S3 †) in DMSO-d 6 reveal the same barrier (DG ‡ ¼ 74 AE 2 kJ mol À1 ) for amide cis-trans isomerisation as observed for a similar acetylated rotaxane.</p><!><p>Photometric titrations of (rac)-2 and (rac)-2Ac with Fe(ClO 4 ) 3 (Fig. 2a and b) show similar bands for the three redox states (TTF, TTF + c and TTF 2+ ) [61][62][63] of both rotaxanes with distinct isosbestic points. These ndings are consistent with structurally related rotaxanes featuring a non-directional TTF-decorated wheel. 38 Cyclovoltammetric (CV) experiments were conducted with dTTFC8, (rac)-2 and (rac)-2Ac in dichloromethane (Fig. 2c). The potentials for (rac)-2 (116 mV and 407 mV) are considerably higher for both oxidation steps as compared to dTTFC8 (64 mV and 362 mV). Both oxidations are thus energetically disfavoured because of the charge repulsion between the TTF cation radical as well as the TTF dication and the ammonium station. In case of (rac)-2Ac (18 mV and 392 mV) the rst oxidation is more easily accomplished in comparison to the free macrocycle and the second oxidation is disfavoured. We attribute this behaviour to a stabilising interaction with the isoxazole moiety on the axle for the rst oxidation.</p><p>For the second oxidation, the limited accessibility of the TTF 2+ by counterions caused by the steric demand of the axle needs to be taken into account. Again these trends were already observed for the non-directional macrocycle and rotaxanes thereof. 38 The reversibility of the redox-waves of (rac)-2 and (rac)-2Ac strongly indicated that the interlocked structures remain intact during the redox switching, however it is reasonable to assume conformational changes to occur due to charge repulsion and charge stabilisation. The data does not show any signicant change in the electrochemical properties by introducing directionality into the TTF decorated wheel.</p><!><p>The two enantiomers of (rac)-2Ac could be separated using HPLC with a CHIRALPAK® IA stationary phase. The optical purity was determined (>99% ee; Fig. 3a) and mirror-image CD spectra were obtained for the neutral enantiomers with bands at 242 nm and 325 nm (Fig. 3b). We assigned the absolute conguration based on the computational results (see below). The oxidised species 2Acc + and 2Ac 2+ show bands at the same wavelengths. While no sign inversion occurs at 325 nm, the band at 242 nm exhibits a sign inversion during the rst and a signicant intensity increase during the second oxidation step. To exclude decomposition to be responsible for the switching, 2Ac 2+ was reduced back to the neutral state using Zn dust and then showed the initial CD spectrum again (Fig. 3d and e dashed lines). Surprisingly, no other CD signals are observed at a higher wavelength, although the change in UV/Vis absorption is most pronounced at 460 nm and 844 nm for the radical cation and at 703 nm for the dication (Fig. 2b). The reason for the sign change remains ambiguous. In fact, conformational changes were observed to induce transitions in CD spectra of non-interlocked TTF derivatives with centrochiral elements earlier. 53,64 Other examples show varying intensities 54 or shis of the maxima 56 upon oxidation of the TTF attached. Nevertheless, no TTF derivative is reported that shows a sign reversal in the maximum of an ECD spectrum without a shi in the wavelength. Apart from TTF derivatives, chiroptical switching via a redox process can be achieved with catechol, 65 viologen, 66 and tetraarylethylene 67 building blocks. Intense switching with a sign reversal was also observed for a viologentype dicationic helquat. 68 Chiral inversion can also be achieved with metal ion complexation 69,70 acid-base-71 and photoswitching. 6,68,72 Computational results</p><p>To investigate whether the redox-induced sign inversion at 242 nm in the ECD spectra of (R mp )-2Ac is due to a change in its electronic properties or to a (co-)conformational change, density functional theory (DFT) calculations were performed at the TPSS-D3(BJ) [73][74][75] and uB97X-D3 (ref. 76) levels. Conformational analyses reveal the structure depicted in Fig. 4 (le) to be the most stable one for (R mp )-2Ac. It is at least 18 kJ mol À1 more favourable than any other possible conformation found by theory (see Table S2 †). For (R mp )-2Ac 2+ , there are two conformations relatively close in electronic energy: Conformer A (Fig. 4 middle) and B (Fig. 4 right) with a ipped naphthalene unit, ca. 9 kJ mol À1 more stable than A. This conformational change is explained by the oxidation of (R mp )-2Ac occuring fairly localised at the TTF unit. 77 The emerging charge of the oxidised TTF moiety is then stabilised by the naphthalene that moves into close proximity of the TTF 2+ . Additionally, an atoms-inmolecules (AIM) analysis suggests that the electrostatic attraction between the naphthalene and TTF moieties outweighs all other non-covalent interactions for (R mp )-2Ac 2+ , while the maximisation of non-covalent interactions (C-H/p and p-pstacking) is the most important factor in the neutral state (see ESI † for details).</p><p>The simulated CD spectra in Fig. 4 were obtained using simplied time-dependent DFT 78 at the uB97X-D3 level. The spectrum of (R mp )-2Ac shows a deviation of around 40-50 nm, while that of (R mp )-2Ac 2+ is off by less than 20 nm compared to experiment. The experimentally detected sign inversion at 242 nm is reproduced well by the calculations. The conformational change of (R mp )-2Ac upon oxidation, however, hardly inuences the shape of the CD spectra as both conformations yield very similar CD spectra in the region between 230 and 400 nm. Therefore, we exclude the conformational change as the prime origin of the sign inversion.</p><p>To rationalise the optical behaviour of (R mp )-2Ac and (R mp )-2Ac 2+ , we examined its valence electronic structure, which is, as expected, dominated by orbitals localised at the TTF moiety (see Fig. S20 †). Analysing the electronic transitions in the spectral region between 230 and 400 nm reveals that practically every excitation involves the TTF unit to some extent. While many transitions are of local nature, i.e., between orbitals in close proximity, quite a few display a chargetransfer-like behaviour (insets Fig. 4 and S21 †). For neutral (R mp )-2Ac, the vast majority of these transitions can be described by advancing an electron from an orbital centred at the TTF core, usually the HOMO, into an orbital located in another part of the rotaxane (e.g. the dimethoxy-phenyl moiety). For (R mp )-2Ac 2+ , the corresponding transitions progress from some orbital in the molecule into an orbital localised at the TTF moiety, usually the LUMO or LUMO+1. This induces differently oriented magnetic dipole transition moments leading to different signs in the CD spectrum. Hence, we conclude that the sign inversion in the CD spectra upon oxidation can be exclusively attributed to the change of the electronic structure.</p><!><p>In conclusion, electrochemically switchable crown ether/ ammonium [2]rotaxanes bearing a directional wheel are reported. The wheel features a redox-switchable TTF unit. The directionality had no observable impact on the electrochemical and optical properties of the racemic mixtures determined by UV/Vis spectroscopy and CV measurements. Instead, the pure enantiomers of the acetylated non-ionic derivatives display a redox-induced reversible inversion of the sign in the ECD spectrum without a change of absolute conguration. The mechanism and the absolute conguration of this chiroptical switch has been examined by computational methods. While co-conformational changes have hardly any impact on the ECD spectra, the changes in electronic structure induced by oxidation play a pivotal role. These results underline the impact of the mechanical bond, which allows the construction of intriguing switchable chemical assemblies with unexpected properties. This is the rst in class example of a redoxcontrolled chiroptical switch with a complete sign reversal based on a mechanically planar chiral rotaxane. In the future, these properties could be employed in materials science to construct novel optoelectronic building blocks.</p>

Royal Society of Chemistry (RSC)

Visualizing and trapping transient oligomers in amyloid assembly pathways

Oligomers which form during amyloid fibril assembly are considered to be key contributors towards amyloid disease. However, understanding how such intermediates form, their structure, and mechanisms of toxicity presents significant challenges due to their transient and heterogeneous nature. Here, we discuss two different strategies for addressing these challenges: use of (1) methods capable of detecting lowly-populated species within complex mixtures, such as NMR, single particle methods (including fluorescence and force spectroscopy), and mass spectrometry; and (2) chemical and biological tools to bias the amyloid energy landscape towards specific oligomeric states. While the former methods are well suited to following the kinetics of amyloid assembly and obtaining low-resolution structural information, the latter are capable of producing oligomer samples for high-resolution structural studies and inferring structure-toxicity relationships. Together, these different approaches should enable a clearer picture to be gained of the nature and role of oligomeric intermediates in amyloid formation and disease.

visualizing_and_trapping_transient_oligomers_in_amyloid_assembly_pathways

<!>Introduction<!>Solution NMR<!>Single particle and non-ensemble averaged methods<!>Trapping transient oligomers to facilitate the characterization of amyloid self-assembly<!>Sample preparation strategies<!>Using antibodies to probe the structure and toxicity of oligomers<!><!>Stabilizing oligomers using non-covalent small molecules<!>Covalent ligands and protein functionalization<!><!>Covalent ligands and protein functionalization<!>Crosslinking strategies<!>Conclusion<!>Declaration of competing interest<!>Acknowledgements<!>Author contributions

<p>Methods to study structure, toxicity, and kinetics of transient amyloid oligomers.</p><p>NMR and single particle methods can characterize lowly-populated oligomers.</p><p>Chemical tools/antibodies stabilize oligomers for structural and toxicity studies</p><p>A combination of methods is needed to fully characterize amyloid assembly pathways.</p><p>Understanding the complex mechanisms of amyloid fibril assembly using "non-perturbing" biophysical methods. A: A schematic of a generic protein self-assembly pathway. The self-association of particular proteins can lead to the formation of cross-β fibrillar structures (amyloid fibrils) but can also lead to the formation of aggregates which lie "off-pathway" from fibril assembly. Assembly intermediates are often lowly-populated, rapidly interconverting, and transiently formed, making them challenging targets for many biophysical techniques, with notable exceptions being NMR (B, C) [[31], [32], [33], [34], [35]] and methods which detect single particles or species (D, E) (e.g. single particle fluorescence - including FRET and 2-color incidence detection, TCCD - [36,37], SPFS [38], and ESI-MS [[39], [40], [41]]). Monomer-oligomer exchange rates and oligomer populations (poligomer) can be obtained through the global fitting of oligomerization models to the observed NMR or single particle data (B, D). The structural information obtained through NMR and single particle/species methods is typically of low resolution but can provide insights into oligomerization interfaces (C), and structural transitions (E). The DEST and PRE data shown in B and C, respectively, were simulated by numerically solving the corresponding McConnell equations using a B1 field of 200 Hz, R2B = 1000 s−1, R2A = 10 s−1, and R1A = 1.5 s−1. The PRE data shown in C were simulated with a distance between residue 160 and the MTSL label (on residue 20) of 1 Å in the excited state (5% population). The black line in the collisional cross-section plot in E represents the expected cross-sections for each oligomer size, assuming isotropic growth, and the dashed red box indicates the point in the self-assembly pathway at which the oligomers of this protein start to undergo structural transitions, as detected by IMS coupled to ESI-MS [17,41]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</p><!><p>For many disease-associated amyloid proteins, it has been recognized that soluble oligomers which form during, or as a result of, fibril assembly can be the major cytotoxic species associated with cellular dysfunction and disease onset [[5], [6], [7], [8], [9], [10]]. Consequently, there has been intense interest in the study of such assembly intermediates, with the aim to better understand the molecular mechanism(s) by which soluble oligomers form and transition into a cross-β structure, as well as to identify structural features associated with cytotoxicity [11]. Unfortunately, the complexity and heterogeneity of amyloid assembly pathways makes such analyses immensely challenging in vitro, let alone in vivo. Additionally, it is difficult to reconcile the vast range of oligomers observed by different research groups under varying experimental conditions. Oligomeric intermediates are typically metastable, lowly-populated, and interconverting with each other and fibril surfaces within the aggregating mixture [12,13]. As a consequence, the properties of specific oligomers cannot be readily determined in detail using most bulk solution methods, as such approaches typically do not allow information to be extracted about individual species within these diverse populations. The structural and kinetic study of oligomeric intermediates thus requires the use of techniques capable of dissecting the properties of individual species within complex mixtures, coupled with careful data analysis to extract the relevant information about their population, lifetime, and structural features. Some of the most powerful methods include those which can directly detect single particles (such as single particle fluorescence, e.g. fluorescence resonance energy transfer (FRET) [14,15], and single particle force spectroscopy (SPFS) [16]) or single species (such as electrospray ionization mass spectrometry (ESI-MS) [[17], [18], [19], [20]]). Solution-phase nuclear magnetic resonance (NMR) spectroscopy, which is unique amongst ensemble techniques for its ability to extract structural and kinetic information about different protein populations in atom-specific detail, can also be used for the characterization of lowly populated and rapidly interconverting species [21]. Additionally, molecular dynamics simulations using a variety of different force fields and approaches can provide insights into the potential repertoire of oligomers formed, which then require parallel experiments for their verification [[22], [23], [24], [25], [26]]. However, the aforementioned experimental approaches are not without their limitations – in particular, the structural resolution obtained using these techniques is generally insufficient to inform rational drug design approaches. Thus, there remains an on-going need to explore complementary methods for the characterization of amyloid oligomers.</p><p>The purposeful manipulation of an amyloidogenic system, with the aim of tuning the self-assembly landscape to favor specific events or species of interest, represents an alternative strategy for the study of amyloid self-assembly. Such an approach can reduce sample heterogeneity and, if used to bias the system towards oligomer formation, may allow mechanistic and structural information to be obtained about these assembly intermediates using a wider range of techniques than would otherwise be possible. Modulation of amyloid assembly can be achieved through the use of small molecule ligands, antibodies, or covalent protein modifications, to generate samples with a range of defined oligomer populations. In combination with methods such as NMR, kinetic modelling, and cell toxicity assays, these samples can provide insights into the role, disease-relevance, and structure of particular oligomeric populations, and validate potential routes for the treatment of amyloid diseases. There are now several examples where the stabilization (or destabilization) of specific species has reduced heterogeneity sufficiently to facilitate detailed structural studies using X-ray crystallography, thereby providing high-resolution insights into these potential therapeutic targets [[27], [28], [29], [30]].</p><p>This review provides an overview of the experimental methods and approaches which can be used to study the structure, kinetics, and disease-relevance of transient amyloid oligomers, and provides examples of their use in vitro. Although the ultimate goal of the amyloid field is to perform these experiments in vivo, in vitro studies allow us to explore the energy landscape of amyloid protein self-assembly and identify general trends between certain structural features (e.g. hydrophobicity, secondary structure) and toxicity. We discuss approaches through which observations can be made without intentional perturbation of the self-assembly process (e.g. using solution NMR, single particle methods, and native ESI-MS), as well as those through which the self-assembly equilibrium is deliberately modified to gain information about specific species. These "non-perturbing" and "perturbing" methods are complementary: most non-perturbing techniques are best suited to the determination of kinetic parameters (yielding information about rates of interconversion and population lifetimes), while the resolution of structural information they can obtain is typically lower. By contrast, perturbing methods offer the opportunity to analyze species using high-resolution structural methods, and hence enable detailed structure-toxicity relationships to be determined. The combination of both of these approaches provides an ideal experimental toolkit for generating more complete descriptions of the molecular mechanisms of amyloid fibril formation and their associated cellular toxicity.</p><!><p>NMR spectroscopy has the capability to characterize transient and heterogeneous systems in all-atom detail, and thus has been widely utilized in the characterization of amyloid protein assembly [21,42,43]. Many powerful NMR methods are sensitive to the properties of "NMR-invisible" species (i.e. those <1% populated or of high molecular weight) that are in rapid exchange with the NMR-visible state(s) [21,44]. In the context of amyloid assembly, this means that the properties (e.g. size, timescale of formation) of lowly populated (ca. 0.5–15%) amyloid oligomers can be indirectly studied via the monomeric precursor, using experiments such as Carr-Purcell-Meiboom-Gill (CPMG) relaxation dispersion, chemical exchange saturation transfer (CEST), paramagnetic relaxation enhancement (PRE), life-time line broadening, dark exchange saturation transfer (DEST), and off-resonance R1ρ relaxation [42]. Using these methods, the relative populations and exchange rates (100–10,000 s−1) between species can be extracted, providing valuable information about the assembly process. Some experiments (e.g. CPMG relaxation dispersion and CEST) are designed to probe exchange with species whose relaxation properties are not very different to those of the monomer, and thus are best suited to the study of small oligomers [[45], [46], [47]]. By contrast, others, such as DEST, life-time line broadening, and off-resonance R1ρ [33], require exchange of the monomer with a higher molecular weight species, making them ideal for the study of large amyloid oligomers or the exchange between monomer and fibrils [32,48].</p><p>The application of these NMR methods, in combination with global fitting of data acquired at a range of protein concentrations and magnetic field strengths, can provide valuable insights into the mechanisms of self-assembly (Fig. 1B). Such an approach has recently been used to interrogate the early stages of aggregation of a minimal peptide from the protein huntingtin (associated with Huntington's disease), providing information about the populations, exchange rates, and secondary structure of oligomers formed by two competing aggregation pathways [31]. Similar strategies have been adopted for other amyloid proteins that form a range of oligomeric states and structures, revealing insights into the binding of amyloid β (Aβ) monomers to fibrils [49], the energy landscape of copper‑zinc superoxide dismutase (SOD1) aggregation [50], and the formation of β2-microglobulin (β2m) oligomers [35,51] – events which are associated with Alzheimer's disease, amyotrophic lateral sclerosis, and dialysis-related amyloidosis, respectively. However, as these methods rely on reversible chemical exchange, this places a limit on the protein concentrations which can be used. There is an apparent irreversibility of the amyloid pathway for samples prepared above their critical protein concentration, and so sample conditions must be carefully selected to minimize the formation of any highly aggregation-prone species, while maintaining a suitable signal-to-noise ratio.</p><p>An alternative NMR approach that can be used to study the assembly of amyloid oligomers involves tilting the energy landscape of aggregation in a controlled manner through the use of hydrostatic pressure [34]. Pressure allows the rapid disassembly of oligomeric species before they convert to pressure-resistant fibrils. This technique therefore permits study of the oligomerization equilibria that would not be accessible to the experiments described above under a constant atmospheric pressure. Pressure-jump NMR experiments, in which the pressure inside the NMR cell is rapidly altered (in a matter of milliseconds), have been used recently to study the interconversion of a highly unfolded Aβ monomer (at high pressure) with an oligomeric species (at low pressure), providing residue-specific information about oligomers that show the first signs of conversion into amyloid [34].</p><p>In addition to probing the kinetics of protein self-assembly, NMR can also be used to investigate the structural properties of amyloid oligomers [31,[52], [53], [54]]. NMR-derived structural insights into these protein complexes can be achieved through the determination of distance restraints from NMR experiments, which are then used to drive simulated annealing calculations [55] or other molecular dynamics approaches [56]. Due to the transient nature of the complexes present in the early stages of amyloid assembly, traditional nuclear Overhauser effect-based structural investigations typically fail and intermolecular distance restraints tend to instead be derived from PRE studies using paramagnetic spin labels (commonly MTSL; S-(1-oxyl-2,2,5,5-tetramethyl-2,5-dihydro-1H-pyrrol-3-yl)methyl methanesulfonothioate) [57] (Fig. 1C). When covalently attached at a specific site on a protein's surface, spin labels can be used to map oligomerization interfaces, even those that are short-lived (< 100 μs) [58]. Data from PRE experiments have been used to generate structural models of β2m dimers and hexamers [35,52] (Fig. 1C), tetramers formed by a minimal huntingtin construct [31], and homo-/heterodimers formed by α- and β-synuclein (the former variant being associated with Parkinson's disease) [53,54].</p><p>Due to the size limitations of solution NMR methods, it has remained challenging to investigate large oligomeric assemblies directly using solution NMR-based approaches. However, with the advance of 13C-methyl-TROSY methods as sensitive reporters of protein structure and dynamics, amyloid oligomers can be studied directly (provided that they exist in a sufficiently large population) [59]. Finally, the arsenal of magnetic resonance techniques to study amyloid formation would not be complete without mentioning solid-state NMR and electron paramagnetic resonance (EPR). Both techniques have contributed substantially to our understanding of the structures of amyloid fibrils [60,61], as well as oligomers of Aβ peptides [62,63] and α-synuclein [64], but are frequently geared towards stable, monodisperse samples (e.g. fibrils or stable oligomers), with some notable exceptions [65,66].</p><p>NMR currently remains the only ensemble method that can yield atom-specific structural and kinetic information (including rates of interconversion and lifetimes) for lowly populated, transient states, by observing their effect on the main species in solution (usually the monomer). However, rather than inferring such information from the interpretation of NMR data, it is also possible to directly observe transient, oligomeric species using single particle and other non-ensemble averaged methods, as described below.</p><!><p>Single particle techniques are unparalleled in their ability to directly detect individual molecules and populations of interconverting species within heterogeneous mixtures. Single particle fluorescence methods (a term we use here to describe approaches which rely on fluorescent dyes, rather than the measurement of intrinsic protein fluorescence) and SPFS have both played key roles in the amyloid field, allowing kinetic and low-resolution structural information to be obtained for the species populated during fibril assembly [[67], [68], [69]]. Other non-ensemble averaged methods, such as ESI-MS, are also able to directly detect specific oligomer populations during assembly. When coupled to other techniques (e.g. ion mobility spectrometry, hydrogen-deuterium exchange, or infrared spectroscopy), ESI-MS is capable of providing structural information for these individual oligomeric species [18,19].</p><p>Single particle fluorescence experiments used for the study of amyloid assembly most commonly require preparation of dual-labelled protein samples, containing an equimolar mixture of protein molecules labelled with one of two distinct fluorescent dyes [67]. From such dual-labelled samples, oligomers can be detected by the observation of simultaneous bursts from the two fluorophores or, in cases where the emission of one fluorophore overlaps with the absorption of the other, by the ability of these molecules to undergo FRET (Fig. 1D) [10,36,37,[70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80]]. Different oligomer populations can be distinguished from one another based on the intensity of fluorescent bursts [79,80], the FRET efficiency [10,36,37], or the stability of the detected oligomers to particular experimental conditions (e.g. dilution into buffer with high or low ionic strengths, or the presence of proteases) [10,37,75,76,79,81]. By using such measurements to monitor the population of specific oligomers in an aggregating mixture over time, the resulting data can be fitted to self-assembly models to determine the rates of oligomer formation and interconversion, as well as thermodynamic parameters for these protein-protein interactions [36,37,76,78,82] (Fig. 1D).</p><p>While single particle fluorescence is immensely powerful, like any technique it relies on certain assumptions and has various limitations. The requirement to perform single particle fluorescence measurements under highly dilute solution conditions (several orders of magnitude less concentrated than the conditions ordinarily used to study protein aggregation in vitro) can limit the types of oligomers which can be observed. Typically, aliquots from a more concentrated aggregating mixture are taken and diluted immediately prior to single particle experiments, and thus unstable and/or highly transient oligomers may dissociate before the data are acquired [79]. However, this issue can be minimized through the use of microfluidic devices to speed up sample analysis [75,83] or by diluting aliquots into a solution of non-fluorescently labelled protein, rather than buffer alone [10]. An additional factor which must be considered is that most single particle fluorescence experiments make use of fluorescently-labelled protein samples, and therefore rely on the assumption that the incorporation of fluorescent dyes, which are often large and hydrophobic, does not perturb the assembly mechanism. This assumption may not always hold true [[84], [85], [86]], and the appropriate selection of fluorophores must be ensured by performing thorough control experiments. It is also possible to perform experiments with fluorescent probes which interact non-covalently with the protein of interest, and which can therefore be added after assembly has taken place [81,82,87,88].</p><p>SPFS relies on the use of mechanical force to perturb interatomic interactions and has been extensively used to study the formation of native protein contacts during folding [89]. However, non-native intermolecular contacts that take place during protein misfolding and self-assembly can also be studied through such methods. Atomic force microscopy (AFM) is the primary SPFS technique which has been used to study amyloid assembly, as the high forces accessible in this method are suitable for the study of amyloidogenic oligomerization events [16]; lower forces can be accessed using other, complementary SPFS methods [90], such as optical tweezers [[91], [92], [93], [94]]. Unlike single particle fluorescence measurements, where soluble oligomers formed at any stage during aggregation can be detected within a single experiment, AFM SPFS experiments tend to be designed to focus on specific oligomerization events – commonly dimerization. The lowering and raising of an AFM cantilever to and from a surface controls the formation and then drives dissociation of individual interactions [95]. For the study of dimerization events, one protein is typically attached to the cantilever tip, whilst the partner of interest (often the same protein) is immobilized on a surface on the sample stage [[96], [97], [98], [99], [100], [101], [102], [103], [104], [105], [106], [107], [108]]. Formation of higher oligomers can be studied using tandem repeat oligomers which are tethered between the surface and cantilever tip [109] or, more recently, using the flexible nanoarray (FNA) approach where a number of monomers are immobilized at various points along a flexible polymer [[110], [111], [112], [113]]. In both cases, the site of covalent attachment and the length/flexibility of the covalent linker need to be carefully selected to ensure that steric constraints do not alter the accessibility of key interaction interfaces or change the behavior of the protein. SPFS methods can yield information concerning the lifetime of specific protein-protein interactions and their strength (force resistance). Furthermore, the distance required to move the cantilever away from the surface to cause disruption of the oligomer can be used to infer the site of interaction [95,114].</p><p>In addition to its use as a SPFS method, AFM can be used as a surface-imaging technique to directly observe the formation and turnover of oligomers during amyloid assembly [68]. Recently, AFM has been coupled with infrared spectroscopy (AFM-IR) to image the secondary structure content of individual amyloid oligomers at the single aggregate level and to identify structural transitions which occur during the self-assembly of various amyloid proteins, including ataxin-3 (the causative agent of spinocerebellar ataxia type-3 or Machado–Joseph disease) [38], huntingtin exon 1 [115], and α-synuclein [116] (Fig. 1E). Such conformational conversion events are often rate-limiting steps in amyloid formation [117], and thus are key processes to characterize in structural and kinetic detail.</p><p>ESI-MS represents an alternative technique for the direct detection of individual monomeric conformers and oligomeric species formed during amyloid assembly. As a soft ionization method, ESI allows non-covalent interactions to be maintained when aggregating proteins are sprayed into a mass spectrometer from a volatile buffer solution [118]. ESI-MS has the advantage over the single particle methods discussed here in that no dye labels or immobilization strategies are required, with the mass accuracy of modern mass spectrometers making it straightforward to detect different oligomeric species that are co-populated [[17], [18], [19], [20]]. Most powerfully, ESI-MS can be directly coupled to other methods, such as ion mobility spectrometry (IMS; which allows oligomers with the same m/z ratio to be separated based on size and shape) [41,[119], [120], [121], [122], [123], [124], [125], [126], [127], [128], [129], [130], [131], [132], [133]], hydrogen-deuterium exchange and related covalent labelling experiments (revealing oligomer interfaces) [[134], [135], [136], [137], [138], [139], [140], [141], [142], [143], [144], [145], [146], [147]], and infrared spectroscopy (IR) [39,40] to yield structural information about the different species present in an aggregating mixture. These techniques have been used to detect structural transitions in amyloid assembly pathways [[39], [40], [41],123,135] (Fig. 1E), produce low-resolution structural models of specific intermediates [144,145,148], and infer the role of different oligomers in amyloid assembly and toxicity [120,130].</p><p>The primary limitation of methods which detect single particles or populations is their structural resolution. Unlike NMR, these techniques do not readily reveal residue- or atom-level information about amyloid assembly, and thus cannot facilitate structure-based ligand design approaches. We note, however, that the recent revolution in cryo-electron microscopy (cryo-EM), including advances in image processing algorithms, has allowed individual species within heterogeneous samples to be studied at high resolution [149]. While cryo-EM has already played a key role in the elucidation of fibril structures at near-atomic resolution [150], there are few examples of its application to amyloid oligomers [8]. This technique nonetheless has the potential to be used in the future to reveal high-resolution structural information for oligomeric samples at a "single species" level.</p><p>NMR and single particle methods remain invaluable for detecting individual oligomer populations and elucidating amyloid pathways. These approaches, in combination with methods which allow access to higher-resolution information (discussed below), facilitate progress towards more refined descriptions of amyloid assembly pathways.</p><!><p>Obtaining high-resolution structural and functional insights into specific amyloid oligomers typically requires the use of samples which predominantly contain a single species. While it is possible to reduce the heterogeneity of oligomer samples through size separation approaches [151], the degree of sample homogeneity achievable through this method is limited, as the self-assembly landscape may start to rapidly re-equilibrate after isolation of individual species. Careful control of sample preparation conditions (e.g. the availability of air-water interfaces, or buffer composition and pH) can bias self-assembly landscapes towards specific oligomeric states (Section 3.1), but the resulting oligomer distributions are often broad. Furthermore, such an approach does not address the experimental challenges which remain concerning how to trap and kinetically/structurally characterize amyloid intermediates in an in vivo setting. Four primary tools have emerged which can favor the production of narrow distributions of oligomers, or sometimes even a specific oligomer state, without requiring specific buffer conditions: oligomer-binding antibodies (Section 3.2), non-covalent small molecule ligands (Section 3.3), covalent ligands or protein modifications (Section 3.4), and crosslinking (Section 3.5).</p><!><p>For certain amyloid proteins, different sample preparation strategies have been established which have been shown to favor specific oligomer distributions. Lyophilization, followed by resuspension and incubation at high protein concentrations, has been used to promote the formation of kinetically-trapped α-synuclein oligomers that can then be further enriched by centrifugation, size-exclusion chromatography, or other size separation methods [152]. While oligomer distributions produced by this approach are still broad (predominantly 10-40mers, although species up to 90mers have been detected) [8,153,154], the enrichment of oligomers in these samples has nonetheless facilitated their study via a range of biophysical techniques [8,136,138,[153], [154], [155], [156], [157], [158]]. Notably, lyophilization has been used to produce α-synuclein samples for cryo-EM, leading to two low-resolution (18–19 Å) reconstructions of toxic cylindrical oligomers [8], and solid-state NMR, where structural properties of these same oligomers were compared with those of non-toxic, small molecule-stabilized oligomers [159] to understand the structural determinants of oligomer toxicity [64]. Similarly, samples prepared through incubation of amyloid proteins in carefully-selected buffers have allowed structure-toxicity relationships to be uncovered for oligomers formed by the N-terminal domain of the Escherichia coli HypF protein (prepared in additive-containing solutions) [160,161] and Aβ peptides (prepared in low salt buffers at low temperature [162,163] or in the presence of detergent micelles [26,164]), amongst others. In general, such studies have highlighted that structural features which promote promiscuous interactions with other cellular components (e.g. enhanced surface hydrophobicity or the presence of structured elements which can insert into membranes) are often associated with toxicity [26,64,165,166], while the proportion of β-sheet structure does not generally appear to play a clear role [167].</p><!><p>An emerging therapeutic avenue for the treatment of amyloid diseases is the use of antibodies to capture and neutralize toxic oligomers, due to the ability of these proteins to bind target epitopes with high specificity and affinity [168,169]. Such molecular recognition properties also make antibodies ideal tools for stabilizing specific, transient amyloid intermediates for detailed study [170,171] and for detecting the presence of particular structural features [172]. The A11 antibody, in particular, has played an important role in the amyloid field [6]. Although A11 was raised against an oligomeric mimic of Aβ40 (in the form of gold nanoparticles coated with Aβ40 peptides), this polyclonal antibody recognizes pre-fibrillar, toxic oligomers formed by a range of amyloid proteins with diverse primary sequences and native folds, suggesting that toxicity is associated with a common set of structural features [6]. Understanding precisely what these structural features are, how much they vary between different amyloid proteins, and which oligomeric species within a given self-assembly pathway possess these characteristics is still not understood.</p><!><p>Non-covalent strategies for the stabilization of particular oligomer populations, exemplified by nanobody- and metal ion-stabilized β2m oligomers. A: Crystal structure of a dimer of a truncated β2m variant (ΔN6-β2m) stabilized by a nanobody (green) [28]. B: Crystal structure of a Cu2+-stabilized hexamer of the H13F β2m variant. The Cu2+ ions are colored in orange [29]. In both A and B, β2m protomers are shown in various shades of blue. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</p><!><p>Non-covalent small molecules offer an alternative approach to capture amyloidogenic intermediates. In a similar manner to antibodies [178], such ligands can be invaluable tools to interfere with distinct microscopic events in amyloid self-assembly [[184], [185], [186], [187]], although identification of such compounds is complicated by the poor ligandability of most monomeric amyloid precursors (which are commonly intrinsically disordered or partially folded). The discovery of non-covalent ligands specifically for the oligomeric forms of amyloid proteins presents additional challenges, as protein-protein interactions are inherently difficult to modulate with small molecules [188]. While small molecules have been identified that stabilize natively oligomeric amyloid precursors – e.g. the functional tetramers of transthyretin (the aggregation of which results in familial amyloid polyneuropathy) and immunoglobulin light chain dimers (involved in light chain amyloidosis) [[189], [190], [191], [192]] – the identification of compounds that bind specifically to non-native, oligomeric assembly intermediates is far more challenging: less structural information is available for non-native intermediates to guide ligand design and it can be difficult to detect oligomer-specific interactions due to the low population of these species. Screening methods [193] that are well-suited to the identification of oligomer-binding compounds include kinetics approaches, which can identify the microscopic events that are modulated by a given compound [187], and ESI-MS (sometimes also coupled with IMS), which is sufficiently sensitive to detect lowly-populated intermediates and can identify the oligomeric state of the ligand-bound species [194].</p><p>In addition to compounds which are identified through screening, small molecules and other ligands which are thought to modulate amyloid assembly in vivo can be used in vitro to gain insight into assembly pathways. In particular, several metal ions with known or proposed roles in amyloid disease have been shown to promote the formation of amyloid oligomers [[195], [196], [197]]. A striking example of this was demonstrated by Calabrese et al., where Cu2+-mediated stabilization of a β2m variant hexamer allowed a high-resolution structure to be obtained of this oligomer by X-ray crystallography, showing a ring-like arrangement of protomers with a native-like fold (Fig. 2B) [29].</p><p>For natively disordered amyloid proteins, obtaining discrete oligomer populations through non-covalent binding is immensely challenging, as small molecule or metal ion binding tends to result in a distribution of oligomers [159,[198], [199], [200], [201], [202], [203]]. Nonetheless, through bulk structural measurements in combination with assays in cells, structure-toxicity relationships have been obtained for various natively disordered amyloid proteins, including α-synuclein [159,202,203] and Aβ peptides [159,200,201,204,205].</p><!><p>In recent years, covalent modification has become an increasingly utilized tool for the modulation of protein-protein interactions [[206], [207], [208], [209], [210], [211], [212], [213], [214], [215]]. A covalently bound small molecule may exert an effect on a protein or protein complex either via (a) non-covalent interactions (which have been reinforced by the covalent bond), or (b) by modifying the protein's surface properties or topography. We will refer to these two categories of modifications as "covalent ligands" and "protein functionalization", respectively. Covalent ligands can offer improved affinity and selectivity over their non-covalent analogues [213,216,217], thereby overcoming some of the difficulties associated with using small molecules to target the dynamic and poorly structured oligomers formed by many amyloid proteins. Modification of a protein's behavior through functionalization does not require the conjugated chemical moiety to have a high non-covalent affinity for the target; it can instead effectively act as a chemical post-translational modification [218,219], altering the protein's surface properties [27,220] or acting as a steric block [30]. We also note that sequence variation can be considered as a special case of protein functionalization which alters the chemistry and/or steric bulk of protein sidechains without the need for chemical modifications to be performed post-translationally. The effect of sequence variation on the thermodynamic stability of amyloid precursors and oligomers, and on the kinetics of protein self-assembly has been extensively studied and reviewed elsewhere [29,[221], [222], [223], [224], [225], [226], [227], [228]].</p><!><p>Covalent strategies for the control of oligomer populations in amyloid protein samples. A: Covalent ligands have been shown to be powerful modulators of oligomerization equilibria and can allow oligomer distributions to be tuned based on the affinity and location of the protein-ligand interaction [27]. B: The use of photolabile groups (e.g. N-2-nitrobenzyl) to sterically or chemically prevent amyloid proteins and peptides from accessing particular regions of the self-assembly landscape can allow oligomer populations to be controlled in a UV-dependent manner [30]. C: Covalent crosslinking using the PICUP or diazirine-based approaches represents a means of trapping a distribution of oligomers formed by a self-assembling protein, and the resulting crosslinked species can be separated (e.g. by SDS-PAGE, or using other, higher-throughput size/mass separation approaches) for individual structure and toxicity studies [[239], [240], [241]].</p><!><p>While the strategies discussed above have focused on methods to stabilize particular oligomeric states, sample homogeneity can also be improved by destabilizing or preventing the formation of other species in an amyloid assembly pathway. For example, the formation of inter-peptide backbone hydrogen bonds is essential for fibril formation [231] and so blocking the ability of the backbone to form these non-covalent interactions provides a means to prevent a protein from accessing certain regions of the self-assembly energy landscape. Chemical or steric blocking of backbone hydrogen bonds can be achieved through the incorporation of certain backbone mimics, such as the tripeptide β-strand mimic "Hao" [232] or through amide N-alkylation [233]. These approaches have been shown to restrict the self-assembly of a range of model amyloid peptides, including those derived from Aβ [30,[234], [235], [236]], tau (involved in Alzheimer's disease and other neurodegenerative disorders) [234], β2m [237], and islet amyloid polypeptide (IAPP; associated with type II diabetes) [238]. Recently, it has also been demonstrated that such covalent modifications can be applied in a reversible manner to tune oligomer populations with temporal control. The use of photolabile N-2-nitrobenzyl groups in place of (or in combination with) N-alkylation, for example, can allow precise control over amyloid oligomer populations, and hence cytotoxicity, of model Aβ peptides (Fig. 3B) [30]. The application of this approach to other model peptides and full-length amyloid proteins could thus drive novel insights into the role of different assembly intermediates and structural features in amyloid disease.</p><!><p>Crosslinking reactions which are rapid and indiscriminate in their amino acid preferences offer promising opportunities for capturing snapshots of transient oligomers formed by amyloidogenic proteins or peptides [242]. Such reaction characteristics are partially or fully exhibited by both the photo-induced crosslinking of unmodified proteins (PICUP) approach [243] and diazirine-based photochemical crosslinking [244]. The enhancement of oligomer stability resulting from covalent crosslinking renders the assembly intermediates within such samples amenable to purification by size separation approaches, allowing pure oligomer samples to be prepared for detailed structural and functional analysis [239,240,245] (Fig. 3C).</p><p>PICUP is a rapid, radical-based crosslinking method which can be used without the need for prior functionalization of the target protein with photoreactive groups [246]. Instead, metal complexes (typically tris-bipyridyl ruthenium(II)) are oxidized in the presence of visible light and subsequently abstract single electrons from amino acid sidechains (commonly tyrosine, cysteine, tryptophan, and methionine), rendering them capable of forming covalent bonds with suitable proximal residues [247]. PICUP has become an established method for the stabilization and study of amyloid oligomers [240,[248], [249], [250]], and the purification of crosslinked samples to yield individual oligomers has been demonstrated using a sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) extraction method [239,240] (Fig. 3C). The ability to obtain individual samples of well-defined (by mass, if not conformation), stabilized oligomers through PICUP has allowed the structure and toxicity of different Aβ oligomers to be probed. Ono et al. successfully isolated crosslinked Aβ40 dimers, trimers, and tetramers (all with at least 94% purity) and were able to individually characterize the secondary structure, amyloidogenicity, and cytotoxicity of each species, ultimately finding a correlation between all these variables [239]. With some modifications [251], the PICUP crosslinking approach, with subsequent oligomer purification, has also been applied to Aβ42 [240].</p><p>Despite the advantages of PICUP crosslinking chemistry, the requirement for an amino acid sidechain radical to encounter a radical scavenger or a readily oxidizable sidechain means that intermolecular crosslinking between protein molecules can occur through diffusion-controlled collision events, independently of genuine protein-protein interactions [248]. Such events can be avoided through the use of diazirine-based crosslinking, as the carbenes which form upon irradiation of diazirine groups with UV light have nanosecond lifetimes and are rapidly quenched by reaction with solvent if no crosslinkable residues are in proximity [252]. Although diazirine groups have to be introduced into the target protein or peptide by synthesis [25,241,253], covalent modification (e.g. via cysteine using methanethiosulfonate-functionalized diazirines [254]), or the use of unnatural amino acids during protein expression [255,256], the advantages offered by the short lifetime of the carbene, the high yield of potential crosslinks formed, and the rapidity of their formation when using LED illumination (reducing irradiation times from minutes or hours to seconds) [254] make diazirines attractive tools for capturing transient amyloidogenic interactions [25,241,244,253].</p><p>In theory, protein photo-crosslinking is well-suited to trap disease-relevant oligomers in cells or in vivo, as well as to identify the cellular components with which these oligomers interact. However, in practice, such an approach presents many challenges, notably the potential for very low signal-to-noise ratios due to the vast number of species within cells to which an amyloid protein can crosslink, as well as the complexities associated with subsequent data analysis. The use of crosslinking reagents with extremely short lifetimes and which offer the capacity for precise temporal control, such as diazirines, in combination with a method for enrichment of the crosslinked species (e.g. through affinity tags or alkyne-functionalized crosslinkers) addresses some of these challenges. Such an approach, in combination with quantitative proteomics has already been shown to be capable of identifying low-affinity, non-amyloidogenic protein-protein interactions in living cells [257]. Photo-crosslinking thus holds great potential for the study of amyloid assembly in physiologically- and disease-relevant systems.</p><p>When attempting oligomer-trapping methods, and particularly crosslinking strategies, it is important to keep in mind that while oligomer stabilization can dramatically improve sample homogeneity and offers advantages for structural characterization, the metastable and dynamic nature of amyloid intermediates can also be an important characteristic, particularly when considering oligomer toxicity. Oligomer dynamics, including protomer dissociation and exchange, can play important roles in toxicity [64,258]. While some crosslinked oligomers have been observed to undergo detectable dynamic motions [250], in other cases, crosslinking has been observed to suppress dissociation events which would otherwise contribute towards cell death [259]. It is therefore vital to employ a range of approaches to unpick the nature and potential cytotoxicity of different oligomers during amyloid assembly, keeping in mind that methods which are best suited to generating samples for high-resolution structure elucidation and those best suited for assessing oligomer toxicity are not necessarily the same.</p><!><p>Amyloid assembly intermediates are intimately involved in amyloid diseases, often representing key cytotoxic species which interact aberrantly with each other and other cellular components [11]. While the challenges presented by the transient nature, dynamics, and heterogeneity of these oligomeric intermediates have hindered structural and functional studies, continual advances in biophysical methods and chemical tools have allowed increasingly detailed insights to be gained. In this review, we have explored the role that NMR and single particle/species methods can play in gaining kinetic and low-resolution structural descriptions of lowly populated and transient oligomeric intermediates. In addition, strategies which allow specific oligomer populations to be stabilized (e.g. through the use of antibodies, small molecule ligands, or chemical crosslinking) can facilitate higher-resolution structural studies and investigation of detailed structure-toxicity relationships. It is important, however, to keep a balance between stabilizing a sample sufficiently to make it amenable to analysis through the desired methods and avoiding tipping the oligomerization equilibria to biologically- or disease-irrelevant species. The different strengths and caveats of the aforementioned methods make all these techniques complementary and emphasize the need to employ a wide range of integrated methods and tools from chemistry, biophysics, structural biology, and cellular biology to gain a complete description of these disease-relevant self-assembly pathways and to inform the rational design of much-needed treatments.</p><!><p>The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.</p><!><p>We thank members of our laboratories for helpful discussions. This work was supported by The Wellcome Trust (109154/Z/15/Z and 204963), the 10.13039/501100000266EPSRC (EP/N035267/1, EP/N013573/1) and the ERC (322408). A.J.W. holds a Royal Society Leverhulme Trust Senior Fellowship (SRF/R1/191087).</p><!><p>EEC and TKK wrote the first draft. All authors curated information, reviewed, and edited the manuscript.</p>

PubMed Open Access

An aqueous electrolyte of the widest potential window and its superior capability for capacitors

A saturated aqueous solution of sodium perchlorate (SSPAS) was found to be electrochemically superior, because the potential window is remarkably wide to be approximately 3.2 V in terms of a cyclic voltammetry. Such a wide potential window has never been reported in any aqueous solutions, and this finding would be of historical significance for aqueous electrolyte to overcome its weak point that the potential window is narrow. In proof of this fact, the capability of SSPAS was examined for the electrolyte of capacitors. Galvanostatic charge-discharge measurements showed that a graphitebased capacitor containing SSPAS as an electrolyte was stable within 5% deviation for the 10,000 times repetition at the operating voltage of 3.2 V without generating any gas. The SSPAS worked also as a functional electrolyte in the presence of an activated carbon and metal oxides in order to increase an energy density. Indeed, in an asymmetric capacitor containing MnO 2 and Fe 3 O 4 mixtures in the positive and negative electrodes, respectively, the energy density enlarged to be 36.3 Whkg −1 , which belongs to the largest value in capacitors. Similar electrochemical behaviour was also confirmed in saturated aqueous solutions of other alkali and alkaline earth metal perchlorate salts.

an_aqueous_electrolyte_of_the_widest_potential_window_and_its_superior_capability_for_capacitors

<!>Results<!>Capability of SSPAS as an electrolyte in graphite-based capacitors.<!>Effect of metal oxides for the graphite-based capacitor.<!>Discussion<!>Conclusion<!>Methods

<p>It has been generally understood that aqueous electrolytes have many advantages compared with non-aqueous solvents with respect to electrochemical behaviour as well as economic and environmental impacts. However, there exists serious disadvantage in aqueous electrolytes that water is easily electrolyzed to generate gases. This is attributed to the narrow electrochemical potential windows of aqueous solutions. As a matter of fact the thermodynamic potential window of water is known to be 1.23 V. For the study on capacitors the width of potential window is essentially important, since the energy storage in electric double-layer capacitors is proportional to the square of applied voltage 1 . Therefore, the use of aqueous electrolytes in capacitors should be accompanied by the extension of the potential window. Numerous attempts have been reported to extend the potential window of water. In 5 M (M = mol dm −3 ) LiNO 3 aqueous solutions 2 , the potential windows were determined to be 2.3 V(− 0.55~1.75 V) by a constant current (50 μ A cm −2 ) method. The potential window of 2.0 V was reported in a 0.1 M KCl unbuffered aqueous electrolyte by using nanostructured platinum electrodes, where the change in local acidity at the electrodes contributed to the expansion of the potential window. A gel electrolyte 3 consisting of the mixture of polyvinyl alcohol and KOH aqueous solution gave the potential window of 2.0 V. Much attention has been focused on electrode materials of high overpotentials for oxygen and/or hydrogen evolution. An attempt was made for supercapacitors (we will call just capacitor hereafter) consisting of the composites of carbon nanotubes with MnO 2 in the positive electrode/active carbon in the negative electrode in KNO 3 aqueous solution gave 2.0 V for the maximum charging voltage 4 . Other attempts to improve the operation voltage of aqueous electrolytes were reported by using asymmetric and symmetric capacitors, i.e. MnO 2 /carbon asymmetric capacitors [5][6][7][8] , and a carbon/carbon symmetric capacitor 9 . In the case of MnO 2 /graphene capacitor in 1 M Na 2 SO 4 aqueous solution 5 , a cell voltage was 2.0 V giving a large energy density of 25.2 Whkg −1 . In asymmetric aqueous capacitors, MnO 2 / nanoporous activated carbon 6 and MnO 2 /high purity carbon nanotubes 7 , the operation voltages were 1.5 V, and 2 V, respectively. In a symmetric carbon/carbon capacitor consisting of a homogeneous mixture of 80% activated carbon, 10% of acetylene black and 10% of binder 9 , the operation voltage was 1.6 V. In a review paper 1 , data are summarized on a variety of capacitors using various aqueous electrolytes and various electrodes. However, the potential window listed was 1.8 V at the maximum.</p><p>As a result from earlier studies [1][2][3][4][5][6][7][8][9][10] , the potential window of aqueous electrolytes is limited at around 2 V even though by using any specific electrode materials. Although the expansion of the water window to 2 V is a great advance in aqueous electrolytes, it is still not enough to replace non-aqueous electrolytes with aqueous electrolytes.</p><p>The aim of the present study is to expand the potential window of aqueous electrolytes based on the view point of solution chemistry. At first, a question arises why water is easily electrolyzed. There are two major impacts to contribute the electrolysis of water. One is the acid equilibrium of water and the other is the hydrogen bond between water molecules. It is well known that electrolysis of water is sensitive in the acidity. However, to our knowledge, no one has paid attention electrochemically with respect to the hydrogen bond of water. The hydrogen bond is originated between a hydrogen and a neighboring oxygen (or other electronegative atoms) at the distance shorter than 0.3 nm. There is a trade-off relationship between the covalent O-H bond and the hydrogen bond 11 , that is, weaker the hydrogen bond, stronger the O-H bond. This leads to a conclusion that the O-H bond of water should be strengthened if a water molecule is isolated from others because of the weakened hydrogen bond. As a matter of fact, the O-H bond strength in isolated gaseous water is even stronger than the O-H bonds of methanol and ethanol, i.e. 497 kJmol −1 in water is compared with 436 and 437 kJmol −1 of methanol and ethanol 12 . The addition of ions into water disturbs the hydrogen bond network, where the electronegative oxygen atom of water is attracted to positive ions and the electron poor hydrogen atom is attracted to negative ions.</p><p>In the case of saturated sodium perchlorate aqueous solution (SSPAS), since sodium perchlorate is extremely soluble in water (the solubility is 219.6 g in 100 g water at 25 °C), only 3.3 water molecules exist per one sodium perchlorate molecule. Under such a condition the hydrogen bond could be destroyed almost completely due to the lack of neighboring water molecules and also the strong hydration to Na + and ClO 4</p><p>− . The acid equilibrium could be also limited under the condition that the content of free water is too low for H + to form hydronium ion, H 3 O + . Note that H + has considerably large hydration energy among mono-valent ions, and hence only the hydrated species is able to exist in aqueous solutions.</p><p>We do not know in detail, but it is true that the evaporation rate of SSPAS is extremely slow owing to the strong hydration. This unusual phenomenon is known to be a theoretical base that water may exist in Mars 13 . Similar behaviour was also reported in a saturated magnesium perchlorate aqueous solution 13 . This suggests that the saturated magnesium perchlorate aqueous solution (SMPAS) would possibly be a superior electrolyte. Consequently, it is not surprising that the potential windows of SSPAS is extended to the region of non-aqueous solvents because of the enhanced strength of O-H bond due to the loss of hydrogen bond.</p><p>In the present paper, we will report a definite evidence for the widest potential window of SSPAS and demonstrate its superior capability as the electrolyte for capacitors using only low cost standard materials for this purpose.</p><!><p>Cyclic voltammetry. Cyclic voltammetry (CV) is most commonly used to investigate the electrochemical properties of electrolytes and electrode materials [14][15][16][17][18][19] . The CV measurements for SSPAS were performed together with typical acidic (1 M H 2 SO 4 ) and basic (1 M NaOH) aqueous solutions by a BAS CV-50W using a glassy carbon for a working electrode, a platinum counter electrode and an Ag/AgCl reference electrode under the argon atmosphere. Measurements were made separately for the positive scan to 2.3 V and for the negative scan to − 2.0 V at the scan rate from 30 mVs −1 to 200 mVs −1 at 25 °C. The cyclic voltammograms are exhibited in Fig. 1. Because of large over potential of the glassy carbon used for the working electrode, the potential windows are relatively wide. Even though, the potential window of SSPAS is remarkably large compared with those of typical acidic and basic solutions. The potential window of SSPAS was determined to be approximately 3.2 V from the cyclic voltammogram.</p><!><p>A proposed scheme of the electrical double-layer capacitor for SSPAS is illustrated in Fig. 2 under the charging, where Na + and ClO 4</p><p>− might be strongly attracted to negative and positive electrodes respectively because of the weakened shield due to limited number of water molecules.</p><p>The capability of SSPAS as the electrolyte for capacitors was examined first by a simple symmetrical graphite-based capacitor consisting of the following mixture: 80% graphite, 10% acetylene black and 10% carbon felt (we call hereafter a graphite acetylene black mixture or simply a graphite mixture abbreviated as GA). Then GA was made to form a thin film under the pressure as described later, where SSPAS well penetrated through thus made GA film compared with a pure graphite film. Galvanostatic charge-discharge experiments were performed under the following conditions: cut-off voltage 3.2 V, current density 15 mA cm −2 using a cation exchange membrane (CEM) as a separator, where voltage was plotted against capacity (mAh). For testing the reliability of SSPAS, the charge and discharge measurements were repeated 10,000 times (Fig. 3a). As seen in Fig. 3a, except the first charging plot, the galvanostatic cycles are consistent within 5% deviations for 10,000 cycles. The average energy density was 0.45 Whkg −1 (based on the total mass of active materials) and 76% of the charge and discharge efficiency and the time spent for one cycle was 12 s. The detailed gas analysis was carried out after the charge-discharge measurements by the gas chromatogram using a Shimadzu GC-2014 under the helium gas flow at the rate of 25 ml min −1 , where the whole cell was vacuumed before its opening for the analysis of inside gases. Hydrogen gas was not detected and oxygen was detected, but within the background. The results definitely indicate that SSPAS behaves well as the electrolyte at the operation voltage of 3.2 V.</p><p>The addition of activated carbon (AC) to both negative and positive electrodes forming a symmetrical capacitor increased the energy density remarkably as shown in Fig. 3b-e. Since the complete water free activated carbon was not easily obtained, the charge-discharge curves were affected by a small amount of water contained, the curves were unstable above 3 V. Therefore we chose the cut off-voltage at 3 V only in the capacitors consisting of the activated carbon mixtures. In Fig. 3b, cation exchange membrane (CEM) was used as the separator, while in Fig. 3c and d, a membrane filter (MF) and a filter paper (FP) were also used as separators, to compare with the 13 and number of free water molecules would not be enough to form a hydrogen bond.</p><p>result of using CEM. The result indicates that there exists little difference in the shapes of charge-discharge curves, and in the values of the energy density, that is 7.3~8.3 Whkg −1 , by the use of these separators. The times spent for one cycle (Ts) were all similar in Fig. 3b,c and e to be about 300 s. The increased addition of AC increased the energy density to be 18.7 Whkg −1 at 40% AC (Fig. 3e).</p><!><p>It has been known that metal oxides contribute to store energy in capacitors. Among a variety metal oxides, we have examined the capability of SSPAS for graphite-based capacitors containing naturally abundant metal oxides such as Fe 2 O 3 and Fe 3 O 4 , V 2 O 3 and V 2 O 5 , and MnO 2 . of AC with a CEM, (c) with a MF and (d) with a FP as the separator (e). Charge and discharge cycles of a symmetric graphite capacitor containing 40% of AC with a MF as the separator. Other specific conditions are described in Table 1.</p><p>First of all, we tried to examine the individual contributions in negative and positive electrodes especially for an asymmetric capacitor by using a reference Ag/AgCl electrode. We chose the electrode consisting of graphite mixture as a working electrode and the electrode containing 30% Fe 2 O 3 as a counter electrode. Experiments were carried out under the N 2 gas bubbling at 25 °C. The galvanostatic charge-discharge cycles plotted against time(s) are exhibited in Fig. 4-1, where (a) refers to the potential in the counter electrode, (b) the potential in the working electrode and (c) refers to the cell voltage. It can be seen in this figure that the plots (a) and (b) were almost symmetrical to the reference. This means that the electron absorption in the negative electrode and loss in the positive electrode takes place simultaneously. The cell voltage is the sum of the absolute values of (a) and (b).</p><p>In Fig. 4-2, the galvanostatic charge-discharge cycles, the cell voltages versus capacity (mAh), are shown for various symmetric and asymmetric capacitors containing metal oxides, Fe 2 O 3 , Fe 3 O 4 , V 2 O 3 , V 2 O 5 and MnO 2 . As seen in these figures, the charge-discharge curves are different in shape from those of usual capacitors, particularly in the symmetric capacitors containing iron oxides, where the curves looked like those in typical rechargeable batteries having plateaus. The addition of metal oxides brought remarkable gain in the energy density. This may owe to the redox effects by metal oxides. It should be noted in symmetric capacitors (4-2b) and (4-2d) containing Fe 2 O 3 and Fe 3 O 4 , respectively that the charge and discharge curves moved toward one direction according to the repetitions. It may be expected that a redox reaction takes place between Fe(II) and Fe(III). Similarly, redox reactions are also expected in the addition of V 2 O 3 and V 2 O 5 , because vanadium possesses four oxidation states from V(II) to V(V). MnO 2 is used in positive electrodes in (g) and (h) because of its electron emitting in nature. The results and specific conditions are summarized in Table 1.</p><p>Although sodium perchlorate is most soluble in any perchlorate salts, there exist other metal perchlorate salts of high solubility in water. Particularly, saturated lithium perchlorate aqueous solution behaves most similarly to SSPAS as exhibited in charge and discharge curves of a symmetric capacitor consisting of graphite mixture (Fig. 5a). However, our interest has been focused on more naturally abundant metal perchlorate salts, Mg(ClO 4 ) 2 , Ca(ClO 4 ) 2 , Ba(ClO 4 ) 2 and Al(ClO 4 ) 3 . Galvanostatic cycles of symmetric capacitors containing these saturated aqueous solutions as electrolyte are shown in Fig. 5b-e. It is interesting to see in the discharge curves in (b) Mg(ClO 4 ) 2 and (e) Al(ClO 4 ) 3 that the curves are not linear, being larger in the capacity and hence having larger energy densities compared with SSPAS. This might owe to the partial reductions of Mg 2+ and Al 3+ to Mg and Al respectively during charging like as rechargeable batteries.</p><!><p>In Fig. 1, from the CVs of dilute aqueous solutions, the decomposition voltage shifts towards positive direction from basic (1 M NaOH) to acidic (1 M H 2 SO 4 ) solutions as usual. The CV of SSPAS indicates that SSPAS is oxidized at more positive voltage than the decomposition voltage of 1MH 2 SO 4 to be about + 1.6 V and reduced at more negative voltage than the decomposition voltage of 1 M NaOH to be about − 1.6 V. This leads to the potential window of SSPAS is approximately 3.2 V. The potential window thus determined above 3 V is largest being ever reported for any aqueous solutions. It should be noted that the CV curve for SSPAS is nearly symmetrical. Since the concentration of H 3 O + and OH − would be very low because of the lack of free water to hydrate in SSPAS, the electrolysis could be caused by the direct decomposition of the OH bond of water, and hence the potential barrier is expected to be the same in the oxidation and in the reduction. This reflects the nearly symmetrical CV curve of SSPAS.</p><p>The large potential window of SSPAS could be resulted from the weakened hydrogen bond of water. In order to evaluate the hydrogen bond, NMR measurements were performed, since the hydrogen bond of water is related to the chemical shift of 1 H NMR signal. In an extreme case, under the supercritical condition, where water approaches to gaseous form and hence the hydrogen bond should be weakened, the chemical shift of 1 H NMR signal of water moves to the higher magnetic field compared with those measured under normal conditions 20 . The 1 H NMR of water was measured in SSPAS and in 1 M NaClO 4 aqueous solution, respectively, and the chemical shifts were determined to be 3.69 ppm in SSPAS and 4.76 ppm in 1 M NaClO 4 aqueous solution. This upfield shift in SSPAS is attributed to the weakened hydrogen bond in SSPAS despite the downfield contribution due to strong hydration towards Na + , though the quantitative contribution by the hydration is not known. Furthermore, the line-width at the half height in SSPAS was 0.0269 ppm, which was much smaller than 0.0483 ppm in 1 M NaClO 4 aqueous solution. This narrowing of the line-width in SSPAS can be explained by the weakened dipole-dipole coupling between the neighboring proton spin through the hydrogen bond 21 .</p><p>The result in the CV measurement for SSPAS showing the large potential window was consistent with the stable galvanostatic charge-discharge performances at the high operation voltage in Fig. 3. In Fig. 3a, the galvanostatic charge-discharge cycles for the symmetric graphite-based capacitor were stable within 5% deviations for 10,000 cycles and the time spent for one cycle was 12 s. In this figure, the charging curves deviate from the linearity at the high applied voltage. We estimate in storing energy that the electrical double-layer process as illustrated in Fig. 2 could be combined by an additional redox process owing to an electron adsorption and an emission in the negative and positive electrodes, respectively as written bellow.</p><p>x</p><p>x</p><p>The deviations from the linearity in galvanostatic curves become larger in the presence of activated carbon (AC) as seen in Fig. 3b,c and d, where the discharge curves also deviate from the linearity. The energy densities increased more than the ten times by the addition of AC compared with the capacitor consisting of only graphite-acetylene black mixture (Fig. 3a). In Fig. 3b,c and d, the galvanostatic curves are similar with the similar energy densities in spite of using different separators, CEM, MF and FP, respectively. The time spent for one charge-discharge cycle (Ts) were about 300 s in all cases. These results indicate that the mobility of ions through separators is not important. As a matter of fact, Na + and ClO 4 − are able to pass through MF and FP, while only Na + can pass through CEM. The increased addition of AC gives a considerable gain in the energy density as shown in Fig. 3e, i.e. the symmetric capacitor consisting of 40% activated carbon yielded the energy density of 18 Whkg −1 . This value is quite large in carbon-based capacitors 14,21,22 , despite of using standard inexpensive carbon materials. It should be noted that the cycle time (Ts) also increased by the addition of AC from 12 s of the graphite-based capacitor to 750 s of the capacitor containing 40% AC. These results suggest that the storing energy does not proceed simply through an electric double-layer process, but proceeds through composite processes. On the assumption that the cycle time (Ts) is caused by the diffusion controlled mechanism for the simple graphite capacitor, the enlarged Ts due to the addition of AC would be attributed to a slower additional process. The latter slower process is estimated to be an electrochemical process such as an electron adsorption-emission reaction.</p><p>As exhibited in Fig. 4-2, the galvanostatic curves of the capacitors containing metal oxides are different in shapes from those of the carbon-based capacitors in Fig. 3. The discharge curves of the asymmetric capacitors containing Fe 2 O 3 , Fe 3 O 4 , V 2 O 3 or V 2 O 5 in the negative electrodes are all similar, i.e., slowly decrease until 1.7 V in the case of Fe 2 O 3 and Fe 3 O 4 , and until 2.0 V in the case of V 2 O 3 and V 2 O 5 , then decrease relatively fast to zero. Consequently, the energy density is larger in the later cases. As seen in Fig. 4-2b (containing Fe 2 O 3 ) and Fig. 4-2d (containing Fe 3 O 4 ), the charge and discharge curves of the symmetric capacity look no longer like capacitor, instead rechargeable batteries having plateaus at the voltage above 1.0 V.</p><p>A number of studies have be concerned with respect to the role of a variety of metal oxides, such as RuO 2 , MnO 2 , Fe 3 O 4 , IrO 2 and V 2 O 5 for capacitors [23][24][25][26][27] . Especially, RuO 2 has been studied most extensively because of its conductivity and capability of fast reversible electron transfer between multiple oxidation states within 1.2 V as written below 15 .</p><p>where 0 ≤ x ≤ 2 Since the acid equilibrium is unknown under the present condition in SSPAS, the equilibrium (3) might be preferably written as below.</p><p>In the case of vanadium oxides V 2 O n (where n is 3 or 5), the mechanism could be similar as written below.</p><p>where x is not necessarily integer. The existence of equilibrium (4) was supported by the fact that the negative electrode became basic (pH = 11.3 measure after the dilution by water) after the full charge of capacitor. We do not deny the possibility of redox reactions of vanadium itself, because vanadium possesses four oxidation states from 2 to 5 within 1 V. On the other hand, in the positive electrode, the GA releases electron to form a positively charged form as described by the equation ( 2) or an equilibrium analogous to (4) as written below.</p><p>x 2</p><p>The equation (2′ ) would be more favorable than (2), because the positive electrode is acidic (pH = 2.31 measured after dilution by water) after the full charge.</p><p>XRD measurements were carried out to examine the structural change in graphite mixture (GA) by the full charge of the capacitor, i.e., GA containing 10% V 2 O 3 in the negative electrode and only GA in the positive electrode. As seen in Fig. 6-1, the diffraction pattern of the negative electrode exhibits a sharp peak at 2θ = 26°(a), which is characteristic of graphite 28 . On the other hand, the same peak at the positive electrode (b) is broadened after the charge. This indicates that the graphite in the positive electrode tends to lose a distinct structure to be amorphous according to the release of electron, but not to form graphite oxide 29 . A similar XRD result was also confirmed in the presence RuO 2 .</p><p>An XPS measurement was carried out for samples produced in the same way as described in Fig. 6-1 under the same condition by a ULVAC PHI 5000 VersaProbe III. The spectra are exhibited in Fig. 6-2 together with that of a graphite sample before use, which does not contain perchlorate. The peak corresponding to the graphite is assigned at 284.4 eV 30 appearing at the middle. The spectra of the samples after use are observed at the edge of the large oxygen 1 s peak of perchlorate. The peak of the negative electrode (red line) shifts slightly to the lower energy and the peak of the positive electrode shifts slightly to the higher energy. The shifts are within 0.5 eV, which is too small to prospect any major change in 2p orbital of graphite during charge and discharge. As a matter of fact, peaks of graphite oxide were reported to be larger than 286 eV 30 . In conclusion, the result of XPS is in agreement with that of XRD, where major difference in chemical bond would not take place during charge and discharge.</p><p>As described above, the role of vanadium and iron oxides in the negative electrode is to adsorb electron during the charge. On the other hand, as seen in Fig. 4-2g, MnO 2 was effective in the positive electrode. This means that MnO 2 emits electron during the charge as reported in an earlier paper 5 . On the basis of the above assumption for the adsorption and for the emission of electron by metal oxides, we made capacitors containing 30% of MnO 2 in the positive electrode. The charge and discharge cycles are exhibited in Fig. 4-2g and h, where GA with 20% AC and 30% Fe 3 O 4 was involved in the negative electrode, respectively, and the energy densities and the time spent for one cycle (Ts) were 16.9 Whkg −1 and 24.1Whkg −1 , 306 s and 442 s, respectively. The result indicates that Fe 3 O 4 is more effective than AC for larger energy density in the capacitors containing MnO 2 in the positive electrode. A capacitor containing 60% of Fe 3 O 4 and MnO 2 in the negative and in the positive electrode gave the energy density of 36.3 Whkg −1 and Ts was 700 s. The energy density is largest of the present series of experiments.</p><p>In earlier papers 5,7,14 , galvanostatic charge-discharge measurements for capacitors containing manganese oxide in positive electrodes were performed in aqueous solutions. The results are summarized as follows. a: MnO 2 /graphene in 1 M Na 2 SO 4 , operation voltage 2 V, current 5 mAcm −2 and Ts 900 s 5 , b: MnO 2 /AC in 2 M KNO 3 , operation voltage 2.2 V, current 100 mAg −1 and Ts 1200 s 7 , c: α MnO 2 /graphene in 6 M KOH, operation voltage 2 V, 1 Ag −1 and Ts 1000 s 14 . In these earlier studies, Ts was around 1000 s, though the conditions were all different. A quantitative comparison for these results involving the present study is difficult, since the materials used, the electrolytes and the galvanostatic conditions are all different. Even though, the charge-discharge rates are all similar from 700 s to 1200 s. This fact indicates that the rate of storing energy would be determined by (2) XPS spectra for carbon 1 s of graphite. The sample were taken in the same way as in Fig. 6(1) under the same condition. Because of the large 1 s signal of perchlorate oxygen, the S/N ratio of the sample signals are lower compared with the standard peak of original graphite (green). The red peak corresponds to the negative electrode and blue one positive electrode, respectively. electrochemical reactions instead of a diffusion controlled mechanism, and that SSPAS behaves well as equal as other dilute aqueous solutions.</p><p>It is interesting to see the charge and the discharge curbs for the symmetric capacitor containing Fe 2 O 3 (Fig. 4-2b) and Fe 3 O 4 (Fig. 4-2d), because they look like as rechargeable batteries having plateaus in the discharge curves, and furthermore the curves shift to one direction. We do not know in detail at moment, but it may be estimated that a redox reaction takes place between Fe(II) and Fe(III) during the charge and the discharge keeping the same oxide structures. The electron exchange reaction between Fe 2+ and Fe 3+ has been long known or it is the history of electron exchange reaction 31 . At moment, the detailed analysis is not possible, but it is important for understanding the charge-discharge mechanism in metal containing capacitors.</p><p>It has been found that perchlorate salts other than NaClO 4 , such as LiClO 4 , Mg(ClO 4 ) 2 , Ca(ClO 4 ) 2 , Ba(ClO 4 ) 2 and Al(ClO 4 ) 3 , are very soluble in water and that their saturated aqueous solutions works as excellent electrolytes. Galvanostatic cycles of symmetric graphite-based capacitors containing saturated aqueous solutions of these salts are exhibited in Fig. 5 with their specific conditions in Table 2. The saturated lithium perchlorate aqueous solution is quite similar to SSPAS (Fig. 5a). However, we are more interested in naturally abundant other perchlorate salts. Particularly, the saturated Mg(ClO 4 ) 2 aqueous solution (SMPAS) is the superior electrolyte as well as SSPAS. As seen in Fig. 5b and Table 2, and the current density is 40 mAcm −2 , which is largest at the present study, and hence raises the power density as large as 472 Wkg −1 . The discharge curve deviates from a linear line being slow down at below 1 V and such a discharge curve increases the energy density to be 1.2 Whkg −1 , which is more than double compared with 0.45 Whkg −1 in SSPAS. The time spent for one cycle is 10 s, which is shortest in the present study. A similar deviation from the linearity in the discharge curve was observed in the case of Al(ClO 4 ) 3 . Since the standard redox potentials for Mg 2+ /Mg and Al 3+ /Al are − 1.66 V and − 2.36 V, respectively, the partial reductions of Mg 2+ and Al 3+ to metals could not be ruled out under the present conditions even though in consideration of strong hydrations toward Mg 2+ and Al 3+ .</p><p>Recently, an aqueous electrolyte of using an eutectic hydrate melt which consists of a mixture of two organic lithium salts, that is Li(TFSI) 0.7 (BETI) 0.3 •2H 2 O, where TFSI is (bis(trifluoromethylsurphonyl)imide and BETI bis(pentauluoroethylsulphonyl)imide was reported for the use of Li ion battery 32 . The paper represents that this hydrate melt has a potential window over 3 V exhibiting an excellent capability for the Li ion battery. At moment, it is difficult to compare the difference in the above hydrate melt and saturated aqueous solutions of perchlorate salts as the electrolytes.</p><p>A need exists to use batteries or capacitors under extremely low temperatures. The eutectic temperature of SSPAS is − 37 °C and that of SMPAS is even lower at − 67 °C13 . Considering these data, the capacitors of using SSPAS or SMPAS would be functionally operative at very low temperatures.</p><!><p>Finally we conclude the present study. The most important finding was to successfully expand the potential window of the aqueous electrolyte first over 3 V by the use of the saturated sodium perchlorate aqueous solution (SSPAS). The electrolyte was demonstrated to behave well for graphite-based capacitors with respect to the stability for charge-discharge repetitions and the enlarged energy densities by the addition of activated carbon and metal oxides. It was also found that the other perchlorate electrolytes, particularly, the saturated Mg(ClO 4 ) 2 aqueous solution (SMPAS) is very feasible for the superior electrolyte. On the basis of the present results, together with the safety and economy impacts, SSPAS or SMPAS could replace non-aqueous electrolytes in commercial capacitors in the near future.</p><!><p>A graphite capacitor was produced by the following procedure. A mixtures of carbon powder, i.e., graphite (J-SP-α of Nippon Graphite Industries Ltd.) 80%, acetylene black (Denka) 10%, carbon felt (TOYOBO) 10%, was pressed at 1 kgcm −2 by a hydraulic machinery to make a thin film. Thus made films were wetted by SSPAS and used for both negative and positive electrodes. These were assembled with a separator to make a capacitor using a Hohsen battery unit, where glassy carbons (Tokai carbon) are used in both current collectors. As separators, non-conductive water permeable sheets such as a cation exchange membrane (NEOSEPTA CIMS), a filter paper (ADVANTEC 5B) and a membrane filter (Millipore JVWP) and a PPS fiber (TORAY Torcon) were able to be used. Galvanostatic measurements were carried out by using an instrument of Bio-Logic VSP at temperature 30 °C. A Rigaku MiniFlexII was used for XRD measurements and a JNM-ECX400 P for NMR measurements. Safety test. It has been known that dried sodium perchlorate has potential danger of explosion in the presence of organic compounds. Therefore, we made a safety test as follows: the mixture of sodium perchlorate and graphite containing activated carbon or vanadium pentoxide was heated at 200 °C and examined the change of the mixture in increasing temperature. As a result, nothing was happened by the heating and we confirmed the safety of the capacitors.</p>

Scientific Reports - Nature

Incorporation of Bulky and Cationic Cyclam-Triazole Moieties into Marimastat Can Generate Potent MMP Inhibitory Activity without Inducing Cytotoxicity

The synthesis and matrix metalloproteinase (MMP) inhibitory activity of a cyclam–marimastat conjugate and its metal complexes are described. The conjugate, synthesized with a copper(I)-catalyzed Huisgen 1,3-dipolar cycloaddition (“click” reaction), contains two zinc-binding groups (ZBGs). The metal complexation behavior with copper(II) and zinc(II) was investigated using UV/Vis spectrophotometry and 1H NMR spectroscopy, respectively, demonstrating that the first equivalent of the metal ion was chelated by the cyclam-triazole moiety rather than the hydroxamic acid site. Thus, the corresponding mononuclear metal–cyclam complexes were successfully prepared with one equivalent of the metal salt. Both the cyclam–marimastat conjugate and its metal complexes exhibited slightly reduced potency against MMP-1, but essentially identical inhibitory activity against MMP-3. The conjugate and its metal complexes displayed little or no cytotoxicity, further supporting their potential suitability for imaging MMP localization and activity. To the best of our knowledge, this is the first report that describes the incorporation of metal complexes into an MMP inhibitor without influencing the preexisting ZBG, and the first report of the evaluation of structures containing more than one ZBG as MMP inhibitors.

incorporation_of_bulky_and_cationic_cyclam-triazole_moieties_into_marimastat_can_generate_potent_mmp

Introduction<!><!>Introduction<!><!>Synthesis of the cyclam–marimastat conjugate 4<!><!>Synthesis of the cyclam–marimastat conjugate 4<!>Metal complexation<!><!>Metal complexation<!><!>Metal complexation<!><!>Metal complexation<!><!>Metal complexation<!>MMP inhibition studies<!><!>MMP inhibition studies<!>Cytotoxicity<!>Conclusions<!>Experimental Section

<p>Matrix metalloproteinases (MMPs) are zinc-containing endopeptidases capable of degrading extracellular matrix constituents.1 These enzymes play a pivotal role in a variety of physiological processes, including tissue remodeling, wound healing, embryonic development and angiogenesis.2 Overexpression of MMPs has been implicated in the progression of various pathologies, including cancer,3 arthritis4 and cardiovascular disease.5</p><p>The significance of these pathologies has led in turn to the development of a large number of synthetic MMP inhibitors (MMPIs).6 Most MMPs share a high degree of structural and functional similarity, which makes selective inhibition a major challenge.6a For many MMPIs, lack of target selectivity and/or undesired activity against other metalloproteinases trigger(s) dose-limiting side effects, typically musculoskeletal syndrome.3b</p><p>Many MMPIs consist of a peptidomimetic backbone, which forms noncovalent interactions with the enzyme, and a zinc-binding group (ZBG) capable of chelating and ultimately inactivating the catalytic zinc(II) ion.7 Hydroxamates are monoanionic, bidentate chelators, and are commonly employed as ZBGs.7–8 Marimastat (1, Figure 1) is a well-studied hydroxamate-based MMPI, and was the first compound in this class to complete clinical trials as an anticancer drug.9 Although marimastat exhibits good oral bioavailability, development was eventually terminated because of severe side effects arising from a lack of selectivity.9a</p><!><p>Structures of marimastat (1), cyclam (2) and acetohydroxamic acid (3).</p><!><p>Much recent research in the MMPI field has focused on the use of ZBGs other than hydroxamic acids as a way to increase selectivity.6a Cyclam 2 has recently been evaluated as a ZBG in this context and showed improved potency against MMPs relative to acetohydroxamic acid 3 (12-fold against MMP-1 and 19-fold against MMP-3).10 It has been proposed that the azamacrocycle acts by binding the active-site Zn2+, but this has not been experimentally demonstrated, and it is known that some MMPIs act without directly binding to the active-site metal.6a</p><p>This report describes the synthesis and evaluation of the dual ZBG conjugate 4 (Figure 2). To the best of our knowledge, the plentiful literature on MMPIs does not include investigation of structures with more than one ZBG. Either or both the cyclam (ZBG1) and hydroxamic acid (ZBG2) moieties in 4 could act as ZBGs, and the interaction of compound 4 with MMPs and other proteins in vitro and in vivo was therefore of interest. Evaluation of the corresponding metal–cyclam complexes would afford insight into the effect of an appended metal–cyclam moiety (bulky and cationic) on the potency and selectivity of marimastat as an MMPI. There are surprisingly few previous reports of metal complexes being evaluated as MMPIs,11] and none of the metal complexes previously studied also contain an additional, unmetallated ZBG. To the best of our knowledge, no MMPI has ever been synthesized with a remotely pendant metal complex. Complexes of this type, coordinated to an appropriate radionuclide, have potential as new tools for imaging MMP activity. Finally, construction of 4 and its metal–cyclam complexes extends our recent approach using copper(I)-catalyzed azide–alkyne cycloaddition (CuAAC; "click" reaction) to synthesize metal–cyclam complexes containing pendant biological ligands12 to complexes that include peptidomimetic protease inhibitors. Such methodology firstly shows the tolerance of the CuAAC reaction for more complex side chains, and secondly allows the assessment of the selectivity of metal binding when more than one chelating group is present.</p><!><p>Structure of cyclam–marimastat conjugate 4.</p><!><p>Cyclam–marimastat conjugate 4 and its metal complexes were synthesized following a convergent strategy (Scheme 1). The two required precursors 513 and 613d, 14 were successfully prepared according to literature procedures (see the Supporting Information). It is known that a dioxolanone ring like that in 6 can be opened by hydrochloric acid to give an α-hydroxycarboxylic acid.14e Thus mixing the two precursors 5 and 6 carried the risk that residual trifluoroacetic acid (TFA) in the amine salt 5 could catalyze the same ring opening to give a mixture of the desired acetonide 7 and the unwanted α-hydroxycarboxylic acid analogue 8. Coupling of amine trifluoroacetate 5 to carboxylic acid 6 was therefore effected by modifying the literature procedures:13d, 14e residual TFA in crude 5 was first neutralized with N,N-diisopropylethylamine (DIPEA) before the resulting material was added slowly to a solution of carboxylic acid 6 in anhydrous dichloromethane (DCM) in the presence of 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC⋅HCl), hydroxybenzotriazole (HOBt) and DIPEA. In this way, the azide-capped acetonide 7 was obtained in 73 % yield from the coupling of 5 to 6, a higher yield than those previously reported for coupling 6 or analogues to similar amine trifluoroacetates.13d, 14e, 15 The undesired α-hydroxycarboxylic acid 8 was isolated in ≤5 % yield. The 1H NMR spectrum of flash-column-purified 7 indicated that the sample contained less than 10 % of the unwanted diastereoisomers according to a comparison of peak integrals. These impurities were removed by recrystallization (ethyl acetate/hexane, 1:20; see the Supporting Information).</p><!><p>Synthesis of the cyclam–marimastat conjugate 12 and its metal complexes 13 and 14 as well as azide-capped marimastat 9. Reagents and conditions: a) EDC⋅HCl (1.1 equiv), HOBt (1.1 equiv), DIPEA (3.0 equiv), DCM, RT, 2.5 h, 73 %; b) 50 % NH2OH/H2O, THF, reflux, 1 h, 9: 81 %, 11: 83 %; c) propargyl-tri-Boc cyclam (1.0 equiv), CuSO4⋅5 H2O (0.05 equiv), sodium ascorbate (0.10 equiv), tBuOH/H2O (1:1), RT, 1.5 h, 82 %; d) TFA/DCM/H2O (90:5:5), RT, 6 h, followed by RP-HPLC purification, 95 %; e) M(ClO4)2⋅6 H2O (M=Cu or Zn) (1.0 equiv), EtOH, reflux, 3 h, 13: 63 %, 14: 89 %.</p><!><p>Literature reports suggested that hydroxamic acid 9, formed by opening the dioxolanone ring of 7 with hydroxylamine, has considerable potential to bind metal ions.7, 16 Indeed yields for the copper(I)-catalyzed Huisgen 1,3-dipolar cycloaddition between alkynes and azides containing hydroxamic acids are generally very poor,17 suggesting that interaction of the hydroxamic acid with copper can hinder this reaction. As a result, the reaction between azide 7 and propargyl-tri-Boc cyclam (prepared as reported previously12a, c, 18) was carried out prior to ring opening of acetonide (Scheme 1). This cycloaddition was initially performed overnight (12–18 hours) to give poor and variable yields (24–52 %). Monitoring the reaction by TLC and LC-MS, it was found that the cycloaddition was complete after 1.5 hours, and that desired product 10 gradually underwent ring opening to the corresponding α-hydroxycarboxylic acid (revealed by appearance of a new peak at m/z 924.4). Therefore, the reaction was quenched after 1.5 hours, and the yield significantly improved to 82 %.</p><p>The dioxolanone ring of 10 was opened by direct nucleophilic attack of hydroxylamine15 to give the hydroxamic acid 11 in 83 % yield (Scheme 1). Removal of the Boc groups was carried out under previously optimized conditions (TFA/DCM/H2O, 90:5:5);12a the crude product was purified by reversed-phase HPLC (see the Supporting Information) to afford trifluoroacetate 12 in excellent yield (95 %). Isolation of the free amine from trifluoroacetate 12 was hampered by the exceptional solubility of 4 in water (bestowed by the combination of hydroxamic acid, hydroxyl group and three secondary amines). Therefore, trifluoroacetate 12 was directly used in subsequent metal complexation reactions.</p><!><p>The cyclam–marimastat conjugate 12 contains two ZBGs: the cyclam (ZBG1) and hydroxamic acid (ZBG2) moieties. Hence, complexation of this conjugate with one equivalent of a metal ion could give rise to four different binding modes: the metal ion could be exclusively chelated by (1) cyclam or (2) the hydroxamic acid, it could (3) interact in part with each ZBG, or (4) dynamically move from a kinetic interaction with one ZBG to a thermodynamic interaction with the other. Either the first or fourth binding mode is required to achieve the synthesis of the target metal–cyclam complexes 13 and 14 (Scheme 1), but it is of wider interest to establish the chronology of the 12–metal interaction.</p><p>In order to determine the mode of binding between conjugate 12 and metal ions, copper(II) and zinc(II) were chosen for study using complementary analytical methods: UV/Vis spectrophotometry for copper(II) and 1H NMR spectroscopy for zinc(II). As a control, azide-capped marimastat 9 was synthesized (Scheme 1) to allow characterization of the interaction between the hydroxamic acid moiety and these metal ions.</p><p>Spectrophotometric titration of hydroxamic acid 9 with Cu(ClO4)2 in methanolic solution was performed (Figure 3) to obtain a λmax value for the copper(II) complex of 9 as a reference for the titration of the cyclam–marimastat conjugate 12 with Cu(ClO4)2. The absorbance at 403 nm in the titration spectra increased when copper(II) salt was added up to ten equivalents, thus indicating chelation of Cu2+ by the hydroxamic acid moiety in 9. A gradual decrease in the intervals of absorbance increase suggests that this complexation involves a weaker association than that typically observed for complexation of Cu2+ by N-functionalized cyclam derivatives.12a The absorbance apparent at 800 nm in Figure 3 is due to the metal salt, as the simple addition of Cu(ClO4)2 into methanol gave rise to this absorbance in the same manner.</p><!><p>UV/Vis spectrophotometric titration of hydroxamic acid 9 (5 mm) with Cu(ClO4)2 (500 mm) at intervals of 5 min in CH3OH at 25 °C (inset: absorbance at 403 nm versus equivalents of Cu(ClO4)2 added).</p><!><p>Cyclam–marimastat conjugate 12 was titrated with Cu(ClO4)2 under the same conditions (Figure 4). An absorbance at 605 nm increased essentially linearly with the addition of Cu(ClO4)2, reaching a maximum upon addition of one equivalent of copper(II). During this time course (ca. 30 minutes), no increase of absorbance was observed elsewhere in the spectrum, including at ∼403 nm, implying that the first equivalent of copper(II) added interacted only with the cyclam site and not with the hydroxamic acid. Further addition of Cu(ClO4)2 up to five equivalents resulted in a continuous rise of the absorbance at ∼403 nm, with the increment of this rise progressively decreasing. As expected, the magnitude of this increase is similar to that observed in the case of hydroxamic acid 9. Given that the typical λmax values for copper(II) complexes of N-functionalized cyclam (550–625 nm)12a are significantly different to those for the copper(II)–hydroxamate complexes (∼403 nm, as seen for 9), these UV/Vis titration profiles imply that a stoichiometric 1:1 complexation of the cyclam unit in 12 with Cu(ClO4)2 occurs in the first instance, followed by an interaction between the hydroxamic acid and the metal ion.</p><!><p>UV/Vis spectrophotometric titration of the cyclam–marimastat conjugate 12 (5 mm) with Cu(ClO4)2 (500 mm) at intervals of 5 min in CH3OH at 25 °C (inset: absorbances at 403 nm and 605 nm versus equivalents of Cu(ClO4)2 added).</p><!><p>The different λmax values of the copper(II) complexes of 9 and 12 manifested in clear differences between these solutions discernible to the naked eye: the former gave a pale green solution, while the latter appeared dark blue (see the Supporting Information).</p><p>The corresponding titrations of 9 and 12 with Zn(ClO4)2 were monitored by 1H NMR spectroscopy. A deuterated solvent screen showed that all four proton signals of the α-hydroxy hydroxamic acid (CH(OH)CONHOH) in 9 were only observed when deuterated N,N-dimethylformamide ([D7]DMF) was used as solvent (Figure 5). These four proton signals were assigned by comparison with literature 1H NMR data for marimastat and α-dehydroxy marimastat analogues.9b, 13d, 14e The methine proton (CHCHOH) couples to both the adjacent methine and hydroxyl protons with a coincident coupling constant (6.8 Hz), giving rise to an apparent triplet at 4.04 ppm, and the hydroxyl proton (CHCHOH) signal splits into a doublet at 5.73 ppm. The addition of one equivalent of Zn(ClO4)2 resulted in (1) the disappearance of two hydroxyl proton signals due to metal-ion-induced deprotonation, (2) a downfield shift and broadening of the signals arising from the hydroxamic NH and residual H2O protons, and (3) a multiplicity change from an apparent triplet to a doublet for the methine proton (CHCHOH) signal, caused by deprotonation of the neighbouring hydroxyl group. Further addition of zinc(II) beyond one equivalent did not prompt any further substantial changes in the 1H NMR spectrum. These results imply that the hydroxyl group adjacent to the hydroxamic acid is involved in the binding of 9 to Zn2+, which, to the best of our knowledge, has not been previously reported (Figure 6).</p><!><p>1H NMR spectroscopic titration of hydroxamic acid 9 (0.125 m) with Zn(ClO4)2 (1.00 m) at intervals of 15 min in [D7]DMF at 25 °C. S=nondeuterated solvent residual peaks.</p><p>Previously reported (I),11a our expected (II) and apparent (III) modes of binding between α-hydroxy hydroxamic acid and a metal ion.</p><!><p>It was expected that [D7]DMF could also be used for the titration of the cyclam–marimastat conjugate 12 with Zn(ClO4)2; however, the 1H NMR spectrum of 12 in the absence of metal salt surprisingly failed to give clear signals for any of the three α-hydroxy hydroxamic acid protons (CH(OH)CONHOH) (Figure 7 a). A further deuterated solvent screen tested deuterated chloroform (CDCl3), water (D2O), dimethyl sulfoxide ([D6]DMSO) and acetonitrile (CD3CN), but none of these solvents allowed clear visualization of these three protons (data not shown). Based on the UV/Vis spectrophotometric study of 12 with Cu2+, it was envisaged that Zn2+ was likely to be directly chelated by the cyclam moiety upon addition of one equivalent of the metal ion. As such, despite the obfuscated nature of the three α-hydroxy hydroxamic acid proton signals in [D7]DMF, the 1H NMR titration of 12 with Zn2+ was nonetheless performed in this solvent for consistency with the 1H NMR study with 9. Attention focused on the signals arising from the cyclam-triazole moiety in the 1H NMR spectra (Figure 7). It was found that all well-defined proton signals of 12, particularly in the regions corresponding to the cyclam and triazole protons, were split into multiplets upon addition of one equivalent of Zn2+ at 25 °C. The triazole singlet proton signal of 12 was split into six discrete singlets; these appeared poorly resolved when zinc(II) was first introduced, but were fully resolved after heating the sample at 80 °C for 1 hour. Comparing these changes with the 1H NMR spectra of previously reported zinc(II)-cyclam complexes12a suggests that complexation of the cyclam-triazole moiety within 12 with Zn2+ has occurred. Further changes to the cyclam- and triazole-derived signals were not observed when a total of three equivalents of zinc(II) were added. Taken together, these results suggest that the first equivalent of Zn2+ does indeed coordinate to the cyclam-triazole moiety.</p><!><p>1H NMR spectroscopic titration of the cyclam–marimastat conjugate 12 (0.02 m) with Zn(ClO4)2 (1 m) in [D7]DMF. a) 0.0 equiv; b) 1.0 equiv, 25 °C, 5 min; c) 1.0 equiv, 80 °C, 5 min; d) 1.0 equiv, 80 °C, 1 h; e) 2.0 equiv, 80 °C, 1 h; f) 3.0 equiv, 80 °C, 1 h. S=nondeuterated solvent residual peaks.</p><!><p>Both UV/Vis spectrophotometric and 1H NMR spectroscopic studies clearly demonstrated that the first proposed binding mode dominates the complexation of cyclam–marimastat conjugate 12 with zinc(II) and copper(II) when only one equivalent of the metal ion is added. This complexation behaviour provided simple synthetic access to the target metal–cyclam complexes 13 and 14. The complexation of trifluoroacetate 12 with one equivalent of copper(II) or zinc(II) perchlorate was performed in ethanol at reflux for 3 hours to ensure complete conversion, and the corresponding mononuclear metal–cyclam complexes 13 and 14 were obtained as blue and white powders in yields of 63 % and 89 %, respectively (Scheme 1). The constituent cations and anions of the metal complexes, that is, [M–ClO4]+ and ClO4−, were observed as characteristic signals in the high resolution mass spectra and IR spectra, respectively. Elemental analysis data showed that these metal–cyclam complexes contain up to three equivalents of water.</p><!><p>The ability of the marimastat derivatives 7–9 and 11–14 to inhibit MMP-1 and MMP-3 was tested using the established assay with the fluorogenic substrate Mca-Pro-Leu-Gly-Leu-Dpa-Ala-Arg-NH2 (see the Supporting Information).19 Marimastat 1, cyclam 2 and metal complexes 15 and 16 (Figure 8)12a were also assayed against these MMPs as controls. The data collected from these assays were fitted to the tight-binding inhibitor equation20 to obtain apparent inhibition constant (Ki(app)) values (Table 1).</p><!><p>Structures of the two metal–cyclam-based control compounds that do not contain a hydroxamic acid.</p><p>Ki(app) values [nm] for the marimastat-derived compounds against MMP-1 and MMP-3</p><p>[a] nid=no inhibition detected at 10 μm.</p><!><p>The cyclam–marimastat conjugate 12 exhibited slightly diminished efficacy (ca. 9-fold lower) against MMP-1 in comparison to marimastat 1. However, the potency of this conjugate against MMP-3 is comparable to that of marimastat 1. Metallation of the cyclam-triazole moiety resulted in only a slight reduction in MMP inhibitory activity (see data for 13 and 14); protection of the cyclam site with three bulky Boc groups had surprisingly little effect, with derivative 11 retaining a high inhibitory activity against both MMPs tested. No MMP inhibition was detected for cyclam 2 at 10 μm. These results suggest that the bulky cyclam moieties (protonated, metallated, or Boc-protected) exert little influence on the ability of these marimastat conjugates to inhibit both metalloproteinases, and that the marimastat unit (ZBG2) beats the cyclam scorpionand ligand (ZBG1) as a ZBG at the MMP active site.</p><p>Installing an azido group at the end of the alkyl chain in marimastat (as in 9) slightly reduces MMP inhibitory activity, whereas further protection of the hydroxamic acid (as acetonide 7) or its replacement with a carboxylic acid (8) leads to a total loss of MMP inhibitory activity. Metal complexes 15 and 16, which lack the hydroxamic acid altogether, show no ability to inhibit MMPs. These results underline the importance of the hydroxamic acid for the MMP inhibitory activity of marimastat derivatives. Moreover, these data point towards a mechanism of action for compounds 9 and 11–14 that involves hydroxamic acid binding to the MMP active site metal ion—rather than a cyclam–zinc(II) interaction.</p><!><p>The cytotoxicity of the marimastat derivatives 7–9 and 11–14 was assayed against human acute monocytic leukemia cells (THP1) in triplicate in the range of 0.5–50 μm for seven days. Cell death/viability was measured using the resazurin reduction assay and calculating percentage fluorescence compared to a nontreated control. With the exception of the Boc-protected cyclam–marimastat conjugate 11, which resulted in some toxicity at the highest concentration tested, the marimastat derivatives did not display any cytotoxicity (see the Supporting Information).</p><!><p>The synthesis of the cyclam–marimastat conjugate 12 was accomplished using "click" chemistry. The metal complexation behavior of this conjugate with copper(II) and zinc(II) has been studied using UV/Vis spectrophotometry and 1H NMR spectroscopy, respectively, demonstrating that both copper(II) and zinc(II) ions are first chelated by the cyclam-triazole moiety rather than the hydroxamic acid site when one equivalent of the metal ion is added. Thus, the mononuclear metal–cyclam complexes 13 and 14 could be prepared; to the best of our knowledge, for the first time, metal complexes have been incorporated into an MMPI.</p><p>MMP inhibition studies show that appending a cyclam-triazole moiety to marimastat reduces inhibitory activity against MMP-1 by approximately one order of magnitude, but has little or no effect on potency against MMP-3. Neither conjugate 12 nor its metal complexes 13 and 14 exhibited significant cytotoxicity to mammalian cells. Our results also indicate that it is the hydroxamic acid group—and not the cyclam unit—of these cyclam–marimastat conjugates that is key to the zinc binding interaction at the MMP active site. Future work with simpler analogues of 4 containing only the hydroxamic acid and the azamacrocycle (i.e., just the two ZBGs) would allow a more detailed investigation of their relative metal binding effectiveness at the enzyme active site. Furthermore, the results reported here open the way to a new strategy for imaging MMP localization and activity, using conjugates of marimastat and other MMPIs with metal complexes.</p><!><p>See the Supporting Information for full experimental procedures and spectral data.</p>

PubMed Open Access

CRISPR-Cas9 strategy for activation of silent Streptomyces biosynthetic gene clusters

Here we report an efficient CRISPR-Cas9 knock-in strategy to activate silent biosynthetic gene clusters (BGCs) in streptomycetes. We applied this one-step strategy to activate multiple BGCs of different classes in five Streptomyces species and triggered the production of unique metabolites, including a novel pentangular type II polyketide in Streptomyces viridochromogenes. This potentially scalable strategy complements existing activation approaches and facilitates discovery efforts to uncover new compounds with interesting bioactivities.

crispr-cas9_strategy_for_activation_of_silent_streptomyces_biosynthetic_gene_clusters

<!>Reagents and Media<!>Strains and Growth conditions<!>Construction of genome editing plasmids<!>Interspecies conjugation<!>Validation of promoter knock-in and genome editing<!>RNA isolation and Real-time quantitative PCR (RT-qPCR)<!>Fermentation, ethyl acetate extraction and LC-MS analysis metabolites from wild type and engineered Streptomyces strains<!>Extraction and NMR analysis of phosphonate compounds<!>Isolation and NMR analysis of PTM compounds<!>Isolation and NMR analysis of type II polyketide from S. viridochromogenes<!>Fermentation, extraction and LC-MS analysis of RED, ACT and indigoidine from wild type and engineered Streptomyces strains

<p>Microbial natural products are a rich source of pharmaceutical agents and current advances in genomics have unveiled a vast source of potential unexplored BGCs. Because majority of encoded metabolites of these BGCs are undetectable using current analytical methods due to minimal or zero BGC expression under laboratory conditions (such BGCs are commonly defined as silent BGCs1), strategies to activate BGC expression and trigger metabolite production are critical to realize the full potential of Nature's chemical répertoire.1 While heterologous expression bypass native regulation networks and can be engineered rationally,2 entire biosynthetic pathways often spanning large areas of genomes will have to be cloned and refactored.3,4 Additionally, heterologous hosts may lack regulatory, enzymatic or metabolic requirements necessary for product biosynthesis. Inducing cluster expression in native hosts circumvents these limitations but may be hindered by low homologous recombination efficiencies. Technologies that improve genetic manipulation of streptomycetes will expedite discovery and characterization of BGCs in their native contexts as well as guide the improvement of heterologous systems.5</p><p>CRISPR technology has enabled the genetic manipulation of many genetically recalcitrant organisms.6,7 The Streptococcus pyogenes CRISPR-Cas9 system was recently reconstituted in model streptomycetes to delete genes and entire BGCs as well as perform site-directed mutagenesis and gene replacement at significantly improved efficiencies.8–11 Here we extend this CRISPR-Cas9 technology to perform strategic promoter knock-in for the activation of silent BGCs in native Streptomyces hosts (Fig. 1a).</p><p>To demonstrate that CRISPR-Cas9 can be used to efficiently and precisely introduce heterologous promoters into Streptomyces genomes for BGC activation, we selected well-characterized pigment BGCs, namely the indigoidine cluster in Streptomyces albus,12 as well as the actinorhodin (ACT) and undecylprodigiosin (RED) clusters in Streptomyces lividans.13,14 Using CRISPR-Cas9 mediated knock-in, we replaced upstream promoter regions of main biosynthetic operons or pathway-specific activators with constitutive promoters that are stronger than the commonly used ermE* promoter and work in multiple Streptomyces species (Supplementary Results, Supplementary Fig. 1).15,16 In S. albus, CRISPR-Cas9 increased knock-in efficiency of the kasO* promoter upstream of the indC-like indigoidine synthase gene compared to without CRISPR-Cas9 (Fig. 1b). Higher knock-in efficiency observed with 2 kb homologous arms as compared to 1 kb arms is consistent with homology-directed repair of Cas9-induced double stranded breaks. Co-introduction of longer inserts such as the ~1 kb thiostrepton-resistance cassette (tsr) with kasO*p was achieved at lower efficiencies but it was still higher than that of inserting kasO*p alone without CRISPR-Cas9. Selected solely on apramycin, tsr-kasO*p knock-in strains grew on thiostrepton plates while maintaining pigment production as expected of an activated indigoidine synthase cluster (Fig. 1c, Supplementary Fig. 2). Similar to S. albus, recovery of desired kasO*p knock-in strains in S. lividans was greatly enhanced with the use of CRISPR-Cas9 (Fig. 1b). Confirming successful activation of the RED and ACT clusters, the engineered strains produced red undecylprodigiosin and pH-responsive actinorhodin-related metabolites respectively (Fig. 1d, Supplementary Fig. 3–5).</p><p>Together, these results demonstrated that CRISPR-Cas9 can be used to precisely introduce heterologous genetic elements into Streptomyces genomes at relatively high efficiencies for secondary metabolite production from silent BGCs. The enhanced knock-in efficiencies allowed use of donor DNA with shorter homology flanks as well as the introduction of larger genetic elements, both of which will be challenging without CRISPR-Cas9. While homologous recombination occurs efficiently in model strains like S. lividans and S. albus without CRISPR-Cas9, for other strains like Streptomyces roseosporus, the increase in efficiency afforded by CRISPR-Cas9 is critical and allows genetic manipulation of otherwise challenging strains (Fig. 1b).</p><p>Next, we employed this strategy to activate two silent unexplored BGCs from S. roseosporus with relatively high homology to known BGCs. The S. roseosporus NRRL15998 genome contains 29 predicted BGCs,17 the majority of which are yet to be characterized (Supplementary Table 2).18 One of the predicted BGCs showed >90% sequence identity to the polycyclic tetramate macrolactam (PTM) cluster in Streptomyces griseus (Supplementary Table 3), which was refactored for expression in S. lividans by introducing individual promoters in front of each of the six genes.19 Notably, insertion of a single strong promoter failed to drive cluster expression in the heterologous system.19 Here in the native S. roseosporus host, knock-in of kasO*p upstream of the first open reading frame (ORF) was sufficient to drive expression of PTM biosynthetic genes (Supplementary Fig. 6) and yielded the production of photocyclized alteramide A (1, m/z 511.2808, [M+H]+) and a second PTM 2 (m/z 513.2961, [M+H]+) with the same planar structure as dihydromaltophilin (Fig. 2a, Supplementary Note). Since alteramide A photocyclization is spontaneous,20 we surmised that alteramide A was the original metabolite produced by S. roseosporus. Interestingly, 2 was not identified in the previous study involving the almost identical S. griseus cluster,19 suggesting possible host-dependent factors or differences between native and heterologous hosts.</p><p>S. roseosporus also possesses a phosphonate BGC with genes showing high homology and synteny to the Streptomyces rubellomurinus FR-900098 BGC (Supplementary Table 4).21,22 Intriguingly, BLASTP search within ~2000 NCBI-deposited actinobacteria assemblies for FR-900098 biosynthetic enzymes did not uncover similar BGCs (accessed in May 2016), suggesting that S. roseosporus has the uncommon biosynthetic potential to synthesize the antimalarial compound, which to date has been attributed to S. rubellomurinus and Streptomyces lavendulae.21 To determine if S. roseosporus can produce FR-900098, we introduced a bidirectional P8-kasO*p promoter cassette to drive expression of the putative frbD operon and frbC homolog (Supplementary Fig. 8, 9). The engineered strain produced 3 with 31P-NMR, HMBC and mass values consistent with FR-900098 (Fig. 2b, Supplementary Note), validating the inherent ability of S. roseosporus to make FR-900098. The estimated FR-900098 titer of 6–10 mg/L in the engineered strain, while lower than the 22.5 mg/L reported for S. rubellomurinus,21 is ~1000-fold higher than the minimum inhibitory concentration against the malarial parasite,23 suggesting that this activation strategy may be applied for bioactivity-guided discovery.</p><p>We next asked whether this activation strategy can be generally applied to uncharacterized BGCs of different classes in multiple Streptomyces species, namely S. roseosporus (Supplementary Table 2), Streptomyces venezuelae (Supplementary Table 5) and Streptomyces viridochromogenes (Supplementary Table 6). For pathway-specific activation, we targeted single and bidirectional promoter cassettes to the first ORF(s) of the main biosynthetic operon(s) predicted based on gene directionality alone or if available, predicted transcriptional activators (Supplementary Fig. 10, 11). Introduction of single or bidirectional promoter cassettes into additional clusters in S. roseosporus and S. venezuelae yielded production of unique compounds that were not observed for the parent strains (Fig. 2c–e). For example, cluster 3 in S. roseosporus was predicted to be a nucleoside-type I PKS with biosynthetic enzymes for incorporation of a 3-amino-5-hydroxybenzoic acid starter unit and naphthalene ring formation. Insertion of kasO*p upstream of the main synthase gene encoding a loading domain and three PKS modules triggered the production of a major metabolite with m/z 405 (Fig. 2c). A distinct compound with m/z 780 was observed for another engineered S. roseosporus strain, in which kasO*p was introduced upstream of a predicted LuxR-type regulator within a type I PKS cluster (Fig. 2d). In S. venezuelae, insertion of a bidirectional promoter cassette between a type III PKS gene encoding an RppA synthase and a cytochrome P450 gene resulted in production of pigmented products (Fig. 2e). Production of these newly observed metabolites was independently validated at least three times in solid and liquid MGY media to be unique to the respective knock-in strains and detected in the parent wild type strains.</p><p>Identification of a novel compound using CRISPR-Cas9 based promoter knock-in further demonstrates the potential of this strategy for natural product discovery. We isolated and characterized the major product selectively produced by an engineered S. viridochromogenes strain, in which kasO*p was inserted in front of the main biosynthetic operon SSQG_RS26895-26920 of an uncharacterized type II PKS gene cluster NZ_GG657757 (Supplementary Fig. 15). Except for an additional cytochrome P450, NZ_GG657757 has high homology and similar gene arrangement as a spore pigment BGC in Streptomyces avermitilis (Accession number: AB070937.1). The engineered S. viridochromogenes strain produced an obvious brown pigment in liquid and solid medium before sporulation with a major unique metabolite 4 observed by HPLC (Fig. 3a, b). HRMS of the 4 predicted a molecular formula C23H16O8. 1H NMR, 13C NMR, COSY/TOCSY, HSQC and HMBC analyses of 4 revealed a novel polyketide with a dihydrobenzo[α]naphthacenequinone core that is shared by a family of polyketides including frankiamycin, benastatin and pradimicin (Fig. 3c, Supplementary Note).24 The cyclohexanone (ring E) in 4 is atypical and has not been observed for pentangular aromatic polyketides.25 Further mechanistic studies will elucidate the contributions of each enzyme in the biosynthesis of this pentangular polyketide.</p><p>In this study, we showed that relatively small genome perturbations in the form of strategically introduced promoters using the CRISPR-Cas9 technology, are sufficient to activate BGCs of different classes in multiple Streptomyces species, including type I, II and III PKSs, NRPS, hybrid PKS-NRPS and phosphonate clusters. Our current efforts focus on BGCs with 1–2 major predicted biosynthetic operons and we do not expect this strategy to work for all BGCs, especially if global transcriptional changes are required or if there are multiple major operons within the target BGC. For activation of these BGCs, more complex engineering involving knock-in of multiple promoters, manipulation of pathway/global regulators or enzyme/domain swaps and mutations, all of which may also be performed using CRISPR-Cas9. An obvious limitation of this strategy is that it requires introduction of recombinant DNA, which may be challenging for some strains, especially natural isolates. Nonetheless, the activation of multiple clusters in different Streptomyces species highlights the potential of this approach to complement existing strategies, including heterologous expression, to discover, characterize and reengineer BGCs.1 This strategy should be generally applicable and potentially scalable to better explore the biosynthetic potential of streptomycetes.</p><!><p>Unless otherwise indicated, all reagents are obtained from Sigma. 1 L of MGY medium contains 10 g malt extract broth, 4 g Bacto yeast extract (BD Biosciences), 4 g glucose (1st Base, Axil Scientific) and for MGY agar plates, an additional 20 g of Bacto agar (BD Biosciences). Conjugation experiments involving WM6026 and WM3780 E. coli strains were performed on R2 agar without sucrose: 0.25 g K2SO4, 10.12 g MgCl2•6H2O, 10 g glucose, 0.1 g Bacto casamino acids (BD Biosciences), 5.73 g TES, 20 g agar in 1 L water, autoclaved, after which 1 mL filter-sterilized 50 mg/mL KH2PO4 solution and filter-sterilized 2.94 g CaCl2•2H2O and 3 g L-proline in 5 mL 1 N NaOH were added to the medium.</p><!><p>Strains and plasmids used in this study are listed in Supplementary Table 7. Unless otherwise indicated, strains are propagated in MGY medium at 30 °C. Spore preparations and conjugation protocols were similar to those described by Keiser and Bibb.26 For spore preparations, 1:1000 of a spore preparation or 1:100 dilution of a saturated seed culture is plated on MGY plates and incubated at 30 °C until thick spores are observed. Spores were removed from the plate using 5 mm glass beads (Sigma) and resuspended in sterile TX buffer (50 mM Tris pH 7.4, 0.001% (v/v) Triton X) by vigorous vortexing for 30 s. The eluant containing free spores were pelleted by spinning at maximum speed in an Eppendorf 5810R centrifuge for 10 min, resuspended in 1 mL sterile water and repelleted. The spores were then resuspended in water and stored at –80 °C. A typical spore prep contains ~107–109 spores/mL as determined by serial dilution plating.</p><!><p>All DNA manipulations were carried out in Escherichia coli DH5α or OmniMAX™ (Thermo Fisher). Primers used in this study are listed in Supplementary Table 8. Restriction enzymes were obtained from New England Biolabs. Helper pCRISPomyces-2 plasmids for making promoter knock-in constructs were made by ligating adapter sequences, containing restriction sites flanking the promoter of choice (Supplementary Fig. 16) to facilitate insertion of homology arms, at the XbaI site of pCRISPomyces-2.8 The protospacer of a target cluster was first inserted via BbsI-mediated Golden Gate Assembly as previously described.8 The helper plasmid (pCRISPomyces-2-kasO*p, pCRISPomyces-2-P8-kasO*p) was linearized using SpeI and assembled with the downstream homology arm (2 kb unless otherwise indicated) by Gibson assembly (New England Biolabs). The second upstream homology arm (2 kb unless otherwise indicated) was subsequently inserted by Gibson assembly using HindIII or NheI linearized construct containing the first homology arm. See Supplementary Fig. 17 for workflow to construct genome editing plasmids.</p><!><p>Promoter knock-in constructs were used to transform conjugating E. coli strains and colonies with the appropriate antibiotic resistance (e.g. 50 mg/L apramycin) were picked into LB with antibiotics. WM6026 requires diaminopimelic acid in LB for growth and it was added to LB for subsequent wash and resuspension steps. Overnight cultures were diluted 1:100 into fresh LB with antibiotics and grown to an OD600 of 0.4–0.6. 400 μL of the culture was pelleted, washed twice and resuspended in LB without antibiotics. The washed E. coli cells were then mixed with spores at 1:5 volume ratio and spotted on R2 without sucrose plates. After incubation for 16–20 h at 30 °C, the plates were flooded with nalidixic acid and apramycin and incubated until exconjugants appear. Exconjugants were streaked onto MGY plates containing apramycin at 30 °C followed by restreaking to MGY plates at 37 °C to cure the CRISPR-Cas9 plasmid containing a temperature-sensitive origin of replication. Apramycin-sensitive clones growing at 37 °C were then subjected to validation of promoter knock-in and genome editing as described below.</p><!><p>Genomic DNA from wild type and exconjugants from the indicated strains were isolated from liquid cultures using the Blood and Tissue DNeasy kit (Qiagen) after pretreating the cells with 20 mg/mL lysozyme for 0.5–1 h at 30 °C. PCR was performed using control primers beyond the homology regions or knock-in specific primers (Supplementary Table 8) with KODXtreme Taq polymerase (Millipore). Where indicated, PCR products were subjected to digest with specific restriction enzymes to differentiate between PCR products of wild type genomic sequences and successful genome editing by knock-ins. Positive samples were purified using Qiaquick PCR purification kit (Qiagen) and validated by Sanger sequencing.</p><!><p>RNA from wild type and engineered S. roseosporus were isolated using RNAsy Midi Kit (Qiagen) 72 h after seed cultures were diluted 1:100 into 50 mL of MGY broth in 250 mL baffled flasks containing ~30–40 5 mm glass beads and growth at 30 °C. Isolated RNA was treated with DNase (Qiagen) before being reverse transcribed with random hexamers using SuperScript III (Invitrogen). RT-qPCR was performed on a Roche LightCycler 480 using SYBR FAST qPCR master mix (KAPA). The housekeeping rpsL gene of S. roseosporus was used as constitutive reference to normalize gene expression of each target gene such that rpsL expression = 1.27 Technical triplicates of three biological repeats were performed per condition. Gene-specific primers are listed in Supplementary Table 8.</p><!><p>Liquid seed cultures (2 mL MGY) of wild type and engineered S. roseosporus and S. venezuelae strains were inoculated from a plate or spore stock in 14 mL culture tubes. Seed cultures were incubated at 30 °C with 250 rpm shaking until achieving turbidity or high particle density (typically 2–3 days). Seed cultures were diluted 1:100 into 50 mL of MGY broth in 250 mL baffled flasks containing ~30–40 5 mm glass beads and incubated at 30 °C with 250 rpm shaking (10–14 days for S. roseosporus, 5–7 days for S. venezuelae). The cultures were harvested by pelleting at maximum speed in an Eppendorf 5810R centrifuge for 10 min. The cell pellet was stored at –80 °C while the supernatants were split into two 50 mL falcon tubes. Culture supernatants were extracted three times with equal volume ethyl acetate. For solid-state cultures, the strains were grown on MGY plates at 30 °C for 10 days. The plates were chopped into small pieces and extracted twice with ethyl acetate. Extracts were dried and resuspended in methanol, and analysed by LCMS using ESI source in positive ion mode (Bruker, Amazon SL Ion Trap) equipped with a Kinetex 2.6 μm XB-C18 100 Å (Phenomenex). HPLC parameters were as follows: solvent A, 0.1% trifluoroacetic acid in water; solvent B, 0.1% trifluoroacetic acid in acetonitrile; gradient at a constant flow rate of 0.2 mL/min, 10% B for 5 min, 10% to 100% B in 35 min, maintain at 100% B for 10 min, return to 10% B in 1 min and finally maintain at 10% B for 10 min; detection by ultraviolet spectroscopy at 210, 254, 280, 320 nm.</p><!><p>Liquid seed cultures (2 mL MGY) of wild type and engineered S. roseosporus strains were inoculated from a plate or spore stock into 14 mL culture tubes. Seed cultures were incubated at 30 °C with 250 rpm shaking until achieving turbidity or high particle density (typically 2–3 days). Seed cultures were diluted 1:100 into 50 mL of MGY broth in 250 mL baffled flasks containing ~30–40 5 mm glass beads and incubated at 30 °C with 250 rpm shaking for 10–14 days. The cultures were harvested by pelleting at maximum speed in an Eppendorf 5810R centrifuge for 10 min. The cell pellet was stored at –80 °C while the supernatants were split into two 50 mL falcon tubes, flash frozen liquid nitrogen and lyophilized to dryness. 25 and 10 mL of methanol was added to each tube containing dried supernatant and frozen cell pellets respectively. The methanol mixtures were vortexed for 1 min each and incubated on a platform shaker at 4 °C for 2 h. Samples were clarified by spinning at maximum speed in an Eppendorf 5810R centrifuge for 10 min twice and pooling the methanol extracts from the respective pellets and lyophilized culture supernatants. A generous amount of anhydrous sodium sulfate was added to the extracts and stirred. The extracts were decanted, concentrated to dryness and resuspended in 700 μL deuterium oxide added in two 350 μL aliquots. A spatula-full of Chelex-100 resin (Bio-Rad) was added to each sample in a 1.7 mL centrifuge tube, which was incubated for 30 min at room temperature with agitation on a Thermo microplate shaker. The samples were clarified twice by centrifuging at maximum speed in an Eppendorf benchtop centrifuge for 1 min each time. The supernatants were then filtered using a 10 kDa Vivaspin column (GE Healthcare) and the filtrates were transferred to a 5 mm NMR tube for NMR analysis. 31P-NMR has been acquired using a Bruker DRX-600 spectrometer equipped with a 5mm BBFO cryoprobe. Proton decoupled 31P-NMR spectra are referenced to an external H3PO4 (aq) standard (δ 0.0 ppm). All samples have been acquired for 6000 scans. Identity of FR-900098 was confirmed by 1) spiking with the sample with authentic FR-900098, 2) 31P HMBC data comparison; 3) HRMS data. Production titers were estimated by spiking in known amounts of FR-900098.</p><!><p>The crude extract was fractionated using silica gel flash chromatography and generated 11 fractions: F1 (5% ethyl acetate with 95% hexanes), F2 (15% ethyl acetate with 85% hexanes), F3 (20% ethyl acetate with 80% hexanes), F4 (30% ethyl acetate with 70% hexanes), F5 (40% ethyl acetate with 60% hexanes), F6 (50% ethyl acetate with 50% hexanes), F7 (60% ethyl acetate with 40% hexanes), F8 (80% ethyl acetate with 20% hexanes), F9 (100% ethyl acetate), F10 (100% acetone), F11 (100% methanol). PTM was eluted in F11 according to LCMS analysis. F11 was subjected to semi-prep HPLC using a C18 column (Phenomenex, 250 × 10 mm) with the following gradient: 5~40 min 5%~20% acetonitrile in water with 0.1% formic acid; 40~60 min 20%~50% acetonitrile in water with 0.1% formic acid; 60~70 min 50%~60% acetonitrile in water with 0.1% formic acid. 2 was eluted at 62 min. 1 was eluted at 61 min. NMR analysis was performed on an Agilent 600 MHz NMR spectrometer.</p><!><p>Large-scale cultivation on solid plates (equivalent to 5 L liquid culture) of the knock-in strain was carried out to obtain sufficient amounts of potential new compound. 10-day growth solid plates were soaked in equal volume ethyl acetate overnight. The extract was fractionated using C18 flash column chromatography and the fraction containing the target compound was further subjected to silica gel flash column chromatography. The column elution was monitored by TLC and the fractions containing the target compound were further confirmed by HPLC. NMR analysis was performed on an Agilent 600 MHz NMR spectrometer.</p><!><p>Liquid seed cultures (2 mL MGY) of wild type and engineered S. lividans and S. albus strains were inoculated from a plate or spore stock in 14 mL culture tubes. Seed cultures were incubated at 30 °C with 250 rpm shaking until achieving turbidity or high particle density (typically 1–2 days). For S. lividans, seed cultures were diluted 1:100 and plated onto MGY plates and grown at 30 °C for 3–4 days. The plates were chopped into small pieces and extracted with methanol (RED) or acidified methanol (ACT). For S. albus, seed cultures were diluted 1:100 into 50 mL of MGY broth in 250 mL baffled flasks and grown at 25 °C with 250 rpm shaking for 2–3 days. Culture supernatants of wild type and engineered S. albus strains were extracted twice with equal volume ethyl acetate containing 1% (v/v) formic acid. Extracts were dried and resuspended in methanol prior to analysis by LCMS using ESI source in positive ion mode (Bruker, Amazon SL Ion Trap) equipped with a Kinetex 2.6 μm XB-C18 100 Å (Phenomenex). HPLC parameters were as follows: solvent A, 0.1% trifluoroacetic acid in water; solvent B, 0.1% trifluoroacetic acid in acetonitrile; gradient at a constant flow rate of 1 mL/min, 5% B for 2 min, 5% to 100% B in 15 min, maintain at 100% B for 2 min, return to 5% B and maintain for 2 min; detection by ultraviolet spectroscopy at 500 nm (RED, ACT) or 600 nm (indigoidine). MS/MS was performed in positive auto MS(n) mode with scan range m/z 100–1000.</p>

PubMed Author Manuscript

Phase 1 study of new formulation of patritumab (U3-1287) Process 2, a fully human anti-HER3 monoclonal antibody in combination with erlotinib in Japanese patients with advanced non-small cell lung cancer

BackgroundThis phase 1 study evaluated the safety, tolerability, pharmacokinetics and efficacy of patritumab (U3-1287) Process 2, a new formulation of fully human anti-HER3 monoclonal antibody in combination with erlotinib, an epidermal growth factor receptortyrosine kinase inhibitor (EGFR-TKI) in prior chemotherapy treated Japanese patients with advanced non-small cell lung cancer (NSCLC).MethodsPatients received intravenous patritumab Process 2 formulation at 9 mg/kg every 3 weeks after initiation of 18 mg/kg loading dose combined with continuous daily dose of erlotinib (150 mg QD) until any of the withdrawal criteria are met. Adverse events (AEs) were assessed using CTCAE v4.0 and tumor response was assessed using RECIST v1.1. Full pharmacokinetic sampling and serum biomarker analyses were mainly performed during cycle 1 and 2.ResultsTotal of six EGFR-mutant NSCLC patients including one EGFR-TKI naïve patient received patritumab Process 2 formulation combined with erlotinib. No dose-limiting toxicities were observed. The most frequent AEs were gastrointestinal or skin toxicities, which were generally mild and manageable. One patient discontinued from study due to reversible grade 3 interstitial lung disease. The mean area under the curve (AUC) value was 2640 μg/day/mL; the Cmax value was 434 μg/mL, respectively. The median progression-free survival (95% confidence interval) was 220.0 (100.0–363.0) days. HER3 ligand heregulin was detected in serum from only a patient that maintained most durable stable disease.ConclusionsPatritumab Process 2 formulation in combination with erlotinib was well tolerated compatible with favorable PK profile in Japanese patients with advanced NSCLC.

phase_1_study_of_new_formulation_of_patritumab_(u3-1287)_process_2,_a_fully_human_anti-her3_monoclon

Introduction<!>Patient eligibility<!>Study design and evaluation<!>Pharmacokinetics<!>Biomarkers<!>Statistical method<!>Patient characteristics<!><!>Safety and tolerability<!><!>Safety and tolerability<!>Pharmacokinetics<!><!>Efficacy<!>Biomarker analysis (serum HER3 and heregulin)<!><!>Discussion

<p>The human epidermal growth factor receptor-3 (HER3) is a member of the HER (EGFR/ErbB) receptor family consisting of four closely related type 1 transmembrane receptors (EGFR, HER2, HER3, and HER4). HER receptors are part of a complex signaling network intertwined with the Ras/Raf/MAPK, PI3K/AKT, JAK/STAT, and PKC signaling pathways. HER3 is expressed in many normal tissues and in a variety of solid tumors, including non-small cell lung cancer (NSCLC) [1–4], and increased levels of HER3 have been associated with a negative clinical prognosis, including survival in several tumor types [5–8]. HER3 is the only HER family member that lacks tyrosine kinase activity because of an amino acid substitution in the conserved kinase domain. Thus, interactions of HER3 with binding partners are essential for its biological activity [9]. In particular, HER3 potently activates downstream phosphatidylinositol-3-kinase (PI3K) and AKT pathway signaling by directly binding to PI3K through six consensus phosphotyrosinesites [10]. Recent preclinical and clinical data also suggest that HER3 is involved in resistance to other HER receptor-targeted therapeutics [11–15]. Since HER3 has limited kinase activity, several newly developed monoclonal antibodies (mAbs) are being explored to target HER3 for cancer therapy.</p><p>Patritumab (U3-1287) is a fully human monoclonal immunoglobulin G1 (IgG1) antibody directed against HER3, thereby inhibiting ligand binding [heregulin alpha (HRG-α) and heregulin beta (HRG-β)] and receptor activation and induces HER3 down-regulation. Functionally, patritumab inhibits tumor cell proliferation, survival, and anchorage-independent growth in vitro, and inhibits growth of HER3 expressing xenograft tumor models in vivo [16–19]. In addition, the combined use of patritumab with erlotinib, an epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), led to increased inhibition of tumor proliferation, compared with patritumab alone [18].</p><p>In a first-in-human phase 1 study (ClinicalTrials.gov Identifier: NCT00730470), the safety and tolerability of patritumab were evaluated up to the dose of 20 mg/kg without dose-limiting toxicities (DLTs) [20]. In another phase 1 study (ClinicalTrials.jp Identifier: JapicCTI-101,262) in Japanese patients, patritumab was well tolerated up to 18 mg/kg without DLTs and PK profile was similar to the US phase I study [21]. Regarding the combined approaches of former formulation of patritumab (patritumab Process 1) with other molecular targeting agents, both erlotinib in patients with NSCLC and trastuzumab and paclitaxel in patients with HER2 overexpressing metastatic breast cancer were evaluated [22, 23]. The drug substance and product for use in nonclinical studies, phase 1 clinical studies, and phase 2 clinical studies during early phases of development of patritumab were manufactured using Manufacturing Method Process 1. Subsequently, a new method, Process 2 was developed to manufacture the drug substance and product for use in a global phase 3 study, with the aim of increasing the yield of the target protein and improving properties of the drug substance and/or product. Based on both safety profile and clinical activities of patritumab Process 1 combined with EGFR-TKI, erlotinib in patients with advanced NSCLC, this study evaluated that the safety and pharmacokinetics of patritumab Process 2 in combination with erlotinib and potential biomarkers related to patritumab were also evaluated.</p><!><p>This study was conducted based on the Declaration of Helsinki and the Guidelines for the Clinical Evaluation Methods of Anti-Cancer Drugs in Japan (Japanese Ministry of Health, Labour, and Welfare notification, November 1, 2005). The study was approved by the institutional review board of study site.</p><p>The main eligibility criteria were as follows: a histologically or cytologically confirmed diagnosis of stage IIIB/IV NSCLC in a patient who had experienced disease progression while on the standard therapy or in a patient intolerant of, or not eligible for the standard therapy (prior EGFR-TKIs therapy allowed); a patient age ≥ 20 years; an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1; a life expectancy of more than 3 months; and adequate hematologic, hepatic, and renal functions. The exclusion criteria included the administration of chemotherapy, radiotherapy, or biological therapy in the 4 weeks (2 weeks for palliative radiotherapy and kinase inhibitors) prior to enrollment; other active malignancies; history or presence of interstitial lung disease (ILD); history (within 6 months before enrollment) or presence of severe cardiovascular or cerebrovascular disease, pulmonary thrombosis, deep vein thrombosis, or other clinically severe pulmonary disease; any of the following complications, including clinically severe infections requiring systemic administration of an antimicrobial agent, antiviral agent or other agents; presence of chronic diarrhea, inflammatory bowel disease or partial ileus; presence of peptic ulcer; fluid retention requiring treatment; corneal disease; uncontrolled diabetes mellitus; hypertension; psychiatric symptoms; appositive test for hepatitis B virus surface antigen, hepatitis C virus antibody or human immunodeficiency virus antibody; history of a bleeding diathesis; and history of serious hypersensitivity to drugs containing polysorbate 20. All patients provided informed consent, and the study was conducted in accordance with the current Good Clinical Practice standards. This study was registered at ClinicalTrials.jp Identifier:JapicCTI-152,841.</p><!><p>This study was an open-label, non-randomized, phase 1 study of patritumab Process 2 formulation of fully human anti-HER3 monoclonal antibody in combination with erlotinib in Japanese patients with advanced NSCLC that was conducted at single site in Japan. The primary objective was to evaluate the safety and tolerability of patritumab Process 2 formulation combined with erlotinib in Japanese patients with advanced NSCLC. Secondary objectives were to assess the PK profile, preliminary tumor response, to evaluate incidence of anti-patritumab antibody, and to explore patritumab-related biomarkers. Patritumab Process 2 formulation was administered as a 60-min intravenous (i.v.) infusion at 18 mg/kg for the initial dose and at 9 mg/kg for the second and subsequent doses every 3 weeks in combination with an oral daily dose of erlotinib 150 mg (150 mg QD). Patients received fixed dose of patritumab Process 2 formulation at 9 mg/kg every 3 weeks after initiation of 18 mg/kg loading dose combined with erlotinib at 150 mg QD in single dose cohort until any of the withdrawal criteria are met. Withdrawal criteria are disease progression, unacceptable toxicity, ILD, dosing postponed/discontinued for more than 3 weeks, subject's request to withdraw from study treatment, and other instances in which the study cannot be continued in the judgment of the investigator. The initial 21 days after the first administration (cycle 1) were regarded as the DLT evaluation period, and six patients were enrolled at single dose cohort. In the DLT assessments, if none/one of the six patients had a DLT that dose was considered to be tolerable. Adverse events (AEs) were graded using the National Cancer Institute Common Terminology Criteria for AEs, version 4.0. A DLT was defined as any of the following events occurring during cycle 1 (the initial 21 days) as related to either patritumab or erlotinib: (1) grade 3 or higher febrile neutropenia, or persistent (more than 7 days) grade 4 neutropenia; (2) grade 4 thrombocytopenia, or grade 3 thrombocytopenia requiring blood transfusion; (3) uncontrollable grade 3 or higher fatigue, anorexia, nausea, vomiting, skin disorder (e.g., skin eruption, urticaria), and diarrhea despite maximal supportive therapy; (4) grade 3 or higher toxicity, with the exception of (1)–(3) as well as pyrexia without neutropenia, transient electrolyte abnormality, and transient lab-oratory abnormality not requiring treatment and without clinical symptoms; and (5) toxicity requiring suspension of erlotinib therapy for more than 7 days during the DLT evaluation period. Tumor response was determined for all patients with measurable and/or non-measurable lesions according to Response Evaluation Criteria in Solid Tumors (RECIST version 1.1). Tumor measurements by CT or MRI were obtained at baseline, every 6 weeks thereafter and Cycle 1 Day 21.</p><!><p>Pharmacokinetics were evaluated in all patients received patritumab Process 2 formulation in combination with erlotinib. Blood samples were collected at pre-dose and 1 (end of infusion), 4, 7, 24, and 72 h after the start of first dose infusion, on Days 8 and 15 of Cycle 1, and on Day 1 of Cycles 2, 3, and 4. Serum concentrations of patritumab Process 2 formulation were determined by enzyme-linked immunosorbent assay (ELISA). Pharmacokinetic parameters after the first dose were calculated by non-compartmental analysis using WinNonlin (Ver.6.2 CERTARA G.K., Japan).</p><p>Pharmacokinetic statistical analyses were performed using SAS System Release 9.2 (SAS Institute Japan Ltd., Tokyo, Japan).</p><!><p>Serum soluble HER3 and the HER3 ligand, heregulin (HRG) levels were also evaluated in all patients. Blood for serum biomarkers was collected on Day 1 (before administration), 8, 15, and 21 of Cycle 1, and Day 21 of Cycle 2 and changes in both soluble HER3 and HRG serum levels were evaluated. Soluble HER3 levels were measured by enzyme-linked immunosorbent assay (ELISA). In addition, soluble HRG was also evaluated immunologically according to the previous report [24, 25].</p><!><p>All patients who received study medication were included in the analysis of safety and efficacy. Safety and efficacy statistical analyses were performed by SAS System Release 9.2 (SAS Institute Inc., Cary, NC, USA).</p><!><p>Six Japanese patients with advanced NSCLC were enrolled and were evaluated in this study. The baseline characteristics of the patients are summarized in Table 1. The age range was 54.0–78.0 years (median: 72.5 years), and all six patients harbored EGFR mutation (exon 19 deletion, n = 2; L858R, n = 4; T790M, n = 1). Five patients received prior EGFR-TKI therapies treated by at least any one of gefitinib, erlotinib, and afatinib, and one patient was an EGFR-TKI therapy naïve patient. The median number of prior chemotherapy regimens was 2 (range, 1 − 5). At the time of data cutoff, all patients had discontinued treatment: one because of an adverse event (grade 3 ILD), one because of patient withdrawal and four because of disease progression.</p><!><p>Baseline patient characteristics</p><p>ECOG Eastern Cooperative Oncology Group, EGFR Epidermal Growth Factor Receptor</p><!><p>The DLTs occurring during cycle 1 were evaluated. No DLTs were observed in all patients. The AEs reported for all treatment cycles are summarized in Table 2.</p><!><p>Adverse events in more than 20 % of patients</p><p>Preferred Terms are coded using MedDRA version 19.0</p><!><p>The most common overall AEs (≥ 50 %) were diarrhea, stomatitis, dermatitis acneiform, dry skin, and paronychia which were generally mild and manageable. Most of the AEs were related to both patritumab and erlotinib and were generally mild and manageable. No grade 4 or grade 5 AEs occurred in this study. One patient discontinued both patritumab and erlotinib treatment because of a drug-related AE. An elderly female patient with gefitinib-pretreated advanced NSCLC developed grade 3 ILD (onset, day 86); after the discontinuation of both patritumab and erlotinib treatment, steroid administration was conducted and ILD was resolving. No patients developed anti-patritumab antibodies after the administration of patritumab Process 2 formulation in this study.</p><!><p>Mean +/− sd serum concentration for patritumab Process 2 formulation versus time is shown in Fig. 1, and descriptive statistics for the PK parameters are summarized in Table 3. The mean area under the curve (AUC) value was 2640 µg day/mL; the Cmax value was 434 µg/mL; and the terminal half-live was 9.18 days, respectively.</p><!><p>The mean ± sd serum concentration for patritumab Process 2 formulation versus time</p><p>Summary of pharmacokinetic parameters of patritumab (U3-1287) Process 2 formulation in Japanese patients with advanced NSCLC</p><p>C max maximum observed serum concentration, T max time of maximum observed serum concentration, AUC 0 − 21day area under the concentration–time curve from day 0 to day 21, AUC 0−∞ area under the concentration–time curve from day 0 to infinity, t 1/2 elimination half-life, Vss the terminal phase volume, CL clearance, CV coefficient of variation</p><!><p>One partial response (PR) and five cases with stable disease (SD) were observed. The PR was observed in an EGFR-TKI naïve patient who had a tumor with an EGFR-activating mutation (L858R). Among the five SD patients, all patients received prior EGFR-TKIs (treated by at least any one of gefitinib, afatinib, and erlotinib) treatment (exon 19 deletion, n = 2; L858R, n  = 3, T790M, n = 1). The median progression-free survival (PFS) (95 % confidence interval) was 222.0 (100.0–363.0) days.</p><!><p>Soluble serum HRG level was detectable in only a patient, subject No. 2, prior the administration (5,190.1 pg/ml), although was not detectable in other samples from five patients (Table 4). In addition, this patient maintained a most durable stable disease for 363 days among six patients, although tumor already acquired a resistance to gefitinib. The soluble HRG level was maintained on during Cycles 1 and 2 in a patient subject No. 2 (7411.2 pg/ml at Day 8 of Cycle 1; 6870.5 pg/ml at Day 15 of Cycle 1; 5399.1 pg/ml at Day 21 of Cycle 1; and 5329.5 pg/ml at Day 21 of Cycle 2). Soluble HER3 level was various in serum obtained from six patients prior the administration (mean 7,475.8 pg/ml; 3,164.0–25,005.5 pg/ml, Table 4). Soluble HER3 level increased post the administration (mean 15,585.8 pg/ml at Day 8 of Cycle 1; 18,016.7 pg/ml at Day 15 of Cycle 1; 18,100.1 pg/ml at Day 21 of Cycle 1, Supple. Table 2).</p><!><p>Patient characteristics and soluble HER3 expression in serum</p><p>PR partial response, SD stable disease</p><!><p>This phase 1 study was conducted primarily to evaluate the safety and tolerability of patritumab Process 2 formulation combined with EGFR-TKI, erlotinib in Japanese patients with advanced NSCLC. The safety and tolerability, PK, anti-patritumab antibody, tumor response, and biomarkers, including sHER3 and sHRG, were explored in this study. Patritumab Process 2 formulation was developed to manufacture the drug substance with the aim of increasing the yield of the target protein and improving properties of the drug substance and/or product.</p><p>Regarding safety and tolerability, no DLTs were reported at all patients (patritumab Process 2 formulation at 9 mg/kg every 3 weeks after initiation of 18 mg/kg loading dose with oral daily dose of erlotinib 150 mg). The most common AEs in this study were gastrointestinal and skin toxicities, which were generally mild and manageable and most AEs in this study were similar to the well-known side effects of EGFR-TKIs. No treatment-related deaths due to AEs were reported. Some SAEs were reported, including grade 3 ILD, which was related to either patritumab or erlotinib treatment. An elder female patient with gefitinib-pretreated advanced NSCLC developed grade 3 ILD (onset, day 86); after the discontinuation of both patritumab and erlotinib treatment, steroid administration was conducted and ILD was resolving.</p><p>PK parameters were calculated by non-compartmental model-based analysis, and AUC0−21day and Cmax were compared with existing data of former Process 1 formulation combined with erlotinib in Japanese patients with non-small cell lung cancer. The AUC0−21day and Cmax (Mean ± SD) of the Process 2 formulation were 2640 ± 544 µg day/mL and 434 ± 121 µg/mL, respectively, suggesting almost comparable exposure obtained with Process1 formulation (AUC0−21day and Cmax: 2480 ± 420 µg day/mL and 400 ± 46.7 µg/mL, respectively) [22]. Furthermore, no neutralizing antibodies were detected in patients in this study after patritumab Process 2 formulation administration, as assessed by an anti-patritumab antibody and cell-based bioassay, similar to findings in the previous studies.</p><p>In regard to the clinical efficacy of the combined treatment, 1 PR and 5 cases with SD were observed among six patients. The PR patient had a tumor with an EGFR-activating mutation (L858R) and EGFR-TKI naïve setting. Among six patients, five patients had available information about T790M status of their tumor by conducting pre- or post-biopsy of tumor tissue when patients developed disease progression against preceding EGFR-TKIs therapy. Although this was limited patients' number, one key remarkable point about potential clinical efficacy in this study is that durable progression-free survival was observed (363, 100, and 297 days) in three T790M wild-type EGFR-TKI refractory patients. These results were encouraging, because they were similar or superior to those obtained with use of the third generation EGFR-TKI, osimertinib (AZD9291) in recent clinical study in patients with previously treated NSCLC and sub-population analysis of patients with no detectable EGFR T790M (69 % of the patients had an estimated response duration of 6 months or longer, with a median progression-free survival of 2.8 months (95 % CI, 2.1 to 4.3; 71 % maturity) in 62 patients with no detectable EGFR T790M [26].</p><p>The current study observed that a patient had a high level of soluble HRG in serum and maintained most durable stable disease, although tumor already acquired a resistance to gefitinib. Previous studies proved that HRG expression level correlated with the efficacy of several kinds of anti-HER3 antibody preclinically as well as clinically [25, 27–30]. U3-1287 also inhibited cell-proliferation in aberrantly heregulin-expressing NSCLC cells [28]. Furthermore, Patritumab combination with erlotinib demonstrated a significantly improved progression-free survival in patients with advanced NSCLC and high level of soluble HRG in serum compared to placebo combination [25]. Although the current study analyzed limited samples, patritumab plus erlotinib might be optimal in patients with EGFR-mutant NSCLC and high level of HRG expression.</p><p>In conclusion, patritumab Process 2 formulation at a dose of 18 mg/kg for the initial dose and at 9 mg/kg for the second and subsequent doses every 3 weeks in combination with an oral daily dose of erlotinib 150 mg was determined to be feasible in regard to the tolerability in Japanese patients with advanced NSCLC. Although some limitations including small patients number exist in this study, preliminary demonstration of both favorable PK profiles and the efficacy of the combined treatment was encouraging, potentially in NSCLC patients with EGFR-activating mutations, where prior EGFR-TKI treatment failed regardless of EGFR T790M status.</p>

PubMed Open Access

Patterned Dried Blood Spot Cards for Improved Sampling of Whole Blood

Dried blood spot (DBS) cards perform many functions for sampling blood that is intended for subsequent laboratory analysis, which include: (i) obviating the need for a phlebotomist by using fingersticks, (ii) enhancing the stability of analytes at ambient or elevated environmental conditions, and (iii) simplifying transportation of samples without a cold chain. However, a significant drawback of standard DBS cards is the potential for sampling bias due to unrestricted filling caused by the hematocrit of blood, which often limits quantitative or reproducible measurements. Alternative microsampling technologies have minimized or eliminated this bias by restricting blood distribution, but these approaches deviate from clinical protocols and present a barrier to broad adoption. Herein, we describe a patterned dried blood spot (pDBS) card that uses wax barriers to control the flow and distribution of blood and provide enhanced sampling by minimizing the hematocrit effect. Patterned cards reproducibly fill four replicate extraction zones independent of the hematocrit. We demonstrate a 3-fold improvement in accuracy for the quantitation of hemoglobin using pDBS cards compared to unpatterned cards. Patterned cards also facilitate the near quantitative recovery (ca. 95%) of sodium with no evidence of a statistically significant difference between dried and liquid blood samples. Similarly, recovery of select amino acids was conserved in comparison to a recent report with improved inter-card precision. We anticipate that this approach presents a viable method for preparing and storing samples of blood in limited resource settings while maintaining current clinical protocols for processing and analyzing dried blood spots.

patterned_dried_blood_spot_cards_for_improved_sampling_of_whole_blood

Introduction<!>Experimental Design<!>Effects of Evaporation on the Quantitation of Hemoglobin<!>Estimation of Sample Volume in 6-mm Paper Punch<!>pDBS Cards Fill Independent of Hematocrit Value<!>Quantitation of Sodium by ICP-AES<!>Quantitation of Amino Acids by HPLC<!>Conclusions<!>Conflicts of Interest

<p>Blood is a complex matrix, comprising cellular and liquid fractions, that contains a wealth of diagnostically relevant biomarkers, which are inclusive of the cells themselves (e.g., neutrophil count), DNA/RNA (e.g., endogenous or from pathogens), and myriad solutes in plasma (e.g., proteins, metabolites, free amino acids). For these reasons, blood is often thought of as the ideal specimen for evaluating the health status of a patient. Obtaining liquid blood samples in centralized facilities or even local clinics is routine practice. In these settings, a trained phlebotomist will collect milliliter volumes of blood by venipuncture, which can either be immediately processed and tested in the laboratory or stored for future analysis within a defined period of time dependent on storage temperature. 1,2 However, these same practices face unique challenges at the point-of-care or in resource-limited settings. Specifically, storage and transportation of liquid blood are complicated by unreliable modes of transportation and inadequate access to cold-chain storage. These limitations often require liquid samples to be discarded due to substantial degradation or significant changes to critical hematological indices.</p><p>In contrast to liquid samples, storing blood in a porous matrix, such as chromatography paper, enhances analyte stability at ambient or even elevated temperatures. 3,4 Dried blood spot (DBS) cards additionally offer simplified sampling using fingersticks and reliable transportation of dried blood by mail, thus circumventing the need for cold chain storage. 5,6 Traditional DBS cards, such as the Whatman 903 Protein Saver card, are a simple construction of a single sheet of thick cellulose cardstock affixed to an envelope for sample identification and handling. 7 Circles are printed onto the surface of the paper using a thin layer of toner to provide guidance for sample application. Fingerstick volumes of blood (e.g., 50-100 µL per spot) are applied to the card and allowed to dry for a minimum of four hours at ambient conditions (and ideally overnight), rendering the card non-biohazardous, before they are sealed and shipped through the mail for laboratory analysis. 8 Self-sampling low volumes of blood without the need for cold chain storage could broadly expand access to basic health information by providing direct-to-consumer testing, facilitate critical population screening, and biobanking efforts. 9 Although traditional DBS cards offer simple operation, require low volumes of blood, and can be collected outside of the clinic, they are severely limited by usability associated with unrestricted sample application zones. This user error can result in non-uniform or smeared blood spots, which will ultimately impact the quality of subsequent laboratory analysis and represents a considerable barrier for ubiquitous use of traditional DBS cards. 9,10 Beyond usability, traditional DBS cards do not account for differences in hematocrit values (Hct)-the ratio of packed red blood cells (RBCs) to total blood sample volume. The normal range of hematocrit spans 36-50% and is affected by variables such as race, sex, age, hydration, and overall health status. 11 Currently, the hematocrit value must be known prior to analysis for accurate quantitation of analytes using DBS cards. Whether caused by filling imprecision or hematocrit, the uniformity of how cells and liquid plasma are distributed throughout the paper cardstock has a substantial impact on the overall utility of a DBS card.</p><p>The hematocrit effect has been extensively reviewed as the main obstacle to overcome for quantitative analysis using traditional DBS cards. [12][13][14][15][16][17][18] Since the hematocrit value represents the ratio of cellular matter to liquid plasma, blood samples with a high hematocrit value (e.g., 55%) will be more viscous than samples with a low hematocrit value (e.g., 30%). Variation in viscosity results in variable sample flow and distribution through the paper, which negatively impacts the reproducibility of sample volumes obtained from a single, fixed punch extraction from DBS.</p><p>Uncontrolled saturation or spreading of blood through the DBS paper can also result in heterogeneous distribution of analytes throughout the area of the resulting DBS (i.e., volcano effect). 19 Because analytes are typically eluted from DBS via a fixed punch, any variation in sample volume and distribution will manifest in downstream clinical measurements causing a lack of precision (i.e., intra-spot agreement) or accuracy (i.e., agreement with liquid sample).</p><p>Many methods for minimizing the hematocrit effect in traditional DBS cards have previously been reported. [20][21][22] Two distinct approaches stand out: (i) whole spot analysis 23,24 and (ii) assay specific calibrants stored within the paper. 25 Both present viable options for minimizing the hematocrit effect by quantitative removal of the entire blood spot (dependent on application of accurate sample volume) or inclusion of an internal standard at a known concentration to estimate extraction efficiency. However, both methods are limited by the number of tests that can be conducted from a single DBS spot. In each format, samples can only be used to perform a single test due to the complete destruction of the entire dried spot or analyte-specific internal standard. Alternatively, three-dimensional blood spheroids eliminate chromatographic effects observed in traditional DBS and reduce the volume of blood required per spot by utilizing functionalized hydrophobic paper. 24 This approach has successfully demonstrated increased stability of enzymes and labile organic compounds. Recently, DBS technologies that operate independent of the hematocrit by constricting sample volume have also been described. The ADX Test Card by Accel Diagnostics utilizes a microfluidic network and magnetic beads to collect, distribute, and analyze blood. 26 The HemaSpot HF comprises pre-cut paper wedges contained within a plastic housing, which hold a finite volume of sample. 27 Similarly, the HemaPEN 28 and Capitainer 29 integrate multiple fixed-volume capillary tubes to standardize the volume of blood applied to a porous matrix. While these devices provide enhanced control over application of sample volume, they do not conform with current clinical collection or automated punching and elution protocols.</p><p>In order to improve the utility of DBS cards with an intent for widespread use, current clinical protocols for sample collection and subsequent analysis should be maintained. Therefore, innovation should build upon the major benefits of traditional DBS technology (i.e., single layer of cardstock). An attractive approach for enhanced sampling is controlling the flow of blood samples in the cardstock with hydrophobic wax barriers. 30 Defining specific areas for (i) sample addition, (ii) distribution, and (iii) storage by wax patterning presents a method for addressing the limitations of current DBS technologies without creating additional clinical barriers. Ideally, blood sampling would be performed via a self-administered fingerstick, simple collection onto a solid matrix, drying, and delivery to a laboratory for testing without significant degradation of the sample at ambient conditions.</p><p>Herein, we describe the creation of patterned dried blood spot (pDBS) cards to address the limitations of traditional DBS cards directly related to the hematocrit effect. Patterning traditional DBS cardstock with hydrophobic wax barriers regulates sample application, distribution, and volume control while operating independently of the hematocrit over a broad range of clinical values (20-60%). A user simply needs to apply a volume of blood to the center of the card and the sample will automatically distribute to four replicate punch zones. Providing more spots for analysis while also maintaining reproducible spreading across physiological hematocrit values can (i) increase the number of technical replicates or (ii) increase the number of clinical assays performed from one sample of whole blood without concern for significant punch-to-punch variation.</p><p>We first investigated the capacity of pDBS cards for quantitative sampling by estimating the volume of blood contained in a standard 6-mm paper punch and reported minimal variation even when the sample input deviates from the World Health Organization (WHO) recommended volume of 75 µL. 5 Next, we demonstrated enhanced usability and spot uniformity independent of the hematocrit for samples collected with pDBS cards compared to traditional, unpatterned cardstock. We highlighted a broad class of analytes to showcase this approach including the quantitation of hemoglobin by UV-vis spectrophotometry, sodium by inductively coupled plasma atomic emission spectroscopy (ICP-AES), and specific amino acids by high-performance liquid chromatography (HPLC). pDBS cards permit enhanced sampling of small volumes of blood that can be generated from a fingerstick and represent a reproducible method capable of performing multiple tests without requiring multiple sample collections or altering established laboratory workflows. We anticipate the quantitative nature of this self-sampling method of blood collection will empower patients by providing critical, accurate diagnostic information at home or in lowincome economies without impacting existing clinical procedures.</p><!><p>Card Design and Fabrication pDBS cards comprise a single layer of cardstock impregnated with wax to form three distinct features: (i) sample addition zone, (ii) lateral distribution channels, and (iii) four replicate, collection punch zones (Figure 1A). We designed our cards to accommodate a sample input volume of 75 µL and output punch diameter of 6-mm in accordance with the WHO recommended specifications for DBS sampling. The design features (e.g., lateral channels) and geometries were informed by our previous experience with whole blood in paper for measuring the hematocrit. 31,32 Whole blood is transported from the sample addition zone along the lateral channels via capillary action and fills four replicate collection punch zones at the end of each channel. Extending the lateral channels past the collection punch zones allowed complete saturation of the punch zone for more accurate sampling compared to traditional DBS cards. Wax printing is typically performed by direct deposition of wax onto relatively thin (≤ 250 µm), smooth papers followed by application of heat to allow the wax to coat the paper fibers. 33 For papers > 250 µm thick, standard printing practices cannot deposit sufficient wax to form complete hydrophobic barriers (Figure S1A). 34 Incomplete barriers resulted in uncontrolled sample flow and represent a challenge for patterning DBS papers. Alternative methods for patterning thick materials with photoresist or paraffin have been reported previously. 35 However, to maintain the numerous benefits of wax printing, we utilized a double-sided wax transfer method 36 to successfully pattern papers commonly used for traditional DBS cards (e.g., Whatman CF-12, Ahlstrom 226, Munktell TFN) (Figure S1B). First, we printed the top and bottom designs onto laminate sheets using a Xerox ColorQube 8580 wax printer. Next, we aligned a sheet of chromatography paper with the top and bottom designs using a custom acrylic alignment jig. Finally, we used a Promo Heat CS-15 T-shirt press (45 seconds at 280 °C) to transfer the wax from the laminate sheets to the paper to form hydrophobic barriers through the full thickness of the paper.</p><p>Patterning each side with a unique design allowed partial coating of the cellulose fibers through approximately half the thickness of the paper to reduce the void volume of the sample addition and lateral distribution channels in pDBS cards (Figure 1B). This process provided an added benefit of minimizing sample input volume while maximizing sample collection volume from the punch zones. After addition of whole blood, we dried pDBS cards under ambient conditions in a biosafety cabinet (ca. 16 hours), whereby they can be used immediately or sealed in a foil pouch with silica desiccant packets and a humidity indicator card for long-term storage. All data presented herein were collected using pDBS cards fabricated from TFN grade cardstock. We chose to demonstrate the utility of our cards for sampling a range of analytes (e.g., hemoglobin, sodium, and select amino acids) and technique groups (e.g., UV-vis spectrophotometry, ICP-AES, and HPLC).</p><!><p>Evaporation at ambient conditions is the driving force for drying samples of blood in DBS cards. Sealing-or partially sealing-sections of our pDBS cards influenced the location and extent of evaporation. Additionally, altering the bottom design of the pDBS card can affect evaporation by controlling the amount of unpatterned card area that is exposed to the environment. We iteratively added or removed a layer of laminate to the top and bottom sides of the pDBS card and evaluated the effects of evaporation on the quantitation of hemoglobin using a modification of the standard Drabkin's assay (Figure S2). The bottom design either (i) excluded (designs A and B) or (ii) included (designs C and D) the lateral distribution channels. Evaluating these design features across a range of hematocrit is critical for understanding the effects of evaporation since these samples have varying volumes of liquid plasma (e.g., 52.5 µL of plasma in 75 µL of 30% hematocrit blood vs. 37.5 µL of plasma in 75 µL of 50% hematocrit blood).</p><p>Excluding the lateral channels and sample addition zone in the bottom design reduced the total void volume of the unpatterned area and eliminated evaporation from the bottom side of the lateral channels and sample addition zone. Reducing the void volume improved reproducibility for card filling. Further covering the lateral channels on the top side of the pDBS card minimized evaporation along the channel and effectively concentrated the blood sample in the collection punch zones. Preconcentration of blood in the collection punch zones resulted in higher percent deviation for the quantitation of hemoglobin (Table S1), which we expect is due to the volume dependency of the Drabkin's assay. 37 Both designs B and C had comparable performance even though design B included no laminate covering the unpatterned area and design C was completely laminated (except at the sample addition zone). We chose to move forward with design B for two reasons: (i) it yielded the lowest percent error for both 30% and 50% hematocrit samples and (ii) reduced the number of laminate layers necessary which simplified the manufacturing and operational processes.</p><!><p>After finalizing the form factor of our pDBS card and minimizing the effect of evaporation through unique bottom patterning, we measured the volume of a dried sample contained in an individual 6-mm paper punch in order to correlate the concentration of an analyte to the total sample of blood. Accurate comparison of liquid reference samples to our pDBS card is dependent on the sample volume contained within a punch. This type of measurement has been accomplished using a variety of methods including ion suppression by liquid chromatographytandem mass spectrometry 20 and electrical conductivity of DBS extract by a ring disk electrode. 10 We utilized the volume dependency of the Drabkin's assay to estimate the output sample volume in our pDBS card. 38 First, we constructed a series of calibration curves (Figure S3A) using liquid hemoglobin standards with varied sample input volumes (3-11 µL) to establish a relationship between linear slope of the calibration curve and sample volume (Figure S3B). Then, we 10 calibrated our pDBS cards with hemoglobin standards and estimated the sample volume contained in a 6-mm paper punch using the resultant linear relationship and slope of the calibration curve in our pDBS card (Figure S3C). All hemoglobin samples reproducibly filled the pDBS cards (Figure S3D). We estimated that each 6-mm paper punch contained 10.3 ± 0.4 µL of whole blood, representing a total output sample volume of approximately 41.2 µL from an input volume of 75 µL blood. The low variation (< 5%) observed in the sample volume contained in a paper punch indicated consistent sample distribution in pDBS cards.</p><p>Deviating from the recommended sample input volume of 75 µL can negatively impact the quantitation of analytes such as hemoglobin. To simulate under-and overfilling, we applied a range of sample volumes 60-90 µL in 5 µL increments at a single hematocrit (Figure S4A). Our pDBS cards reproducibly filled four replicate punch zones with a sample volume ≥ 65 µL (Figure S4B). The average deviation for replicate cards with sample input varying ± 15 µL was only 12.0% compared to the liquid reference sample. This result provided confidence that slight variations in the sample input volume (e.g., from direct addition of a fingerstick rather than sample addition by volumetric pipette) will not substantially impact quantitative results if volumetric sample application is unavailable at the site of collection.</p><!><p>We aimed to further evaluate the effect of sample input on quantitation of hemoglobin by surveying the physiological range of hematocrit values (20-60%). We anticipated that controlling the total area of the pDBS card through patterning would minimize the negative effects of variable sample spreading caused by the hematocrit. Direct comparison of pDBS cards and unpatterned TFN clearly demonstrated how the hematocrit influenced the results of standard assays such as the quantitation of hemoglobin (Table 1). Patterned cards yielded ≤ 7% error across the full range of hematocrit values, while unpatterned cards yielded 3-fold higher percent error at low hematocrit (21% error at 20% hematocrit, Table 1). Inter-and intra-card variation (i.e., spot-to-spot variation) were consistent between both card types (Table S2), which suggested the deviation in the quantitation of hemoglobin can largely be attributed to uncontrolled sample spreading of blood in unpatterned cards. Agreement between pDBS cards (Figure 2A) and unpatterned TFN (Figure 2B) with the reference liquid blood is represented by Bland-Altman plots. 39 The observed bias was reduced in pDBS cards (-0.7 g/dL) compared to TFN (-1.0 g/dL). Similarly, the limit of agreement was narrower for pDBS (2.2 g/dL) than TFN (3.0 g/dL) in comparison to the reference method.</p><p>Patterned cards reproducibly filled four replicate collection punch zones (6-mm diameter) across the full range of hematocrit values (Figure 3A). Since pDBS cards filled independently of the hematocrit, four replicate punches can always be collected for analysis and enable more tests to be performed from a single card. In stark contrast, the diameter of the blood spot in unpatterned TFN decreased with increasing hematocrit (20-60% hematocrit) (Figure 3B). A direct consequence of the decreased blood spot diameter in unpatterned DBS is one less technical replicate punch of dried blood under idealized conditions (Figure 3C).</p><!><p>Blood sodium levels are routinely measured as part of a basic metabolic panel that often includes additional electrolytes such as calcium, chloride, and potassium. Accurate quantitation of sodium is critical for controlling blood pressure and evaluating proper nerve and muscle function. 40 Additionally, because sodium is found both intra-and extracellularly, it represented an attractive analyte class to further evaluate the quantitative capabilities of pDBS cards. The concentration of sodium in blood samples obtained from pDBS cards (1715 ± 21 ppm) was nearly identical to the concentration in the reference liquid sample (1810 ± 24 ppm), suggesting that there is no apparent loss or evaporative concentration of sodium to the TFN paper (Figure 4). A two-tailed Student's t-test yielded a p-value of 0.26, providing no evidence of a statistically significant difference in sodium concentration between the dried and liquid blood samples. The clinical reference range for sodium in blood is 135-145 mEq/L. 41 Both the dried and liquid blood samples fell below the expected range with 74.6 and 78.7 mEq/L sodium, respectively. Both samples were prepared using nitric acid digestion, which included multiple liquid handling and quantitative transfer steps, which could account for the low observed concentrations. While the range of concentrations of sodium extracted from pDBS punches (683.9 ppm) was more dispersed than those from liquid samples of blood (392.4 ppm), the standard deviation was slightly less. Comparison of variances (F-test) yielded a p-value of 0.27, indicating no significant difference between the variance of the data sets. Therefore, the precision of pDBS card microsampling could be amenable to use of calibration standards for quantitative results.</p><!><p>Amino acid analysis via DBS sampling is commonly used for the detection of various inborn errors of amino acid metabolism including phenylketonuria (PKU) in newborns. Efforts to streamline and improve the quantitation of amino acids from DBS have been extensively reported. [42][43][44] For demonstrative purposes, we selected three representative hydrophobic amino acids (e.g., tryptophan, leucine, and proline) and one basic-or positively charged-amino acid (e.g., lysine) for analysis. Recovery of each amino acid from pDBS cards was determined by the ratio of extracted analyte concentration (µM) and liquid reference concentration (µM) as analyzed by HPLC. Two distinct sample groups (e.g., 20% and 40% hematocrit) were selected to represent (i) a high liquid-to-cell ratio-which can be prone to underestimating analytes of interest-and (ii) the average hematocrit obtained from our panel of healthy donors, respectively. Each amino acid yielded excellent recovery for both blood sample groups (Table 2). While most samples fell in the range of 82-93% recovery, two samples yielded higher concentrations when extracted from pDBS cards compared to liquid reference samples (proline 115%, lysine 102%). Resultant loss and variability in analyte recovery may be attributed to the number of liquid handing steps required to extract, process, and derivatize samples prior to analysis by HPLC. However, all reported values in Table 2 are in agreement with other reports where recovery of amino acids ranged from 84.2 ± 22.2-96.0 ± 12.0%. 45 Additionally, the evaluation of interassay precision (i.e., card-to-card 13 comparison) demonstrated a coefficient of variation (%CV) for tryptophan of 0.8-5.2%, leucine 2.6-6.7%, proline 1.0-5.5%, and lysine 5.4-5.7% (Table S3). These %CV values are considerably improved in comparison to recently reported %CV for amino acid analysis by traditional DBS sampling using similar methods (e.g., %CV for leucine 8.3-15.3%). 44 Successful quantitation and improved interassay precision of select amino acids by HPLC supported the enhanced sampling capabilities of pDBS cards.</p><!><p>We aimed to develop a device that can improve the sampling of whole blood at the pointof-care while maintaining current clinical protocols for DBS analysis. Our approach comprised wax-patterned DBS cardstock to restrict the flow and distribution of whole blood with four defined extraction zones. Controlling the flow of blood in the pDBS card allowed reproducible filling across the full range of hematocrit values and reduced the sampling bias for pDBS cards compared to unpatterned TFN cardstock. Specifically, the accuracy for the quantitation of hemoglobin with low hematocrit (20%) was improved by 3-fold using pDBS cards. Sampling was further improved by spatially defining extraction zones, which consistently produced four replicate 6-mm diameter punches from a single application of blood (75 µL), independent of the hematocrit value. We designed these cards to accommodate direct application of fingerstick volumes of blood and modeled ideal conditions by dispensing blood using a volumetric pipette. The highly controlled nature of this method of sample dispensing may be reflective of the conserved inter-and intracard variations reported for both pDBS and traditional DBS cards. We anticipate that the patterned features of pDBS cards will maintain uniform filling and address the reported challenges associated with applying fingersticks to DBS at the point-of-care.</p><p>Surveying common DBS analytical techniques such as ICP-AES and HPLC indicated good agreement with liquid reference samples for the quantitation of sodium and select amino acids, respectively. Additionally, we were able to process and analyze samples of whole blood without changing recommended handling procedures for DBS cards (i.e., amenable to automated punching machines). Standardizing the sample output from pDBS cards could expand the number of tests performed from a single sample collection or permit increased numbers of technical replicates compared to traditional unpatterned DBS cards. Beyond the classes of analytes and techniques demonstrated in this manuscript, quantitative DBS sampling has the potential for myriad applications related to molecular amplification (e.g., screening for viral diseases), nutritional evaluations, immunologic studies, pharmacokinetics, therapeutic drug monitoring, and genetic testing. 46 Since pDBS cards are exposed to ambient conditions during sample application, spreading, and drying, we expect performance may vary under certain environmental conditions at the time of collection, as similarly experienced with traditional DBS cards. For example, sample spreading may be reduced due to extremely dry conditions (relative humidity below 10%) or high temperatures, which could cause excessive evaporation. However, this effect is commonplace for DBS technologies and is not identified as a major obstacle for ubiquitous use. 6 While the pDBS card presented here was used for sampling whole blood, we anticipate that we could expand on this approach to collect and store additional sample types such as saliva, tears, or blood plasma to provide enhanced sampling and quantitative analysis in a workflow that connects the point-ofcare to a clinical laboratory infrastructure.</p><!><p>The authors declare no conflicts of interest.</p>

ChemRxiv

Stereochemical Assignment of the Protein–Protein Interaction Inhibitor JBIR-22 by Total Synthesis**

Recent reports have highlighted the biological activity associated with a subfamily of the tetramic acid class of natural products. Despite the fact that members of this subfamily act as protein–protein interaction inhibitors that are of relevance to proteasome assembly, no synthetic work has been reported. This may be due to the fact that this subfamily contains an unnatural 4,4-disubstitued glutamic acid, the synthesis of which provides a key challenge. A highly stereoselective route to a masked form of this unnatural amino acid now enabled the synthesis of two of the possible diastereomers of JBIR-22 and allowed the assignment of its relative and absolute stereochemistry.

stereochemical_assignment_of_the_protein–protein_interaction_inhibitor_jbir-22_by_total_synthesis**

<!>

<p>Natural products that contain the tetramic acid motif have been studied extensively, and their complexity and biological profiles have led to several total syntheses.[1] For example, equisetin, a close structural analogue of the compounds studied here, has been prepared.[1a–c] However, the synthesis of members of a subfamily that contain an unnatural 4,4-disubstituted glutamic acid unit (1–4, Figure 1) is an unmet challenge.[2] The biological activity displayed by members of this subfamily justifies the development of a concise and general approach for their synthesis.</p><p>A subfamily of tetramic acid natural products containing an unnatural 4,4-disubstituted glutamic acid unit. Syntheses of 1–4 have not been reported thus far. The shown relative and absolute stereochemistry of 2 was assigned by our study.</p><p>Examples of the important activity shown by this subfamily include the inhibition of the CCR5 receptor by Sch210972 (1).[2a,b] A number of CCR5 receptor antagonists are in clinical trials or in use as antiretroviral drugs.[3], [4] In addition, JBIR-22 (2) is the first example of a tetramic acid that acts as a protein–protein interaction (PPI) inhibitor.[2c,d] Compound 2 inhibits the homodimerization of the proteasome assembly chaperone 3 (PAC3), an important protein involved in the formation of the proteasomal machinery. The clinical success of bortexomib,[5] a proteasome inhibitor, supports the study of compounds that target the proteasome or its formation. The fact that the stereochemical assignment of 2[2c] was incomplete when our work began further highlights the need for synthetic studies on this subfamily of tetramic acids.</p><p>Although chemical[6] and enzymatic[7] syntheses of 4-hydroxy-4-methylglutamic acid have been developed, a synthesis of 4-hydroxy-4-iso-propylglutamic acid has not yet been reported, which could be a factor in the lack of synthetic work done on this subfamily. Here we report a short, stereoselective synthesis of a 4,4-disubstituted glutamic acid derivative and the application of this methodology to the first total synthesis of 2. Our studies enabled the assignment of the relative and absolute stereochemistry of 2.</p><p>Our initial synthetic plan was based on the synthesis of 1,3-amino alcohols (e.g. 5). This methodology involved the diastereoselective addition of a metalloenamine 6 to an aldehyde followed by diastereoselective imine reduction (Scheme 1).[8] We proposed that the reaction of 7 with ethyl dimethylpyruvate could establish the required stereogenic center of the tertiary alcohol. Subsequent diastereoselective reduction of the resulting β-hydroxy-N-sulfinyl ketimine 8 could give 9, a precursor of a protected form of the unnatural amino acid 10 (Scheme 1). If accessible, 10 could potentially be used in the synthesis of 2 in an analogous manner to that previously demonstrated for other tetramic acids containing natural amino acids, such as equisetin.[1a–c, 9] It also seemed plausible that the tertiary alcohol in 8 or 9 may cyclize to generate a lactone (e.g. 11 from 9). If this occurred, N-methylation of 11 and removal of the N-sulfinyl group could give the masked 4,4-disubstituted glutamic acid derivative 12. Conversion of 12 to members of this subfamily was considered achievable.</p><p>Ellman's stereoselective synthesis of 1,3-amino alcohols.[8] A possible synthesis of the required unnatural amino acid or a cyclized version. Reagents and conditions: a) diastereoselective aldol reaction; b) diastereoselective reduction; c) lactonization; d) N-methylation and cleavage of the N-sulfinyl group; e) N-methylation and protecting group manipulation.</p><p>The synthesis of 7 was achieved by condensation of (RS)-tert-butanesulfinamide with ethyl pyruvate (8). Using the reported conditions,[10] 7 was obtained in only 30 % yield with the major product being lactone 13 (13:7=5:3, Scheme 2). The formation of 13 likely occurred in situ through an Ti(OEt)4-catalyzed aldol reaction of 7 with ethyl pyruvate (8) followed by lactonization (Scheme S1). Although 13 was not required for the preparation of 2, it could be used in a future synthesis of 1. Optimization of the synthesis of 7 resulted in its isolation in 60 % yield (Table S1). Reaction of 7 with ethyl dimethylpyruvate gave the related lactone 14 (Scheme 2) with excellent diastereoselectivity and yield. As expected, 14 was confirmed as the (Rs,2S) diastereomer by X-ray analysis (Scheme 2).[8], [11] N-methylation of 14 proceeded in high yield to provide 15. While an initial screening of reducing agents gave only recovered lactone 15, the use of NaBH3CN with HCl (4 n in dioxane) resulted in the diastereoselective (d.r.>98 %) reduction of 15 with cleavage of the N-sulfinyl group to give 12 (Scheme 2). The stereochemistry of 12 was assigned by NOE analysis (Scheme 2 and Figure S1). Further analysis suggested that this reaction proceeded by acid deprotection of the N-sulfinyl group followed by the reduction with NaBH3CN (Scheme S2). The observed diastereoselectivity was rationalized based on the preferred approach of the reducing agent from the same side as the ester. This efficient route provided the masked 4-hydroxy-4-isopropyl glutamic acid 12 in just four steps from 8.</p><p>Condensation of 8 and (RS)-tert-butanesulfinamide gave lactone 13 and 7 in a 5:3 ratio. Reagents and conditions: a) (RS)-tert-butanesulfinamide, Ti(OEt)4, Table S1 for optimization; b) (i) LDA, THF, 0 °C. (ii) Ethyl dimethylpyruvate, ZnBr2, −78 °C, 88 %, d.r.>98 %; c) LiHMDS, iodomethane, DMF, −15 °C→RT, 95 %; d) (i) HCl (4 n in dioxane), THF, 0 °C, 10 min. (ii) NaBH3CN, MeOH, 1.5 h, 0 °C, 85 %, d.r.>98 %. X-ray analysis of 14 confirmed the expected (Rs,2S) stereochemistry. The stereochemistry of 12 was determined using NOE analysis (Figure S1).</p><p>With 12 in hand, a synthesis of 2 was attempted because of its unique activity as a PPI inhibitor and the uncertainty associated with its stereochemical assignment. Izumikawa et al. had shown that 2 could be assigned as one of the four stereoisomers shown in Table 1 (diastereomers 2 a and 2 b and their enantiomers 2 c and 2 d).[2c] Given the relatively large distance between the decalin moiety and the unnatural amino acid stereogenic center in 2, it is difficult to assign the relative configuration of these two units. A convergent route to access optically enriched samples of diastereomers 2 a and 2 b was therefore investigated (Scheme 3).</p><p>Retrosynthetic analysis of JBIR-22 diastereomer 2 a.</p><p>Stereochemical assignment of four of the possible stereoisomers of 2 (as reported in reference [2c]).[a] The absolute configuration of stereoisomer 2 a is depicted.</p><p>The tetramic acid core in 2 a would be formed at a late stage, inspired by the conversion of 3-oxo-homoserine lactones to simple tetramic acids through a Claisen-like intramolecular reaction (Scheme S3).[12] A Lacey–Dieckmann condensation of fragment 16 would form the tetramic acid core and provide the unnatural 4,4-disubstituted glutamic acid side chain in one step. Fragment 16 could be accessible through the coupling of 12 and the β-ketothioester 17 a. A late-stage convergent step such as this could ultimately facilitate the coupling of alternate β-ketothioesters to enable access to the other members of this subfamily (Figure 1) or novel analogues. We envisaged that the decalin β-ketothioester could be assembled through an asymmetric Diels–Alder cycloaddition followed by manipulation to introduce the thioester functionality (Schemes 4 and 5).</p><p>Synthesis of 23. Reagents and conditions: a) KHMDS, diethyl 2-butenylphosphonate (19), DME, −78 °C→RT, 69 %, E:Z=8:1; b) Aq. HCl, THF, RT, 12 h, 94 %; c) (i) (1,3-dioxolan-2-ylmethyl)triphenylphosphonium bromide (22), tBuOK, THF, 0 °C, 3.5 h. (ii) 10 % aq. oxalic acid, RT, 1 h, 89 %.</p><p>Assembly of 17 a/b began with an Schreiber ozonolysis[13] of cyclohexene to give acetal 18. Horner–Wadsworth–Emmons (HWE) olefination of 18 using phosphonate 19 provided 20 (8:1 mixture of inseparable E,E:E,Z isomers, Scheme 4). The acid-mediated deprotection of 20 gave dienal 21, which was reacted with Wittig reagent 22, followed by acetal hydrolysis to give the trienal 23 (85 % E,E,E geometry). Trienal 23 was then subjected to an organocatalytic intramolecular Diels–Alder (IMDA) reaction using MacMillan's conditions (Scheme 5).[14] Both enantiomers of 24 were accessed with good enantioselectivities (see Scheme 5 and the Supporting Information for chiral GC analysis). The minor E,Z,E isomer present in the sample of 23 was inert in this IMDA reaction, thus enabling the purification to give either 24 a or 24 b, depending on which enantiomer of the organocatalyst was used (Scheme S4).[14] Elaboration of 24 a and 24 b to give β-ketothioesters 17 a and 17 b, respectively, was achieved through an aldol reaction using S-tert-butyl thioacetate to give 25 a or 25 b, respectively, as an inconsequential mixture of diastereomers, followed by oxidation with Dess–Martin periodinane[15] (Scheme 5).</p><p>Synthesis of β-ketothioesters 17 a (Scheme 3) and 17 b. Reagents and conditions: a) 20 mol % (S,S)-imidazolidinone TfOH, MeCN (2 % H2O), −5 °C, 48 h, 65 %, 87 % ee, d.r. 4:1. b) 20 mol % (R,R)-imidazolidinone TfOH, MeCN (2 % H2O), −5 °C, 48 h, 68 %, 84 % ee, d.r. 4:1. c) (i) LDA, S-tert-butyl-thioacetate, THF, −78 °C, 30 mins. (ii) 24 a 24 b, THF, −78 °C, 2 h, 25 a (66 %); 25 b (69 %). d) Dess–Martin periodinane, DCM, RT, 2 h, 17 a (79 %); 17 b (82 %).</p><p>The final stages involved a silver trifluoroacetate mediated coupling of 12 with either enantiomer of fragment 17 to give 26 a and 26 b, following the protocol developed by the Ley group for the synthesis of equisetin (Scheme 6).[1b, 16] Finally, cyclization onto the lactone in 26 a and 26 b and microwave-assisted ester hydrolysis gave separate samples of the optically enriched diastereomers 2 a and 2 b, which were purified by reverse-phase chromatography. No evidence of epimerization at the C5' position was observed.[17]</p><p>Synthesis of JBIR-22 diastereomers 2 a and 2 b. Reagents and conditions: a) 12, AgCF3CO2, Et3N, THF, 0 °C→RT, 2 h, 25 a—89 %; 25 b—84 %. b) (i) tBuOK, THF, 0 °C→RT, 2 h. (ii) Aq. NaOH, EtOH, 110 °C (MW), 20 mins, 2 a—71 %; 2 b—74 % over 2 steps.</p><p>The assignment of the relative stereochemistry of 2 was completed by comparison of the reported spectroscopic data[2c] for 2 with those obtained for our synthetic samples of 2 a and 2 b. This analysis revealed very similar 1H NMR signals, but clear differences in the 13C NMR spectra, with the signals reported for the isolated sample of 2 all being within ±0.1 ppm of those obtained for diastereomer 2 a. In contrast, there were significant differences when the data was compared to that for diastereomer 2 b (Figure 2 for selected examples and Table S2). Further evidence for the identical relative stereochemistry in 2 and diastereomer 2 a came from doping experiments using UPLC-TOFMS (Figure 2). These studies showed that upon mixing of a sample of natural 2 (retention time=3.3 min) with 2 a, an increase in the size of the peak at 3.3 min was observed, whereas doping of natural 2 with 2 b led to the appearance of a different peak with a retention time of 3.6 min. Comparison of the specific rotation of 2 a (+75.0°, c=0.1, MeOH) with that obtained for natural 2 (+62.0°, c=0.1, MeOH)[18] enabled the assignment of the absolute configuration of 2 as (2S, 3S, 6R, 11S, 5′S, 7′S).</p><p>A) UPLC-TOFMS doping experiment. B) Selected 13C NMR signals of 2 a and 2 b with 2 a/b (a 1:1 mixture of 2 a and 2 b synthesized following an alternative route, Scheme S5). C) Selected 1H NMR signals of 2 a and 2 b with 2 a/b. D) Selected 13C NMR chemical shifts of isolated 2[2c] and 2 a and 2 b (see Supporting Information for full table). UPLC-TOFMS=ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry.</p><p>In summary, a highly stereoselective synthesis of the masked 4,4-disubstituted glutamic acid 12 enabled the first total synthesis of highly enantioenriched samples of two of the possible diastereomers of JBIR-22 (2) by a concise, convergent strategy. The diastereomers 2 a and 2 b were synthesized in ten steps (longest linear route from cyclohexene) in 10.1 % and 11.3 % overall yield, respectively. The synthesis of two of the possible stereoisomers facilitated the assignment of both the relative and absolute configuration of the naturally occurring protein–protein interaction inhibitor 2. The development of a short, stereoselective synthesis of 12 coupled with the convergent nature of this approach should facilitate the future synthesis and biological assessment of all members of this subfamily of natural products as well as novel analogues.</p><!><p>Supporting information for this article is available on the WWW under http://dx.doi.org/10.1002/anie.201411141.</p>

PubMed Open Access

The Effects of Storage Conditions on Lycopene Content and Color of Tomato Hot Pot Sauce

Tomato hot pot sauce (THPS) at different storage temperatures (0, 25, and 37°C) and with two kinds of packaging for 120 days was investigated in this study. High performance liquid chromatography was employed for detecting lycopene and 5-hydroxymethylfurfural (HMF). The changes of lycopene and HMF during storage were regressed with kinetic equation of both zero-order and first-order models, and the latter fitted better. The kinetic equation constant (k value) of lycopene or HMF at 37°C was higher than that at 25°C. The k value of lycopene of PET/PE (P1) packaged THPS was 1.60 times of that of PET/Al/EAA/PE (P2) packaged at 37°C, while it was 2.12 times at 25°C. The k value of HMF of P1 packaged THPS was 1.69 times of that of P2 packaged at 37°C, while it was 1.01 times at 25°C. Significant correlations between color index of L⁎, a⁎, and a⁎/b⁎ and lycopene or HMF were found at storage temperature. Browning color was attributed to both Maillard reaction and degradation of lycopene. In conclusion, lower storage temperature and stronger oxygen barrier property of package could maintain color stability and extend shelf life.

the_effects_of_storage_conditions_on_lycopene_content_and_color_of_tomato_hot_pot_sauce

1. Introduction<!>2.1. Chemicals<!>2.2. Tomato Hot Pot Sauce and Preparation<!>2.3. Color Analyses<!>2.4. Lycopene Analysis<!>2.5. 5-Hydroxymethylfurfural Analysis<!>2.6. Ascorbic Acid Analysis<!>2.7. Statistical Analysis<!>3.1. Changes of Lycopene Content<!>3.2. Changes of HMF Content<!>3.3. Changes of Ascorbic Acid Contents<!>3.4. Changes of Color Index<!>4. Conclusions

<p>Hot pot is one of the most popular Chinese foods in China and has spread all over the world since it is very easy to keep its authentic taste. The core of hot pot taste is the hot pot sauce, which is used to prepare the base soup of hot pot. In the last decade, hot pot sauce has been upgraded from handmade in small kitchen to industrialized central kitchens which are equipped with large sauce cooking bowl up to 1000 kg/batch. This upgrade not only benefits the hot pot restaurants to uniform the recipe and increase the kitchen efficiency, but also provides consumers with alternative choice to cook top-taste hot pot in their own home. Tomato hot pot sauce (THPS) is made from tomato paste, soybean oil, tomato, onion, ginger, and other seasonings and could be classified as vegetable-based semisolid seasoning. Because of its unique soup color, sour taste, and nutritional value, THPS is growing popular among consumers. The sales of THPS also increase rapidly in supermarkets and wholesale market place; thus it becomes a favored product category by food companies and chain restaurant with central kitchen. But the long time storage on shelf (usually 6–12 months) could lead to unfavorable quality changes such as nutrients degradation or browning color, which might be taken as unsuitable for consumption [1].</p><p>There are many studies on the color changes of tomato paste [1], tomato juice [2], tomato powder [3], and tomato sauce [4] during processing and storage. But the color change of THPS during processing and storage remains unclear, and the mechanism behind the color change needs further investigation. Maillard reaction and the ascorbic acid oxidation might be two reasons that contribute to the color change of tomato product during the long-term storage [3]. Lycopene is not only an important characteristic component, but also the major coloring ingredient of tomato and tomato products. Thus lycopene has been a hot topic among the researches on the color changes of tomato products [5], although the changes of amino acid content or reducing sugar are also related to the quality change in storage.</p><p>In this study, the quality of THPS was investigated to explore the mechanism of color change during storage. The contents changes of lycopene and 5-hydroxymethylfurfural (HMF) were tracked under different packaging and storage conditions. It is helpful to guide the optimization of packaging and storage conditions of THPS, so as to improve the shelf life of the products and meet the market demand.</p><!><p>Standard lycopene and 5-hydroxymethylfurfural (HMF) were purchased from Sigma-Aldrich Chemical Co. (United States). Ethanol and acetonitrile of HPLC grade were purchased from Fluka Chemical Co. (Germany). Pyrogallic acid, potassium ferrocyanide, zinc sulphate, and other reagents were of analytical grade.</p><!><p>Tomato paste (cold break) was purchased from COFCO Tunhe Co., Ltd. (China). Other food materials were purchased from local market.</p><p>The THPS was prepared according to the following procedures. Firstly, the samples were weighed and waited for further cooking, including tomato paste (cold break, 28.5 Brix°) 40%, soybean oil 25%, sucrose 14%, fresh onion 10%, pickle ginger 4%, chicken essence 3%, salt 2.5%, soy sauce 1%, citric acid 0.25%, and dry spice mixture (cinnamon, amomum tsao-ko, clove, aniseed, fennel, white cardamom, bay leaf, dried orange peel, and Chinese red pepper, with equal weight) 0.25%. Secondly, as shown in Figure 1, the soybean oil was heated up to 160°C, followed by adding compound spice, pickle ginger, and onion and stirring for 3 min. Thirdly, the tomato paste was added and the sample was kept at the intermittent boiling state for 20 min by gentle heat. Fourthly, sucrose, citric acid, and salt were added and stirred for 6 min. Fifthly, soy sauce was added together with chicken essence with one-minute stirring. Finally the samples were cooled down to 80°C and packaged into 200 g per bag.</p><p>Storage Conditions. There were packaging P1 (polyethylene terephthalate/polyethylene), with oxygen permeability 60.00 cm3/(m2·24 h·0.1 MPa), and packaging P2 (polyethylene terephthalate/aluminum/ethylene acrylic acid copolymer/polyethylene), with oxygen permeability 0.23 cm3/(m2·24 h·0.1 MPa). The storage temperature was 0°C, 25°C, or 37°C, respectively, and they were stored for 0, 30, 60, 90, or 120 days.</p><!><p>The color of THPS was measured using a colorimeter of Labscan XE (HunterLab, Hunter Associates Laboratory Inc., United States). A whole package of THPS 200 g was transferred into a beaker. After mixed for 2 minutes at 3000 r/min by a blender, the samples were placed in Petri dishes and filled to the top. Color was recorded as L∗ (lightness), a∗ (green-red tonality), and b∗ (blue-yellow tonality). The Hue value (a∗/b∗) was calculated based on measured, a∗ and b∗, values [1].</p><!><p>Briefly, a whole package of THPS 200 g was transferred into a beaker. After mixed for 2 minutes at 3000 r/min by a blender, 2.000 g THPS was weighed in a 250 mL flask and wrapped with aluminum foil to prevent exposure to light. The procedure of extraction and HPLC detection was in accordance with previous study [6]. 50 mL of solvent (50 : 25 : 25 hexane/acetone/ethanol containing 2.5% pyrogallic acid) was added with nitrogen protection. After shaken for 10 min, 10 mL of distilled water was added for a further shaking. The hexane phase was filtered through a 0.2 μm nylon filter. One injection volume of filtrate 10 μL was injected into a liquid chromatography equipped with diode array detector (LC-Prominence-20AT and SPD-M20A, Shimadzu Co., Japan). An analytical column C18 (Shim–pack VP-ODS 15 cm × 4.6 mm ID, 5 µm) was employed and kept at 30°C. An isocratic elution of mobile phase with 50 : 50 methanol/acetonitrile was delivered at a flow rate 1 mL/min. Lycopene was detected at 472 nm, and its calibration curves (R2 = 0.984) had previously been established by the standard lycopene. The limit of detection was 2.6 × 10−6 µg/mL, the recovery rate was 92%, and coefficient of variation was 3.44%. The peaks and areas were calculated with LC solution software.</p><!><p>After homogenization of the sample, 5-hydroxymethylfurfural concentration was determined by HPLC [6, 7]. 5.000 g of THPS was placed in a 50 mL centrifuge tube, and 2 mL of 15% (w/v) potassium ferrocyanide and 2 mL of 30% (w/v) zinc sulphate were added with slow stirring and the volume made up with distilled water. After standing for 30 min, the mixture was centrifuged for 1 h at 12,000 r/min. Then 2 mL supernatant was filtered through a 0.2 μm cellulose acetate filter. HPLC apparatus, column, injection volume of sample, and software of chromatograms analysis were the same as lycopene employed in the above part. The column was kept in a stabilizer at 40°C, and an isocratic elution of mobile phase with 90 : 10 water/methanol was delivered at a flow rate 1 mL/min. HMF was detected at 285 nm, and its calibration curves (R2 = 0.992) had previously been established by the standard HMF. The limit of detection was 1.9 × 10−4 µg/mL, the recovery rate was 91%, and coefficient of variation was 4.22%.</p><!><p>Ascorbic acid concentration was determined by HPLC [8].</p><!><p>All experiments were performed in triplicate. Statistical analyses were performed with SPSS 11.5. The results were expressed as the means ± standard deviation (SD) of triplicate. The data were subjected to one-way analysis of variance (ANOVA) and the significance of difference between samples means was calculated by Duncans' multiple range test. P < 0.05 indicates the significant difference. Pearson correlation test was used to analyze the correlation between lycopene, HMF, and color index.</p><p>The reaction model of the relationship between the content change and the time was analyzed by the zero-order equation [9, 10] (1) or the first-order equation [11–14] (2), and the correlation coefficient R2.(1)y=C−kt(2)y=C∗exp−kt,where "y" is the dependent variable of lycopene, HMF, or color index; "t" is the time; "k" is the kinetic equation constant; and "C" is the starting value.</p><!><p>Lycopene is an important characteristic nutrient substance in tomato, and it is also the main coloring material of tomato. Thus it is of practical significance to study the changes of lycopene content during storage period. As shown in Figure 2, the content of lycopene did not change significantly during the storage of the two types of packaging (P1 and P2) under the storage conditions of 0°C (P > 0.05). At 25°C and 37°C, the contents of lycopene in the two types of packaging (P1 and P2) decreased with the prolongation of storage. After storage for 30 days, the content of lycopene at 37°C was significantly lower than that of the same packaging at 25°C (P < 0.05). Tamburini et al. [15] found that there was no change in lycopene content of tomato purée during one year's storage. A similar result was found, and no change was observed in lycopene content of tomato ketchup during 8 months of storage at 30°C [6]. The stability of lycopene might be attributed to the thermal inactivation of enzymes that might expose lycopene to oxidants by destroying the cell wall.</p><p>In this study, the moisture content of THPS was low and the oil content was close to 20%. During the high temperature frying process, the tomato lycopene was dissolved from the cell wall and transferred to the oil and exposed to the oxidizing environment. During the storage period it could further extend the lycopene degradation [16–18]. Oxygen permeability rate of P2 packaging was much lower than that of P1, thus reducing the lycopene oxidation loss. As shown in Figure 2, the content of lycopene in the P2 packaged THPS was significantly higher than that of the same storage time in P1 packaged sample (P < 0.05) at 25°C or 37°C for 30 days.</p><p>The fitting results of the zero-order kinetic model and the first-order kinetic model were shown in Table 1. The lycopene loss rate of the two types of packaged THPS under the conditions of 25 and 37°C storage was well fitted with the zero-order kinetic and the first-order kinetic model equation, where R2 of the first-order equation was higher than that of the zero-order equation. The relationship between lycopene and the time-dependent change in THPS was more consistent with the first-order kinetic model equation. The degradation of free lycopene and encapsulated lycopene in the storage model system also showed that lycopene degradation was accorded with the first-order kinetic model, and the kinetic constants increased with raising storage temperature [12]. It has also been reported that the degradation of free lycopene content was at a lower rate in oil media comparing with water media [13].</p><p>As shown in Table 1, k value of first-order kinetic model at 37°C was 1.86 times of the k value at 25°C for P1 packaged THPS, while it was 2.46 times for P2 packaged THPS. Because of the lower oxygen permeability, packaging P2 showed a greater effect on suppressing degradation of lycopene than packaging P1. When THPS was stored at 37°C or 25°C, the k value of P1 packaged THPS was 1.60 or 2.12 times of the k value of P2 packaged THPS, respectively. It could be seen that the storage temperature and the oxygen permeability of the packaging had great influence on the degradation of lycopene in THPS.</p><!><p>HMF is a product of the Maillard reaction at early stage, and the HMF content can be used as a measure of the extent of the Maillard reaction [19]. HMF is promoted to produce brown nitrogen-containing polymers, making the product color deterioration for a longer storage time. As shown in Figure 3, the content of HMF in the THPS of P1 and P2 package was not significantly changed (P > 0.05) at 0°C within the storage period. At 25°C and 37°C, the contents of HMF in the THPS of P1 and P2 package increased with the storage time.</p><p>Storage temperature was an important factor in affecting the reaction speed of Maillard reaction. The HMF content of THPS with P1 package was significantly higher if stored at 37°C than that stored at 25°C, when both samples were stored for more than 30 days. The same rule of HMF content of THPS with P2 package was found, when samples were stored for more than 60 days. Packaging could affect the amount of HMF in THPS during whole storage period. But in this study, it was found that the HMF content in THPS was significantly different (P < 0.05) between P1 package and P2 package, when THPS was stored at a high temperature (37°C) and more than 60 days.</p><p>The fitting results of HMF content and storage time by using zero-order kinetic model and first-order kinetic model were shown in Table 2. The results showed that the growth of HMF content was in accordance with the zero-order kinetics and the first-order kinetic model equation. And the coefficient of determination (R2) of first-order kinetic equation was higher than that of the zero-order kinetic model at 25°C and 37°C storage. Thus the first-order kinetic model equation was used to analyze the relationship between the content of HMF in THPS and storage time. Similarly, in a kheer mix powder storage model, the formation of HMF followed a first-order reaction at 37 or 45°C also and showed a good correlation [14].</p><p>As shown in Table 2, the kinetic equation constant (k value) of HMF at 37°C was higher than that at 25°C. The k value of HMF of P1 packaged THPS was 1.69 times of that by P2 packaged at 37°C, while it was 1.01 times at 25°C. It could be seen that there was no significant difference in the content of HMF in P1 and P2 package at 25°C (P > 0.05). But when the storage temperature was high (37°C), the P2 package was better than P1 package to inhibit the increase of HMF content.</p><!><p>Ascorbic acid oxidation can also cause nonenzymatic browning. During storage, the ascorbic acid oxidation degradation is often dependent on the processing method and the storage conditions. Ascorbic acid degradation followed first-order kinetic equation in strawberry jam during storage, and the rate constant (k) increased with an increase in the temperature [20]. As the TPHS is usually subjected to a long period of boiling, ascorbic acid oxidation degradation is promoted and will cause the sample color to become brown. The content of ascorbic acid before storage was less than 1.0 mg/kg, and there was no significant change at 0, 25, and 37°C during storage (P > 0.05). It showed that the ascorbic acid was almost all destroyed during the thermal processing.</p><!><p>The change in color can be used to evaluate the shelf life of the THPS, which is one of the most important indicators of the THPS quality or other tomato products [21, 22]. In order to highlight the change of the redness of THPS, the color constant a∗/b∗ value is introduced to better evaluate the color [1]. Both a∗/b∗ value and a∗ value are used as an important index of international trade in tomato products. The higher the L∗, a∗, and a∗/b∗ value of the tomato products, the more acceptable the color [3, 6]. In Figures 4(a), 4(b), and 4(c), it could be seen that there was no significant difference in L∗, a∗, a∗/b∗ between P1 and P2 at 0°C (P > 0.05). At 25°C or 37°C, the values of L∗, a∗, or a∗/b∗ in the TPHS were decreased with the storage time prolonged. This was consistent with the decrease of lycopene content and the increase of HMF content.</p><p>When the THPS in P1 package was stored at 37°C after 30 days, the L∗ value was significantly lower than that at 25°C (P < 0.05). But a significantly different L∗ value of P2 package at 37°C and 25°C was found after 60 days of storage (P < 0.05). It was also found that the L∗ value of the P2 packaged TPHS at 37°C was still higher than the L∗ value of the same storage period at 25°C with P1 package (Figure 4(a)). When the THPS in P1 package or P2 package was stored at 37°C for more than 30 days, the a∗ value was significantly lower than that at 25°C (P <0.05). The values of a∗ of P2 package THPS storage at 37°C were significantly higher than those of the P1 packaged THPS at 25°C (Figure 4(b)). The value of a∗/b∗ of P1 packaged THPS storage at 37°C after 30 days was significantly lower (P < 0.05) than that at 25°C. But a significantly different a∗/b∗ value of P2 package at 37°C and 25°C was found after 60 days of storage (P < 0.05). There was no significant difference in the a∗/b∗ value between THPS stored at 37°C in P2 package and at 25°C in P1 package for 60 or 90 days (P > 0.05). When the THPS was stored for 120 days, it was found that the a∗/b∗ value of the P2 packaged TPHS stored at 37°C was significantly higher (P < 0.05) than that of the P1 packaged TPHS stored at 25°C (Figure 4(c)). As a result, the P2 package reduced the deterioration of the color index compared to the P1 package. Even if the storage temperature rose to 37°C, the color index of P2 sample has equal degree of reduction to the P1 sample at 25°C.</p><p>HMF content can reflect the browning of processed fruit and vegetable products during storage, thus affecting the L∗, a∗, and a∗/b∗ of the THPS. As shown in Table 3, the Pearson correlation coefficients of HMF and L∗, a∗, a∗/b∗ were significantly negatively correlated (r = −0.881~−0.988) under different storage temperatures and packaging types. Thus the loss of L∗, a∗, and a∗/b∗ was mainly caused by Millard reaction, which is consistent with the changes HMF presented above [3]. The degradation of lycopene mainly produces ketones, aldehydes, alcohols, furan, olefins, aromatics, and a small amount of acids and esters [23]. There was a significant positive correlation (indicated by Pearson correlation coefficient) between lycopene and L∗, a∗, a∗/b∗ under different storage temperature and packaging (r = 0.929–0.995). Differently, it was not found that the change of lycopene was significant during 8-month storage in tomato ketchup [6] and 5-month storage in tomato powder [3]. The stability of lycopene might be attributed to the thermal inactivation of enzymes that might expose lycopene to oxidants by destroying the cell wall [24]. However, it is known that THPS is processed by high temperature soybean oil, and part of lycopene is extracted from cell wall and dissolved in oil. In this study, lycopene of THPS shows a poor stability unless placed in oxygen resistance packaging and kept in low temperature storage. Therefore, the HMF content which could be used as index of the Maillard reaction and the content of lycopene had significant effect on the color change of THPS during storage. During the storage period, the control of lycopene content decrease and the HMF content increase can effectively maintain the color of THPS.</p><!><p>When the storage temperature was 25°C and 37°C, the lycopene and color index (L∗, a∗, a∗/b∗) of the two kinds of packaged THPS were significantly decreased (P < 0.05), while the HMF content was increased (P < 0.05). The changes of the above parameters were not significant at 0°C (P > 0.05). The changes of lycopene and HMF during the storage of THPS can be fitted with the first-order equation. At 25°C and 37°C, the degradation of color index (L∗, a∗, a∗/b∗), the decrease of lycopene content, and the increase of HMF content all showed similar trends, indicated by Pearson correlation coefficient.</p><p>Low temperature and high oxygen resistance packaging can reduce the increase in HMF and lycopene reduction, slow down the storage process of browning, protect lycopene, and improve the color of THPS at the end of the storage period. The L∗, a∗, a∗/b∗ of oxygen resistance packaging is also approximately the same as or better than that of the composite film at 25°C. The effect of oxygen resistance packaging on extending shelf life can be more obvious than that of composite film if THPS is stored under unfavorable high temperature. 30 kinds of polyphenols in tomato [25], which may transfer into tomato paste and THPS, will play a role in inhibition of lycopene oxidation. The effects of antioxidant polyphenols on lycopene protection should be investigated in further studies. These pieces of information could be used to guide the processing and storage of THPS.</p>

PubMed Open Access

Expanding the concept of chemically programmable antibodies to RNA-aptamers: a novel class of chemically programmed biotherapeutics

Chemically programmed antibodies represent a new class of biologic drugs that acquire their specificity through chemistry rather than through biology. To date, this approach has used small molecules and peptides to direct targeting and to extend the pharmacokinetics and otherwise enhance the biological function of the small molecule or peptide through Fc-based mechanisms of the antibody. However, other classes of therapeutically active molecules, such as aptamers, should benefit from antibody conjugation and the chemically programmed antibody approach. Aptamers are structured nucleic acid ligands often selected using the \xe2\x80\x98selective evolution of ligands by exponential enrichment\xe2\x80\x99 (SELEX) procedure. Although aptamers are a promising class of therapeutics because of their excellent binding and inhibitory properties, only a single VEGF-targeting aptamer is an approved drug. For in vivo applications, aptamers suffer from low chemical stability (these molecules are readily degraded by nucleases in serum) and poor pharmacokinetic properties (circulatory half lives are on the order of several minutes). Nuclease resistance can be enhanced significantly by incorporating 2\xe2\x80\x99 ribose modified nucleobases; 2\xe2\x80\x99-O-methyl modified oligonucleotides have acceptable serum stabilities. Other oligonucleotide modifications are also being explored to solve this difficult problem. Here, we demonstrate for the first time site-specific conjugation of an aptamer to the aldolase antibody 38C2 to produce aptamer programmed cpAbs. Conjugation of the VEGF-targeting aptamer ARC245 to the well-characterized chemically programmable antibody 38C2 resulted in a biologically active aptamer-antibody conjugate that had significantly increased functional affinity and circulatory half-life as compared to the free aptamer. The aptamer-cpAb strategy developed here should be general and readily transferable to other aptamers. Aptamer-based cpAbs of the type developed here represent a promising new class of aptamer immunotherapeutics that combine the favourable characteristics of aptamers with those of antibodies.

expanding_the_concept_of_chemically_programmable_antibodies_to_rna-aptamers:_a_novel_class_of_chemic

<p>Key to understanding of the concept of chemically programmable antibodies is the catalytic antibody 38C2 that efficiently catalyzes aldol and related reactions through an enamine mechanism.[1] The reactivity of this and related antibody aldolases is provided by an exceptionally nucleophilic lysine residue located on the heavy chain variable domain. This lysine residue can be selectively and covalently labelled with 1,3 diketone- or β-lactam-equipped ligands such as small molecules or peptides to reprogram the binding specificity of the antibody (Fig. 1).[2] Thus, in contrast to classic monoclonal antibodies that acquire their specificity through biology (gene rearrangement and hypermutation), chemically programmed antibodies (cpAbs) acquire their specificity through chemistry. Conjugation to the antibody equips the small molecule or peptide ligand with the pharmacokinetic properties of the antibody and antibody effector functions mediated by the antibody Fc domain. Several studies have shown that this strategy increases the therapeutic efficacy of peptides and small molecules by several orders of magnitude in animal models.[2a,c,f,h] Currently four peptide-based cpAbs are in human clinical trails (www.clinicaltrials.gov).</p><p>To date, this approach has used small molecules and peptides to direct targeting. However, other classes of therapeutically active molecules, such as aptamers, should benefit from antibody conjugation. Aptamers are structured nucleic acid ligands often selected using the 'selective evolution of ligands by exponential enrichment' (SELEX) procedure.[3] Although aptamers are a promising class of therapeutics because of their excellent binding and inhibitory properties,[4] only a single VEGF-targeting aptamer is an approved drug.[5]</p><p>For in vivo applications, aptamers suffer from low chemical stability (these molecules are readily degraded by nucleases in serum [6]) and poor pharmacokinetic properties (circulatory half lives are on the order of several minutes [7]). Nuclease resistance can be enhanced significantly by incorporating 2' ribose modified nucleobases; 2'-O-methyl modified oligonucleotides have acceptable serum stabilities.[8] Other oligonucleotide modifications are also being explored to solve this difficult problem.[9]</p><p>To date, most strategies aimed at enhancing the pharmacokinetic properties of aptamers have focused on covalent attachment of ligands such as polyethylene glycol (PEG) to reduce renal clearance.[11] In one study, conjugation of a 40 kD PEG to an aptamer increased the circulatory half-life from several minutes to 23 h.[11d] Data from a phase I clinical trail with PEGylated aptamer ARC1779 indicate that the circulatory half life is 2 h in humans.[12] The extent and site of PEGylation must be evaluated for each aptamer since not all aptamers tolerate chemical conjugation to PEG molecules above a certain size.[13] Antibody programming could provide an attractive alternative to current strategies for extending aptamer half lives. By attaching an aptamer to the chemically programmable antibody the therapeutically valuable binding specificity of the aptamer should be combined with the bivalency, the long in vivo half-life and effector functions of the antibody. In order to explore the potential of aptamer-based programming of antibodies, we synthesized the β-lactam based heterobifunctional linker 3 (Fig. 2) with a reactive maleimide portion for attachment to a thiol modified aptamer.[14] The synthetic scheme for antibody aptamer conjugation is outlined in Figure 3. For our proof of concept experiments, we chose the thiol-modified anti-VEGF aptamer ARC245 since this aptamer is fully 2-O-methyl modified, highly nuclease resistant, and its binding and inhibitory properties are well characterized.[11d] Linker 3 was first reacted with the aptamer and after purification cp38C2 was specifically reacted with the lactam portion to yield an irreversible linkage. The antibody and aptamer-conjugated antibodies were analyzed by gel electrophoresis as shown in Figure 4.</p><p>The reactive lysine is located on the heavy chain of 38C2 and consistent with this and the crystal structure of the antibody complex with a β-diketone, we observed that only the heavy chain band was shifted to a higher molecular weight under reducing conditions indicative of site-specific labelling.[1c,o,r] Labelling was complete as determined by loss of aldolase activity (Supporting Information).</p><p>In order to evaluate the binding properties of our aptamer-cpAbs we performed a displacement ELISA in which either the unlabeled ARC245 or cp38C2-ARC245 competed for binding to surface-coated VEGF165 with biotinylated-ARC245.[14] Data from this assay is shown in Figure 5A. cp38C2-ARC245 showed a 60-fold lower EC50 value than the aptamer alone (0.69 nM vs. 41 nM). Based on these results, the affinities of aptamer and aptamer-cpAb were determined by the method of Oroz et al.[14] In this experiment, the affinity of ARC245 was determined to be 1.8 nM and the aptamer-cpAb had a 30-fold higher affinity of 66 pM (Fig. 5B). This result shows that by antibody conjugation, the functional affinity of an otherwise monovalent aptamer was increased significantly. Other reports indicate that bivalent aptamers have a higher functional affinity than their monovalent counterparts.[15]</p><p>The therapeutic target of ARC245 is VEGF, a proangiogenic factor excreted by many tumors to stimulate blood vessel growth into the tumor and to maintain a supply of oxygen and nutrients to rapidly dividing tumor cells.[16]</p><p>ARC245 is a potent anti-VEGF antagonist that prevents VEGF from binding to the VEGF receptor. To study the biological activity of cp38C2-ARC245, we performed cell migration assays using human umbilical cord endothelial cells (HUVEC) in a transwell assay format. Cells were seeded into the top chamber of 8-µm transwell plates and allowed to migrate at 37 °C for 4 h towards the bottom chamber to which 10 ng/mL VEGF was added.</p><p>As shown in Figure 6, addition of 50 nM 38C2-ARC245 conjugate potently inhibited VEGF-mediated cell migration, demonstrating that the biological activity of ARC245 was retained after antibody conjugation. It is well established that compounds that inhibit VEGF-mediated cell migration in a transwell assay also block proangiogenic signalling in vivo provided they demonstrate favourable pharmacokinetic properties.[17]</p><p>The pharmacokinetic properties of cp38C2-ARC245 were evaluated in athymic nude mice. cp38C2-ARC245 (100 µg; 5 mg/kg) was injected intravenously and blood was collected at various time points up to 96 h post injection by tail bleeding. The concentration of aptamer ARC245 was analyzed by ELISA. In order to detect the intact antibody-aptamer conjugate an ELISA assay was developed in which h38C2 was first captured from serum. A biotinylated antisense oligonucleotide was then added that annealed to the aptamer and was detected with streptavidin HRPO. In all experiments the first time point (5 min) was defined as 100%. The hcp38C2-ARC245 conjugate showed a clearance half-life of approximately 21 h. In parallel, the concentration of the antibody 38C2 was determined from the same blood samples (Supporting Information). This half-life was approximately 68 h. The most likely explanation for the difference in half-lives of the antibody and the functional aptamer is either nuclease digestion of the aptamer portion or cleavage of the heterobifunctional linker. While we believe that the addition of a 5'-cap to the aptamer and modifications of the heterobifunctional linker might increase the overall stability of the conjugate, the increase in circulatory half-life of the antibody conjugate determined here (as compared to the free aptamer) is very significant. In accord with the results of Healy et. al. on unconjugated aptamers, the circulatory half-life of the fully 2'O-Me modified ARC245 was determined here to be less than 30 min following intravenous dosing.[13a] Thus the cpAb approach provides aptamers with a very substantial increase in circulatory half-life that should translate into less frequent dosing regimens for aptamer drugs in a therapeutic setting.</p><p>In summary, we demonstrate for the first time site-specific conjugation of an aptamer to the aldolase antibody 38C2 to produce aptamer programmed cpAbs. Conjugation of the VEGF-targeting aptamer ARC245 to the well-characterized chemically programmable antibody 38C2 resulted in a biologically active aptamer-antibody conjugate that had significantly increased functional affinity and circulatory half-life as compared to the free aptamer. The aptamer-cpAb strategy developed here should be general and readily transferable to other aptamers. Aptamer-based cpAbs of the type developed here represent a promising new class of aptamer immunotherapeutics that combine the favourable characteristics of aptamers with those of antibodies. This approach might also be applicable to chemically programmed vaccines.[18]</p><p>Chemical reactivity of catalytic antibody 38C2 and active site structure showing enamine formation with Lys H93 [1r]</p><p>Synthesis of heterobifunctional linker 3.</p><p>Irreversible programming of aldolase antibody 38C2 with aptamer ARC245.</p><p>Representative SDS acrylamide gel after conjugation of antibody and aptamer. Lane 1, unmodified 38C2; lane 2, human 38C2 (hu38C2) after conjugation to aptamer; lane 3, mouse 38C2 (38C2) after conjugation to ARC245; lanes 1', 2', and 3', samples as in first three lanes under reducing conditions.</p><p>A) Competitive ELISA with increasing amounts of either unmodified ARC245 or hcp38C2-ARC245 incubated with 20 nM biotinylated ARC245. Biotinylated ARC245 was detected with streptavidin HRPO and percent displacement was plotted. B) Resulting linearization scheme according to Oroz et al.[14] From the slopes, the KDs for ARC245 and hcp38C2-ARC245 were determined to be 1.81 nM and 66 pM.</p><p>Transwell migration assay of HUVEC cells migrating toward 10 ng/mL recombinant human VEGF165. cp38C2-ARC245 was applied at a concentration of 50 nM. Cells were allowed to migrate for 4 h; n=3, p= 0.014.</p>

PubMed Author Manuscript

Experimental validation of FINDSITEcomb virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders

BackgroundIdentification of ligand-protein binding interactions is a critical step in drug discovery. Experimental screening of large chemical libraries, in spite of their specific role and importance in drug discovery, suffer from the disadvantages of being random, time-consuming and expensive. To accelerate the process, traditional structure- or ligand-based VLS approaches are combined with experimental high-throughput screening, HTS. Often a single protein or, at most, a protein family is considered. Large scale VLS benchmarking across diverse protein families is rarely done, and the reported success rate is very low. Here, we demonstrate the experimental HTS validation of a novel VLS approach, FINDSITEcomb, across a diverse set of medically-relevant proteins.ResultsFor eight different proteins belonging to different fold-classes and from diverse organisms, the top 1% of FINDSITEcomb’s VLS predictions were tested, and depending on the protein target, 4%-47% of the predicted ligands were shown to bind with μM or better affinities. In total, 47 small molecule binders were identified. Low nanomolar (nM) binders for dihydrofolate reductase and protein tyrosine phosphatases (PTPs) and micromolar binders for the other proteins were identified. Six novel molecules had cytotoxic activity (<10 μg/ml) against the HCT-116 colon carcinoma cell line and one novel molecule had potent antibacterial activity.ConclusionsWe show that FINDSITEcomb is a promising new VLS approach that can assist drug discovery.

experimental_validation_of_findsitecomb_virtual_ligand_screening_results_for_eight_proteins_yields_n

Background<!>Results<!><!>E. coli dihydrofolate reductase (DHFR)<!>Protein tyrosine phosphatases (PTP)<!>Ubiquitin-modifying enzyme (UCE)<!>Tryptophanyl tRNA synthetase (TrpRS)<!>Thioredoxin peroxidase2 (TP2), cAMP-dependent protein kinase (cDPK) and nucleosome assembly protein 1(NAP1)<!>Discussion<!>Conclusions<!>Details about reagents are provided in SI<!><!>FINDSITEfilt for ligand virtual screening using experimental bound structures<!><!>FINDSITEfilt for ligand virtual screening using experimental bound structures<!>FINDSITEX for ligand virtual screening using experimental binding data without bound structures<!>FINDSITEcomb for ligand virtual screening<!>Comparison of FINDSITEcomb to traditional docking-based methods<!><!>Comparison of FINDSITEcomb to traditional docking-based methods<!><!>Large scale testing of FINDSITEcomb on generic drug targets<!><!>Experimental validation of FINDSITEcomb<!>Acquisition and quantification of thermal shift assays<!>Data analysis<!>Antimicrobial and cytotoxic assays on cancer cell lines<!>Abbreviations<!>Competing interests<!>Authors’ contributions<!>Additional file 1<!><!>Acknowledgement

<p>Traditional experimental approaches to drug discovery rely on two different strategies [1]. The first selects a reliable therapeutic target that might be essential for an organism's or cell's survival, and then, using chemical library screening, potential leads that bind to and modulate the activity of the target in vitro and subsequently, in vivo, are identified. The second approach tests small molecules on animal disease models or cell cultures (called phenotypic screening), and once activity is gleaned, the protein target is experimentally identified by target deconvolution [2]. Both approaches have contributed to the discovery of new drugs despite suffering from substantial disadvantages of high cost and time. Fragment-based drug discovery approaches have recently gained prominence as a distinct and complementary approach to drug discovery [3]. Integration of a robust VLS methodology with experimental HTS approaches constitutes one of the many methods that might accelerate the drug discovery process [4].</p><p>Despite its current limitations, VLS may be employed as a possible first step in drug discovery [5]. It not only aids in the selection of an appropriate protein target but also narrows down the chemical space that is experimentally screened to arrive at significant protein-ligand interactions. In practice, both ligand- and structure-based VLS approaches [6] have been used. The principal disadvantage of a ligand-based approach is the need for a priori knowledge of a set of ligands known to bind to the target [7]. Structure-based approaches require a high-resolution structure of the target; this situation typically only holds for a minority of proteins in a given proteome [8]. To overcome these limitations, ligand homology modeling (LHM) was developed to predict ligands that bind to the protein target [9-11]. LHM relies on the fact that evolutionarily distant proteins share functional overlap and their ligand-binding information provides diverse bound ligands that can be employed in a general VLS approach. Thus, it does not suffer from the limitations of quantitative structure-activity relationship (QSAR)-based approaches. In large scale benchmarking, the FINDSITEcomb LHM approach exhibited significant performance advantages over traditional approaches in terms of enrichment factor, speed, and insensitivity as to whether experimental or predicted protein structures are used [12]. However, experimental assessment of the method, where blind predictions are made and then experimentally tested, has not been done. To ensure robustness, a diverse set of proteins and ligands must be examined, and the strengths and limitations of the approach demonstrated.</p><p>A reliable and fast method that would test VLS predictions and identify hits could help accelerate the drug-discovery process. This could help alleviate the inherent complexity of treating diseases due to cross-reactivity and could address the rapid evolution of resistance to available drugs by pathogenic microbes. We have resorted to the thermal shift assay methodology to assess the predictions from VLS [13]. The methodology is an inexpensive way to assess the binding of small-molecules by the stability they confer on thermal denaturation of the protein target of interest. Upon thermal denaturation, the hydrophobicity of proteins increases, leading to an increase in fluorescence of an extrinsic fluorophore reporter dye. This method is amenable to miniaturization and can screen hundreds of molecules simultaneously for their ability to bind to the protein target of interest.</p><p>Recognizing the importance of these issues, in the present paper, to assess if FINDSITEcomb [12] can improve VLS, we selected an assortment of medically-relevant proteins with differing fold-architectures from diverse organisms including the causative agents of human and primate malaria, Plasmodium falciparum and Plasmodium knowlesi, an opportunistic pathogen Escherichia coli, and proteins implicated in mammalian disorders (from Homo sapiens and Rattus norvegicus). For these proteins, top ranked ligands predicted by FINDSITEcomb are experimentally assessed for binding by thermal-melt assays. After validating the small molecule binding predictions, we tested their physiological function by their ability to kill bacteria such as multi-drug resistant E. coli (MDREC), methicillin-resistant Staphylococcus aureus (MRSA), Vancomycin-resistant Enterococcus faecium (VREF), and their cytotoxic activity using HCT-116 colon carcinoma tumor cell line. The encouraging experimental results for both binding and physiological activity show that FINDSITEcomb is an effective VLS tool.</p><!><p>The section summarizes the results from FINDSITEcomb's VLS predictions on eight different proteins and their validation by the thermal shift assay methodology.</p><p>Prior to assessing the VLS results on the eight protein test set, the thermal shift methodology was validated on three proteins having known binding and nonbinding ligands. Only cognate protein-ligand pairs showed shifts in the transition mid-point of thermal melt curves, Tm, while non-cognate ligands displayed no such shifts (Additional file 1: Figure S1 and SI).</p><p>We next applied the methodology, as shown in Figure 1, in benchmark mode to eight diverse proteins, viz., FINDSITEcomb only considered template proteins whose sequence identities to the target was <30%. Typically on the order of 50 ligands per protein gave interpretable thermal shift curves. Of these, the experiments identified a total of 47 small-molecule/protein binding interactions with μM or better affinities. Ten ligands with apparent nM binding affinities (less than 1 μM) were identified for dihydrofolate reductase from E. coli and the two mammalian protein tyrosine phosphatases (PTPs). Except for a small fraction of known inhibitors, which further validated the methodology, most are novel. The prediction percentage success rate ranged from 3.9% of ligands tested for the P. falciparum ubiquitin-conjugating enzyme to almost 47% for dihydrofolate reductase from E. coli (Table 1). This is a major advancement over previously reported success rates [14]. The small-molecules that displayed biological activity had low μM or nM affinities in the in vitro thermal shift assay (Table 2; Additional file 1: Tables S3-S5). This supports the conjecture that their in vivo biological activity might result from binding of the small-molecule with the intended target protein. A more detailed summary of the results is presented below.</p><!><p>Flowchart of the overall approach and the thermal shift assay results. The first panel shows the in silico approach to predicting protein-small molecule interactions. All predictions were in benchmarking mode with a 30% template SID cutoff and the top 1% of the hits tested using thermal-shift assays. The second panel shows a representative fraction of the thermal melt curves that showed positive shifts for the tested proteins. The numbers are the NSC notation that identifies each small-molecule. DHFR is E. coli dihydrofolate reductase, 1000001 is a PTP from R. norvegicus, 1000006 is a PTP from H. sapiens, TrpRS is tryptophanyl tRNA synthetase from H. sapiens, UCE is ubiquitin-conjugating enzyme from P. falciparum, NAP1 is nucleosome assembly protein 1 from P. knowlesi, TP2 is thioredoxin peroxidase 2 from P. falciparum and cDPK is the wild-type cAMP-dependent protein kinase, catalytic subunit from H. sapiens. Small-molecule binders were tested for their antimicrobial & cytotoxic activity against HCT-116 colon carcinoma cell line.</p><p>Results from the thermal shift assays on eight proteins, ranked by best ligand binding*</p><p>1000001: Carboxy-terminus phosphatase domain of protein tyrosine phosphatase (2NV5), DHFR: Dihydrofolate reductase, UCE: Ubiquitin conjugating enzyme, TrpRS: Tryptophanyl tRNA synthetase, TP2: Thioredoxin peroxidase 2, 1000006: catalytic domain of protein tyrosine phosphatase (2G59), cDPK: Catalytic subunit of cAMP-dependent protein kinase, NAP1: Nucleosome assembly protein 1. aPositive thermal shift is indicated by the notation + ve. KD indicates dissociation constants. bThe dissociation constant reported in this table are computed from the thermal shifts obtained. *The values reported in this table are experimental in-vitro values.</p><p>Antimicrobial and anticancer activities of a representative set of small-molecules b</p><p>*Reported inhibitors of DHFR independently picked up by our predictions and validated experimentally. @Small molecule with known anti-cancer properties (valrubicin). ¥Small molecules with known anticancer properties (Sunitinib), MIC: Minimum inhibitory concentration required for 90% clearance, μg/mL units. ND: No significant inhibition. NA: not applicable. DH5α: E. coli strain DH5α, MRSA: Methicillin-resistant S. aureus, MDREC: Multi-drug resistant E. coli, VREF: Vancomycin-resistant E. faecium, HCT-116: Colon carcinoma cell line. IC-50: inhibitory concentration for 50% growth inhibition, μg/mL units. aFor additional details, see legend from Table 1. bThe values reported in this table are experimental in-vitro values.</p><!><p>In silico screening of E. coli DHFR was carried out with FINDSITEcomb in benchmarking mode (Additional file 1: Table S2A). The top 1% of predictions, with 83 small-molecules, was assessed for binding (Table 1). Fifteen ligands, representing 47% of interpretable curves, showed binding (Figure 1 and Table 1). Of these 15 hits, representing μM or better binders, six were previously reported inhibitors of DHFRs from various organisms [15-19]. Among these known binding molecules, methotrexate (NSC740) showed the maximum thermal shift of ~30°C followed by 7H-Pyrrolo(3,2-f) quinazoline-1, 3-diamine (NSC339578) [15], methylbezoprim (NSC382035) [16], pralatrexate (NSC754230) [17], pemetrexed (NSC698037) [18] and 6,7-bis(4-aminophenyl) pteridine-2,4-diamine (NSC61642) [19]. The approximate dissociation constant (KD) of 62 nM for the enzyme-methotrexate (NSC740) complex matches reported literature values, which range from 2 to 50 nM [20-22], within experimental error. Thus, the thermal shift methodology provides an approximate KD. The five other known inhibitors bind DHFR with low μM or nM KDs (Additional file 1: Table S3).</p><p>Nine small molecules are novel hits with no reported binding to/activity against DHFRs. These molecules are chemically diverse. The 15 different hits cluster into 10 distinct chemical classes based on a Tanimoto coefficient (TC) cutoff of 0.7 (Additional file 1: Figure S2A). NSC309401, the top novel hit in Table 1, showed apparently better binding to E. coli DHFR than methotrexate (KD of 48 nM and a thermal shift of almost 31 degrees) and showed inhibition against several antibiotic-resistant microbial strains (Table 2). It displayed a promising MIC of 7.8 μg/mL against E. coli DH5α and a reasonable MIC (31.25 μg/mL) against MRSA and VREF. It also has very potent activity against the HCT-116 colon carcinoma cell line with an IC-50 of 0.13 μg/mL (Table 2).</p><p>This corroborates findings from the NCI human tumor cell line growth inhibition assay showing that this molecule has activity (potency not revealed) against several cancer cell lines including melanoma, prostrate, colon, and breast (http://pubchem.ncbi.nlm.nih.gov, CID: 24198955, substance SID: 573494, compound name: MLS002701801) [23]. We posit that its activity is at least partly due to DHFR inhibition. Since NSC309401 inhibits both prokaryotic and eukaryotic systems, it might be a broad specificity antifolate. 2, 4-diaminoquinazolines and their derivatives are known to inhibit DHFR (a prominent example is trimetrexate) (Rosowsky, et al., 1995) but their structures are different from NSC309401, a 7-[(4-aminophenyl) methyl]-7Hpyrrolo [3, 2-f] quinazoline-1, 3-diamine, in that the latter compound has a novel tricyclic heterocycle.</p><p>Another interesting small molecule, with no previously reported binding to DHFR, was NSC80735, with a KD of 1.7 μM and a MIC of 10.9 μg/mL against HCT-116 (Additional file 1: Table S3). The other novel hits had affinities ranging from 6-75 μM; these hits represent potential compounds that could be improved to increase their medical significance vis-à-vis DHFR inhibition. A single novel hit had a poor affinity of ~460 μM.</p><!><p>The top 1% of VLS predictions (Additional file 1: Table S2B and S2C), representing 86 and 59 molecules, were tested on PTPs 1000001 and 1000006, respectively. Ten molecules, 24% of the interpretable curves, showed positive shifts for PTP 1000001, and six molecules, 14% of the interpretable curves, showed positive shifts for PTP 1000006 (see Figure 1 and Table 1). However, it should be noted here that a few of the reported molecules have low Q values representing poor signal compared to the thermal unfolding curve of the protein alone (see Materials and Methods) (Additional file 1: Table S4). All these compounds are novel hits, with no reported binding to/activity against PTPs. At a TC cutoff of 0.7, the 10 ligands showing experimental binding to 1000001 clustered into eight different subgroups (Additional file 1: Figure S2B), while the six ligands showing experimental binding to 1000006 clustered into four different subgroups (Additional file 1: Figure S2C). This again demonstrates the diversity of ligands selected by FINDSITEcomb. Next, 32 predictions ranked below the top 1% from VLS were randomly selected and tested experimentally on 1000001 and 1000006 to demonstrate that the obtained hit rate for the top 1% was appreciably better than the background. Convincingly, as inferred by the lack of shift in Tm, none showed any binding.</p><p>Among the ten hits for 1000001, seven had μM affinities, three had nM affinities with the compound NSC134137 showing a maximal thermal shift of ~12°C. This translates into an approximate KD of 406 nM (Additional file 1: Table S4). Five of these compounds, 50% of the hits, displayed cytotoxic activity against HCT116. Valrubicin (NSC246131), (a known anticancer agent that intercalates with DNA [24]), was also shown to bind to PTP1000001 with an approximate dissociation constant of 1.5 μM. NSC246131 binding to PTP 100001 hints at promiscuity of this molecule. Three hits, NSC111552, NSC30205 and NSC88882 also showed potent cytotoxic activity (IC-50 of 2.20 μg/mL, 0.15 μg/mL and 4.44 μg/mL, respectively), while NSC106863 showed reasonable cytotoxic activity with an IC-50 of 14.5 μg/mL against the HCT-116 colon carcinoma cell line (see Table 2; Additional file 1: Table S4). We note that a single paper reports the cytotoxic activity of NSC111552 derivatives against cancer cell lines [25]. While there is no literature describing the anticancer properties of either NSC30205 or NSC88882, 9-aminoacridine-based compounds are known to be cytotoxic towards cancer cell lines [26-33]. Thus, the mode of action of NSC30205 could be similar [31]. We also posit that the PTP human homologue is one of the targets responsible for the cytotoxic activities of these molecules.</p><p>All six hits for 1000006 have apparent KDs that range from 168 nM-271.5 μM (Additional file 1: Table S4). The top hit was NSC133351 with an approximate dissociation constant of 168.3 nM. NSC92794, with a KD of 161.9 μM, displayed reasonable cytotoxic activity with an IC-50 value of 9.8 μg/mL against HCT-116 colon carcinoma cell line. None of the other hits of 1000006 displayed discernible cytotoxic activity. Since 1000001 and 1000006 are both PTPs and share substantial structural similarity, there were instances where 1000001 binders also bind 1000006 (Additional file 1: Table S6 and SI).</p><!><p>For P. falciparum UCE, 80 molecules from the top 1% of FINDSITEcomb predictions (Additional file 1: Table S2G), were experimentally tested for binding (Table 1); only 51 gave interpretable thermal shift curves. Two molecules, 4% of the interpretable curves, showed binding (see Figure 1 and Table 1). NSC93427 binds to UCE, with a thermal shift of ~15°C that translates into an approximate KD of 1.4 μM. Another compound, NSC50651, showed an apparent KD of 197 μM (Additional file 1: Table S5). Future studies to assess the inhibition of in vitro cultures of P. falciparum by these small-molecules are needed to establish their utility as lead compounds for malaria treatment.</p><!><p>For TrpRS, 94 compounds from the top 1% of the VLS (Additional file 1: Table S2D) were experimentally screened (Table 1). Five, constituting 42% of the interpretable curves, showed thermal shifts (see Figure 1 and Table 1). The ligands clustered into three different subgroups (Additional file 1: Figure S2D) based on a TC cutoff of 0.7. The most interesting small-molecule that binds TrpRS was Sunitinib (NSC 750690) with an approximate KD of 1.3 μM and an IC-50 of 1.1 μg/mL for HCT-116. The observed effect might be due to its inhibition of multiple targets (receptor tyrosine kinases are known Sunitinib targets [34]).</p><p>Two other small molecules, NSC88882 and NSC37168, with ~ KDs of 3.8 μM and 9.1 μM respectively, also showed potent inhibition of HCT-116, with IC-50s of 4.44 μg/mL and 1.34 μg/mL, respectively (Table 2). NSC88882 has been shown to possess activity in the several bioassay trials undertaken by the NCI suggesting high promiscuity across several protein targets (http://pubchem.ncbi.nlm.nih.gov/, substance SID: 26665273, CID: 68249) [31]. NSC37168 also binds multiple targets within different cell types [3,35]. However, none of these reports suggest binding/inhibition of TrpRS. Other compounds that bind TrpRS were NSC50690 and NSC55152, having KDs of 7.7 μM and 39.6 μM, respectively (Additional file 1: Table S4).</p><!><p>TP2 from P. falciparum, the catalytic domain of the cDPK from H. sapiens and NAP1 from P. knowlesi were tested with moderate success. Their thermal melt assay results are collated in Table 1 and Additional file 1: Table S5, with additional VLS results summarized in Additional file 1: Table S2F, S2E and S2H, respectively. Experimental thermal melt curves are shown in Figure 1. As can be seen in Additional file 1: Table S5, all these small-molecules bind with μM affinities (ranging from 41 μM-371.5 μM), making a few of them potential candidates for further development.</p><!><p>In this paper, we describe the large-scale experimental validation of the FINDSITEcomb VLS methodology and demonstrate that the approach is applicable to a wide variety of proteins. In contrast, previous instances of VLS coupled to experimental screening of ligands reported in the literature mostly concentrate on either a single enzyme or a single enzyme family [36-41]. FINDSITEcomb, being a hybrid of structure-based and ligand-based VLS approaches, has many advantages: It identifies a structurally diverse set of ligands as potential hits, retains the speed of traditional ligand-based approaches, and removes the requirement of traditional structure-based approaches that a high-resolution structure of the protein target of interest be solved. Thus, ~75% of a given proteome is accessible to this VLS methodology. This affords the possibility not only of identifying novel hits, but also for repurposing FDA approved drugs, and concomitantly suggesting possible drug side effects.</p><p>Demonstration of the methodology on a diverse set of proteins with differing folds suggests that the method is a general and effective approach to discovering novel protein-ligand binding interactions. The primary success rates of 4%-47% are dramatic when compared to rates reported in the literature. Since only a tiny fraction of the protein/ligand binding predictions were assessed experimentally (20-50 of the top ranked predictions from FINDSITEcomb), these success rates are even more significant than the raw numbers would suggest. For instance, in another study describing the HTS of a diverse library of 50,000 small-molecules against E. coli DHFR, the primary hit rate was 0.12% [14], whereas 47% of the 32 molecules predicted by FINDSITEcomb bind with μM affinities or better. Indeed, the finding that many ligands have KDs in the nM and μM range is encouraging. For three different proteins, novel nM binders were identified. Demonstration of antibacterial and cytotoxic activity by some of these compounds further suggests that the present methodology is a promising approach to identify novel hits and could help enrich the drug discovery pipeline. However, we are aware that hits generated through thermal-shift methodology relying on an extrinsic fluorophore will require additional validation.</p><p>Not only has a methodological advance been demonstrated, but also the results hold possible medical significance. We have identified several interesting hits that might represent starting scaffolds for drug design for a number of clinically important protein targets. For example, DHFR, a pivotal enzyme in the nucleotide biosynthetic pathway in E. coli [42] evolves resistance to available inhibitors by several mechanisms [43,44]. This is a major problem because drug-resistant E. coli causes the highest number of infections in hospitalized patients [35]. Thus, there is an urgent need to identify novel potent inhibitors of DHFR. In that regard, the current study provides nine novel structurally diverse small-molecule binders with apparent affinities ranging from nM to μM that are interesting hits that could be developed as lead molecules for E. coli DHFR inhibition. By assessing the potential of these ligands against a diverse set of drug-resistant microbial strains and colon cancer cells, we established the range of effectiveness of these compounds. A potent antibacterial and 7 molecules with cytotoxic effect against HCT-116 colon carcinoma cell line were found. This information can be exploited in designing species-specific inhibitors. Yet other examples are the pathogens P. falciparum, which causes malignant malaria in humans, and P. knowlesi, implicated in an emergent form of malaria that can infect humans [45]. Rapid evolution of resistance to known antimalarials is a major issue [46]. The present study yielded 8 hits to three different enzymes that carry out critical processes of ubiquitin-mediated post-translational modification (UCE) [47], oxidative protection of the parasite during its intraerythrocytic stages (TP2) [48] and histone transport & chromatin assembly (NAP1) [49], in the pathogen. Finally, four distinct target proteins representing members of three families, tRNA synthetases [50], phosphatases and kinases [51,52] implicated in diseases such as cancer, were examined with 24 novel protein-ligand binding interactions reported. Interestingly, these studies also identified unanticipated binding interactions of well-known drugs with alternative targets. Sunitinib, a well-documented inhibitor of receptor tyrosine kinases [34], binds to TrpRS with high-affinity. This reinforces the belief that drug molecules, at least partly, work by interfering with the function of multiple targets within the cellular milieu. It is well known that developing a new drug is a time consuming and expensive process that can take 12–15 years. Such off-target interactions could be exploited towards repurposing available drugs for alternative protein targets, thus reducing the cost and time duration of drug-discovery.</p><!><p>In conclusion, we have demonstrated that FINDSITEcomb is an automated, robust and rapid methodology that can identify novel protein-ligand binding interactions that are often in the nM range or better, and which, in combination with appropriate mechanistic studies and biological activity assays can be a promising tool for lead identification/drug discovery. The presented results show that predicted structures can be successfully used for virtual ligand screening, and by exploiting the ideas of LHM, diverse novel small molecule binders can be identified even when the closest template is distantly related to the protein target of interest. Since medically relevant proteins often have a large number of evolutionarily related solved, holo protein structures that can serve as templates, they are a particularly good class of targets for the present methodology. However, we note that the methodology also works when there are few solved holo templates structures in the PDB, e.g. for GPCRs [12]. Work is now in progress to extend and experimentally validate the approach on a broader class of proteins and small molecule ligands.</p><!><p>Figure 2 shows the flowchart of FINDSITEcomb methodology [12] in combination with experimental validation protocol. FINDSITEcomb is a composite approach consisting of the improved FINDSITE-based approach [9] FINDSITEfilt and the extended FINDSITE-based approach FINDSITEX [53]. In what follows, we detail the two FINDSITE-based component approaches and their benchmarking and prediction results.</p><!><p>Flowchart of FINDSITE comb .</p><!><p>The FINDSITEfilt flowchart is shown in Figure 3(A) and consists mainly of three steps: (A) Finding a sub-set of protein template in the library of holo PDB structures (experimental structures with bound ligands) that are putatively evolutionarily related to the target using target sequence and threading approaches; (B) Filtering the sub-set of holo PDB structures using the target structure (experimental or modeled) and structure comparison methods; (C) Selecting pockets and ligands from the filtered sub-set for binding site and virtual screening predictions.</p><!><p>Flowchart of two FINDSITE-based component approaches (A) FINDSITE filt (B) FINDSITE X .</p><!><p>FINDSITEfilt [12] employs a heuristic structure-pocket alignment procedure and a sequence dependent scoring function to rank the holo templates in step (B) above. The alignment is evaluated using the sequence dependent score:</p><p>(1)SP-score=∑alignedresiduea,bBLOSUM62a,b,</p><p>where BLOSUM62(a,b) is the BLOSUM62 substitution matrix [54]. Templates are ranked by their SP-scores and the ligands corresponding to the top 100 templates are selected as template ligands for ligand virtual screening.</p><!><p>FINDSITEfilt's performance relies on the existence of a sufficient number of holo PDB structures homologous to the target. This is not true for most membrane proteins where even apo structures (structures without bound ligands) are rare. Thus, for some of the most interesting drug targets, such as the G-Protein Coupled Receptors (GPCRs) and ion-channels, FINDSITEfilt has limited performance. The FINDSITEX approach [53] was developed to overcome the shortcomings of FINDSITEfilt on these kinds of targets. The flowchart of FINDSITEX is shown in Figure 3(B). FINDSITEX utilizes experimental binding data without ligand bound experimental structures. To use the benefits from structure comparison, structures of proteins in experimental ligand binding database are modeled. FINDSITEX uses the fast version of the structure modeling approach TASSERVMT [55] (TASSERVMT-lite [53]) to create a virtual library of protein-ligand structures analogous to the PDB holo structures but without experimentally solved protein-ligand complex structures. Since there is no reliable pocket information for the virtual holo structure, whole structure comparison of the target to the templates (in the virtual holo structures) using fr-TM-align [56] is used. To reduce false positives, especially for targets like GPCRs where almost all structures are similar (TM-score > 0.4), a sequence dependent score similar to the SP-score in Eq. (1) over the fr-TM-aligned residues is used instead of the TM-score. The ligands of the top ranked templates are used as template ligands for searching against compound library. To identify template-ligand pairs, the DrugBank drug-target relational database [57] and the ChEMBL bioactivity database [58] are used.</p><!><p>FINDSITEcomb is the combination of FINDSITEfilt that uses holo PDB structures as templates and FINDSITEX that utilizes two independent ligand binding databases. For a given target and compound library, if there is no target structure input, TASSERVMT-lite [53] models the structure. Then, three independent virtual ligand screening runs are conducted: (a) FINDSITEfilt using the holo PDB structure library; (b) FINDSITEX using the DrugBank virtual holo structure library; and (c) FINDSITEX using the ChEMBL virtual holo structure library. For each virtual screening library, the following score is used to measure the likelihood of a compound to be a true compound of the target:</p><p>(2)mTC=w∑l=1NlgTCLl,LlibNlg+1-wmaxl∈1,…,NlgTCLl,Llib,</p><p>where TC stands for the Tanimoto Coefficient [59], Nlg is the number of template ligands from the putative evolutionarily related proteins; L l and L lib stand for the template ligand and the ligand in the compound library, respectively; w is a weight parameter. The first term is the average TC [11]. The second term is the maximal TC between a given compound and all the template ligands. Here, we empirically choose w = 0.1 to give more weight to the second term so that when the template ligands are true ligands of the target, they will be favored. For a given compound, three independent virtual screenings give three mTC scores and the maximal score is used for the combined ranking.</p><p>In this study, to experimentally validate FINDSITEcomb under non-trivial conditions, i.e. there are no close homologous templates to the target, we have excluded all templates having sequence identity > 30% to given target in the PDB holo structures, DrugBank targets and ChEMBL targets.</p><!><p>We previously conducted a benchmarking test of FINDSITEcomb on the DUD set (A Directory of Useful Decoys set [60]) and compared our results to the state-of-the-art docking-based methods for ligand virtual screening. The DUD set is designed to help test docking algorithms by providing challenging decoys. It has a total of 2,950 active compounds and a total of 40 protein targets. For each active, there are 36 decoys with similar physical properties (e.g. molecular weight, calculated LogP) but dissimilar topology. Two freely available traditional docking methods AUTODOCK Vina [61] (http://vina.scripps.edu/) and DOCK 6 [62] (http://dock.compbio.ucsf.edu/DOCK_6/) were compared to FINDSITEcomb. AUTODOCK Vina was tested on the DUD set and shown to be a strong competitor against some commercially distributed docking programs (http://docking.utmb.edu/dudresults/). DOCK 6 is an update of the DOCK 4 program [62]. These two methods represent state-of-the-art traditional docking-based approaches that are computationally expensive, but do not require a known set of binders for a given target as opposing to traditional ligand similarity-based approaches. FINDSITEcomb also does not require a known set of binders for the target, but is an order of magnitude faster than docking methods. Most importantly, FINDSITEcomb does not require a high-resolution experimental structure of the target. Thus, it is applicable for screening both large compound library and for genomic scale targets.</p><p>The performance of a given approach for virtual screening is evaluated by the Enrichment Factor (EF) within the top x fraction (or 100x%) of the screened library compounds defined as:</p><p>(3)EFx=Numberoftruepositiveswithintop100x%Totalnumberoftruepositives×x.</p><p>A true positive is defined as an experimentally known binding ligand/drug or one that has a TC = 1 to an experimentally validated binding ligand/drug. For x = 0.01, EF0.01 ranges from 0 to 100 (100 means that all true positives are within the top 1% of the compound library). Another evaluation quantity employed here is the AUAC (area under accumulative curve of the fraction of true positives versus the fraction of the screened library).</p><p>The performance of the three approaches on the DUD set using experimental target structures is shown in Table 3. FINDSITEcomb shows about 3 times the EF0.01 of AUTODOCK Vina or DOCK 6 for the top 1% selected compounds, with an EF0.01 of 13.4 versus 4.80 and 3.72, respectively. FINDSITEcomb has significantly better overall performance in terms of its AUAC (0.774 vs. 0.586 and 0.426). Although we do not have direct access to some of the commercially available approaches compared in Ref. [63], we note that FINDSITEcomb has a better AUAC than the best performing GLIDE (v4.5) [64,65] (mean AUAC = 0.72) and all other compared methods: DOCK 6 (mean AUAC = 0.55), FlexX [66] (mean AUAC = 0.61), ICM [67,68] (mean AUAC = 0.63), PhDOCK [69,70] (mean AUAC = 0.59) and Surflex [71-73] (mean AUAC = 0.66) [63]. The results of DOCK 6 in Ref [63] are better than that in Table 3 is due to the use of flexible docking and expertise in input preparation in Ref. [63], whereas here we employed default input and rigid docking.</p><!><p>Performance of methods on the 40 protein DUD set using experimental structures</p><p>aNumbers in parentheses are two-sided p-values of Student-t test between FINDSITEcomb and docking methods.</p><!><p>We next examined the effect of target structure quality on the performance of methods. In Table 4, we show the enrichment factors EF0.01 and EF0.1 of different methods using experimental and modeled target structures for a subset of 30 targets from DUD set. The other 10 targets are not included because the modeled structures have extended long tails (not compact) and their dimensions are too large for docking methods. The results of FINDSITEcomb change very little when modeled structures as compared to experimental structures are used. This is not the case for either DOCK6 or AUTODOCK whose performance significantly deteriorates.</p><!><p>Comparison of methods for the 30 protein DUD set using experimental and modeled structures</p><!><p>Since FINDSITEcomb is much faster than traditional docking approaches and can use modeled as well as experimental structures, we can perform large-scale testing on drug targets (some of which lack experimental structures). This kind of test is not feasible for traditional docking methods. We tested FINDSITEcomb on a set of 3,576 DrugBank [57] targets that we can confidently model using TASSERVMT-lite [53]. We use modeled target structures even for those targets that have experimental PDB structures. Drugs of all the 3,576 targets are buried in a background of representative compounds that are culled to TC < 0.7 to each other from the ZINC8 library [74]. The total number of screened compounds for each target is 74,378 (6,507 drugs +67,871 ZINC8 compounds).</p><p>The test results are shown in Table 5. FINDSITEcomb achieves an average enrichment factor of 52 for the top 1% of (viz. ranked within the top 744) selected compounds; moreover, about 65% of the targets have an EF0.01 > 1 (EF = 1.0 is by random selection). Thus, on average about half of the true drugs of typical target will show up within top 1% of the screened compounds. FINDSITEcomb will be helpful in enriching true binders for 65% of the targets in a typical genome sequence. We note that FINDSITEcomb is better than any of its individual components. The major contribution to FINDSITEcomb is from FINDSITEfilt or holo PDB structure templates.</p><!><p>Performance of FINDSITE methods for 3,576 drug targets</p><!><p>For the experimental blind validation of this work, a compound library with molecules from the National Cancer Institute (NCI) and ZINC8 [74] (TC < 0.7) as background was used. The open chemical repository maintained by the Developmental Therapeutics Program (DTP) at NCI/NIH is a comprehensive set of small molecules consisting of compounds from the diversity set, mechanistic set, natural product set and approved oncology drug set. Compounds constituting the diversity set were derived from a parent library of ~140,000 compounds based on the following criteria: (1) Distinctness of the molecule, its pharmacophores and its conformational isomers, (2) Rigidity (5 or fewer rotatable bonds), (3) Planarity and (4) Pharmacologically desirable features. Compounds constituting the mechanistic set were selected from a seed library of 37,836 compounds tested on the NCI human tumor 60 cell line screens and represent compounds that show a broad range of growth inhibition. Compounds in the natural product set were selected from 140,000 compounds in the DTP open repository collection based on (a) origin, (b) purity, (c) structural diversity (differential scaffolds structures with varied functional groups), and (d) availability. The compounds in the approved oncology drug set consist of current FDA-approved drugs.</p><p>The reason for using NCI molecules was that they are easy to obtain. The NCI molecules are downloaded from NCI (http://dtp.nci.nih.gov/branches/dscb/repo_open.html) and consist of 1597 molecules from the Diversity Set III, 97 from the Approved Oncology Drugs Set IV, and 118 from the Natural Product Set II (total 1812 NCI molecules). The important fact is that no a priori target-compound binding information is used in both virtual screening and experimental validation. Together with the ZINC8 background, a total of 69683 molecules are screened by FINDSITEcomb. NCI molecules ranked within the top 1% (i.e. higher than ~700th) for each target are subsequently considered for thermal shift experimental validation.</p><!><p>High throughput thermal shift assays were carried out following established guidelines (Additional file 1: Table S1) [13,75]. Protein melting curves were obtained from samples aliquoted in 96-well plates using a RealPlex quantitative PCR instrument from Eppendorf (Eppendorf, NY, USA), with Sypro orange dye from Invitrogen as the fluorescent probe. A uniform final concentration of 5 X (supplied as a 5000 X stock solution) was used in all experiments. The dye was excited at 465 nm and emission recorded at 580 nm using the instrument's filters. A heating ramp of 1°C/min from 25°C to 74°C was used, and one data point acquired for each degree increment. For standardization, different buffers and pH were checked. Thereafter, 100 mM HEPES pH 7.3 and 150 mM NaCl were used in all unfolding experiments. The volume of each reaction was 20 μl, and appropriate dye and protein controls were included. All experiments were done with a minimum of two replicates, with the mean value considered for further analysis. Several drugs/small molecules interact with Sypro orange and lead to aberrant signal enhancements. An additional control to rule out drug-dye interaction was carried out with all the constituents kept constant except for the protein of interest. The protein/protein-drug curves were reported after subtracting the respective dye alone/drug-dye curves.</p><p>Each melting curve was assigned a quality score (Q), the ratio of the melting-associated increase in fluorescence (ΔFmelt) to the total fluorescence range (ΔFtotal). Q = 1 is a high-quality curve, while Q = 0 indicates no thermal transition [75]. Though an arbitrary Q value cutoff was not applied to judge curve quality, the curves were manually curated with Q values reported. A substantial fraction of ligands tested against the various proteins displayed no thermal transitions, Q = 0, or showed multi-step unfolding behavior. These were ignored (see Table 1).</p><!><p>Subsequent to standardization, (see SI Methods), the validity of the top 1% of FINDSITEcomb's predictions on the test set of eight diverse proteins was examined. To be conservative, we focused only on those protein/ligand pairs showing single sigmoidal thermal transition curves. The fit to Boltzmann's equation (Eq. 1) was employed to estimate the melting temperature from the observed intensity, I.</p><p>(4)I=Imin+Imax-Imin1+eTm-Ta</p><p>Imin and Imax are the minimum and maximum intensities; a denotes the slope of the curve at the transition midpoint temperate, Tm [13]. To estimate thermodynamic parameters, both van't Hoff [76] and Gibbs-Helmholtz analyses were done [77]. To estimate the approximate ligand-binding affinity at Tm, Eq. (2) from reference [78] was used with slight modifications; ΔCp is ignored.</p><p>(5)KLTm=exp-ΔHR1Tm-1ToL</p><p>KL(Tm) is the ligand association constant and [L] is the free ligand concentration at Tm ([LTm] ~ [L]total, when [L]total > > the total concentration of protein. KD is the inverse of KL(Tm).</p><p>To eliminate the possibility of thermal shifts arising because organic molecules form colloidal aggregates [79], the complete NCI set was compared to the database of known aggregators maintained at http://advisor.bkslab.org/search/. Since the thermal shift assay is incompatible with the presence of detergents, (the method of choice to eliminate aggregation-based thermal shifts), we limited ourselves to estimate chemical similarity to known aggregators. At a stringent TC cutoff of 0.9, none of the molecules reported as possessing either binding or antimicrobial/cytotoxic activities are similar to known aggregators.</p><!><p>Antimicrobial and anti-cancer tests were performed as in [80]. DHFR binders were tested on E. coli DH5α [positive control: Nitrofurantion (10 mg/ml in DMSO, negative control: DMSO], multi-drug resistant E. coli SMS-3-4 (ATCC BAA-1743) (MDREC) [positive control: Nitrofurantion (10 mg/ml in DMSO), negative control: DMSO], methicillin-resistant S. aureus (ATCC 33591) (MRSA) [positive control: Vancomycin (10 mg/ml in DMSO), negative control: DMSO], vancomycin-resistant E. faecium (ATCC700221) (VREF) [positive control: Chloramphenicol (10 mg/ml in DMSO), negative control: DMSO], and colon carcinoma cells HCT-116 [positive control: etoposide (20 μg/ml in DMSO), negative control: DMSO]. Phosphatase (1000001 and 1000006) binders and tryptophanyl tRNA synthetase binders were tested on the colon carcinoma cell line HCT-116.</p><!><p>VLS: Virtual ligand screening; HTS: High throughput screening; DMSO: Dimethyl sulfoxide; PTP: Protein tyrosine phosphatase; DHFR: Dihydrofolate reductase; UCE: Ubiquitin-conjugating enzyme; TrpRS: Tryptophanyl tRNA synthetase; NAP: Nucleosome assembly protein; TP: Thioredoxin peroxidase; cDPK: Catalytic domain of cAMP-dependent protein kinase.</p><!><p>The authors declare no competing financial interest. We are currently applying for patents relating to the content of the manuscript.</p><!><p>BS analyzed and compiled the virtual ligand screening (VLS) data, designed and carried out the experimental high-throughput thermal shift (HTS) assays, analyzed and interpreted the data, and drafted the manuscript. HZ carried out the computational VLS experiments, analyzed the VLS data, drafted the sections on VLS and critically reviewed the manuscript. JK was instrumental in designing and analyzing the antibacterial and anticancer activity assays and helped in critically reviewing the manuscript. JS conceived of the study, participated in its design and coordination, provided appropriate resources, helped analyze the data, and was involved in drafting and critically reviewing the manuscript. All authors read and approved the final manuscript.</p><!><p>Detailed FINDSITEcomb VLS results, Thermal shift assay standardization: methods and results, HTS protocol table, detailed results on the thermal shift assay and biological activity assay for the eight protein in tabular form, discussion on the differences between 1000001 and 1000006 VLS and experimental overlap and figure depicting the diversity of compounds picked up by the current methodology.</p><!><p>Click here for file</p><!><p>This project was funded by GM-37408 and GM-48835 of the Division of General Medical Sciences of NIH, with partial support by the International Cooperative Biodiversity Groups Grant U01 TW007401 from NIH and NSF. The authors wish to thank Drs. Steven Almo, Greg Crowther, Wesley Van Voorhis, Paul Schimmel, Eugene Shakhnovich, Susan Taylor, the Structural Genomics of Pathogenic Protozoa Consortium and the New York Structural Genomics Consortium for providing proteins, Sebastian Engel and Chris Lane for assisting with the antibacterial studies, Ambrish Roy for critically reading the manuscript and Bartosz Ilkowski for managing the computer cluster on which the computations were conducted.</p>

PubMed Open Access

Omeprazole Induces NAD(P)H Quinone Oxidoreductase 1 via Aryl Hydrocarbon Receptor-Independent Mechanisms: Role of the Transcription Factor Nuclear Factor Erythroid 2\xe2\x80\x93Related Factor 2

Activation of the aryl hydrocarbon receptor (AhR) transcriptionally induces phase I (cytochrome P450 (CYP) 1A1) and phase II (NAD(P)H quinone oxidoreductase 1 (NQO1) detoxifying enzymes. The effects of the classical and nonclassical AhR ligands on phase I and II enzymes are well studied in human hepatocytes. Additionally, we observed that the proton pump inhibitor, omeprazole (OM), transcriptionally induces CYP1A1 in the human adenocarcinoma cell line, H441 cells via AhR. Whether OM activates AhR and induces the phase II enzyme, NAD(P)H quinone oxidoreductase 1 (NQO1), in fetal primary human pulmonary microvascular endothelial cells (HPMEC) is unknown. Therefore, we tested the hypothesis that OM will induce NQO1 in HPMEC via the AhR. The concentrations of OM used in our experiments did not result in cytotoxicity. OM activated AhR as evident by increased CYP1A1 mRNA expression. However, contrary to our hypothesis, OM increased NQO1 mRNA and protein via an AhR-independent mechanism as AhR knockdown failed to abrogate OM-mediated increase in NQO1 expression. Interestingly, OM activated Nrf2 as evident by increased phosphoNrf2 (S40) expression in OM-treated compared to vehicle-treated cells. Furthermore, Nrf2 knockdown abrogated OM-mediated increase in NQO1 expression. In conclusion, we provide evidence that OM induces NQO1 via AhR-independent, but Nrf2-dependent mechanisms.

omeprazole_induces_nad(p)h_quinone_oxidoreductase_1_via_aryl_hydrocarbon_receptor-independent_mechan

Introduction<!>Cell culture and treatment<!>Cell viability assay<!>Determination of Functional Activation of AhR<!>Real-time RT-PCR assays<!>Western Blot Assays<!>Small interfering RNA (siRNA) transfections<!>Analyses of data<!>Results and Discussion

<p>The aryl hydrocarbon receptor (AhR) is a member of basic - helix – loop – helix / PER – ARNT – SIM family of transcriptional regulators [1–3]. In humans, the AhR is highly expressed in the lungs, thymus, kidney and liver [4]. The AhR is predominantly cytosolic, localized in a core complex comprising two molecules of 90-kDa heat shock protein and a single molecule of the co-chaperone hepatitis X-associated protein-2 [5, 6]. AhR activation results in a conformational change of the cytosolic AhR complex that exposes a nuclear localization sequence(s), resulting in translocation of this complex into the nucleus [7, 8]. In the nucleus, AhR dissociates from the core complex, dimerizes with the AhR nuclear translocator, and initiates transcription of many phase I and phase II enzymes such as cytochrome P450 (CYP) 1A1, glutathione S-transferase-α(GST-α), and NAD(P)H quinone reductase-1 (NQO1), by its interaction with the xenobiotic responsive elements present in the promoter region of these genes [9–12]. AhR is of particular interest to toxicologists and extensive research has been conducted on its role in the bioactivation of polycyclic and aromatic hydrocarbons leading to carcinogenesis [13]. However, the creation of knockout and transgenic mice has provided mechanistic insights into the potential role(s) that AhR might play in normal physiological homeostasis [14–17].</p><p>Several structurally diverse compounds activate AhR. The protypical or classical AhR ligands are characteristically planar, aromatic, and hydrophilic molecules that includes polycyclic aromatic hydrocarbons such as benzo [α] pyrene and halogenated aromatic hydrocarbons such as 2,3,7,8-tetrachlorodibenzo-p-dioxin [18]. Additionally, several nonclassical synthetic compounds such omeprazole, lansoprazole, thiabendazole, and primaquine can activate AhR-dependent gene expression indirectly. Although these compounds are not AhR ligands by themselves, they are thought to activate AhR-dependent gene expression, either via metabolic conversion into a ligand or by their ability to affect a cellular pathway that results in AhR activation [19–23].</p><p>Omeprazole (OM), a benzimidazole derivative, is a proton pump inhibitor that inhibits gastric acid secretion both in humans [24] and in animals [25, 26]. It has been widely used in the management of gastric acid disorders in humans [24]. Studies have shown that omeprazole activates AhR in human and rat hepatocytes [27, 28]. Recently, we observed that OM increases AhR-regulated CYP1A1 expression in the human adenocarcinoma cell line, H441, [29]. Whether OM can modulate the AhR-regulated phase II enzyme, NQO1, in fetal primary human microvascular endothelial cells (HPMEC) is unknown. Thus, the goals of this study were to investigate the effects of OM on AhR-mediated expression of NQO1 in HPMEC. Specifically, we chose HPMEC for our experiments because they express AhR [30] and they are used to study mechanisms of diseases such as bronchopulmonary dysplasia (BPD) where AhR might play a significant role [31, 32]. Using these cells, we tested the hypothesis that OM will increase NQO1 expression in wild type HPMEC, but not in AhR-deficient HPMEC.</p><!><p>HPMEC, the primary microvascular endothelial cells derived from the lungs of human fetus were obtained from ScienCell research laboratories (San Diego, CA; 3000). HPMEC were grown in 95% air and 5% CO2 at 37°C in specific endothelial cell medium according to the manufacturer's protocol. Cells were treated with either 0.01% v/v dimethyl sulfoxide (DMSO) (Sigma Aldrich, St. Louis, MO; 276855) or 100 μM omeprazole (OM) (Sigma Aldrich St. Louis, MO; O104) for up to 48 h.</p><!><p>Cell viability was determined by a colorimetric assay based on the ability of viable cells to reduce the tetrazolium salt, MTT (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide), to formazan. HPMEC were seeded onto 96-well microplates and treated with DMSO or OM at varying concentrations (0.5 – 100 μM) for up to 48 h. The cell viability was then assessed by MTT reduction assays as outlined in the MTT Assay protocol (American Type Culture Collection, Manassas, VA).</p><!><p>It is widely established that functional activation of AhR results in its translocation into the nucleus, which results in transcriptional activation of the phase I enzyme, CYP1A1. Therefore, we determined the functional activation of AhR by analyzing the expression of CYP1A1 mRNA levels.</p><!><p>Cells were grown on six-well plates to 60–70% confluence, after which they were treated with DMSO or OM. At 24 or 48 h of exposure, total RNA was isolated and reverse transcribed to cDNA as mentioned before [29]. Real-time quantitative RT-PCR analysis was performed with 7900HT Real-Time PCR System using iTaq Universal SYBR Green Supermix (Biorad, Hercules, CA; 1725121). The sequences of the primer pairs were hAhR: 5′-CACCGATGGGAAATGATACTATCC-3′ and 5′-GGTGACCTCCAGCAAATGAGTT-3′; hCYP1A1: 5′-TGGATGAGAACGCCAATGTC-3′ and 5′-TGGGTTGACCCATAGCTTCT-3′; hNQO1: 5′-ACGCCC-GAATTCAAATCCT-3′ and 5′-CCTGCCTGGAAGTTTAGGTCAA-3′; hNrf2: 5′-AAA CCA GTG GAT CTG CCA AC-3′ and 5′-GAC CGG GAA TAT CAG GAA CA-3′; hβ-actin: 5′-TGACGTGGACATCCGCAAAG-3′ and 5′-CTGGAAGGTGGACAGCGAGG-3′. β-actin was used as the reference gene.</p><!><p>Whole-cell protein extracts from the cells treated with DMSO or OM 100 for up to 48 h were obtained by using nuclear extraction kit (Active Motif, Carlsbad, CA; 40010) [29]. β-actin was used as a reference protein. The protein extracts were separated by 10% SDS-polyacrylamide gel electrophoresis and transferred to polyvinylidene difluoride membranes. The membranes were incubated overnight at 4°C with the following primary antibodies: anti-AhR antibody (Santa Cruz Biotechnologies, Santa Cruz, CA; sc-5579, dilution 1:500), anti-CYP1A1 antibody (gift from P.E. Thomas, Rutgers University, Piscataway, NJ, dilution 1:500), anti-NQO1 antibody (Santa Cruz Biotechnologies, Santa Cruz, CA; sc-16464, dilution 1:500), anti-β-actin antibody (Santa Cruz Biotechnologies, Santa Cruz, CA; sc-47778, dilution 1:1000), anti-Nrf2 (Santa Cruz Biotechnologies, Santa Cruz, CA; sc-722, dilution 1:500) and anti-phosphoNrf2 (S40) antibodies (Abcam; ab76026, Cambridge, MA; dilution 1:1000). The immuno-reactive bands were detected by chemiluminescence methods.</p><!><p>HPMEC were seeded in fibronectin-coated 6-well plates at 60–70% confluence 24 h before transfection. Transfections were then performed with either 50 or 100 nM control siRNA (Dharmacon, Lafayette, CO; d-001810) or 50 nM AhR specific siRNA (Dharmacon, Lafayette, CO; L-004990) or 100 nM Nrf2 specific siRNA (Dharmacon, Lafayette, CO; L-003755) using LipofectamineRNAiMAX (Life Technologies, Grand Island, NY; 13778030). After 24 h of transfection, the cells were treated with DMSO or OM for up to 48 h. siRNA mediated knockdown of AhR or Nrf2 was validated by determining the expression of AhR and Nrf2 mRNA and protein by real time RT PCR analysis and western blotting, respectively. Additionally, the cells were harvested at the indicated time points to determine the expression of NQO1 mRNA and protein.</p><!><p>The results were analyzed by GraphPad Prism 5 software. At least three separate experiments were performed for each measurement, and the data are expressed as means ± SEM. The effects of OM, AhR or Nrf2 gene and their associated interactions for the outcome variables were assessed using ANOVA techniques. Multiple comparison testing by the posthoc Bonferroni test was performed if statistical significance of either variable or interaction was noted by ANOVA. A p value of <0.05 was considered significant.</p><!><p>In this study, we investigated the effects of OM on the expression of NQO1 enzyme in wild type (WT), AhR- and Nrf2-deficient HPMEC in vitro. The present study demonstrates that OM induces NQO1 expression in HPMEC via mechanism(s) entailing Nrf2 activation. In human fetal lung-derived WT and AhR-deficient HPMEC in vitro, OM transcriptionally induced NQO1 expression when compared to controls, whereas, in Nrf2-deficient HPMEC, the lack of OM-mediated induction of NQO1 enzyme correlated with the deficiency of a functional Nrf2 gene.</p><p>The AhR is a versatile transcription factor that has important physiological functions in addition to its widely established role in the induction of a battery of genes involved in the metabolism of xenobiotics. Studies from our laboratory and others have reported that AhR may be a crucial regulator of oxidant stress and inflammation through the induction of several detoxifying enzymes or via "cross-talk" with other signal transduction pathways. Several in vitro studies suggest that OM activates AhR in human and rat hepatocytes [27, 28, 33, 34] and the mechanistic role of AhR in the induction of CYP1A enzymes by OM in vitro has been extensively studied [29, 35, 36]. However, whether OM induces the phase II enzyme, NQO1, via AhR is unknown. Therefore, we conducted experiments with OM in primary human fetal lung-derived HPMEC in vitro, both in the presence and absence of a functional AhR, to delineate the precise role of AhR in OM-mediated induction of NQO1 enzyme.</p><p>The concentration of OM used in this study was comparable to those used in previous studies [37, 38]. More importantly, we included the blood concentrations that are observed in humans following OM therapy [39]. Initially, we tested the cytotoxicity of OM in HPMEC by MTT assay. OM in concentrations up to 100 μM did not affect the viability of HPMEC (Fig. 1A). To determine the effects of OM on the functional activation of AhR, we initially determined the expression of the prototypical marker of AhR activation, CYP1A1, in HPMEC treated with the vehicle, DMSO, or OM. Real-time RT-PCR analyses indicated that OM increases CYP1A1 mRNA levels in a dose-dependent manner when compared to DMSO-treated cells (Fig. 1B). Next, we determined the effects of OM on the expression of the AhR-regulated phase II enzyme, NQO1. OM increased NQO1 mRNA (Fig. 1C) and protein levels (Figs. 1D and E). Interestingly, when compared to its effects on CYP1A1 expression, OM induced NQO1 expression only at a higher concentration of 100 μM, which suggests that OM has a differential concentration specific effect on phase I and II enzymes. To ascertain whether the AhR is a crucial regulator of OM-mediated increase in NQO1 expression in fetal HPMEC, we performed AhR siRNA transfection experiments to knockdown AhR. AhR siRNA significantly decreased AhR (Fig. 2A) and CYP1A1 (Fig. 2B) mRNA and AhR protein (Fig. 2D) expression. Surprisingly, AhR deficiency failed to abrogate OM-mediated increase in NQO1 mRNA (Fig. 2C) and protein (Figs. 2D and E) expression. These findings thus disprove our hypothesis that OM induces NQO1 expression via AhR-mediated mechanisms.</p><p>Nuclear factor erythroid 2–related factor 2 (Nrf2), which regulates the antioxidant response element (ARE)-driven gene battery is a major transcription factor that modulates NQO1 expression [40]. Hence, we finally conducted experiments to determine whether OM induces NQO1 via Nrf2. Interestingly, we observed that OM-treated cells had increased phosphoNrf2 (S40) expression compared to vehicle-treated cells (Figs. 3B, C, and E). This finding suggests that OM activates Nrf2 signaling since phosphorylation of Nrf2 at S40 leads to dissociation of Nrf2 from its inhibitor Kelch-like ECH-associated protein 1, which in turn results in the translocation of Nrf2 into the nucleus where it activates ARE-mediated gene expression [41]. OM has been similarly shown to increase nuclear Nrf2 accumulation in mice [42]. Although Mahmoud-Awny et.al. [43] observed that OM increases Nrf2 mRNA levels in rats with an ischemic/reperfusion insult, OM had no effect on the Nrf2 mRNA levels (Fig. 3A) in our study. These discrepant findings may be attributed to the differences in species, cell type, and the nature of underlying insult. Identical Nrf2 mRNA levels (Fig. 3A) between vehicle- and OM-treated cells suggest that OM activates Nrf2 pathway via unknown posttranscriptional mechanisms in HPMEC. To determine whether Nrf2 is a critical regulator of NQO1 expression in OM-treated cells, we knocked down Nrf2 by transfecting the cells with Nrf2 siRNA. Nrf2 siRNA significantly decreased Nrf2 and NQO1 mRNA (Figs. 4A and B) and protein (Figs. 4C and D) expression, which indicates that Nrf2 regulates the constitutive expression of NQO1 in HPMEC. Furthermore, OM failed to increase NQO1 mRNA (Fig. 4B) and protein (Figs. 4C and D) expression in Nrf2-deficient cells, supporting the hypothesis that OM-mediated induction of the NQO1 enzyme occurs via Nrf2-dependent mechanisms. Although a previous study has shown that OM increases hepatic NQO1 mRNA levels in rats [44], the mechanism of NQO1 induction was not investigated. To the best of our knowledge, this is the first study to demonstrate that Nrf2 is directly involved in OM-mediated induction of NQO1 in HPMEC in vitro. The mechanisms of OM-mediated activation of Nrf2 are unknown and deserve further investigations.</p><p>In summary, we provide evidence that OM induces pulmonary NQO1 enzyme in vitro via AhR-independent, but Nrf2-dependent mechanisms. Our results suggest that OM can be used to investigate Nrf2 biology in the lung, which can lead to the discovery of novel therapies in the prevention and treatment of oxidative stress-induced disorders like BPD in premature infants, and acute respiratory distress syndrome, chronic obstructive pulmonary disease, and malignancies in adults.</p>

PubMed Author Manuscript

An enzyme-free molecular catalytic device: dynamically self-assembled DNA dendrimers for <i>in situ</i> imaging of microRNAs in live cells

DNA has become a promising material to construct high-order structures and molecular devices owing to its sequence programmability. Herein, a DNA machine based on branched catalytic hairpin assembly (bCHA) is introduced for dynamic self-assembly of DNA dendrimers. For this system, a Y-shaped hairpin trimer tethered with three kinds of hairpins (H1, H2 and H3) is constructed. The introduction of an initiator (I) triggers a cascade of CHA reactions among hairpin trimers, leading to the formation of DNA dendrimers.Through labeling fluorophore/quencher pairs in the hairpin trimers, this catalytic DNA machine is applied as a versatile amplification platform to analyze nucleic acids using microRNA-155 (miR-155) as a model analyte. Benefiting from the "diffusion effect", the proposed bCHA achieves a greatly improved sensitivity in comparison with traditional CHA. This catalytic amplifier exhibits high sensitivity toward miR-155 detection with a dynamic range from 2.5 nM to 500 nM and demonstrates excellent selectivity to distinguish the single-base mismatched sequence from the perfectly complementary one, which is further applied to detect low-abundance miR-155 spiked in complex matrices with minimal interference. This method is further applied for in situ imaging of miR-155 in different live cells. The bCHA reaction can be specifically triggered by intracellular miR-155, achieving monitoring of the dynamic miRNA expression and distribution. Overall, our proposed enzyme-free dynamic DNA self-assembly strategy provides a versatile approach for the development of DNA nanotechnology in biosensing and bioimaging, and monitoring the cellular miRNA-related biological events.

an_enzyme-free_molecular_catalytic_device:_dynamically_self-assembled_dna_dendrimers_for_<i>in_situ<

Introduction<!>Principle of bCHA<!>Native polyacrylamide gel electrophoresis (PAGE)<!>Amplication biosensing of microRNA<!>Amplication efficiency of bCHA<!>In situ imaging of miR-155 in live cells<!>Conclusions<!>Native polyacrylamide gel electrophoresis (PAGE)<!>Morphology characterization<!>Dynamic light scattering (DLS) and zeta potential<!>Conflicts of interest

<p>Deoxyribonucleic acids (DNAs) have been considered as promising building blocks to fabricate a variety of nanostructures and devices owing to their sequence programmability and specic recognition properties. 1 The applications of DNAs as engineering materials provide a solid foundation for the development of DNA nanotechnology and materials science. 2 DNA nanotechnology can be mainly divided into two categories: structural DNA nanotechnology and dynamic DNA nanotechnology, in which DNA strands are employed to program the spatial and temporal distribution of matter. 3 Based on 'bottom-up' engineering approaches, structural DNA nanotechnology has realized the fabrication of 2D and 3D DNA assemblies with various sizes and spatial structures, such as DNA lattices, 4,5 DNA origami, 6 DNA tetrahedron structures, [7][8][9] DNA nanotubes 10,11 and so on. Unlike structural DNA nanotechnology, dynamic DNA nanotechnology lays emphasis on the non-equilibrium dynamics, in which the formation of DNA nanostructures results from successive dynamic assembly of DNA motifs. 3 That is, the nanostructures formed by dynamic DNA nanotechnology can present mechanical operation processes. To date, a variety of dynamic DNA devices have been constructed, which are propelled by DNAzymes, 12 specic DNA-modifying enzymes 13,14 and toehold-mediated strand displacement (TMSD) reactions. [15][16][17] The TMSD reaction, a concept pioneered by Yurke et al., occurs when an invading strand displaces a target strand on a double-stranded complex with the help of a single-stranded sequence (termed a toehold). 18 By means of the toehold sequence, the DNA invasion reaction can be accelerated and realize the kinetically controlled self-assembly of DNA. 3,19 Thus, the TMSD reaction has been used as powerful tool to program enzyme-free DNA circuits and DNA nanomachines. 20,21 To date, synthetic molecular machines have spurred substantial research efforts in the elds of biosensing for detecting a variety of targets such as miRNA, proteins and so on, and bioimaging for accurate miRNA imaging in living cells. 34,35 Catalytic hairpin assembly (CHA) can be considered as one of the most prominent TMSD reactions. In CHA, DNA hairpins are kinetically trapped and exist metastably. Upon the introduction of an initiator, successive assembly steps are triggered among DNA hairpins to form branched junctions via cascades of strand displacement reactions, accompanied by a disassembly step in which the initiator is displaced to catalyze another CHA process. 17 Since one initiator can be continuously replaced and recycled to trigger a new reaction, CHA has been applied as a powerful enzyme-free signal transducer for isothermal amplication analysis of a wide range of targets from nucleic acids, small molecules to proteins and even cancer cells. [22][23][24][25][26] Very recently, CHA has been further applied to construct diverse DNA structures and molecular machines. 27 MicroRNAs (miRNAs) are a group of small noncoding RNA molecules that play important roles in a series of cellular processes such as cell differentiation, proliferation, apoptosis and so on. [28][29][30] More and more research has demonstrated that the cellular dysregulated expression of miRNAs is related to the genesis of many cancers. [31][32][33] Therefore, it is necessary to sensitively detect miRNAs for early diagnosis of cancers and cellular level research. Currently, beneting from the advantages of CHA, some CHA-based detection methods have been established for quantitative detection and analysis of miRNA expression. [36][37][38][39] However, effective signal amplication of miR-NAs is still greatly needed due to their low expression level in cells.</p><p>Herein, we construct an enzyme-free catalytic device based on bCHA for dynamic self-assembly of DNA dendrimers. This strategy involves the formation of a Y-shaped hairpin trimer which contains a Y-scaffold and three kinds of hairpins. The assembly into explicit DNA dendrimers is initiated and mediated via a series of CHA processes among the hairpin trimers. By using the target-triggered mechanism, we demonstrate the versatile applications of the proposed bCHA for signal ampli-cation biosensing and in situ imaging of miR-155 in live cells with high sensitivity and selectivity. For all we know, this is the rst time an intracellular CHA process is reported for in situ monitoring the dynamic expression and distribution of miRNA in live cells. Compared with other molecular devices, especially traditional CHA, the major advantage of our proposed bCHA is the signicantly improved amplication efficiency which beneted from the "diffusion effect". In bCHA, three hairpins are localized on a Y-scaffold DNA, which thus provides an addressable substrate for those released initiators, achieving greater control for cascade hairpin assembly.</p><!><p>The proposed bCHA strategy consists of a Y-scaffold DNA and three kinds of hairpins (HP1, HP2 and HP3). The sequences and the secondary structures of the oligonucleotides used in this work are listed in Table S1 and Fig. S1, † respectively. The assembly pathways are shown in Fig. 1a. The Y-scaffold DNA is composed of three single-stranded DNAs (ssDNAs), Y1, Y2 and Y3, in which each strand contains three segments: a long "sticky end" to interact with its complementary sequence on the corresponding hairpin and two parts to hybridize with the other two strands. On the basis of Watson-Crick base pairs, the Yshaped hairpin trimer is formed via the hybridization of the "sticky ends" between the Y-scaffold DNA and hairpins (Fig. 1a, reaction 1). The formed hairpin trimer can metastably coexist in solution, and acts as a building block to self-assemble DNA dendrimers upon addition of the initiator to activate the dynamic self-assembly process of bCHA. During the bCHA, the initiator hybridizes and docks to the exposed toehold domain a of H1 and subsequently displaces the parts of x, b, and y from the duplex of the stem in H1 via a TMSD reaction, opening the loop of H1 (Fig. 1a, reaction 2). The opened loop makes the branch migration irreversible. Meanwhile, the newly exposed domain b* of H1 hybridizes with domain b of H2, which is the component of a proximal hairpin trimer in solution, to operate the branch migration, resulting in the opening of the loop of H2 and the formation of the hybrid of two three-arm branched hairpin structures (Fig. 1a, reaction 3). Another proximal hairpin trimer then invades the hybrid because the toehold domain c of H3 can dock to the newly exposed domain c* of the hybrid. And then a disassembly step is performed, in which H3 displaces I from the complex to catalyze another dynamic selfassembly process (Fig. 1a, reaction 4). One CHA reaction is completed as above. Theoretically, this branching chain growth would continue to form DNA dendrimers aer a cascade of CHA processes among the hairpin trimers (Fig. 1a, reaction 5), which is thus termed branched catalytic hairpin assembly (bCHA).</p><p>The morphology of the DNA dendrimers assembled via bCHA was characterized by microscope imaging (Fig. 1b). In the absence of an initiator, no assembly event of hairpin trimers occurs. In contrast, a large number of two-dimensional hyperbranched DNA structures appear upon adding the initiator into the hairpin trimers. The size distribution of the hairpin trimers before and aer being incubated with the initiator was further measured by DLS (Fig. 1c). The size of hairpin trimers is determined to be 45 AE 15 nm, whereas, it signicantly increases to 4.5 AE 2.5 mm upon addition of the initiator, which are consistent with the observation in microscopy images. Therefore, the above results fully demonstrate the successful dynamic self-assembly of DNA dendrimers via bCHA as anticipated. Furthermore, the zeta potential of the DNA dendrimers was measured to be À8.35 AE 3.44 mV, which can be attributed to the negatively charged phosphate backbones of the packed DNA strands constituting the DNA dendrimers (Fig. S2 †).</p><!><p>As a proof-of-concept experiment, the assembly of Y-scaffold DNA was veried by native PAGE (Fig. 2a). The bands in lanes 1, 2 and 3 correspond to Y1, Y2 and Y3, respectively, which migrate faster than the assembled Y-scaffold DNA (lane 7). The bands representing Y1 + Y2, Y1 + Y3, and Y2 + Y3 (lanes 4, 5, and 6) are in between. These results indicate the effectivity of the assembly process, and Y-scaffold DNA has been formed as designed. Subsequently, we compared the assembly pathways of traditional CHA and the proposed bCHA by native PAGE. For the traditional CHA, three-arm DNA junctions are formed through self-assembly of H1, H2 and H3 triggered by the initiator, while in bCHA the DNA dendrimers are generated using hairpin trimers as building blocks. As shown in Fig. 2b, lanes 10-12 are H1, H2 and H3, respectively, while lane 9 corresponds to the mixture of H1, H2 and H3 without an initiator. These bands are almost at the same migration rate. In the presence of the initiator, three-arm DNA junctions are formed (lane 8), which migrate slower than hairpin species. The formation of Yscaffold DNA in lane 13 is almost the same as that shown in Fig. 2a. When the Y-scaffold DNA is mixed with H1, H2 and H3 at a ratio of 1 : 1 : 1 : 1, the hybrid of the Y-shaped hairpin trimer is formed in lane 14. With the addition of the initiator, the band corresponding to the hairpin trimer disappears and the assembly products with much lower mobility are observed in lane 15, demonstrating the formation of DNA dendrimers with high molecular weight via the bCHA.</p><!><p>Since the initiator can be displaced to continuously trigger a new cycle of assembly, we further employed the bCHA strategy as a catalytic amplier for sensitive and selective detection of microRNA. It has been reported that miR-155 plays an important role in various physiological and pathological processes, and can be considered as an important biomarker for diagnosis, staging, progression, and prognosis of cancers. 40,41 To demonstrate the feasibility of the bCHA for amplied detection of miR-155, H1 is modied with a uorophore (FAM) at the 3 0 terminus and a quencher (Dabcyl) at the appropriate position (Fig. 3a). In the absence of miR-155, the efficient quenching effect resulted from the fact that the closely positioned Dabcyl quencher makes the uorescent emission from the FAM minimal. In contrast, the introduction of the miR-155 initiates dynamic self-assembly among hairpin trimers, resulting in the opening of H1 to remove the quencher from the uorophore. Thus, the signicantly amplied uorescent signal output can be monitored for highly sensitive detection of miR-155. The real-time uorescence triggered by different concentrations of miR-155 was measured to investigate the growth kinetics of the proposed bCHA (Fig. 3b). At the beginning of the reaction, the annealed hairpins on trimers are in a closed structure so that the uorophore and the quencher are brought into close proximity, resulting in an "off" uorescence signal. This phenomenon is veried by monitoring the uorescence intensity of the control sample consisting of only H1. For the blank sample without miR-155, the uorescence intensity should be almost the same as the control since no DNA dendrimer is generated and the uorophore separate from the quencher. However, a slightly increased uorescence is observed, which can be attributed to the system leakage induced by few imperfectly annealed hairpin species. Thankfully, the uorescence intensity of the blank sample remains at a low level which has a negligible inuence on the reaction, demonstrating that the Y-shaped hairpin trimers can metastably coexist in the absence of an initiator. Upon the introduction of target miR-155, the self-assembly process of bCHA is activated, resulting in the formation of hyperbranched DNA structures. In this case, the uorescence of H1 is recovered with an enlarged spatial distance between the uorophore and the quencher, resulting in the "uorescence-on" mode. The increased uorescence intensity is in direct proportion to the concentration of miR-155. In particular, the emission intensity rapidly reaches a plateau when the concentrations of miR-155 are at 250 nM and 500 nM, indicating a large proportion of reactants can be depleted when the initiator is at high concentrations. The bCHA protocol has revealed high amplication efficiency for quantitative analysis of miR-155. As low as 2.5 nM miR-155 can be well distinguished from the blank. This sensitivity is satisfactory and comparable with other molecular devices. 43,44 To further assess the quantitative behavior of the proposed method, we choose 20 000 a.u. as the threshold, at which all samples can be taken into consideration. A log-linear trend between the initial concentration of miR-155 and the time to reach a uorescence threshold of 20 000 a.u. is shown as Fig. 3c. This relationship is presented as log 10 [time] ¼ À7.63 À 1.1 log 10 [C] with a correlation coefficient (R 2 ) of 0.99. Furthermore, ve parallel measurements are performed to study the repeatability of this strategy by adding 50 nM miR-155 to trigger the bCHA. The relative standard deviation (RSD) of 3.01% indicates the acceptable repeatability of the proposed catalytic amplication platform for biosensing of miRNAs.</p><p>Moreover, the specicity of the proposed bCHA strategy for miRNA analysis was conrmed by using one-base mismatched, three-base mismatched, and perfectly complementary miR-155 as the analytes, respectively (Fig. 3d). Under the same reaction conditions, this method could completely distinguish mismatched miR-155, even one-base mutant, showing high sequence specicity toward the target miRNA due to the precise hybridization properties of TMSD reactions. To assess the reliability of this assay in real samples, the standard addition method was implemented by detecting miR-155 with different concentrations (5 nM, 25 nM, and 50 nM) spiked in 100-fold diluted healthy human serum. As shown in Table S2, † the recoveries of miR-155 range from 95.6% to 108.0% with the RSD of 2.8-3.3%. The results indicate that the bCHA strategy has a high ability to prevent interference for miRNA analysis, which thus is available for the development of diagnostic systems in clinical applications.</p><!><p>To demonstrate the amplication efficiency of bCHA, control experiments were carried out using free DNA hairpins instead of hairpin trimers to perform the traditional CHA, in which the miR-155 triggered a cascade of assembly steps with H1, H2 and H3 to form a three-arm DNA junction (Fig. S3a †). The comparison of real-time uorescence intensities between CHA and bCHA triggered by different concentrations of miR-155 could be observed (Fig. S3b †). In the absence of an initiator, the uorescence intensities of both systems remain at low levels. The slightly higher uorescence of bCHA can be attributed to the system leakage induced by the mutual interference among multiple DNA sequences. The corresponding uorescence intensity at the reaction time of 360 min is presented in Fig. 3e and S3c. †The uorescence intensities of bCHA can be obviously distinguished from those of CHA upon the addition of miR-155 with the same concentrations (25 nM and 50 nM). In particular for high concentration of the initiator (50 nM), the signal amplication capability of bCHA was calculated as (F bCHA(50 nM) À F bCHA(0 nM) )/(F CHA(50 nM) À F CHA(0 nM) ), showing that the bCHA had about a 1.68 times higher uorescence signal than the traditional CHA. Thus, the proposed bCHA system provides signicantly improved amplication efficiency for the detection of initiators (target miR-155 detection in this assay). We can attribute this phenomenon to the "diffusion effect". 42 Briey, in a traditional CHA system the released initiators during reaction may interact with other hairpins present in solution. Nevertheless, the released initiators from bCHA are much more likely to trigger the nearby hairpin molecules attached on the Yscaffold DNA for cascade hairpin assembly, which thus achieves greater control over directing reaction pathways.</p><!><p>It has been reported that miR-155 is overexpressed in many types of cancer cells, especially breast cancer. 41 Thus, MCF-7 cells (human breast adenocarcinoma cell line) were selected as the model to investigate the optimal time and monitor the dynamics of the bCHA in live cells (Fig. 4a). We rst test the stability of hairpin trimers, in which free H1 and hairpin trimers were treated with 100-fold diluted healthy human serum for 6 h, respectively. The result shows that the uorescence recovery from H1 in hairpin trimers was much lower than that of free H1 (Fig. S4 †), demonstrating that the structure of the hairpin trimer could protect hairpins from nuclease degradation to a certain degree. Subsequently, the transfection times required for bCHA activation by miR-155 in MCF-7 cells were investigated (Fig. 4b and S5 †). On prolonging the transfection time, the uorescence intensities increase gradually, and robust uorescence signals produced by intracellular miR-155 can be readily observed at 4 h. 3D confocal uorescence imaging further conrmed that the hairpin trimers have successfully entered MCF-7 cells and have been activated by miR-155 in the cytoplasm (Fig. 4c). We further designed a mutated H1 (six-base mismatched H1), named mH1, to the mechanism of bCHA in living cells. Almost no uorescence was observed since the mH1 cannot hybridize with miR-155 to form DNA dendrimers, demonstrating that the observed uorescence was indeed produced by target-induced assembly of hairpin trimers among H1, H2 and H3 (Fig. S6 †).</p><p>To demonstrate the amplication efficiency of the proposed bCHA for monitoring intracellular miR-155, MCF-7 cells were transfected with only H1, the mixture of hairpin monomers (H1, H2 and H3) and hairpin trimers to perform direct uorescence in situ hybridization (FISH) which involved the use of a singlestranded DNA probe modied with FAM and Dabcyl, traditional CHA and bCHA, respectively. (Fig. 5a and b). When MCF-7 cells were transfected with only H1, since H1 was opened by miR-155 via TMSD reactions with a ratio of 1 : 1, a weak uorescence signal was observed. However, for the transfection of hairpin monomers H1, H2 and H3 together, the traditional CHA reaction occurred by intracellular miR-155, showing a clear uorescence signal due to the isothermal target recycling amplication of CHA. Interestingly, in comparison with traditional CHA, thanks to the "diffusion effect" discussed above, the strongest uorescence signal could be observed when MCF-7 cells were treated with hairpin trimers, demonstrating the feasibility of bCHA for in situ imaging of intracellular miRNAs with enhanced signals. Flow cytometry analysis was further carried out (Fig. 5c and S7 †). Compared with MCF-7 cells treated with either H1 or three hairpin monomers (H1, H2 and H3), the hairpin trimer-transfected MCF-7 cells showed a signicantly enhanced uorescence signal, which was well consistent with the confocal microscopy results.</p><p>To further demonstrate the effectivity of bCHA, control experiments were performed in which MCF-7 cells were pretreated with miR-155 mimics and the miR-155 inhibitor, respectively, and MCF-7 cells without treatment acted as the control group (Fig. 6). As anticipated, no uorescence readout was observed by transfecting the anti-miRNA antisense inhibitor oligonucleotide because it can bring down the content of intracellular miR-155. In contrast, MCF-7 cells treated with miR-155 mimics to imitate the high expression of miRNA-155 showed much more intense green uorescence than the untreated cells. It was clearly demonstrated that the uorescence readout of the bCHA system was closely related to the miR-155 concentration in living cells, and the signal increased with increasing miR-155 concentration.</p><p>To investigate the capacity of the bCHA strategy to evaluate intracellular miRNA expression levels in different live cells, four types of cells, including normal human hepatocytes (L-02), human cervical cancer cells (HeLa), and breast cancer cells (MCF-7 and MDA-MB-231) were respectively transfected with hairpin trimers with identical concentrations (200 nM) at 37 C for 4 h (Fig. 7). From Fig. 7, it can be seen that the expressions of miR-155 in different cell lines are various. Because the expression level of miR-155 in normal L-02 cells is very low, 45 the uorescence signal is emerged hardly in L-02 cells. In contrast, the uorescence signals can be readily observed in cancer cells since miR-155 is overexpressed in cancerous processes. 46 In addition, MCF-7 and MDA-MB-231 cells show stronger uorescence intensities than HeLa cells, which is in accordance with previous reports that the expression level of miR-155 is higher in MCF-7 and MDA-MB-231 cells than in HeLa cells. 47,48 Moreover, the bCHA system can be applied as a general platform for the detection of other miRNAs, such as miR-21 (Fig. S8 †). It has been proven that miR-21 is an oncogene which is overexpressed in many cancers, such as breast cancer, lung cancer and so on. 49,50 Compared with the uorescence signal induced by miR-155 in MCF-7 cells under the same conditions (CLSM imaging of MCF-7 cells in Fig. 7), a stronger uorescence signal could be observed because the expression level of miR-21 is higher than that of miR-155 in MCF -7 cells. 51,52 In addition, traditional CHA and direct FISH are also performed in which bCHA exhibits a stronger uorescence signal than CHA and direct FISH, demonstrating the proposed bCHA strategy can be used as a general platform for detecting various miRNA targets with high sensitivity and selectivity.</p><!><p>In summary, we have successfully demonstrated an enzyme-free DNA catalytic device of bCHA for dynamic self-assembly of DNA dendrimers. In comparison with traditional CHA, the signal amplication efficiency of bCHA is signicantly improved by means of the "diffusion effect", achieving sensitive and selective in vitro detection of miRNAs and in situ imaging of miRNAs in live cells. Given the versatility of DNA, this dynamic DNA catalytic device can be readily used for amplied detection of a wide range of analytes through combining with aptamer recognition, such as proteins, small molecules and even tumor cells. Therefore, the proposed bCHA strategy holds great potential not only in the construction of complex DNA structures but also as a versatile amplication platform in the elds of biosensing and bioimaging.</p><!><p>The reaction pathways of the catalytic DNA device were conrmed using 8% acrylamide gel. Firstly, 2.7 mL of 30% acrylamide/bis-acrylamide gel solution (29 : 1), 1 mL of 10Â TAE buffer, 90 mL of 10% ammonium persulfate (APS), 10 mL of N,N,N 0 ,N 0 -tetramethylethylenediamine (TEMED) and 6.2 mL of double-distilled deionized ultrapure water were mixed to prepare the hydrogel. Aer polymerization for 30 min at room temperature, the gel was soaked in 1Â TAE buffer (pH 8.0). Subsequently, 12 mL of each sample was mixed with 2 mL of 10Â loading buffer and added to the resulting 8% native polyacrylamide gel for electrophoresis. The PAGE was run at the voltage of 170 V for 5 min and 110 V for about 45 min. Then, the gels were stained with diluted 4S Red Plus (Shanghai Sangon Biotech, China) for 40 min at room temperature. Finally, the images of the stained gels were recorded using a Tanon 2500R gel imaging system (Shanghai, China).</p><!><p>For microscope imaging, 2 mL of each annealed H1, H2 and H3 (10 mM for each) were added to 6 mL of the as-prepared Yscaffold DNA, resulting in the formation of hairpin trimers aer reaction at 25 C for 1 h. The hairpin trimers as the reaction precursor were further mixed with an isometric volume of the initiator (0.1 mM), followed by incubation at 25 C for 1.5 h. The resultant products were washed by centrifugation at 10 000 rpm for 3 min with double-distilled deionized ultrapure water. The washing step was repeated three times to remove salt ions in solution. Then, 10 mL of the sample was dropped onto the glass slides. Finally, the images were taken on a microscope (Leica DM4 P, Germany) in transmission mode.</p><!><p>The size distribution and zeta potential of the hairpin trimers and DNA dendrimers were measured on a Zetasizer Nano Series ZEN3700 (Malvern Instruments, UK). The DNA dendrimers were prepared according to the method mentioned above, which were diluted to 700 mL with double-distilled deionized ultrapure water for measurement.</p><p>Fluorescence monitoring 2 mL of the initiator with different concentrations was rapidly mixed with 12 mL of hairpin trimers (the preparation method was the same as mentioned above) and 26 mL of TE buffer. The real-time uorescence intensity was recorded immediately using a LineGene 4800 Real-Time detection system (Hangzhou, China) with intervals of 30 s. And the reaction was performed at 37 C for 6 h.</p><p>Cell culture MCF-7 cells, HeLa cells, L-02 cells and MDA-MB-231 cells were all cultured in DMEM supplemented with 10% fetal calf serum, penicillin (100 mg mL ), and streptomycin (100 mg mL À1 ) in a humidied and 5% CO 2 incubator at 37 C. PBS buffer (0.01 M, pH 7.4) was used to wash cells.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Structural and biochemical studies of the glucuronoyl esterase OtCE15A illuminate its interaction with lignocellulosic components

Glucuronoyl esterases (GEs) catalyze the cleavage of ester linkages between lignin and glucuronic acid moieties on glucuronoxylan in plant biomass. As such, GEs represent promising biochemical tools in industrial processing of these recalcitrant resources. However, details on how GEs interact and catalyze degradation of their natural substrates are sparse, calling for thorough enzyme structure-function studies. Presented here is a structural and mechanistic investigation of the bacterial GE OtCE15A. GEs belong to the carbohydrate esterase family 15 (CE15), which is in turn part of the larger α/β-hydrolase superfamily. GEs contain a Ser-His-Asp/Glu catalytic triad, but the location of the catalytic acid in GEs has been shown to be variable, and OtCE15A possesses two putative catalytic acidic residues in the active site. Through site-directed mutagenesis, we demonstrate that these residues are functionally redundant, possibly indicating the evolutionary route toward new functionalities within the family. Structures determined with glucuronate, in both native and covalently bound intermediate states, and galacturonate provide insights into the catalytic mechanism of CE15. A structure of OtCE15A with the glucuronoxylooligosaccharide 23-(4-O-methyl-α-d-glucuronyl)-xylotriose (commonly referred to as XUX) shows that the enzyme can indeed interact with polysaccharides from the plant cell wall, and an additional structure with the disaccharide xylobiose revealed a surface binding site that could possibly indicate a recognition mechanism for long glucuronoxylan chains. Collectively, the results indicate that OtCE15A, and likely most of the CE15 family, can utilize esters of glucuronoxylooligosaccharides and support the proposal that these enzymes work on lignin-carbohydrate complexes in plant biomass.

structural_and_biochemical_studies_of_the_glucuronoyl_esterase_otce15a_illuminate_its_interaction_wi

Introduction<!>Kinetic characterization of catalytic residue substitutions<!><!>Catalytic OtCE15A variants in complex with GlcA and benzyl glucuronoate<!><!>Catalytic OtCE15A variants in complex with GlcA and benzyl glucuronoate<!><!>Catalytic OtCE15A variants in complex with GlcA and benzyl glucuronoate<!><!>Catalytic OtCE15A variants in complex with GlcA and benzyl glucuronoate<!>OtCE15A in complex with GalA<!><!>OtCE15A in complex with GalA<!><!>OtCE15A in complex with oligosaccharides<!><!>OtCE15A in complex with oligosaccharides<!>OtCE15A in complex with xylobiose<!><!>OtCE15A in complex with xylobiose<!>Discussion<!>Enzyme production and assays<!>Production of glucuronoxylan-derived oligosaccharides<!>Crystallization and ligand soaking<!>Structure determination and refinement<!>Intact protein MS<!>Author contributions<!>

<p>Glucuronyl esterases (GEs)4 are enzymes able to cleave ester linkages connecting lignin to glucuronoxylan in the plant cell wall. GEs are promising tools for improving biomass-processing technologies by reducing the recalcitrance of so-called lignin-carbohydrate complexes (LCCs) in lignocellulosic biomass (1). Since the characterization of the first fungal GE, StGE2 from Schizophyllum commune (2), GEs have now been identified in many biomass-degrading microbes including fungi and bacteria and are classified into carbohydrate esterase family 15 (CE15) in the carbohydrate-active enzymes database (CAZy; www.cazy.org (3)). Although great strides have been made in recent years to advance our understanding of GEs, little is known about their molecular interactions with substrates and products and about the nature of the biological substrates they target in the plant cell wall.</p><p>GEs belong to the α/β-hydrolase superfamily and possess a catalytic triad common with serine-type hydrolases. All of the CE15 members characterized to date exhibit glucuronoyl esterase activity on various model substrates. Activity on LCCs extracted from woody biomass has also been demonstrated in a few cases (4–6). In recent work, we have revealed that some bacterial CE15 members have more promiscuous substrate specificities, where certain enzymes are able to hydrolyze both glucuronoate and galacturonoate (GalA) esters (7). The first structurally and biochemically characterized CE15 members were of fungal origins, and only recently have bacterial CE15 members been investigated (7–11). The only GE protein structure currently deposited with a ligand is StGE2, a variant containing an alanine substitution of the catalytic serine, which is in complex with a methyl ester of the monosaccharide 4-O-methyl glucuronate (4-O-MeGlcA) (8). As GEs have been shown to act on LCCs, to liberate glucuronoxylan from lignin for further metabolism, the physiological substrate for GEs is most likely glucuronoxylan or glucuronoxylooligosaccharides rather than small 4-O-MeGlcA moieties (4–6). Our recent characterization of the bacterial GE TtCE15A from Teredinibacter turnerae showed that GEs are indeed able to interact with oligosaccharides (xylotriose appended with 4-O-MeGlcA) and that this interaction is mediated by key residues in the active site (11). However, direct molecular evidence of GE-xylan interactions are still lacking, and further structural information is needed.</p><p>Consistent with serine-type hydrolases, members of the CE15 family contain a Ser-His-Asp/Glu catalytic triad. However, recent characterizations of bacterial CE15 members have revealed how the location of acidic residue of the catalytic triad is not conserved among GEs. In fungal GEs, the catalytic acid is located in a noncanonical position relative to typical α/β-hydrolases, but in the structures of the bacterial CE15 members MZ0003, discovered in a marine arctic metagenome, and TtCE15A the putative acidic residue was located on the canonical loop (10, 11). In TtCE15A, substitution of its catalytic acid residue to alanine led to a >30-fold reduction in turnover rate, and, interestingly, full activity could not be rescued in the variant by introducing the acidic residue at the noncanonical position exhibited in fungal and many other bacterial GEs. Sequence analysis of CE15 has revealed that several members, such as OtCE15A from the soil bacterium Opitutus terrae, have acidic residues at both the canonical and noncanonical positions, raising questions regarding the identity of the catalytic acid in these enzymes (7). Additionally, the observation of CE15 members with acidic residues at both positions may implicate evolutionary transitions between the two positions that could affect interactions with substrates and/or products.</p><p>Here, we have investigated by mutagenesis the residues involved in catalysis and carbohydrate binding in the enzyme OtCE15A and, furthermore, present a series of structures of OtCE15A with different ligands, including monosaccharides and, for the first time in CE15, di- and oligosaccharides. We confirmed the importance of a Ser-His-Asp/Glu catalytic triad in the enzyme and showed that both of its putative acidic residues can play a role in substrate hydrolysis. We also determined structures of the enzyme with GlcA, in both native and covalently bound intermediate states, which give insights into the catalytic mechanism of the enzyme and the CE15 family as a whole. Attempts to trap the model substrate benzyl glucuronoate (BnzGlcA) in the active site were unsuccessful, although a structure was determined with BnzGlcA found in a site on the edge of the active site cleft that may indicate the route of the substrate prior to hydrolysis. We also determined a structure of OtCE15A in complex with GalA, and we show how this promiscuous activity is made possible in the enzyme. Finally, structures determined with the tetrasaccharide 23-(4-O-methyl-α-d-glucuronyl)-xylotriose and the disaccharide xylobiose showcase how the enzyme can indeed act on glucuronoxylan-derived fragments. Collectively, the results advance our understanding of the CE15 family as a whole and provide useful insights for further developing biochemical biomass conversion technologies.</p><!><p>The activity of OtCE15A and nine other bacterial CE15 members has previously been characterized on model substrates, laying the foundation for these mechanistic studies (7) (Table S1). All CE15 members contain a catalytic triad comprised of Ser-His-Glu/Asp, as found in other serine-type hydrolases. Substitution of the catalytic residues in many serine-type hydrolases has resulted in significantly compromised but detectable activity in several enzyme variants (12, 13). Here, we have quantitatively assessed the effects following substitution of all catalytic residues of the CE15 enzyme OtCE15A using BnzGlcA as a model substrate (Table 1). Substitution of either the catalytic serine (Ser-267) or histidine (His-408) with alanine significantly compromised the OtCE15A turnover rate (kcat), reducing the rate by 17,000- and 1,700-fold, respectively. Compared with the TtCE15A S281A variant, where the kcat only decreased 370-fold (11), the S267A variant of OtCE15A was dramatically crippled. OtCE15A is an interesting member of CE15 and the α/β-hydrolase superfamily in that it features acidic residues at both the canonical and noncanonical positions (Glu-290 and Asp-356) (Fig. 1). Previous investigations of TtCE15A showed how attempting to shift its single catalytic acid from the canonical to the noncanonical position resulted in a severely crippled enzyme regarding both kcat and Km (11). Intriguingly, substitution of either acidic residue in OtCE15A with alanine resulted in only a 1.5- or 3-fold decrease in kcat (Table 1), and only upon substitution of both acidic residues was the kcat decreased by a similar degree as that of the E374A variant of TtCE15A (100-fold versus 33-fold, respectively). The results collectively imply that whereas one of the residues may be the principle acidic residue in the catalytic mechanism, the other residue is functionally redundant.</p><!><p>Kinetic parameters of BnzGlcA esterase activity of the WT OtCE15A and alanine variants of its catalytic residues</p><p>Errors represent S.D. from triplicate experiments</p><p>Catalytic residues of OtCE15A and other CE15 members. Comparison of the catalytic triads of OtCE15A (PDB code 6GS0; A), TtCE15A from T. turnerae (PDB code 6HSW; B), and StGE2 from Thermothelomyces thermophila (previously Sporotrichum thermophile; PDB code 4G4G; C) shows alternate positions of the catalytic acid residue in TtCE15A and StGE2, whereas an acidic residue is present in both locations in OtCE15A. The methyl ester of 4-O-methyl glucuronoate determined in the structure of StGE2 (PDB code 4G4J) is shown in green sticks from structural alignment of the CE15 proteins.</p><!><p>To advance the understanding of the interactions between enzyme, substrates, and products in CE15, we pursued structures of OtCE15A, and its variants, in complex with various ligands. We determined the structure of the WT OtCE15A in complex with the product GlcA (Fig. 2A). Relative to the apo-structure previously determined, binding of GlcA resulted in minimal changes in the enzyme's structure (all atom root mean square deviation of 0.639 Å), and the binding of the uronic acid to OtCE15A is very similar to that seen in the structure of the fungal StGE2 (catalytic S213A variant) in complex with the methyl ester of 4-O-MeGlcA (Fig. 2B) (8). In OtCE15A, the GlcA is positioned by a series of hydrogen bonds: one between the C2 hydroxyl and Trp-358, two between the C2 and C3 hydroxyls with Glu-305, two between the C3 and C4 hydroxyls with Lys-271, and one between C4 hydroxyl and the catalytic serine (Ser-267). The C5 carboxylate is oriented similarly to that observed in the StGE2 complex structure and makes a hydrogen bond to the main-chain nitrogen of a conserved active-site arginine (Arg-268 in OtCE15A and Arg-214 in StGE2), which, as for most α/β-hydrolases, is likely to contribute to forming the oxyanion hole to stabilize the negatively charged transition state during catalysis. A notable difference from the StGE2 complex structure, however, is that the side chain of the conserved arginine in OtCE15A is oriented toward the glucuronic acid and makes two additional hydrogens bonds: one between O5 of the pyranose ring and one of the arginine's Nη atoms and one between the carboxylate and the arginine's Nϵ. Thus, this side chain almost certainly contributes to formation of the oxyanion hole. In all structurally characterized bacterial GEs, the arginine appears to be locked in place by a conserved aspartate (Asp-207 in OtCE15A), whereas the equivalent residue in the two solved fungal structures is a glutamine and results in the arginine side chain in those structures being rotated away from the uronic acid–binding site.</p><!><p>Glucuronate bound to OtCE15A. Binding of glucuronate to the WT OtCE15A (A; PDB code 6SYR) and S267A OtCE15A variant (C; showing both anomers of the carbohydrate; PDB code 6SYV) is similar to that of the methyl ester of 4-O-methyl glucuoronoate determined in the structure of StGE2 from T. thermophila (B; previously S. thermophile; PDB code 4G4G with the ligand taken from 4G4J by structural alignment). Notably, the side chain of the conserved active-site arginine is found rotated toward, and interacts with, the glucuronate molecule in the OtCE15A product ligated structures differently than in the StGE2 substrate ligated structure.</p><!><p>To investigate the substrate binding in OtCE15A, we sought to obtain complex structures of the catalytically impaired S267A enzyme variant with GlcA and the model substrate BnzGlcA, respectively. An S267A-GlcA complex structure was determined to high resolution (1.12 Å) and showed that in the absence of the catalytic serine, the glucuronate binds identically as in the WT protein (Fig. 2C). Notably, this high-resolution structure facilitated the observation of both glucuronate anomers being present. Despite several attempts, we were unable to trap the Michaelis complex with BnzGlcA in our experiments as, presumably, the activity of the S267A variant was still too high to preserve the intact substrate in the active site even in short soaks (as short as ∼5 s). However, we were able to obtain a structure with GlcA bound in both active sites (for this particular complex, a crystal form with two molecules in the asymmetric units was used) and an additional BnzGlcA molecule near one of the active sites (Fig. 3). The substrate molecule is located along the edge of the active site cleft, making only one hydrogen bond between its C3 hydroxyl and the carboxylate of Asp-207. Although making minimal interactions with the protein, its close proximity to the active site makes this interaction interesting, as it could indicate a mechanism for substrate recognition and a route into the active-site cleft.</p><!><p>Benzyl glucuronoate trapped on the surface of the S267A OtCE15A variant (PDB code 6T0E). Presumably, the cleavage rate was too fast to capture the Michaelis–Menten complex with benzyl glucuronoate over the short crystal soaking period (10 s) but allowed capture of the uncleaved substrate along the edge of the active site cleft ∼10 Å from the catalytic center (glucuronate portion in green and benzyl portion in magenta).</p><!><p>We also pursued a complex structure of a catalytic histidine mutant (H408A) with BnzGlcA. We determined the structure of the H408A variant in the absence of substrate and saw only minimal changes in the protein structure (Fig. 4A). As for the S267A variant, despite several attempts, we were unable to trap the Michaelis complex with BnzGlcA in the H408A variant. However, following a 5-s substrate soak, we were able to determine the structure of the product GlcA covalently bound to the catalytic serine (Ser-267) through the C5 carboxylate (Fig. 4B). All active-site residues in this complex structure, including the catalytic serine, are in equivalent positions as in the WT structures. However, the GlcA is slightly rotated along an axis between the C2 and C3, leading to the C6 moving 1.2 Å closer to the catalytic serine and enabling the linkage to the serine oxygen. The other C6 oxygen, now the carbonyl of the acyl intermediate, is still positioned by the conserved active site arginine and maintains its interactions with the residue through both its main-chain nitrogen and Nϵ atoms. To complete the esterase reaction, a water molecule, presumably from the bulk solvent, would come in and attack the linkage at the C6 position.</p><!><p>Trapping the glucuronate covalent intermediate in the OtCE15A H408A variant. Shown is the OtCE15A H408A variant in the absence (A; PDB code 6SZ0) and presence of benzyl glucuronoate (B; PDB code 6SZ4). Presumably, the acylation rate was too fast to capture the Michaelis–Menten complex with benzyl glucuronoate over the short crystal soaking period (5 s) but allowed capture of the acyl-enzyme intermediate with the glucuronate moiety covalently linked to the catalytic nucleophile Ser-267. In both structures, a water molecule, hydrogen-bonded to Asp-356, fills the void left from substitution of the catalytic histidine. The covalent serine-glucuronoyl adduct is shown with the density from an omit map, at 4σ, created in Phenix (39) by omitting GlcA and the Cα, Cβ, and Oγ of Ser-267. C, an alternate orientation of the serine-glucuronoyl adduct showing the linkage. D, mass spectrum of the OtCE15A H408A variant in the absence (blue) and presence of benzyl glucuronate (red) leads to the production of a new mass consistent with the glucuronate covalent intermediate.</p><!><p>This is the first structure of a trapped covalent intermediate in a CE15 member. The result was quite unexpected, as without the histidine, the catalytic serine is expected to be a poor nucleophile. In the WT protein, decomposition of the covalent intermediate is assumed to be quick because the substrate turnover rate is high and only noncovalently linked GlcA products have been observed in previously determined structures. To explore whether the covalent intermediate could be detected in solution with the H408A variant and was not an artifact of crystallization, we determined the mass of the protein using intact-protein MS, in the presence and absence of added BnzGlcA. In the absence of added substrate, the protein sample resulted in three prominent masses (45,888.0 ± 1.2, 46,065.1 ± 1.6, and 46,146.2 ± 1.6 Da), with the lowest mass closely resembling the expected mass of 45,889.38 of the protein lacking the N-terminal methionine (Fig. 4C). The heavier masses differ from the smallest by +178 and +258 Da and are consistent with acylation of the protein with gluconoyl and 6-phosphogluconoyl groups, respectively, similar to those previously observed with other His-tagged proteins overexpressed in Escherichia coli (14). In the presence of BnzGlcA, a new signal of 46,240.5 ± 1.7 Da appears and is consistent with the glucuronidation of the gluconoyl-modified protein. Note that the mass change due to glucuronidation (+176) is too similar to the mass of the gluconoyl modification (+178) and prevents the detection of glucuronidation of the unmodified protein directly. Although the MS methodology is not quantitative, qualitatively we can conclude that not all enzyme molecules are glucuronidated, which is not highly surprising because the H408A enzyme variant retains some activity and thus detection of only a proportion of the covalent intermediate would be expected. Taken together, the detection of the covalent intermediate in solution indicates that the intermediate in the crystal structure is not an artifact and likely indicates that the rate of deacylation is significantly decreased in this enzyme variant, which enables its detection.</p><!><p>Previous characterizations of OtCE15A and other bacterial CE15 members revealed that some enzymes are able to use MeGalA as a substrate with specificity constants similar to those for MeGlcA (7). To elucidate how OtCE15A could facilitate this reaction, we soaked crystals of the S267A variant with MeGalA. Although we were unsuccessful in obtaining the Michaelis complex, we were able to determine a 1.34 Å structure of the OtCE15A in complex with the product of the reaction, GalA, and the configuration was quite distinct compared with that of GlcA. The distinction principally lies in the pyranose being flipped relative to the C6, which results in the anomeric hydroxyl group being bound in the same position as the C4 of GlcA in previous structures (Fig. 5). The β anomer of GalA has been modeled here with its hydroxyl interacting with Lys-271. Whereas the flipped pyranose results in the position of the C2 and C3 being swapped, the equatorial hydroxyl groups from both carbons are positioned similarly as in the nonflipped GlcA structure. The C4 hydroxyl group projects out of the cleft and possibly makes a weak/long-distance hydrogen bond with Trp-358 (3.5 Å). Last, the C6 carboxylate is positioned close to where the GlcA carboxylate is found in other structures, but in a different orientation, as one of the oxygen atoms forms hydrogen bonds with the Nϵ2 of His-408 and the other with one of Arg-268's Nη atoms.</p><!><p>Galacturonate bound to the OtCE15A S267A variant (PDB code 6SZO). Presumably, the cleavage rate was too fast to capture a Michaelis–Menten complex with methyl galacturonoate over the crystal soaking period (60 s) but allowed capture of the galacturonate product in the active site. The galacturonate is shown in yellow sticks, and a DMSO molecule, used as a solvent for the substrate, present in the oxyanion hole is shown in sticks.</p><!><p>The interaction between one of the GlcA carboxylate oxygens and Arg-268, through the Nϵ and main-chain amino group, is absent in the GalA structure, and instead hydrogen bonds are formed between these atoms and the carbonyl of a DMSO solvent molecule. Although it is possible that the positioning of the GalA C6 carboxylate observed here is an artifact of the S267A substitution, the S267A structure determined with GlcA still shows the C6 carboxylate positioned in the same way as in the WT enzyme. Thus, it is likely that the observed configuration is biologically relevant and facilitates catalysis. It is noteworthy that the residue Phe-141, previously proposed to interact with lignin-derived aromatics in bacterial CE15 members (7), is rotated away from the active site to accommodate the binding of DMSO and exposes a leucine (Leu-269) in the pocket. Interestingly, sequence analysis of CE15 members revealed a correlation between MeGalA activity and the presence of a Leu or small residue at the equivalent position of Leu-269 in OtCE15A (Fig. S1). CE15 members such as OtCE15D and CE15B from Solibacter usitatus (SuCE15B), which lack MeGalA activity, have a large residue at the equivalent position and could contribute to defining the substrate specificity. To explore this hypothesis, we determined the effects of substitution of the OtCE15A Leu-269 with tyrosine on the enzyme's MeGlcA and MeGalA activities (Table 2). Introduction of a tyrosine at this position did indeed perturb the enzyme's activity with MeGalA, increasing the Km 10-fold and decreasing the kcat 6-fold relative to its MeGlcA activity. However, the effects were not as pronounced as expected relative to the huge differences in MeGlcA versus MeGalA activity observed in CE15 homologs containing a similar residue at this position. Thus, these results suggest that the type of residue at this position contributes to MeGalA specificity in OtCE15A. However, the less pronounced effects of the residue substitution suggest that either other undefined determinants contribute to the lack of MeGalA activity in other CE15 members or introduction of a tyrosine at the Leu-269 position in OtCE15A is insufficient to replicate the same architecture found in other CE15 homologs.</p><!><p>The effect of the L269Y subsitution on the kinetic parameters of OtCE15A with model substrates</p><p>Esterase activity with methyl esters of GlcA and GalA are shown. Errors represent S.D. from triplicate experiments. Ksi, substrate inhibition constant. NA, not applicable.</p><!><p>Although the biological substrates of CE15 enzymes are believed to be glucuronoxylan ester–linked to lignin, how the enzymes interact with this substrate remains elusive. To investigate the interaction between OtCE15A and glucuronoxylan, we performed soaking experiments with various glucuronoxylan-derived oligosaccharides produced from partial enzymatic digestion of xylan. Following several soaking experiments, we were able to determine structures of OtCE15A with the tetra-saccharide 23-(4-O-methyl-α-d-glucuronyl)-xylotriose (commonly referred to as XUX), which is the largest ligand in a CE15 protein structure to date.</p><p>The 4-O-MeGlcA moiety of XUX binds in a very similar way as the single GlcA in the WT and S267A OtCE15A structures (Fig. 6), although with loss of a water molecule, normally hydrogen-bonding with the C4 hydroxyl. The binding of the 4-O-MeGlcA moiety is highly similar to that seen in the StGE2 structure complexed with 4-O-methyl-d-glucuronoate. Together, the observations indicate that OtCE15A does not discriminate between glucuronoxylans containing 4-O-methylated or nonmethylated GlcA residues in glucuronoxylan. This is a significant finding, as previous reports of fungal GEs have indicated that those enzymes require the 4-O-methyl substitution for activity (15–18), and thus this difference in substrate specificity could be a significant distinction across the CE15 family. However, more extensive comparative analyses between bacterial and fungal CE15 members are required to fully elucidate this difference in specificity.</p><!><p>OtCE15A in complex with the glucuronoxylan oligosaccharide XUX (PDB code 6T0I). The oligosaccharide, produced from beech xylan as described under "Experimental procedures," is shown with the 4-O-methyl-α-d-glucuronate moiety in green sticks and the xylotriose moiety in orange sticks.</p><!><p>In the XUX complex structure, besides interactions with the 4-O-MeGlcA, there is a lack of polar interactions between the protein and the oligosaccharide. Instead, the xylotriose portion of the oligosaccharide packs across the upper face of the cleft, burying 579 Å2 of solvent-accessible surface area and bridging across residues Val-313, Phe-314, Trp-358, and His-408. Previous docking simulations with OtCE15A and inhibition studies of TtCE15A with XUX have implicated the conserved active-site tryptophan (Trp-358 in OtCE15A) as a major contributor to the interactions with xylooligosaccharides (7, 11). Here, we can directly validate that Trp-358 contributes to binding of glucuronoxylooligosaccharides. A symmetry-related protein molecule is closely positioned to the active site, and the xylose moiety on the reducing end is found to interact with two residues of this symmetry-related protein molecule: Nϵ2 of His-56 with the O1 and O2 and the carbonyl of Gln-55 with the O2. The position of the symmetry mate would sterically restrict binding of longer gluronoxylooligosaccharides extended from the reducing end and may be slightly distorting the orientation of the xylan chain of XUX observed here. However, the close packing of the xylose units and the evidence from previous biochemical studies suggest that the binding position is biologically relevant. Future structural studies, potentially of other CE15 enzymes in complex with XUX or other glucuronoxylan-derived oligosaccharides, would be highly informative to possibly corroborate this result.</p><!><p>To gain further insight into substrate binding, we pursued soaking of corn cob xylan into OtCE15A. However, analyses of the corn cob xylan used (Sigma) revealed that it lacked any uronic acids (GlcA or 4-O-MeGlcA) and that instead of consisting of polysaccharides, it was comprised essentially of short xylooligosaccharide fragments dominated by xylobiose (data not shown). In light of this, the OtCE15A structure determined with two xylobiose molecules upon soaking with the mixture was not surprising, although it serendipitously reveals interesting features of OtCE15A (Fig. 7A).</p><!><p>OtCE15A in complex with xylobiose. Shown is the overall structure of OtCE15A, showing the two xylobiose-binding sites (PDB code 6SYU) highlighted in green and magenta (A) for the active site (B) and secondary site (C), respectively. The secondary site is ∼25 Å from the active site. D, a proposal of how the secondary xylobiose site could connect to the XUX found in the active site. Potential xylose moieties connecting the xylobiose observed in the second site to the XUX molecule observed in the active site are shown by orange hexagons. The region of the protein proposed to interact with lignin is colored in cyan.</p><!><p>One of the xylobiose molecules is found in the active site of the enzyme with a xylose moiety binding analogously to GlcA and XUX, except for the lack of the C5 carboxylate and the xylobiose being β-linked instead of the α-linked GlcA in XUX (Fig. 7B). The presence of xylobiose in the active site suggests that xylose or xylooligosaccharides might inhibit the enzyme reaction. Indeed, kinetic characterization revealed that xylose inhibits the BnzGlcA esterase reaction with a Ki of 48.1 mm (Fig. S2). Analogously, the presence of either 100 mm xylose or xylobiose reduced the enzymatic activity by ∼50%, suggesting a common mechanism of inhibition between the two molecules. Glucose, in concentrations up to 250 mm, does not inhibit the BnzGlcA esterase reaction (<10% inhibition), indicating a specificity for xylooligosaccharides. The inhibition by xylose is likely not biologically relevant however, as xylose concentrations would be unlikely to reach such levels during active cell wall degradation by microorganisms. However, the inhibition could have significant effects industrially, where large scale saccharification of biomass leads to high concentrations of simple sugars that could hamper the esterase reaction.</p><p>The second xylobiose is bound in a site located about 25 Å from the active site with the sugar packed between a short helical region and a loop comprised of residues 222–228 (Fig. 7C). The xylobiose is modeled such that it packs with the nonreducing end projecting into the cleft and the reducing end projecting away from the protein. The sugar makes only a few interactions with the protein, with only hydrogen bonds between the main-chain amino of Ala-223 and O2 of the nonreducing xylose residue and between the main-chain carbonyl of Ser-218 and O3 of reducing xylose residue. This loop region in other OtCE15A structures (residues 220–227) has large B-factors likely resulting from considerable movement of the loop. However, in the presence of xylobiose, the B-factors of this region are reduced significantly. The biological relevance of this binding is unclear, and its presence may be just an artifact of the soaking condition. However, an alternative hypothesis could be that the protein can interact with xylan chains not only in the active site but possibly also in other surface-binding sites similar to those found in other CAZymes (19). However, further investigations are needed to explore these possibilities.</p><!><p>The Michaelis complex with the BnzGlcA proved unobtainable by the methods tested here. A previous study of the CE15 enzyme MZ0003 reported similar difficulties in obtaining the equivalent complex (10). From the ligand complex structures determined here, it has become evident that the conserved arginine in the CE15 family likely makes significant contributions to catalysis by not only positioning the substrate carboxyl group, but also potentially aiding catalysis by stabilizing the oxyanion intermediate (i.e. forming the oxyanion hole). This is most evident in the OtCE15A-H408A complex structure with the GlcA covalent intermediate, where the arginine still contributes to the positioning of the carbonyl group. Similar to other α/β-hydrolases, the CE15 members also share some similarity around the stabilization of the oxyanion, aided by the main-chain amide nitrogen at the end of the helical dipole that is proximal to the catalytic serine. However, an arginine residue is rarely found following the catalytic serine in other α/β-hydrolases, not even within the CE15 family's closest relatives, CE7 (comprising acetyl xylan esterases and cephalosporin-C deacetylases). Instead, a variety of other strategies are used across the α/β-hydrolase superfamily to stabilize the oxyanion intermediate. Most commonly utilized, and what is found in CE7, is a loop region with its main-chain amide nitrogen groups projecting toward the catalytic serine, which is positioned analogously to the CE15 conserved arginine side chain (20–23). We suggest, therefore, that the Arg side chain, although slightly differently positioned in the fungal and bacterial structures studied to date, contributes to the transition state stabilization in the catalytic mechanism, explaining its conservation in >95% (26 of 27) of characterized CE15 sequences. In the bacterial CE15 enzymes, the conserved arginine is kept in this position by interaction with an acidic residue not conserved among fungal CE15 members. In both OtCE15A and MZ0003, having the arginine in the active state likely aids in driving the forward cleavage reaction too efficiently to allow trapping of the Michalis complex even in the absence of the catalytic serine. In future endeavors, it would be highly interesting to explore not only the importance of this residue in GE-catalyzed reactions but also substitutions that could possibly enable attainment of Michaelis complexes.</p><p>The minimal effect of single substitutions of either potential acidic residue of the OtCE15A catalytic triad showed that these residues are functionally redundant. In CE15, most members carry either one of the acidic residues, and, given the nature of the protein fold and similarities within the family, it is unlikely that this is a case of convergent evolution. Instead, the presence of two functional acidic residues may indicate an evolutionary route toward new functionalities. While the acidic residue of the first characterized α/β-hydrolase superfamily members was found to be at the position equivalent to the OtCE15A Glu-290 (20), more recent investigations of α/β-hydrolase superfamily members have additionally observed the acidic residues at the noncanonical position equivalent to the OtCE15A Asp-356 (24–26). In TtCE15A, which possesses a single catalytic acid, a switch between the two positions did not yield an enzyme with WT activity, and its active site may have adopted a clear specialized configuration (11). Thus, the double acidic residues of OtCE15A may, in contrast, be a state midway between the two observed putatively specialized locations and CE15 enzyme functionalities.</p><p>As for other serine α/β-hydrolases, the reaction mechanism of glucuronoyl esterases proceeds through an acyl-enzyme intermediate. The rate-limiting step of the two-step mechanism varies among serine α/β-hydrolases and can be affected by the substrate or biochemical conditions utilized (27). For OtCE15A and other bacterial CE15 enzymes characterized to date (7), a relatively consistent kcat when utilizing different esters of GlcA would suggest that it is the deacylation step that is rate-determining in these enzymes. The absence of an acyl-enzyme intermediate in crystallographic studies with the WT OtCE15A indicates that the deacylation rate is too rapid to observe the intermediate on the time scales utilized. However, upon substitution of the catalytic histidine, the detection of the acyl-enzyme by MS and crystallography in addition to the decrease in Km for GlcA substrates fits well with the accumulation of the covalent intermediate if breakdown of the intermediate is rate-limiting, as has been analogously observed with glycosidase variants (28, 29). Presumably then, the active site architecture, with the oxyanion hole priming substrate for nucleophilic attack, is elegantly constructed for rapid scission of the ester linkage, even when members of the catalytic triad are absent.</p><p>The GlcA moieties of glucuronoxylan are not always methylated, and the ratio of their etherification likely varies, depending on a host of factors, such as species, tissues, cell type, etc. (30–33). Whereas several reports have suggested that the 4-O-methyl substitution is crucial for activity among fungal CE15 enzymes (15–18), its requirement for activity has not been observed among the bacterial members characterized to date (7, 11). Structures of the OtCE15A enzyme with GlcA and 4-O-MeGlcA, as a part of XUX, determined here reveal that the position and interactions with O4 of the bound sugar are the same as those observed in the StGE2 (8). However, in the GlcA complex structures, a water molecule is commonly found filling the void left by the absence of methyl substituent and makes a hydrogen bond to the C4 hydroxyl. In fact, there is more space in this corner of the cleft to accommodate potentially a larger substitution at the C4 position, such as an acetylation. However, to the best of our knowledge, no such substitutions occur in nature. Taken together, the results indicate that the OtCE15A (and likely many other CE15 enzymes) is versatile and can utilize both methylated and nonmethylated GlcA substrates in addition to substrates with or without extended carbohydrate portions such as found in glucuronoxylan in plant biomass. OtCE15A can also utilize GalA esters as substrates, unique to a subset of CE15 members, and we showed that it accomplishes this by binding the sugar in a flipped orientation, which to the best of our knowledge is the first time a similar occurrence with carbohydrate active enzymes has been observed.</p><p>In this work, we have determined several ligand complex structures with OtCE15A to shed light on the catalytic mechanism and how the CE15 enzymes interact with the carbohydrate portions of their complex substrates. Our structure of OtCE15A with XUX is the first structure of a CE15 protein with a carbohydrate larger than a monosaccharide. The structures determined with BnzGlcA, found in a site close to the active site, and xylobiose, with the sugar found in a secondary site ∼25 Å from the active site, could indicate sites on the enzyme for interactions with longer glucuronoxylooligosaccharides (Fig. 7D). It remains elusive whether, and how, these enzymes may interact with the lignin portion of their physiological substrates in the plant cell wall, which may be illuminated by further investigations.</p><!><p>Enzyme variants were created by site-specific mutagenesis by the QuikChange method using the primers listed in Table S2 (34). OtCE15A enzymes were recombinantly produced in E. coli BL21 (λDE3) and purified as described previously (7). Glucuronoyl esterase activity was assayed with BnzGlcA, MeGlcA, or MeGalA (Carbosynth) and monitored continuously with the K-URONIC kit (Megazyme) as reported previously (7). The xylose competitive inhibition constant was determined with BnzGlcA as the substrate with increasing xylose concentrations. Inhibition assays with xylose, xylobiose, and glucose were carried out with BnzGlcA as the substrate at concentrations of 3.5 mm (at the enzyme's Km) and at 350 μm (10-fold less than the Km). All kinetic data were fitted using GraphPad Prism 8.</p><!><p>The aldouronic acid XUX was produced using a GH30 xylanase from Bacteroides ovatus (BoGH30, locus tag BACOVA_03432), which was obtained by cloning, expressing, and purifying the protein as described previously (35). The gene was amplified by PCR using the primers listed in Table S2 and subsequently cloned into a modified pET-28a vector containing a cleavage site for tobacco etch virus protease in place of the native thrombin cleavage site (generously provided by N. Koropatkin, University of Michigan). The protein was produced by overexpression in E. coli BL21 (λDE3) and purified by Ni2+ immobilized metal affinity chromatography by standard procedures on an ÄKTA Explorer (GE Health Sciences). XUX was produced by BoGH30 digestion of beech xylan (Sigma-Aldrich). Overnight, room temperature digestion reactions (500 μl) were carried out in 25 mm sodium phosphate at pH 7 with 10 mg/ml beech xylan and 0.5 mg/ml purified BoGH30. The enzyme was removed by ultrafiltration through a 10-kDa Amicon spin filter, and the filtrate was dried by lyophilization.</p><!><p>Crystals of OtCE15A were prepared by sitting drop (0.3 μl drops) in MRC two-drop crystallization plates (Molecular Dimensions) with protein (at concentrations between 20 and 30 mg/ml) mixed with reservoir solutions in either a 3:1 or 1:1 ratio by aid of an Oryx 8 robot (Douglas Instruments). Crystals utilized for soaking were obtained directly from, or through slight optimization of, crystallization conditions from the JCSG+ or Morpheus crystal screens (Molecular Dimensions) (36, 37), most close to the originally identified crystallization conditions (7). The final crystallization conditions for each data set obtained are summarized in Table S3.</p><p>Solutions utilized for soaking experiments with BnzGlcA or MeGalA (Carbosynth) were made by mixing the mother liquor with a saturated solution of substrate, prepared in DMSO. Crystals were then extracted and soaked in 1 μl of the soaking solution for varying time periods before being flash-frozen in liquid nitrogen. The resulting data sets published here had the following soaking conditions: OtCE15A-S267A-BnzGlcA complex was achieved by soaking for 10 s, OtCE15A-S267A-GalA complex was achieved by soaking for 60 s, and the OtCE15A-H408A-GlcA complex was achieved by soaking for 5 s. Soaking of crystals with GlcA, XUX prepared from BoGH30 digestion of beech xylan, and xylobiose from corn cob xylan (Carbosynth) utilized saturated solutions of the compounds raised up in the mother liquor. Crystals were allowed to soak for at least 1 h before being flash-frozen in liquid nitrogen.</p><!><p>All of the data sets were processed with XDS (38), and the structures were determined in Phenix (39) by either rigid body refinement with Phenix Refine (40) when isomorphous with the published structure (PDB code 6GS0 (7)) or molecular replacement with Phaser using the same as search model in the case of structures OtCE15A-S267A-GalA (PDB code 6SZO) and OtCE15A-S267A-BnzGlcA (PDB code 6T0E) (41). Coot (42) and Phenix Refine were used in iterative cycles of manual and computational refinement. Where possible, the ligand restraint files were obtained from the CCP4 library (43). The BnzGlcA compound was created in PyMOL, and its restraints were created with Phenix eLBOW (44). The data collection, processing, and refinement statistics for all of the data sets can be found in Table S4. For the 6SYV and 6SYU data sets, although the overall completeness for the data sets is low, the data sets are >94% complete up to 1.3 and 1.6 Å, respectively. The less complete data in the higher-resolution shells still contribute to robust refinement and have been kept for this reason. The solvent-accessible surface area buried by the xylotriose portion of XUX was calculated in PyMOL by subtraction of area of the complex from the sum of the area of the protein and ligand separately (i.e. (Aprotein + Aligand) − Acomplex).</p><!><p>Observation of the covalent glucuronoyl-OtCE15A H408A intermediate in solution was achieved by analysis of a cleavage reaction by MS using an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific) equipped with the heated electrospray ion source. Purified enzyme was dialyzed into 5 mm NH4HCO3, pH 7, prior to utilization in the reaction. A reaction mixture of 20 mg/ml OtCE15A-H408A with 10 mm benzyl d-glucuronoate was mixed and left for 2 min before being quenched with 30% (v/v) methanol and 0.1% (v/v) formic acid. The quenched reaction mixture, containing ∼4 mg/ml protein, was analyzed via the direct infusion at 1 μl/min; alternatively, a protein sample without the added benzyl d-glucuronoate was analyzed to serve as the control. The samples were ionized in the positive mode at 3.0 kV, and analyzed in the Intact Protein mode using the low-resolution (15,000 target resolution) full MS scanning with five microscans in the precursor ranges 500–2000 or 1000–1200; alternatively, the high-resolution SIM scanning at 240,000 target resolution with 10 microscans and SIM isolation windows of 4, 6, and 12 was performed on the selected precursor ions. Higher-energy collision-induced dissociation spectra were recorded at 240,000 resolution and 25 normalized collision energy with 5 microscans in the range 100–2000 with the isolation window of 3.0 at the precursor ions with the m/z 1241, 1246, and 1251. Data were inspected using the Xcalibur Qual Browser viewer (Thermo Fisher Scientific); the high-resolution spectra were charge-deconvoluted using the Xtract feature in the Xcalibur to yield the monoisotopic masses of the proteoforms, and the low-resolution Orbitrap spectra were deconvoluted using the ESIprot online tool (45) to give the average molecular masses.</p><!><p>S. M., L. L. L., and J. L. conceptualization; S. M., J.-C. N. P., L. L. L., and J. L. data curation; S. M., L. L. L., and J. L. validation; S. M., J.-C. N. P., L. L. L., and J. L. investigation; S. M. visualization; S. M., J.-C. N. P., L. L. L., and J. L. methodology; S. M., L. L. L., and J. L. writing-original draft; S. M., L. L. L., and J. L. project administration; S. M., L. L. L., and J. L. writing-review and editing; L. L. L. and J. L. resources; L. L. L. and J. L. supervision; L. L. L. and J. L. funding acquisition.</p><!><p>The work performed at Chalmers University of Technology was supported by the Knut and Alice Wallenberg Foundation through the Wallenberg Wood Science Center. Funding for collaborative work between Chalmers University of Technology and Copenhagen University was provided by the Novo Nordisk Foundation (NNF17OC0027698, Biotechnology-based Synthesis and Production Research). Funding for synchrotron travels was provided in part by the Danish Ministry of Higher Education and Science through the Instrument Center DANSCATT. The authors declare that they have no conflicts of interest with the contents of this article.</p><p>This article contains Tables S1–S4 and Figs. S1 and S2.</p><p>glucuronoyl esterase</p><p>carbohydrate esterase family 15</p><p>glucuronate/glucuronic acid</p><p>galacturonate/galacturonic acid</p><p>benzyl glucuronoate</p><p>methyl glucuronoate</p><p>methyl galacturonoate</p><p>23-(4-O-methyl-α-d-glucuronyl)-xylotriose</p><p>lignin-carbohydrate complex</p><p>Protein Data Bank.</p>

PubMed Open Access

Controlling the rotation modes of hematite nanospindles by dynamic magnetic fields

The magnetic field-induced actuation of colloidal nanoparticles has enabled tremendous recent progress towards microrobots, suitable for a variety of applications including targeted drug delivery, environmental remediation or minimally invasive surgery.Further size reduction to the nanoscale requires enhanced control of orientation and locomotion to overcome dominating viscous properties.Here we demonstrate how the coherent precession of nanoscale hematite spindles can be controlled via dynamic magnetic field. Using time-resolved Small-Angle Scattering and optical transmission measurements, we reveal a clear frequency-dependent variation of orientation and rotation of an entire ensemble of hematite nanospindles. Our findings 1 are in line with the different motion mechanisms observed for much larger, micron sized elongated particles near surfaces. The different dynamic rotation modes promise hematite nanospindles as a suitable model system towards field-induced locomotion in nanoscale magnetic robots.

controlling_the_rotation_modes_of_hematite_nanospindles_by_dynamic_magnetic_fields

Introduction<!>Results and Discussion<!>Conclusion

<p>Field-driven actuation on magnetic particles builds the foundation of various intriguing applications, including self-propelling particles in active matter, 1,2 mixers in microfluidics, 3 and viscosity probes in nanorheology, 4 but also aspects based on structure formation, such as field-induced self-organization [5][6][7] and smart fluids. 8,9 Biological microorganisms such as magnetotactic bacteria are inspiring model systems for magnetic microswimmers 10 operating at low Reynolds numbers, but also large enough so that their movement and dynamics can be tracked by optical techniques. The development of artificial magnetically-driven micro-and nanorobots has received tremendous attention in the last few years, 2,11,12 leading to advanced applications including magnetic two-arm nanoswimmers 13 or the combination of magnetic hyperthermia and magnetically driven propulsion for local pollutant remediation. 14 Achieving a remotely controlled, sustained translational motion for active Brownian particles in a viscous fluid is a challenging endeavour. This is typically approached by advanced synthesis of complex, chiral structures, 15 such as helical structures for magnetically actuated propulsion in dynamic, rotating or oscillating magnetic fields. 16 Very recently, a rich variety of motion mechanisms has been achieved using achiral, elongated objects with perpendicular magnetization. [17][18][19] Even random shapes based on nanoparticle aggregates have been shown to succeed as fast magnetic micropropellers. 20 All these particles propel when stirred by a relatively weak rotating uniform magnetic field (of the order of a few mT). The motion mechanism is tunable from tumbling through precessing to rolling motion via the frequency of the rotating magnetic field, 19 ultimately fading into the step-out behavior associated with declining propulsion velocity at highest frequencies. 21 These examples emphasize the great potential of dynamic magnetic fields for the controlled locomotion of mesoscopic magnetic particles in a viscous medium and the design of magnetoresponsive soft matter.</p><p>If the particle size is reduced to the nanoscale, thermal effects dominate, and stochastic motion of the particles due to random collisions (i.e., Brownian motion) complicate a controlled steering of magnetic nanoparticles in viscous fluids. 22 One of the rare examples of successfully synthesized propellers with dimensions below 1 µm was demonstrated with carboncoated aggregates of nanoparticles involving a post-synthesis selection process. 23 Hematite nanospindles represent a peculiar case of anisometric nanoparticles that promise to progress magnetohydrodynamics to an even smaller length scale. Hematite nanospindles are achiral, elongated nanoparticles (i.e., particles with at least two dimensions between 1-100 nm) that intrinsically exhibit a magnetization perpendicular to the long axis. This geometry is similar to the microwires with artificially engineered perpendicular magnetization 17,19 and therefore promising for locomotion of nanoobjects in dynamic magnetic fields. As the particle moments align parallel with an applied magnetic field, the hematite nanospindles orient with their long spindle axis perpendicular to a static field direction. 24,25 Within this plane perpendicular to the field the spindle orientation fluctuates randomly. There are two different characteristic relaxation frequencies associated with (1) a rotation of the spindle along the long rotational axis and (2) a rotation along the minor axes.</p><p>Here we demonstrate that by application of a rotating magnetic field in a suitable frequency range, the dynamic reorientation of hematite nanospindles can be forced into a synchronized spinning. Using time-resolved small-angle X-ray scattering (SAXS), we reveal how the orientation of an ensemble of water-dispersed hematite nanospindles can be tuned between a coherent precession and a collinear alignment by suppression of one of the two distinct rotation directions. The time-resolution of stroboscopic SAXS provides information on the dynamic particle orientation while applying alternating or rotating magnetic field.</p><p>Our results are supported with complimentary optical transmission measurements and agree with theoretical estimates of the rotational diffusion constant. The observations demonstrate that hematite nanospindle hold out the key features for future application as nanopropellers.</p><!><p>To achieve well-separated relaxation time scales, a large aspect ratio of the hematite spindles is required. We therefore synthesized hematite nanospindles according to the hydrolysis method developed by Matijević and co-workers that allows to tune the aspect ratio. 26 TEM analysis reveals an average diameter of 51.5 nm and a particle length of 374 nm along with normal size distributions in the range of 13-20%, corresponding to an aspect ratio of around 7.3 (Figure S1). Small-angle X-ray scattering (SAXS) of the colloidal suspension of nanospindles in water, performed at the instrument ID13 (ESRF), confirms the average particle diameter of 49.9 nm with an intermediate lognormal size distribution of 9.6% (Figure S5). The quasi-static magnetization measurement of the colloidal suspension further confirms the weakly ferromagnetic behavior of hematite above the Morin transition by the pseudo-superparamagnetic field dependence typically observed for magnetically blocked nanoparticles in dispersion (Figure S2). Refinement of the Langevin behavior reveals an integral nanoparticle moment of 7.643 •10 −19 J/T, corresponding to 82414(705) µ B . Along with the morphological particle volume of 5.19 •10 −22 m 3 as determined from TEM and SAXS analysis, a spontaneous magnetization of 1473 A/m is derived. The obtained spontaneous magnetization represents only 74% of the bulk value for hematite of ∼ 2000 A/m, 27 in agreement with earlier reports. 24,28 From this follows that the particles are not interacting and hence can freely rotate in suspension when applying external magnetic fields.</p><p>The anisotropy of the relaxation frequencies is confirmed by depolarized dynamic light scattering (DDLS, Fig. S3) and AC magnetic susceptometry (ACMS, Fig. S4). The rotational diffusion constant D R = 149(7) s −1 derived from DDLS analysis agrees well with the theoretical estimate of 179 s −1 for an ellipsoid of revolution of the same dimensions 29,30 and corresponds to a characteristic frequency of ν ⊥ = D R /π = 47(2) Hz. In contrast, ACMS reveals a characteristic frequency of ν ACMS = 278 Hz. The strong difference between these characteristic frequencies highlights the different mechanisms probed by both techniques.</p><p>Whereas DDLS is sensitive to the orientational diffusion of the particles in dilute dispersion, and hence can only sense the rotation around the minor spindle axis, ACMS probes the fieldinduced orientation of the spindle magnetization, including contributions of both rotation around the minor and principal axes. The characteristic frequency for rotation around the principal spindle axis is therefore not unambiguously accessible from ACMS, and will lie well beyond ν ACMS = 278 Hz. The significant difference between the characteristic frequencies for rotation around principal and minor spindle axes is an important prerequisite for a tunable motion control: we expect that for a magnetic field rotating with a frequency between both characteristic frequencies, a transition between coherent precession and synchronized spinning of nanospindles in dispersion is achievable. 31 Small-angle scattering probes nanoscale inhomogeneities with suitable spatial resolution to address the orientation distribution of a nanoparticle ensemble, 25,32,33 whereas timeresolved approaches give versatile opportunities to study in-situ nanoparticle ensemble dynamics. [34][35][36] Stroboscopic SAXS provides the necessary time resolution to monitor changes in the orientation distribution near the characteristic frequencies. We therefore performed time-resolved SAXS at the microfocus beamline ID13 (ESRF) to monitor the dynamic fielddependent orientation of hematite spindles driven by a custom-made set of Helmholtz coils.</p><p>The two Helmholtz coils can each generate alternating magnetic fields, and together a magnetic field rotating in the horizontal plane when both applied fields have the same amplitude and frequency with a 90°phase shift (Fig. 1a). The magnetic field period was divided into 20 frames by synchronizing the coil setup with the detector to obtain the time-resolved scattering patterns as shown in Figure 1f. The Maxipix detector allowed to measure stroboscopically up to 300 Hz. To emphasize the scattering anisotropy caused by the particle alignment in the applied field, all the following scattering images will be the difference pattern with respect to the isotropic scattering pattern in zero field (see Fig. S6). At low frequencies of 25 Hz, where the moments of the entire nanospindle ensemble follow the applied field, a periodic variation of the anisotropic scattering intensities is observed for both alternating and rotating magnetic fields (Fig. 2, full period shown in Fig. S7). In alternating magnetic field, the time-resolved variation of scattering intensities indicates a dynamic interplay of order and disorder. Whereas the SAXS intensity is isotropic at times near the zero-field condition (1/2 π and 3/2 π), corresponding to the random nanoparticle orientation in the absence of a magnetic field, a clear scattering anisotropy is observed at maximum field of 10 mT (0 and π). This scattering anisotropy results from the orientation of the spindles perpendicular to the inducing field, where the degree of alignment corresponds well to the Langevin parameter of 1.85, estimated for the integral nanospindle moment in the maximum applied field of 10 mT. We confirm this by computing the expected scattering pattern for a spindle ensemble using the spindle dimensions, integral particle moment, and average applied field for each frame according to the Boltzmann statistics of the particle distribution. 25 As shown in Fig. 2, the computed scattering pattern is in excellent agreement with the measured pattern. In case of a rotating magnetic field of 10 mT, the easy magnetic axes of the nanospindles will maintain their orientation towards the applied field and the nanoparticle ensemble may fulfill a complete turn within one period of the applied field as long as thermal motion and fluid friction are subsidiary effects. We identify this behavior in low frequency rotating magnetic field as coherent precession: the spindle ensemble fulfills precession around the field normal with a coherent phase behavior, albeit different precession angles. The difference between the two cases of alternating and rotating magnetic fields becomes very clear at the 1/2 π and 3/2 π time frames. In these time frames the applied rotating field is oriented parallel to the X-ray beam, resulting in isotropic scattering patterns. However, the difference of the scattering intensities against the zero-field state is negative. The computed scattering pattern (Fig. 2) confirms that the nanospindle ensemble is oriented parallel to the detector plane, whereas for the alternating field these time frames correspond to an isotropic, disordered ensemble at nearly zero field and hence vanishing difference scattering intensities. The evolution of difference scattering patterns with increasing frequency for both the alternating and rotating field (Fig. 3) reveals how the time-dependent fluctuation of the scattering intensities disappears, while the scattering anisotropy remains. This is a clear signal of a transition from the dynamic particle reorientation observed at low frequency towards a confined particle arrangement. A more quantitative picture is established by analysis of the time-and frequency-dependent scattering anisotropy of the two field configurations (Fig. 4a and 4b), derived as the difference between scattering intensity in horizontal and vertical directions (see SI). Whereas in the low frequency case (25 Hz) a clear time-resolved variation between maximum and vanishing scattering anisotropies is evident, the increasing magnetic field frequency is accompanied with a significant phase lag of the scattering anisotropy. This is a strong indication that there is a dissipative process acting such that the nanospindles cannot follow the dynamic magnetic field anymore at elevated frequencies.</p><p>The time-dependent amplitude in scattering anisotropy decreases, corresponding to a more and more static orientation of the ensemble of nanospindles. However, there is a significant scattering anisotropy even at the highest investigated stroboscopic frequency of 300 Hz at all times. This indicates that the average orientation of a significant portion of the nanospindle ensemble is not isotropic.</p><p>For higher frequencies beyond 300 Hz, only time-averaged scattering anisotropies, corresponding to the dotted lines in Fig. 4a and b, are accessible from time-averaged SAXS data. Over the complete frequency range, these illustrate the transitions between different types of collective motion (Fig. 4c). A maximal scattering anisotropy occurs for 150-200 Hz, i.e. in between the characteristic frequencies for rotation around the minor axis (47 Hz as determined from DDLS) and principal axis (beyond 278 Hz as estimated from ACMS and DDLS). In this frequency range, rotation around the principal axis is still allowed while rotation around the minor axis is inhibited. Beyond the characteristic frequencies for rotation around both principal and minor axes, the spindles do not follow the field variation anymore. Consequently, the scattering anisotropy decreases continuously, indicating an increasingly isotropic orientation of the nanoparticle ensemble.</p><p>Despite the similar behavior of the scattering anisotropy with dynamic field frequency, a different spindle orientation distribution for alternating and rotating magnetic fields at intermediate frequency is inferred from the scattering intensities shown in Fig. 3b. The differential scattering patterns correspond well to those computed for orientation distributions with the long spindle axis either confined to the plane perpendicular to the alternating magnetic field or to the direction perpendicular to the rotating field plane (Fig. 3b). In case of the alternating field, the time-independent but anisotropic scattering intensity indicates that the spindle long axes stabilize permanently in the plane perpendicular to the field direction. We understand this such that beyond the characteristic frequency for rotation around the minor axis, the average field-induced angular moment becomes larger than the disordering Brownian momentum. In effect, the spindles become confined in the plane perpendicular to the field and fulfill random rotation on this 2D plane. 37 In the rotating case, on the other hand, a particle experiences a constant torque produced by the rotating magnetic field that increases with frequency and eventually becomes significantly larger than Brownian random fluctuation within the 2D plane. A self-stabilizing rotational motion is favored as the viscous friction is reduced in a rotation around the long axis as compared to precessing motion involving rotation around the short axis. As a result, the spindle long axis stabilizes permanently in the direction perpendicular to the rotating field plane such that the magnetic moments can follow the rotating field on the shortest path of least action. We understand this as a synchronized spinning: the ensemble of collinearly aligned nanospindles rotates synchronously around their major spindle axes. The field-induced, frequency-dependent reorientation variation observed by time-resolved SAXS is strongly supported by optical transmission measurements (Fig. 5). The optical transmission of linearly polarized laser light through a dilute suspension of elongated nanoparticles depends directly on the relative orientation of laser light polarization and principal nanoparticle axis. For hematite nanospindles in a static magnetic field, an increase in optical transmission with applied static field parallel to the polarization direction and a decrease in optical transmission for a magnetic field applied perpendicular to the polarization direction is consequently observed (Fig. 5a). The time-resolved optical transmission recorded in rotating magnetic field of 25 Hz (Fig. 5b) oscillates exactly between the maximum and minimum static transmission, confirming that the entire nanoparticle ensemble follows the applied field. Similarly, in alternating magnetic field of 25 Hz (Fig. 5c) the timeresolved optical transmission oscillates between the transmission extrema and 1, indicating considerable orientation of the nanospindles in the maximum applied field and isotropic orientation in zero field. With increasing frequency of both rotating and alternating magnetic field (Fig. 5d), the full orientational order of the static or nearly-static case is not reached anymore. This is indicated by the decrease of the time-resolved amplitudes as well as by the center of the relative optical transmission approaching 1. However, the time-averaged anisotropy remains high, so that the full rotation amplitudes move above the isotropic case (I/I 0 = 1, grey line in Fig. 5d), indicating that a new, ordered state is achieved. The baseline of the rotation amplitude above 1 indicates that in the characteristic frequency range (with a maximum at 200-250 Hz), a significant portion of the spindles must be aligned perpendicular to the polarization direction at all times, which can only be the case if the spindles are aligned perpendicular to the rotating field plane. Likewise, the oscillation amplitudes in the alternating field do not reach the fully isotropic state at elevated frequencies, supporting the anisotropic nanospindle orientation observed with SAXS.</p><p>To summarize the response of the nanospindle ensemble in rotating fields: at low frequencies below the characteristic relaxation frequencies, the nanospindles follow the magnetic field and remain quasi-statically oriented with their major axis perpendicular to the inducing magnetic field, corresponding to coherent precession around the field normal. For intermediate magnetic field frequencies between the two relaxation time scales, rotation around the minor particle axis becomes suppressed, resulting in a decreasing precession angle. In consequence, the particles are driven into a collinearly aligned orientation of the major particle axis with synchronized spinning around the normal to the rotation plane. At high frequencies beyond the characteristic frequencies of rotation around both axes, the spindle ensemble disorients toward isotropic disorder.</p><!><p>We have elucidated the frequency-dependent reorientation behavior of hematite nanospindles in dynamic magnetic fields. The study emphasizes the potential of dynamic fields to control the rotation modes of shape anisotropic colloidal magnetic nanoparticles with perpendicular magnetic anisotropy.</p><p>Stroboscopic SAXS resolves signatures of different types of motion with a clear enhancement of the particle orientation in the intermediate frequency range between the characteristic relaxation time scales. The orientation behavior strikingly differs between alternating or rotating magnetic field. Time-resolved SAXS is a valuable tool to investigate this type of dynamic self-organization in-situ towards nearly collinear alignment of nanospindles perpendicular to the rotating magnetic field. The peculiar behavior in rotating magnetic field from coherent precession to synchronized spinning is understood similar to the frequency dependent variation of motion mechanisms of individual microwires near a surface boundary, ranging from tumbling and precessing to a rolling motion with increasing frequency. 19 With further increasing frequency, the effective field that aligns the particle upwards reduces due to the increasing phase lag of the spindle magnetization towards the rotating magnetic field. For dynamic frequencies well above the characteristic frequencies for rotation around the major axis, the synchronized rotational motion of the spindle ensemble ceases. This corresponds well to the step-out behavior observed as a decay in propulsion velocity of helical objects in rotating field with increasing frequency. 21,38 The characteristic frequencies for rotational diffusion of hematite spindles are adjustable by variation of the spindle length and aspect ratio through synthetic considerations. This will enable direct tuning of the frequency range needed to control the different rotation modes. The ability to control the dynamic reorientation of large ensembles (in the order of 10 10 ) nanoscale magnetic particles establishes an important step towards field-driven actuation and locomotion. With this prerequisite, oriented locomotion of a swarm of nanoparticles may become accessible using complex magnetic field geometries, such as combined rotating and static magnetic fields. 39</p>

ChemRxiv

Insights into MiRNA Regulation of the Human Glycome

Glycosylation is an intricate process requiring the coordinated action of multiple proteins, including glycosyltransferases, glycosidases, sugar nucleotide transporters and trafficking proteins. Work by several groups points to a role for microRNA (miRNA) in controlling the levels of specific glycosyltransferases involved in cancer, neural migration and osteoblast formation. Recent work in our laboratory suggests that miRNA are a principal regulator of the glycome, translating genomic information into the glycocode through tuning of enzyme levels. Herein we overlay predicted miRNA regulation of glycosylation related genes (glycogenes) onto maps of the common N-linked and O-linked glycan biosynthetic pathways to identify key regulatory nodes of the glycome. Our analysis provides insights into glycan regulation and suggests that at the regulatory level, glycogenes are non-redundant.

insights_into_mirna_regulation_of_the_human_glycome

Introduction<!>Glycogene target analysis and pathway annotation<!>General Analysis of Glycogene Regulation<!>Predicted Regulatory Hubs in N-linked Glycosylation Pathway<!>Predicted Regulatory Hubs in O-linked Glycosylation Pathway<!>Predicted Regulatory Hubs Affecting Terminal Glycan Epitopes on both N- and O-linked Glycans<!>Summary

<p>The cell surface is coated with glycans, complex biopolymers that form a critical interface with the extracellular world and inform diverse processes from immune recognition to cancer metastasis. Glycosylation is an intricate process requiring the integrated action of multiple proteins, including glycosylation enzymes (glycosyltransferases and glycosidases), sugar nucleotide transporters and trafficking proteins, to synthesize discrete structures appended onto serines and threonines (O-linked) or asparagines (N-linked) on proteins or onto lipids. The glycome is highly regulated during embryogenesis [1,2] and defects in glycan biosynthesis cause congenital disorders, 64 of which have been identified to date [3]. Despite the importance of glycosylation, there is currently little understanding of how glycan biosynthesis is controlled. Alteration of mRNA levels of glycosylation-related genes (glycogenes) maps onto concomitant alterations in the glycome, arguing that regulation of glycogene transcripts is important, although a direct relationship is not always observed [1].</p><p>MicroRNA (miRNA) are short endogenous noncoding RNAs ~22 nts in length that can either promote mRNA degradation or inhibit translation, downregulating associated protein levels [4]. Recently, work by several groups has pointed to a role for microRNA in controlling glycosylation [5,6,7,8,9]. To date, seven human glycogenes (C1GALT1[6], MANEA [10], FUT4 [9], FUT8 [11], GALNT1 [8], GALNT7 [7,8] and NDST1 [5]) have been validated as miRNA targets. A role for miRNA as a major regulator of glycan biosynthesis has been suggested by work in C. elegans [12] and by unpublished results in human cell lines from our laboratory. Analysis of miRISC complexes during the developmental stages of C. elegans showed robust enrichment of glycogene transcripts associated with miRNA. Work in our laboratory using the NCI-60 cancer cell set found strong correlations between the glycome and miRNA expression levels and identified three new glycogene/miRNA interactions (in submission). Taken together, the data suggests that miRNA are a principal regulator of the glycome.</p><p>Identifying the regulatory relationship between miRNA and a target gene currently relies on target prediction analysis. Although miRNA can bind anywhere within an mRNA (5′-UTR, coding region or 3′-UTR), the majority of prediction analysis focuses on the 3′-UTR, which is widely regarded as the main site of miRNA action [4]. Algorithms such as miRanda, PicTar and TargetScan rely on a combination of the thermodynamic stability of the miRNA/gene interaction and factors such as target site conservation between species to identify and prioritize miRNA interaction partners [13,14]. A single miRNA can have hundreds of predicted targets and predictions have been used to identify regulatory networks for systems as diverse as cancer [15] and schizophrenia [16]. Genes with higher numbers of predicted miRNA binding sites show increased levels of repression, faster mRNA decay rates and increased evolutionary conservation [17,18,19]. Herein we overlay predicted miRNA regulation of glycogenes onto maps of the common glycan biosynthetic pathways to identify key regulatory nodes of the glycome. Our analysis provides insights into glycan regulation and shows that at the regulatory level, glycogenes are non-redundant.</p><!><p>The human miRNA target site miRSVR-miRanda prediction datasets for both conserved and non-conserved miRNAs with "good" miRSVR scores (miRSVR < −0.1) were downloaded from the latest release of microRNA.org (2010 August release) and combined to make a "total" dataset [20,21]. This dataset was then checked for duplicative entries using the built in unique function in R and checked against the original datasets. No duplications were observed. A comprehensive list of glycosylation related genes (glycogenes, 538 genes, 913 transcripts) was created based on Maupin et al [22], the Kyoto Encylopedia of Genes and Genomes (KEGG)[23] and Nairn et al [1]. This list includes trafficking proteins, glycosyltransferases, glycosidases, nucleotide sugar transporters and highly glycosylated proteins (mucins, cadherins, etc.) but excludes lectins (see Supplemental Table 1). For reference, 3′-UTR lengths were obtained from the UCSC genome browser (Build GRCh37/hg19) using the unique known gene ids for the transcripts [24]. The miRNA/glycogene target prediction data was extracted from the combined miRNA prediction dataset.</p><p>To obtain the number of total and unique miRNA/glycogene interactions we determined the frequency of each mirna/transcript interaction using the Table function in R. Summing the counts for all miRNA sites on a given transcript gave us the total hits for that glycogene (Total). For unique hits (Unique), we summed the number of unique miRNAs that interacted with a given transcript. The Total and Unique hit levels were then mapped in Cytoscape 3.0.1 [25] and overlaid onto the glycosylation pathways. For our analysis, we considered only validated mRNA sequences from the RefSeq database (designated by NM). Where no such transcript existed for the gene, the largest known transcript was used. Where more than one NM designated transcript existed for a single glycogene, the data for the transcript with the highest total number of miRNA sites were used in our pathway map. To identify highly targeted glycogenes, we first determined the average and standard deviation for the number of total hits of all genes in the dataset (Average = 131.8, Std. Dev.= 103.1). Glycogenes were then defined as "highly targeted" if their total hits were ≥ 235 (i.e. 1 standard deviation above the mean) [18,26].</p><!><p>Glycosylation patterns are known to be highly variable between species [27,28]. In contrast, there is high conservation among enzymes in glycosylation pathways, possibly driven by strong functional constraints [29]. This argues that the regulation of glycogenes by factors such as miRNA may be species specific, accounting for the variation in observed carbohydrate epitopes. Conservation of miRNA target sites across species is an important aspect of most target prediction algorithms. Mammalian-specific miRNA have fewer predicted conserved targets than do broadly conserved miRNA [30], arguing that species-specific regulation is not well represented in the subset of conserved target sites. However, when non-conserved sites are included in miRNA target prediction analysis, decreases in sensitivity and precision are observed, thus many analysis programs use a conservation filter [14]. In recent work, Betel et al introduced miRSVR, a new filter for miRanda predictions based on supervised learning from miRNA transfection datasets [21]. The use of miRSVR-miRanda identifies both conserved and non-conserved miRNA binding sites with improved accuracy. Thresholding miRanda predictions using a miRSVR score of −0.1 or better gives a prediction set with a reasonable probability of downregulation [21]. To study glycogene regulation, we created a dataset containing the conserved and nonconserved miRSVR-miRanda miRNA/target predictions with a miRSVR score of −0.1 or below. We then determined the total predicted number of miRNA binding sites within the 3′-UTR of an mRNA as a metric for probability of miRNA-mediated gene regulation [17,18]. Genes can be cooperatively regulated by multiple miRNAs [31,32]. The total number of predicted binding sites strongly correlates with repression levels and mRNA decay rates, irrespective of the prediction algorithm used and independent of the length of the 3′-UTR [17,18]. We observed no significant differences in the distribution of total binding sites for glycogenes compared to the entire gene set (Supplemental Figure 1).</p><p>Using this dataset, we defined a "highly regulated" glycogene subset, i.e. genes for which the total number of predicted miRNA binding sites is ≥ 235 (1 S.D. above the average for all genes, see Materials and Methods) [18,26]. A list of the top 10 most "highly regulated" glycogenes is given in Table 1. At the top of the list was CHSY3, a chondroitin sulfate synthase with an average length 3′-UTR (843 bp, Average = 1265 bp for all genes, St. Dev.= 1367). Chondroitin sulfate is a proteoglycan important in brain development [33] and recent work has shown that miRNA modulation of related chondroitin synthetase sqv-5, the C. elegans homologue of CHSY1 (another "highly regulated" gene, see Supplemental Table 1), is a critical regulator of neurodevelopment in worms. More than 70% of all miRNA are expressed in the brain and miRNA have a strong impact on brain development, suggesting a potential role for miRNA regulation of CHSY3 in this highly coordinated process [34].</p><p>To gain greater insight into regulatory hubs in glycan biosynthesis, we mapped our analysis of glycogene regulation onto the canonical N-linked, O-linked and terminal glycan biosynthetic routes. The results of this analysis are discussed in more detail in the following sections.</p><!><p>In N-linked glycosylation, a core Glc3Man9GlcNAc2-oligosaccharide is transferred onto select asparagines in a nascent polypeptide from a dolichol precursor by oligosaccharyltransferases (STT3A/B: catalytic subunits). This glycan is trimmed to Man9 and then elaborated by glycosidases and glycosyltransferases, giving rise to high mannose, hybrid and complex structures as shown in Figure 1. Glycogenes at several key points in the N-linked pathway are predicted as "highly regulated" hubs, including MAN1 genes, select MGAT genes and FUT8 (red asterisks, Figure 1). Similar results are observed when only "Unique" hits are considered (Supplemental Figure 2). The MAN1 gene family (MAN1A1, MAN1A2) encodes mannosidases that control trimming of high mannose structures to Man5, a required prerequisite for hybrid and complex epitopes. High mannose sugars are the dominant N-linked epitope on both embryonic and pluripotent human stem cells [35,36] and differentiating mouse stem cells show a loss of high mannose concomitant with increased levels of MAN1 transcripts [1], suggesting that their regulation is important in early embryogenesis. Work in our laboratory has validated MAN1A2 as a target of at least three miRNA, arguing that MAN1 transcripts are a hub for miRNA based regulation (unpublished results).</p><p>The MGAT genes encode a series of enzymes responsible for transferring N-acetylglucosamine (GlcNAc) onto core mannose residues to create complex branched structures. The branching patterns of N-glycans play a crucial role in cellular differentiation and altered branching patterns are associated with immune recognition and cancer [37,38]. The predicted miRNA regulation across the MGAT family is highly variable. MGAT2 and MGAT4A, which catalyze formation of biantennary and triantennary branched glycans, respectively, are "highly regulated" hubs. In contrast, MGAT5, which creates tetraantennary glycans essential in immunity, is not a major target of miRNA regulation despite an average 3′-UTR length (1550 bp). MGAT5 activity is exquisitely regulated by available UDP-GlcNAc levels, which can be tuned by the expression levels of upstream MGAT enzymes with higher affinity for the sugar nucleotide including MGAT2 [37]. This may negate the need to regulate MGAT5 through miRNA-mediated mechanisms.</p><p>The FUT8 gene encodes the fucosyltransferase which adds α-1,6 fucose onto the core GlcNAc of N-linked glycans. Alterations in core fucosylation have been linked to cancer and emphysema [11,39,40] and recent data points to a role in controlling TGFβ signaling [41]. Our analysis predicts that FUT8 is "highly regulated" by miRNA. Recently, FUT8 was shown to be a target of two miRNAs downregulated in hepatocarcinoma, a cancer associated with high levels of core fucose [11]. Taken together, the data suggest that miRNA regulation of FUT8 is a major mechanism for controlling levels of core fucosylation.</p><!><p>In contrast to N-glycans, canonical O-linked glycans have a single common sugar, α-linked N-acetylgalactosamine (GalNAc), which forms the core structure attached to serines or threonines. This glycan is then elaborated by a host of glycosyltransferases making more complex epitopes. As shown in Figure 2, multiple "highly regulated" genes are predicted by our analysis including several of the enzymes that initiate O-linked glycosylation (GALNTs), the core-2 synthesizing enzyme GCNT1, and the sialyltransferase ST6GALNAC3 (which synthesizes α-2,6-sialylGalNAc-α-Ser/Thr (sialylTn antigen)). The GALNT family is a large family of ~20 enzymes that transfer the core GalNAc residue onto serines and threonines in the polypeptide backbone. They have distinct but overlapping requirements for peptide sequence [42]. Little is known of the regulatory mechanisms controlling mRNA and protein levels of these enzymes, although dynamic changes in both have been observed. Based on our analysis, GALNTs display isoform dependent miRNA regulation. Several GALNT's are among the top 10 most "highly regulated" glycogenes, which is not due to a significantly larger 3′-UTR for these genes (GALNTs 1, 3 and 7, Table 1, Figure 2). Gaziel-Sovran et al identified both GALNT1 and GALNT7 as targets of miR-30b/d, miRNA associated with metastasis in melanoma [8]. GALNT7 was also found to be a target of miR-378, with a role in osteoblast differentiation [7], showing that multiple miRNA target GALNT7 in line with our analysis. Although no miRNA targeting GALNT3 have yet been identified, levels of this gene alter in response to inorganic phosphate, calcium and vitamin D, in line with the type of dynamic regulation that miRNA provide [42]. In contrast to the highly regulated GALNTs, there are multiple family members that are predicted to have very low levels of regulation (<60 predicted hits, GALNTs 5, 8, 9 and 14, Figure 2). This may be due to the length of the gene transcripts, which are all below the average (range 52–734 bases). The disparity in predicted miRNA-based regulation of these genes belies their presumed redundancy. Knockouts of GALNTs, including GALNT3, cause subtle phenotypes in mice, attributed to functional redundancy [2,42]. The presence of subtle phenotypes however argues that the redundancy is not total, this is primarily attributed at present to substrate specificity differences however differences in miRNA regulation of transcripts, such as those predicted by our analysis, may also play a role.</p><!><p>Both N- and O-linked glycans are elaborated with common terminal modifications. These include poly-N-acetyl lactosamine chains (poly-LacNAc) which can be Type I (β-1,3 linked) or Type II (β-1,4 linked, Figure 3A), sialic acids (Figure 3), blood groups and Lewis Antigens (Figure 4). Our analysis identifies isoform specific regulation of the genes involved in these complex biosynthetic pathways. Isoforms involved in both Type I and Type 2 polyLacNAc synthesis pathways that are "highly regulated" genes include the initiating galactosyltransferases B3GALT2 (Type 1), B4GALT4 and B4GALT6 (Type 2) and elaborating GlcNAc transferases (Type 2: B3GNT2, B3GNT5, Figure 3A). Only three sialyltransferases, ST6GALNAC3, ST6GAL2 (Figure 3A) and ST8SIA4 (Figure 3B) are predicted to be "highly regulated". Of these, ST8SIA4 (PST) is particularly interesting because it is one of two sialyltranferases that synthesize polysialic acid, a critical modification of the neural cell adhesion molecule (NCAM) in the brain. ST8SIA4 is expressed in adult brain and has recently been shown to play a role in dendritic cell maturation, while the other polysialic acid enzyme ST8SIA2 (STX) is only expressed in early stages of embryogenesis. The need to constantly modulate ST8SIA4 levels in maturing dendritic cells may explain why this gene is more regulated than the ST8SIA2 isoform [43]. Few of the genes involved in Lewis structure and blood group formation are predicted to be "highly regulated", with the exception of FUT4, an enzyme involved in Lewis x and Lewis y formation. FUT4, also known as CD15, is again one of the few known glycogene targets of miRNA [9].</p><!><p>MiRNA are relatively unexplored as regulators of the glycome. Our recent work has shown that these non-coding RNA play a critical role in controlling glycosylation. Overlaying our predicted miRNA/glycogene interaction levels onto the glycan biosynthetic pathways points to major regulatory hubs, including the early steps of both the N-linked (MAN1A1, MAN1A2) and O-linked (GALNTs) pathways. In line with our analysis, five of the seven glycogenes identified as miRNA targets to date are predicted to be "highly regulated" genes (GALNT1, GALNT7, FUT4, FUT8, MANEA). We found glycogene regulation to be isoform specific, with only some isoforms designated as "highly regulated" genes. This type of isoform-specific regulation may explain why, even when functionally redundant enzymes are present, knockouts show subtle phenotypes often in the brain (behaviour) or the immune system, where miRNA play important roles. Changes in miRNA may underlie the altered glycosylation observed in dynamic processes such as cancer metastasis and embryogenesis, opening new opportunities to unravel the glycocode.</p>

PubMed Author Manuscript

Parallel Synthesis of An Oligomeric Imidazole-4,5-dicarboxamide Library

A library of oligomeric compounds was synthesized based on the imidazole-4,5-dicarboxylic acid scaffold along with amino acid esters and chiral diamines derived from amino acids. The final compounds incorporate non-polar amino acids (Leu, Phe, Trp), polar amino acids (Ser, Asp, Arg), and neutral amino acids (Gly, Ala), and where designed to be useful in screening for inhibitors of protein-protein interactions. Many of the protected and deprotected oligomers show evidence of conformational isomers persistent at room temperature in aqueous solution. A total of 317 final oligomers, out of 441 targeted compounds, were obtained in high analytical purity and of sufficient quantity in order to submit them for high-throughput screening as part of the NIH Roadmap.

parallel_synthesis_of_an_oligomeric_imidazole-4,5-dicarboxamide_library

Introduction<!>Results and Discussion<!>Conclusion

<p>The design and preparation of compound libraries for application in high-throughput screening is a well-known approach to hit identification in drug discovery research.1,2 The library design criteria are generally target dependent, with the choice of scaffold or building blocks determined by considering known bioactive compounds or hypothesis or both.3-5</p><p>Protein-protein interactions (PPI) are significant events in signaling within and between cells, and as such are potential targets for intervention by small molecules in order to modulate or treat diseases related to these signals.6-10 The design of inhibitors for PPIs has, in the past, been considered intractable due to the size and flatness of the associating surfaces. Yet, most buried interfaces rely on "hot spots" that require relatively few residues in order to obtain the majority of the thermodynamic driving force for the PPI.11,12 Thus, targeting a PPI "hot spot" is a practical approach to reduce the overall size and molecular weight of a potential PPI inhibitor.</p><p>Good progress toward the design and discovery of inhibitors of PPIs has been reported in recent years by generating a suitable mimic of one of the two protein surfaces.13-18 In general these inhibitors mimic secondary structures, such as β-turns,3,10 β-strands,19 or an α-helix,9,10,20 in order to accurately display important residues or "hot spots" of the PPI in a proper orientation. This approach can yield compounds with drug-like or nearly drug-like features;21,22 therefore, the use of inhibitors of PPIs as therapeutic agents is anticipated.23</p><p>We have previously employed the imidazole-4,5-dicarboxylic acid scaffold in the design of CD81 proteomimetics that were based on the comparable distance between carbon atoms of the imidazole-4,5-dicarboxamide (I45DC) substituents with the spacing of side chains in a critical α-helix within the PPI.24,25 These first-generation oligomeric I45DCs were symmetric and utilized two L-amino acids as well as a N,N′-dialkylalkanamine in their design and synthesis.26 Selected oligomers were effective as inhibitors of the CD81-hepatitis C glycoprotein E2 interaction, thereby supporting our design hypothesis.24</p><p>The second-generation oligomeric I45DCs in this project likewise anticipate the distance between substituents on each I45DC to match the distance between side chains found along the length of an α-helix or adjacent along one side of a β-strand.25 The total of four amino acid side chains per oligomer in this design is expected to be a significant improvement and doubles the number of pharmacophoric side chains as compared with the first-generation oligomers. Although only a few amino acids are often involved in a PPI hot spot,11,12 we nonetheless reason the oligomers in this project have greatly improved odds of yielding inhibitors of PPIs when employed in high-throughput screening.</p><p>The number and type of amino acid building blocks that we employed for these oligomeric I45DCs was based on a compromise between those amino acids expected to be important in PPI hot spots and the number of compounds we could reasonably synthesize, purify, and characterize in parallel. Also guiding our selection was the knowledge that aromatic, polar, and ionic amino acid side chains were of equal or greater significance to hydrophobic interactions in many PPIs, such as those in antibody-antigen or enzyme-protein inhibitor interactions.27,28 The oligomeric design uses combinations of two ethylenediamines along with two L-amino acids. Two of the three ethylenediamines used are chiral with Ala and Leu side chains, and were synthesized from their L-amino acids. The seven L-amino acids we chose included two aromatic residues (Tp and Phe), two hydrophobic residues (Leu and Ala), two charged residues (Asp and Arg) and one polar residue (Ser). The monomeric I45DCs were also differentially protected in order to allow selective deprotection of the amino and carboxylic acid termini before coupling in parallel to create a maximum of 441 unique oligomeric I45DCs. A total of 317 of these pure oligomeric I45DCs have been characterized and were obtained in sufficient quantity for submission to the Molecular Library Small Molecule Repository (MLSMR) for use in high-throughput screening as part of the NIH Roadmap.</p><!><p>Ethylenediamine was mono-protected to yield 12{1}, as shown in Scheme 1, by following a literature procedure.29 This compound was further protected with a known procedure30 to give 11{1} and then selectively deprotected to give 6{1} as the free amine, thereby providing the two differentially monoprotected ethylenediamines, 6{1} and 12{1} needed for oligomer synthesis. The other chiral diamines used in this project were synthesized from L-amino acids bearing either N-Boc or N-Cbz protecting groups as shown in Table 1. Boc-L-amino acids, 1{2-3}, were the starting materials for the chiral diamines 6{2-3} as shown in Scheme 2. The amino acids 1{2-3} were converted to their respective methyl esters, 2{2-3}, by slight modification of a known procedure,31 converted to amides 3{2-3} with an NH4OH solution,32 and subsequently reduced to the chiral diamines 4{2-3} with BH3·S(CH3)2 in THF.33 These intermediates were not purified, but first protected with Cbz-Cl to give 5{2-3} following purification.30 Deprotection of the Boc group in 5{2-3} with CF3CO2H in CH2Cl2 yielded 6{2-3}. Likewise, Cbz-L-amino acids, 7{2-3}, were starting materials for the chiral diamines 12{2-3} as shown in Scheme 3. The synthesis again proceeded through methyl esters 8{2-3}, amides 9{2-3}, reduced intermediates 10{2-3}, and the differentially-protected chiral diamines 11{2-3}. Hydrogenation then produced the final chiral diamines 12{2-3} needed for oligomer synthesis.</p><p>The oligomeric design uses the two chiral, mono-protected diamine chemsets 6 and 12 that were synthesized from amino acid amides, along with the two L-amino acid chemsets 14 and 18. The two halves of the oligomers come from chemsets 16 and 20 that are independently synthesized with orthogonal protecting groups in order to allow selective deprotection of these monomeric building blocks (Scheme 4).</p><p>Synthesis of the monomeric building blocks begins with the pyrazine diacid chloride, 13, which is prepared from imidazole-4,5-dicarboxylic acid as previously reported.34 The amino acid ester-substituted pyrazine chemsets 15 and 19 were likewise prepared by following methods previously reported, generally giving good to excellent yields of product (Table 3).26,35</p><p>The monomeric building blocks with a Cbz-protected amino group, chemset 16, were prepared by reacting pyrazine chemset 15 with the Cbz-protected diamine chemset 6 in CH2Cl2 at room temperature from 5-120 hours. These products were purified by column chromatography with EtOAc/hexanes as the eluant. Product was not obtained for 16{2,7} and 16{3,7}. The reason for reagent failure as well as identification of the reaction product(s) for these two reactions was not done. These reactions were attempted more than once with the same results. Reaction yields for the remaining chemset compounds of 16 ranged from 30-80% and averaged 58%.</p><p>Likewise, monomeric building blocks with a benzyl ester-protecting group, chemset 20, were prepared by reacting pyrazine chemset 19 with the N-Boc protected diamine chemset 12 in CH2Cl2 at room temperature from 1-72 hours. These products were likewise purified by column chromatography with EtOAc/hexanes as the eluant. Product was not obtained for 20{3,5} and the reason for this was not further investigated. Reaction yields for the remaining chemset compounds of 20 ranged from 25-89% and averaged 66%.</p><p>The Cbz and benzyl ester, respectively, for isolated chemset intermediates 16 and 20 were deprotected with 1 atm. H2 and 5% Pd/C in MeOH. The reactions were stirred at room temperature from 4.5-29 h for chemset 16 and 11-30 h for chemset 20, at which point the reaction was complete as determined by TLC analysis. The reaction mixture was filtered through celite and the solvent removed under vacuum to afford chemsets 17 and 21, respectively, from chemsets 16 and 20, minus members 17{2,7}, 17{3,7}, and 21{3,5} for which starting materials were unavailable. The yields for chemset 17 ranged from 84-99% and averaged 94%, whereas the yields for chemset 21 ranged from 65-100% and averaged 89%. All of the products were suitable for use without further purification.</p><p>The protected oligomer chemset 22, excluding those examples where monomeric intermediates 17{2,7}, 17{3,7}, and 21{3,5} were unavailable, were prepared in CH2Cl2 at room temperature over 20 h by coupling chemsets 17 and 21 with the water-soluble carbodiimide, EDC·HCl, and dimethylaminopyridine.36 The reaction mixtures were concentrated under vacuum and the product purified by column chromatography with a gradient ranging from EtOAc/hexanes to EtOAc/MeOH as the eluents, affording chemset 22.</p><p>Out of the 361 possible combinations for which monomeric chemset intermediates 17 and 21 were available, a total of 323 products were purified and yields determined, which were generally good (Table 4). The compounds of the protected oligomer chemset 22 were characterized by combined LC-MS and 1H NMR spectroscopy (see supporting information). In a few cases a library member was identified by LC-MS, but was not completely characterized or carried forward due to insufficient amounts of material or contamination with impurities.</p><p>Quantitative deprotection of products of chemset 22 was done with 25% CF3CO2H in CH2Cl2 at room temperature over 2-18 h, using LC-MS analysis to determine when the reaction was complete.</p><p>Following removal of the solvents, the trifluoroacetate salt was exchanged for chloride by dissolving the deprotected oligomer chemset 23 in 0.90 mL of 10% aqueous MeOH with gentle heat as needed for solubilization and adding 100 μL of 1 M HCl. The solutions were immediately frozen in liquid N2 before lyophilizing to dryness.</p><p>Interestingly, we observed two significant signals in the LC-MS analysis of 45 of the protected oligomer library compounds. In all cases both signals have an identical MS spectra that is consistent with the proposed structure. We hypothesize that this is evidence of two conformers that are stable under the conditions of the analysis. Indeed, conformational isomers have been reported for comparable oligomers containing two N-methylimidazole-4,5-dicarboxylic acid rings.37 A majority of the hypothesized conformational isomers that are observed have hydrophobic amino acid side chains located in both substituent amides of chemset, such as combinations of leucine or phenylalanine (see supporting information). However, we do not observe such conformational isomers in the protected oligomers containing tryptophan in chemset 21. It is possible that this is due to a preference for one conformer with the larger tryptophan substituent as compared with leucine or phenylalanine, or that these conformational isomers simply do not resolve in the LC-MS for those examples.</p><p>Our hypothesis of conformational isomers in protected oligomer chemset 22 is further supported by the fact that many compounds show broad and poorly defined 1H NMR spectra, whereas others have comparably well defined signals. Figure 1 compares part of the LC-MS and 1H NMR spectra for 22{2,1,2,2} with 22{2,1,3,2}. Oligomer 22{2,1,2,2} showed only a single peak in the LC-MS analysis while 22{2,1,3,2} shows two peaks hypothesized to be the conformational isomers. The 1H NMR spectra in the aliphatic region for 22{2,1,2,2} is considerably more defined than the comparable region for 22{2,1,3,2}. The broadness of the 1H NMR spectra for 22{2,1,3,2} is therefore hypothesized to result from the presence of conformational isomers having overlap in their 1H NMR chemical shifts or the relative dynamics of the compound on the NMR time scale or both. It is noted, however, that a broad 1H NMR spectrum did not necessarily mean that the oligomer showed two peaks in the LC-MS analysis, since there are examples of this behavior also. Among the potential explanations for this differing behavior include overlap in the retention time of persistent conformers in the LC conditions or that the change in solvent from aqueous CH3CN (LC-MS) versus CDCl3 (1H NMR) alters the conformational behavior between the analyses.</p><p>One concern was that the two signals in the LC-MS analysis represent diasteromeric oligomers resulting from epimerization of a stereocenter under the coupling conditions. We did not expect the coupling conditions to cause in significant epimerization, and note that we observe two signals only in select cases for any given set of hydrophobic amino acids. This variability in behavior is strong evidence against epimerization as the explanation for our results.</p><p>As with the protected oligomers, two significant LC-MS signals were observed in 54 of final compounds of chemset 23. Again, the general trend appears to be related to the presence of two hydrophobic amino acids in chemset 21, although there are exceptions in the deprotected oligomers just as there were for the protected oligomers. Importantly, some protected oligomers with two conformers did not show two conformers when deprotected (e.g., 23{2,2,3,2} and 23{2,2,3,3}), while others did not show two conformers until the oligomer was deprotected (e.g., 23{1,2,3,4} and 23{1,3,3,4}). This is yet further evidence against the formation of diasteromers in the coupling reactions, as diastereomeric compounds of chemset 22 would yield diastereomeric compounds of chemset 23.</p><p>As additional evidence in support of the conformational hypothesis, we performed variable-temperature LC-MS on four deprotected oligomers (23{1,2,3,3}, 23{1,3,3,4}, 23{2,5,3,3}, and 23{1,6,3,3}) that show evidence of two peaks in the LC-MS analysis (see supporting information). The analysis was run from 25 °C to 65 °C, and showed a steady decline in the relative amounts of the lesser conformer as compared to the major conformer. While we did not observe coalescence of the two conformers at 65 °C, it is possible that hydrophobic interactions could continually stabilize the conformation(s) in an aqueous environment. Nonetheless, the differing relative amounts of the two peaks support our hypothesis that these are conformational isomers rather than diastereomers.</p><p>It is commonplace to use VT-NMR spectroscopy in order to examine conformational isomerism in solution. We know from our previous experience with monomeric derivatives that self-association occurs at or above 1 mM in CDCl3 and above 10 mM in DMSO-d6.39 Thus, VT-NMR was performed from 30 °C to 70 °C in DMSO-d6 for 22{2,1,2,2} and 22{2,1,3,2} at 3 mM (see supporting information), resulting in similar 1H NMR spectra observed for both compounds across the range of temperatures. We are unable to assign specific NHs to observed signals, but can nonetheless identify the two imidazole NHs as those signals around 13 ppm, the two amide NHs involved in intramolecular hydrogen bonding as the signals around 11 ppm, the three remaining amide NHs between 8-9 ppm, and the carbamate NH near 7 ppm, as shown in Figure 2 for 22{2,1,3,2}. From inspection it is then clear that there are conformational isomers present in the solution. For example, there are four signals for the two intramolecular hydrogen bonded hydrogens (b). An increase in temperature yields only modest changes on the chemical shifts of the NHs over this entire region. This has previously been reported for oligomeric I45DCs that form conformation isomers observable in DMSO-d6 even at 100 °C.37 Cooling the NMR sample of 22{2,1,3,2} to 30 °C from 70 °C yields the same spectrum as first recorded at 30 °C, indicating the stability of the compounds in a polar solvent at high temperatures.</p><p>We suggest that the conformational isomers may result from differing intramolecular hydrogen bonding interactions, particularly around the I45DC from chemset 21, and perhaps supported by the presence of hydrophobic interactions that protect the hydrogen bond from fast exchange during the LC-MS analysis and on the 1H NMR time scale. We have previously observed two intramolecularly hydrogen bonded conformations in dissymmetrically-disubstituted I45DCs and provided evidence that the favored hydrogen bond donor arose from increasing substitution adjacent the amide nitrogen.38 Moreover, we have shown in model I45DCs that the intramolecular hydrogen bond is relatively strong and worth least 14±1 kcal/mol, as well as observed in an aqueous environment.39 The two conformations for 22{2,1,3,2} shown in Figure 2 are therefore real possibilities for explaining the observed behavior in both the LC-MS analysis and 1H NMR spectra. It is reasonable that 22{2,1,2,2} would also adopt analogous intramolecularly hydrogen bonded conformations, and the lack of a second hydrophobic side chain may increase the dynamics of the conformational exchange.</p><p>The expected intramolecular hydrogen bonding conformations were a valuable design criteria as they fix the distance between amide substituents in order to approximate the separation of nearby side chains in α-helices and β-strands.24,25 The two different conformers would not affect that separation, but do alter the possible hydrogen bonding interactions with the imidazole ring, as hydrogen bond donor and acceptor groups on the ring have their relative positions switched. One conformation about a single I45DC of the oligomer, relative to the other I45DC conformer, may also be valuable as the oligomers optimize binding interactions at protein interfaces. In this way the conformational isomers could be of added value in the use of these oligomers in screening for inhibitors of protein-protein interactions.</p><!><p>A total of 317 final products in chemset 23 that were both analytically pure and of sufficient quantity were submitted as HCl salts to the Molecular Library Small Molecule Repository (MLSMR) for high-throughput screening by the as part of the NIH Roadmap. A total of 37 protected intermediates from chemset 22 where likewise submitted to the MLSMR. Chemical and biological data for the oligomers will be accessible free of charge at PubChem (http://pubchem.ncbi.nlm.nih.gov) as the compounds are incorporated into the database and subsequently screened by the Molecular Libraries Probes Production Centers Network (MLPCN). It is reasonably hypothesized that these oligomers will be valuable in the discovery of inhibitors against protein-protein interactions.</p>

PubMed Author Manuscript

Organocatalytic Stereoselective Synthesis of Fluorinated 3,3\xe2\x80\xb2-Linked Bisoxindoles

A highly diastereoselective organocatalytic method that produces 3-fluoro-3\xe2\x80\xb2-hydroxy-3,3\xe2\x80\xb2-bisoxindoles and the corresponding 3-fluoro-3\xe2\x80\xb2-amino derivatives having two adjacent chirality centers from fluorooxindoles and isatins in high yields is described. The reaction occurs in protic solvents at room temperature, it can be upscaled without compromising yield and stereoselectivity, and chromatographic product purification is not required.

organocatalytic_stereoselective_synthesis_of_fluorinated_3,3\xe2\x80\xb2-linked_bisoxindoles

<!>Experimental Section<!>General Procedure<!>3-Fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>Large Scale Synthesis of 3<!>5\xe2\x80\xb2-Chloro-3-fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>5\xe2\x80\xb2-Bromo-3-fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3,5\xe2\x80\xb2-Difluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3-Fluoro-3\xe2\x80\xb2-hydroxy-5\xe2\x80\xb2-methyl-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>7\xe2\x80\xb2-Chloro-3-fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>4\xe2\x80\xb2-Chloro-3-fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>6\xe2\x80\xb2-Chloro-3-fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3,6\xe2\x80\xb2-Difluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>6\xe2\x80\xb2-Bromo-3-fluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3,5\xe2\x80\xb2,6\xe2\x80\xb2-Trifluoro-3\xe2\x80\xb2-hydroxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3-Fluoro-3\xe2\x80\xb2-hydroxy-1,1\xe2\x80\xb2-diphenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3-Fluoro-3\xe2\x80\xb2-hydroxy-1,1\xe2\x80\xb2-dimethyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3-Fluoro-3\xe2\x80\xb2-hydroxy-5\xe2\x80\xb2-nitro-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>3-Fluoro-3\xe2\x80\xb2-hydroxy-6\xe2\x80\xb2-methoxy-1-phenyl-[3,3\xe2\x80\xb2-biindoline]-2,2\xe2\x80\xb2-dione<!>tert-Butyl (1\xe2\x80\xb2-benzyl-3-fluoro-2,2\xe2\x80\xb2-dioxo-1-phenyl-[3,3\xe2\x80\xb2-biindolin]-3\xe2\x80\xb2-yl)carbamate<!>tert-Butyl (1,1\xe2\x80\xb2-dibenzyl-3-fluoro-2,2\xe2\x80\xb2-dioxo-[3,3\xe2\x80\xb2-biindolin]-3\xe2\x80\xb2-yl)carbamate<!>3-(2,2-Bis(phenylsulfonyl)ethyl)-3-fluoro-1-phenylindolin-2-one

<p>The unique physicochemical properties and widespread use of fluorinated organic compounds in the health sciences continues to attract considerable attention. Numerous studies have shown that incorporation of fluorine can improve the therapeutic index of biologically active compounds.1 The introduction of synthetic methods that produce fluorinated derivatives of natural compounds and future drug candidates therefore remains of considerable interest. The construction of carbon-carbon bonds with reactive organofluorine intermediates, however, is often limited by undesirable side reactions and decomposition pathways. Various synthetic strategies that address these issues, for example by mild in situ production of fluoroenolates, have emerged in recent years.2 The 3,3-disubstituted oxindole scaffold is a privileged structural motif and a challenging synthetic target,3 especially if multiple stereocenters are present.4 The medicinal utility and potential of 3-fluorooxindoles, including the potassium ion channel modulator Maxipost (Figure 1),5 has inspired the development of several methods that accomplish direct fluorination of 3-alkyl and 3-aryloxindoles.6 More recently, synthetic alternatives that accomplish C-C bond formation with 3-fluorooxindoles have emerged.7</p><p>A remaining drawback of fluorooxindole transformations is that the use of inert reaction conditions and elaborate work-up procedures generating substantial amounts of chemical waste are required in most cases. Because environmental and sustainability aspects together with operational safety, time efficiency and overall cost considerations play an increasingly important role in industrial and academic laboratories we decided to develop a practical method that addresses these issues using 3-fluorooxindoles as starting material. The reaction with isatins was of particular interest to us as it produces a challenging dimeric oxindole scaffold exhibiting a 3,3′-linkage with two adjacent chirality centers.</p><p>We began our search for an environmentally benign, economically attractive method by screening the reaction of N-phenyl-3-fluorooxindole, 1, and isatin, 2, in water and alcoholic solvents in the presence of catalytic amounts of inexpensive triethylamine at room temperature (Table 1). We found that the reaction proceeds smoothly in the presence of 20 mol% of base in water and is almost complete after stirring for 2 hours at room temperature (entry 1). The formation of the bisoxindole 3 was almost quantitative and occurred with high stereoselectivity. We did not detect formation of by-products and determined the diastereomeric ratio, dr, of 3 as 24:1. As expected, catalytic amounts of the base are required for this reaction and 3 was not formed in the absence of Et3N (entry 2). Screening of other protic solvents revealed that the conversion, reaction time and diastereoselectivity can be further improved (entries 3-6). In addition to optimization of the reaction conditions, we examined the possibility of non-chromatographic product isolation to minimize the overall solvent consumption and labor. Using 10 mol% of triethylamine in isopropyl alcohol we observed that 3 is produced quantitatively from 1 and 2 with 49:1 dr in just 30 minutes (entry 6). Under these conditions, the bisoxindole precipitated quantitatively which greatly facilitates product isolation and renders chromatographic work-up unnecessary.</p><p>Having optimized reaction conditions and a work-up procedure that are both practical and environmentally benign, we continued to determine the reaction scope of the organocatalytic bisoxindole formation. 3-Fluoro-3′-hydroxy-1-phenyl-3,3′-bisoxindole, 3, was isolated in 96% yield and 99:1 dr (Scheme 1). The reaction between fluorooxindole 1 and isatins carrying a halide or a methyl group at position 5 in the fused benzene ring gave the corresponding bisoxindoles 4-7 in 90-96% yield and with at least 95:5 dr. The reaction tolerates substituents at all positions in the isatin electrophile. The chlorinated bisoxindoles 8-10 were produced with very similar results compared to 4. When we employed other brominated and fluorinated isatins in this reaction we obtained 11-13 in 91-92% yields and very high dr's. The isatin compound can also be substituted at the nitrogen. 3-Fluoro-3′-hydroxy-1,1′-diphenyl-3,3′-bisoxindole, 14, and the N-methyl analogue 15 were isolated in almost quantitative amounts and in excellent diastereomeric ratio. The reaction with N-methylisatin and N-methyl-3-fluorooxindole was also conducted in the presence of 20 mol% of triethylamine using either THF or dichloromethane as solvent. In both cases, the reaction occurs under homogeneous conditions and without precipitation of the product 15 which was obtained in quantitative yield and with >99:1 dr. This suggests that the high diastereoselectivity is achieved in solution and not a result of preferential crystallization of one diastereomer from a mixture of rapidly interconverting isomers of 15 (asymmetric transformation of the second kind). Finally the introduction of a strong electron-withdrawing nitro group and an electron-donating methoxy into the isatin ring showed little effects on the chemical and stereochemical outcome. We obtained 16 and 17 in 92-94% yield and very high dr. The triethylamine catalyzed reaction thus affords a variety of 3,3′-bridged bisoxindoles exhibiting two adjacent quaternary chiral centers in almost quantitative yields and with remarkable diastereoselectivity. Our organocatalytic method is operationally simple and leads to multifunctional bisoxindole alkaloid scaffolds. The protocol has several attractive features in addition to the high yields and dr values that are noteworthy. The C-C bond formation is accomplished within 30 minutes using mild reaction conditions, i.e. at room temperature and under air, and we did not observe by-product formation. All products 3-17 were isolated by precipitation and purified by careful washing with isopropyl alcohol-petroleum ether mixtures. The work-up does not require any chromatography which typically is time-consuming and increases both cost and waste production.8</p><p>To reveal the stereochemical outcome of this reaction we resorted to X-ray crystallography. We were able to grow a single crystal of racemic 3-fluoro-3′-hydroxy-1,1′-dimethyl-3,3′-bisoxindole, 15, by slow evaporation of a solution containing small amounts of ethyl acetate in hexanes.9 Crystallographic analysis confirmed that the reaction favors formation of the homochiral diastereomer (Figure 2).</p><p>To the best of our knowledge, the synthesis of 3-fluoro-3′-hydroxy-3,3′-bisoxindoles has not been reported to date and 3-17 are new compounds. Few examples of palladium catalyzed carbon-carbon bond formation with fluorooxindole 1 in dichloromethane and toluene, respectively, are known.7d,10 These methods accomplish asymmetric allylic alkylations and arylations with high yields and stereoselectivities but long reaction times and chromatographic work-up are required. Han and Soloshonok introduced a noncatalytic diastereoselective Mannich reaction via detrifluoroacetylative generation of intermediate 3-fluorooxindole enolates which achieves carbon-carbon bond formation with yields and dr's very similar to our method.7c,11 This reaction is fast and proceeds in etheral solvents or acetonitrile but large excess of base and LiBr additives are required in addition to chromatographic product purification. A very similar copper catalyzed asymmetric aldol-type reaction that utilizes the same detrifluoroacetylation concept was recently reported.12 An inherent drawback of the detrifluoroacetylative enolate generation, however, is the production of stoichiometric amounts of trifluoroacetic acid waste. In comparison to these methods our protocol establishes a significant green chemistry advance as waste resulting from by-products or additives, chromatographic work-up and the use of transition metals are avoided. Thakur and Meshram reported an interesting diastereoselective formation of 3-hydroxy-3,3′-bisoxindoles through catalyst-free on-water synthesis.13 We found, however, that this protocol cannot be generally used for the synthesis of the fluorinated bisoxindoles 3-17. While we successfully reproduced their results with oxindole and isatin, the reaction between N-phenyl-3-fluorooxindole and either isatin or N-phenylisatin using the on-water protocol gave 3 and 14, respectively, in only 3-5% yield after 24 hours.</p><p>We decided to run the reaction between 1 and 2 at the gram scale to determine if the overall efficiency and the environmentally attractive features of our method can be maintained without compromising yield and diastereoselectivity (see Experimental Section). We found that even at the increased reaction scale the product formation is complete within 30 minutes and 3 was isolated in 95% yield and with 99:1 dr. More than one gram of the bisoxindole 3 was thus obtained with an E-factor of 22 and without the use of expensive catalysts and additives or hazardous solvents.14</p><p>Our method is not limited to isatin electrophiles. When we applied the fluorooxindoles 1 and 20 in the reaction with N-Boc imine 18 we were pleased to find that the correspnding amines 19 and 21 were produced in 90-92% yield and with very high dr using the same method (Scheme 2). The reactivity of 3-fluorooxindoles in protic solvents and the utility of our environmentally benign C-C bond formation procedure also extends to Michael additions.15 Employing 1 and 1,1-bis(phenylsulfonyl)ethane, 22, in essentially the same protocol used above we were able to prepare 23 in 99% yield.7a,16 This reaction occurs in isopropyl alcohol in the presence of 10 mol% of triethylamine and is complete within 30 minutes. Again, chromatographic product purification was not necessary.</p><p>In summary, we have introduced an organocatalytic method that produces 3-fluoro-3′-hydroxy-3,3′-bisoxindoles or the corresponding 3-fluoro-3′-amines carrying two vicinal chirality centers in high yields and stereoselectivities. The reaction occurs in non-hazardous isopropyl alcohol or other protic solvents at room temperature within 30 minutes in the presence 10 mol% of triethylamine as catalyst and the bisoxindole formation can be upscaled without compromising yields and diastereoselectivity. Furthermore, the formation of by-products was not observed and chromatographic product purification is not necessary.</p><!><p>Commercially available isatins, reagents and solvents were used as purchased without further purification. 3-Fluorooxindole was synthesized by following literature procedures.7d NMR spectra were obtained at 400 MHz (1H NMR), 376 MHz (19F NMR) and 100 MHz (13C NMR) in deuterated dimethylsulfoxide, acetone or deuterated chloroform. Proton chemical shifts are reported in ppm relative to the solvent peak or TMS.</p><!><p>A mixture of 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and an isatin (0.20 mmol) were added to 1.0 mL of isopropyl or methyl alcohol. Triethylamine (2.8 μL, 0.020 mmol) was added and the solution was stirred for 30 minutes. The resulting solid was isolated after addition of 1.0 mL of petroleum ether and decanting off the liquid. The crude product was purified by washing the solid three times with 1.0 mL of petroleum ether-isopropyl alcohol (1:1).</p><!><p>Compound 3 was obtained as a white crystalline solid in 96% yield (72 mg, 0.19 mmol) and >99:1 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and isatin (30 mg, 0.20 mmol) after sonication in isopropyl alcohol for 30 minutes as described above. Decomp. 204 °C. 1H NMR (399 MHz, DMSO-d6): δ = 10.44 (s, 1H), 7.51 – 7.33 (m, 4H), 7.28 (dd, J = 7.6, 7.6 Hz, 1H), 7.15 (dd, J = 7.5, 7.5 Hz, 1H), 6.98 (s, 1H), 6.95 – 6.90 (m, 2H), 6.84 – 6.77 (m, 2H), 6.62 (d, J = 8.0 Hz, 1H), 6.37 (d, J = 6.2 Hz, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 173.8 (d, JC-F = 2.4 Hz), 168.5 (d, JC-F = 21.6 Hz), 144.4 (d, JC-F = 5.1 Hz), 142.9, 132.9, 132.0 (d, JC-F = 2.6 Hz), 130.7, 129.7, 128.6, 126.9, 126.4, 125.7 (d, JC-F = 4.1 Hz), 124.8, 123.2 (d, JC-F = 2.5 Hz), 121.6 (d, JC-F = 18.8 Hz), 121.3, 109.8, 109.2, 94.0 (d, JC-F = 205.3 Hz), 77.0 (d, JC-F = 23.8 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.2. Anal. Calcd. for C22H15FN2O3: C, 70.58; H, 4.04; N, 7.48. Found: C, 70.39; H, 4.20; N, 7.40.</p><!><p>A mixture of 3-fluoro-1-phenylindolin-2-one (911 mg, 4.0 mmol) and isatin (602 mg, 4.0 mmol) were added to 4.0 mL of isopropyl alcohol. Triethylamine (56.5 μL, 0.40 mmol) was added and the solution was stirred for 30 minutes. The resulting product 3 was obtained as a white solid in 95% yield (1.43 g, 3.8 mmol) and >99:1 dr after adding 6.0 mL of isopropyl alcohol, filtration and washing the solid with a total of 20 mL of petroleum ether-isopropyl alcohol (1:1).</p><!><p>Compound 4 was obtained as a white solid in 94% yield (77 mg, 0.19 mmol) and 96:4 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 5-chloroisatin (37 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, DMSO-d6): δ = 10.62 (s, 1H), 7.54 - 7.38 (m, 5H), 7.35 (dd, J = 8.3, 2.1 Hz, 1H), 7.25 – 7.16 (m, 2H), 7.01 – 6.93 (m, 2H), 6.82 (d, J = 8.3 Hz, 1H), 6.66 (d, J = 8.0 Hz, 1H), 6.26 (bs, 1H). 13C NMR (101 MHz, DMSO-d6): δ = 173.4 (d, JC-F = 2.2 Hz), 168.2 (d, JC-F = 21.6 Hz), 144.4 (d, JC-F = 5.1 Hz), 141.8, 132.9, 132.3 (d, JC-F = 2.6 Hz), 130.5, 129.8, 128.7, 127.6 (d, JC-F = 4.1 Hz), 127.0, 126.3, 125.3, 124.8, 123.4 (d, JC-F = 2.4 Hz), 121.2 (d, JC-F = 19.0 Hz), 111.4, 109.2, 93.9 (d, JC-F = 206.4 Hz), 77.1 (d, JC-F = 24.2 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.9. Anal. Calcd. for C22H14ClFN2O3: C, 64.64; H, 3.45; N, 6.85. Found: C, 64.46; H, 3.50; N, 6.71.</p><!><p>Compound 5 was obtained as a white solid in 91% yield (83 mg, 0.18 mmol) and 95:5 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 5-bromoisatin (48 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, acetone-d6): δ = 9.40 (s, 1H), 7.48 – 7.41 (m, 3H), 7.40 – 7.26 (m, 2H), 7.24 – 7.16 (m, 2H), 7.10 (s, 1H), 6.95 (dd, J = 7.3, 7.3 Hz, 1H), 6.82 – 6.73 (m, 2H), 6.63 (d, J = 7.7 Hz, 1H), 5.85 (s, 1H). 13C NMR (101 MHz, DMSO-d6): δ = 173.3 (d, JC-F = 2.0 Hz), 168.2 (d, JC-F = 21.6 Hz), 144.4 (d, JC-F = 5.0 Hz), 142.1, 133.3, 132.8, 132.3, 129.8, 128.7, 128.0 (d, JC-F = 4.4 Hz), 127.6, 127.0, 126.3, 123.4, 121.2 (d, JC-F = 19.1 Hz), 112.8, 111.9, 109.2, 94.0 (d, JC-F = 206.9 Hz), 77.0 (d, JC-F = 24.1 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.4. Anal. Calcd. for C22H14BrFN2O3: C, 58.30; H, 3.11; N, 6.18. Found: C, 58.30; H, 3.19; N, 6.08.</p><!><p>Compound 6 was obtained as a white solid in 96% yield (75 mg, 0.19 mmol) and 96:4 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 5-fluoroisatin (34 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, DMSO-d6): δ = 10.50 (s, 1H), 7.54 – 7.47 (m, 2H), 7.46 – 7.40 (m, 2H), 7.34 (m, 1H), 7.21 – 7.12 (m, 3H), 7.04 – 6.96 (m, 2H), 6.81 (dd, J = 8.6, 4.2 Hz, 1H), 6.66 (d, J = 8.0 Hz, 1H), 6.14 (m, 1H). 13C NMR (101 MHz, DMSO-d6): δ = 173.7 (d, JC-F = 2.4 Hz), 168.2 (d, JC-F = 21.6 Hz), 157.4 (d, JC-F = 237.8 Hz), 144.4 (d, JC-F = 5.2 Hz), 139.1 (d, JC-F = 1.9 Hz), 132.9, 132.3 (d, JC-F = 2.5 Hz), 129.8, 128.7, 127.2 (dd, JC-F = 7.8, 4.0 Hz), 126.9, 126.3, 123.3 (d, JC-F = 2.4 Hz), 121.2 (d, JC-F = 19.0 Hz), 117.1 (d, JC-F = 23.1 Hz), 112.4 (d, JC-F = 25.0 Hz), 110.8 (d, JC-F = 7.8 Hz), 109.3, 93.8 (d, JC-F = 205.7 Hz), 77.4 (d, JC-F = 24.1 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -122.5 (m), -177.51. Anal. Calcd. for C22H14F2N2O3: C, 67.35; H, 3.60; N, 7.14. Found: C, 67.05; H, 3.56; N, 7.03.</p><!><p>Compound 7 was obtained as a white solid in 90% yield (70 mg, 0.18 mmol) and 97:3 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 5-methylisatin (33 mg, 0.20 mmol) after sonication in isopropyl alcohol for 30 minutes as described above. 1H NMR (399 MHz, DMSO-d6): δ = 10.31 (s, 1H), 7.54 – 7.37 (m, 4H), 7.27 (m, 1H), 7.17 – 7.07 (m, 2H), 6.99 – 6.93 (m, 2H), 6.87 (s, 1H), 6.67 (d, J = 8.0 Hz, 1H), 6.61 (d, J = 8.0 Hz, 1H), 6.23 (bs, 1H), 2.06 (s, 3H). 13C NMR (100 MHz, DMSO-d6): δ = 174.2 (d, JC-F = 2.8 Hz), 168.9 (d, JC-F = 21.7 Hz), 144.9 (d, JC-F = 5.1 Hz), 140.8, 133.5, 132.4 (d, JC-F = 2.7 Hz), 131.1, 130.6, 130.2, 129.0, 127.3, 126.9, 126.2 (d, JC-F = 3.8 Hz), 126.1, 123.5 (d, JC-F = 2.4 Hz), 122.1, 121.9, 109.7 (d, JC-F = 48.5 Hz), 94.4 (d, JC-F = 205.1 Hz), 77.8 (d, JC-F = 23.8 Hz), 21.0. 19F NMR (376 MHz, DMSO-d6): δ = -177.6. Anal. Calcd. for C23H17FN2O3: C, 71.13; H, 4.41; N, 7.21. Found: C, 70.76; H, 4.51; N, 7.13.</p><!><p>Compound 8 was obtained as a white solid in 91% yield (74 mg, 0.18 mmol) and >99.1 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 7-chloroisatin (37 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, DMSO-d6): δ = 10.94 (s, 1H), 7.54 – 7.40 (m, 4H), 7.40 – 7.32 (m, 2H), 7.23 – 7.14 (m, 2H), 7.01 – 6.95 (m, 2H), 6.87 (dd, J = 7.9, 7.9 Hz, 1H), 6.64 (d, J = 8.0 Hz, 1H), 6.36 (m, 1H). 13C NMR (101 MHz, DMSO-d6): δ = 173.7 (d, JC-F = 2.3 Hz), 168.2 (d, JC-F = 21.6 Hz), 144.4 (d, JC-F = 5.1 Hz), 140.6, 132.9, 132.3 (d, JC-F = 2.7 Hz), 130.6, 129.8, 128.7, 127.6 (d, JC-F = 4.1 Hz), 126.9, 126.4, 123.4, 123.3 (d, JC-F = 2.5 Hz), 122.7, 121.3 (d, JC-F = 18.8 Hz), 114.0, 109.3, 93.8 (d, JC-F = 205.7 Hz), 77.5 (d, JC-F = 24.1 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.0. Anal. Calcd. for C22H14ClFN2O3: C, 64.64; H, 3.45; N, 6.85. Found: C, 64.40; H, 3.47; N, 6.78.</p><!><p>Compound 9 was obtained as a white solid in 94% yield (77 mg, 0.19 mmol) and 99:1 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 4-chloroisatin (37 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (399 MHz, DMSO-d6): δ = 10.64 (s, 1H), 7.58 – 7.52 (m, 2H), 7.47 (m, 1H), 7.38 – 7.30 (m, 2H), 7.25 – 7.20 (m, 2H), 7.02 (d, J = 8.1 Hz, 1H), 6.97 (dd, 7.6, 7.6 Hz, 1H), 6.83 (m, 1H), 6.79 (s, 1H), 6.72 (d, J = 7.7 Hz, 1H), 6.66 (d, J = 7.9 Hz, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 173.6 (d, JC-F = 6.0 Hz), 168.6 (d, JC-F = 22.1 Hz), 144.8, 144.4 (d, JC-F = 5.2 Hz), 138.9, 133.2, 132.2 (d, JC-F = 2.8 Hz), 132.1, 131.6, 129.7, 128.5, 126.5, 126.3, 123.6, 122.9 (dd, JC-F = 6.3, 2.1 Hz), 121.9 (d, JC-F = 18.7 Hz), 109.4, 108.7, 93.5 (d, JC-F = 206.1 Hz), 80.0 (d, JC-F = 24.9 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -169.5. Anal. Calcd. for C22H14ClFN2O3: C, 64.64; H, 3.45; N, 6.85. Found: C, 64.38; H, 3.48; N, 6.75.</p><!><p>Compound 10 was obtained as a white solid in 96% yield (79 mg, 0.19 mmol) and 98:2 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 6-chloroisatin (37 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, DMSO-d6): δ = 10.64 (s, 1H), 7.53 – 7.38 (m, 5H), 7.21 – 7.14 (m, 2H), 7.02 – 6.95 (m, 2H), 6.89 (d, J = 8.0, 1H), 6.83 (s, 1H), 6.66 (d, J = 7.9 Hz, 1H), 6.35 (m, 1H). 13C NMR (101 MHz, DMSO-d6): δ = 173.7 (d, JC-F = 2.2 Hz), 168.3 (d, JC-F = 21.6 Hz), 144.4, 144.3 (d, JC-F = 5.1 Hz), 135.1, 132.9, 132.3 (d, JC-F = 2.6 Hz), 129.8, 128.7, 127.0, 126.3, 124.6 (d, JC-F = 4.3 Hz), 123.4 (d, JC-F = 2.5 Hz), 121.4, 121.2, 121.2, 109.9, 109.3, 93.9 (d, JC-F = 205.8 Hz), 76.7 (d, JC-F = 24.1 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.1. Anal. Calcd. for C22H14ClFN2O3: C, 64.64; H, 3.45; N, 6.85. Found: C, 64.49; H, 3.63; N, 6.69.</p><!><p>Compound 11 was obtained as a white solid in 92% yield (72 mg, 0.18 mmol) and 98:2 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 6-fluoroisatin (34 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (399 MHz, DMSO-d6): δ = 10.63 (bs, 1H), 7.54 – 7.37 (m, 5H), 7.18 (dd, J = 7.5, 7.5 Hz, 1H), 7.08 (s, 1H), 7.03 – 6.96 (m, 2H), 6.69 – 6.59 (m, 3H), 6.36 (m, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 174.0 (d, JC-F = 2.2 Hz), 168.4 (d, JC-F= 21.7 Hz), 163.6 (d, JC-F = 245.3 Hz), 144.8 (d, JC-F = 12.7 Hz), 144.3 (d, JC-F = 5.1 Hz), 132.9, 132.2 (d, JC-F = 2.7 Hz), 129.8, 128.6, 127.0, 126.5 (m), 126.3, 123.3 (d, JC-F = 2.4 Hz), 121.7 (dd, JC-F = 4.4, 2.8 Hz), 121.4 (d, JC-F = 18.9 Hz), 109.3, 107.6 (d, JC-F = 22.5 Hz), 98.0 (d, JC-F = 27.0 Hz), 93.9 (d, JC-F = 205.5 Hz), 76.5 (d, JC-F = 24.1 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -109.8 (m), -176.7. Anal. Calcd. for C22H14F2N2O3: C, 67.35; H, 3.60; N, 7.14. Found: C, 66.96; H, 3.76; N, 7.08.</p><!><p>Compound 12 was obtained as a white solid in 91% yield (83 mg, 0.18 mmol) and 97:3 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 6-bromoisatin (46 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (399 MHz, DMSO-d6): δ = 10.62 (s, 1H), 7.54 – 7.36 (m, 5H), 7.22 – 7.12 (m, 2H), 7.06 – 6.93 (m, 4H), 6.65 (d, J = 7.9 Hz, 1H), 6.29 (m, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 173.5 (d, JC-F = 2.3 Hz), 168.3 (d, JC-F = 21.4 Hz), 144.5, 144.3 (d, JC-F = 5.2 Hz), 132.9, 132.2 (d, JC-F = 2.7 Hz), 129.7, 128.7, 126.9, 126.5, 126.3, 125.0 (d, JC-F = 4.2 Hz), 124.1, 123.5, 123.3 (d, JC-F = 2.5 Hz), 121.3 (d, JC-F = 18.9 Hz), 112.6, 109.3, 93.8 (d, JC-F = 206.0 Hz), 76.8 (d, JC-F = 24.2 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.2. Anal. Calcd. for C22H14BrFN2O3: C, 58.30; H, 3.11; N, 6.18. Found: C, 58.04; H, 3.29; N, 6.07.</p><!><p>Compound 13 was obtained as a white solid in 91% yield (75 mg, 0.18 mmol) and 98:2 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 5,6-difluoroisatin (38 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, DMSO-d6): δ = 10.66 (bs, 1H), 7.55 – 7.51 (m, 2H), 7.47 – 7.43 (m, 2H), 7.33 (m, 1H), 7.28 – 7.14 (m, 3H), 7.09 – 7.04 (m, 2H), 6.89 (dd, J = 10.3, 6.8 Hz, 1H), 6.69 (d, J = 8.1 Hz, 1H), 6.36 (m, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 173.7 (d, JC-F = 2.6 Hz), 168.1 (d, JC-F = 21.8 Hz), 150.9 (dd, JC-F = 247.8, 13.9 Hz), 144.9 (dd, JC-F = 240.0, 13.5 Hz), 144.3 (d, JC-F = 5.3 Hz), 139.8 (d, JC-F = 10.2 Hz), 132.9, 132.3, 129.8, 128.7, 126.8, 126.2, 123.4, 121.7, 121.0 (d, JC-F = 18.9 Hz), 114.3 (d, JC-F = 20.2 Hz), 109.3, 99.9 (d, JC-F = 22.4 Hz), 93.6 (d, JC-F = 205.6 Hz), 77.0 (d, JC-F = 24.5 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -135.0 (m), -148.5 (m), -177.0. Anal. Calcd. for C22H13F3N2O3: C, 64.39; H, 3.19; N, 6.83. Found: C, 64.30; H, 3.24; N, 6.81.</p><!><p>Compound 14 was obtained as a white solid in 97% yield (87 mg, 0.19 mmol) and 98:2 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 1-phenylisatin (46 mg, 0.20 mmol) after sonication in methyl alcohol for 30 minutes as described above. 1H NMR (400 MHz, DMSO-d6): δ = 7.58 – 7.37 (m, 9H), 7.36 – 7.19 (m, 4H), 7.01 – 6.83 (m, 3H), 6.66 (dd, J = 12.6, 8.0 Hz, 2H), 6.42 (bs, 1H). 13C NMR (101 MHz, DMSO-d6): δ = 171.7 (d, JC-F = 1.4 Hz), 168.5 (d, JC-F = 21.6 Hz), 144.4 (d, JC-F = 5.2 Hz), 144.0, 133.7, 132.8, 132.3 (d, JC-F = 2.5 Hz), 130.9, 129.8, 129.7, 128.7, 128.3, 127.2, 126.6, 126.4, 124.9, 124.7 (d, JC-F = 4.4 Hz), 123.4 (d, JC-F = 2.4 Hz), 122.6, 121.3 (d, JC-F = 18.9 Hz), 109.3, 109.0, 94.5 (d, JC-F = 207.4 Hz), 76.7 (d, JC-F = 23.7 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -176.8. Anal. Calcd. for C28H19FN2O3: C, 74.66; H, 4.25; N, 6.22. Found: C, 74.55; H, 4.27; N, 6.21.</p><!><p>Compound 15 was obtained as a white crystalline solid in 99% yield (65 mg, 0.20 mmol) and >99:1 dr from 3-fluoro-1-methylindolin-2-one (33 mg, 0.20 mmol) and 1-methylisatin (33 mg, 0.20 mmol) after sonication in methanol for 30 minutes by as described above. Decomp. 196 °C. 1H NMR (399 MHz, CDCl3): δ = 7.72 (d, J = 7.1 Hz, 1H), 7.46 (dd, J = 7.8, 7.8 Hz, 1H), 7.31 (dd, J = 7.8, 7.8 Hz, 1H), 7.22 (dd, J = 7.6, 7.6 Hz, 1H), 6.81 (d, J = 7.8 Hz, 1H), 6.79 – 6.73 (m, 2H), 6.10 (d, J = 7.5 Hz, 1H), 5.68 (s, 1H), 3.26 (s, 3H), 2.85 (s, 3H). 13C NMR (100 MHz, CDCl3): δ = 173.4 (d, JC-F = 8.3 Hz), 171.4 (d, JC-F = 21.2 Hz), 144.9 (d, JC-F = 4.8 Hz), 144.6, 132.3 (d, JC-F = 3.0 Hz), 131.3, 127.0 (d, JC-F = 3.0 Hz), 125.2, 124.3, 123.7, 123.2 (d, JC-F = 2.6 Hz), 121.5 (d, JC-F = 18.2 Hz), 109.3, 108.4, 90.4 (d, JC-F = 200.8 Hz), 79.2 (d, JC-F = 24.6 Hz), 26.4, 26.1. 19F NMR (376 MHz, CDCl3): δ = -174.4. Anal. Calcd. for C18H15FN2O3: C, 66.25; H, 4.63; N, 8.58. Found: C, 66.39; H, 4.68; N, 8.71.</p><!><p>Compound 16 was obtained as a white solid in 92% yield (77 mg, 0.18 mmol) and 97:3 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 5-nitroisatin (36 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (399 MHz, DMSO-d6): δ = 11.22 (bs, 1H), 8.25 (dd, J = 8.7, 2.3 Hz, 1H), 7.56 – 7.41 (m, 6H), 7.25 (dd, J = 7.6, 7.6 Hz, 1H), 7.11 (s, 1H), 7.01 (d, J = 8.6 Hz, 1H), 6.97 – 6.87 (m, 2H), 6.67 (d, J = 7.9 Hz, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 174.0 (d, JC-F = 1.7 Hz), 168.0 (d, JC-F = 21.5 Hz), 149.2, 144.2 (d, JC-F = 5.1 Hz), 141.7, 132.7, 132.5 (d, JC-F = 2.7 Hz), 129.8, 128.7, 127.8, 127.2, 126.4, 126.1, 123.6 (d, JC-F = 2.2 Hz), 120.8 (d, JC-F = 19.0 Hz), 120.4, 110.2, 109.5, 93.8 (d, JC-F = 207.0 Hz), 76.5 (d, JC-F = 24.5 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -177.5. Anal. Calcd. for C22H14FN3O5: C, 63.01; H, 3.37; N, 10.02. Found: C, 63.10; H, 3.57; N, 9.90.</p><!><p>Compound 17 was obtained as a white solid in 94% yield (76 mg, 0.19 mmol) and 99:1 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 6-methoxyisatin (36 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. 1H NMR (399 MHz, DMSO-d6): δ = 10.35 (s, 1H), 7.49 – 7.30 (m, 5H), 7.11 (dd, J = 7.2, 6.7 Hz, 1H), 6.96 – 6.90 (m, 2H), 6.80 (s, 1H), 6.58 (d, J = 7.9 Hz, 1H), 6.33 – 6.27 (m, 2H), 6.25 – 6.16 (m, 1H), 3.67 (s, 3H). 13C NMR (100 MHz, DMSO-d6): δ = 174.2 (d, JC-F = 2.2 Hz), 168.6 (d, JC-F = 21.7 Hz), 161.4, 144.4 (d, JC-F = 6.9 Hz), 133.0, 132.0 (d, JC-F = 2.7 Hz), 129.7, 128.6, 126.9, 126.4, 125.8, 123.2 (d, JC-F = 2.4 Hz), 121.8, 121.7, 117.4 (d, JC-F = 4.4 Hz), 109.2, 106.3, 96.4, 94.0 (d, JC-F = 205.4 Hz), 76.7 (d, JC-F = 23.9 Hz), 55.4. 19F NMR (376 MHz, DMSO-d6): δ = -176.4. Anal. Calcd. for C23H17FN2O4: C, 68.31; H, 4.24; N, 6.93. Found: C, 68.26; H, 4.29; N, 6.91.</p><!><p>Compound 19 was obtained as a white crystalline solid in 92% yield (104 mg, 0.18 mmol) and >99:1 dr from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and tert-butyl (1-benzyl-2-oxoindolin-3-ylidene)carbamate (67 mg, 0.20 mmol) after stirring in isopropyl alcohol for 24 hours as described above. Decomp. 178 °C. 1H NMR (399 MHz, CDCl3): δ = 7.70 (d, J = 7.5 Hz, 1H), 7.59 – 7.40 (m, 6H), 7.32 (dd, J = 7.8, 7.8 Hz, 1H), 7.24 – 7.02 (m, 5H), 6.74 – 6.56 (m, 5H), 5.83 (d, J = 7.5 Hz, 1H), 4.89 (d, J = 15.7 Hz, 1H), 4.45 – 4.28 (m, 1H), 1.28 (s, 9H). 13C NMR (100 MHz, CDCl3): δ = 172.4 (d, JC-F = 8.0 Hz), 170.0 (d, JC-F = 21.8 Hz), 154.09, 145.1 (d, JC-F = 5.1 Hz), 144.0, 135.2, 133.1, 132.1 (d, JC-F = 2.4 Hz), 130.1, 129.8, 128.8, 128.6, 127.2, 126.9, 126.8, 126.0, 125.4 (d, JC-F = 2.8 Hz), 123.2 (d, JC-F = 2.4 Hz), 123.1, 120.5 (d, JC-F = 18.0 Hz), 110.0, 109.1, 90.5 (d, JC-F = 204.3 Hz), 80.3, 66.6 (d, JC-F = 22.9 Hz), 44.3, 28.1. 19F NMR (376 MHz, CDCl3): δ = -170.5. HRMS (ESI-TOF) m/z: [M + Na]+ Calcd for C34H30FN3O4Na 586.2118; Found 586.2111.</p><!><p>Compound 21 was obtained as a white solid in 91% yield (105 mg, 0.18 mmol) and 96:4 dr from 1-benzyl-3-fluoroindolin-2-one (48 mg, 0.20 mmol) and tert-butyl (1-benzyl-2-oxoindolin-3-ylidene)carbamate (67 mg, 0.20 mmol) after stirring in isopropyl alcohol for 24 hours as described above. 1H NMR (399 MHz, CDCl3): δ = 7.67 (d, J = 7.4 Hz, 1H), 7.54 (s, 1H), 7.44 – 7.37 (m, 2H), 7.33 – 7.24 (m, 4H), 7.18 (dd, J = 7.5, 7.5 Hz, 1H), 7.15 – 7.06 (m, 2H), 6.99 (dd, J = 7.5, 7.5 Hz, 2H), 6.68 – 6.59 (m, 3H), 6.57 – 6.45 (m, 2H), 5.69 (d, J = 7.5 Hz, 1H), 5.13 (d, J = 15.9 Hz, 1H), 4.93 (d, J = 15.7 Hz, 1H), 4.79 (d, J = 15.8 Hz, 1H), 4.47 – 4.25 (m, 1H), 1.29 (s, 9H). 13C NMR (100 MHz, CDCl3): δ = 172.2 (d, JC-F = 7.5 Hz), 170.7 (d, JC-F = 23.1 Hz), 154.1, 144.1 (d, JC-F = 5.0 Hz), 143.9, 135.2, 134.5, 132.1 (d, JC-F = 3.1 Hz), 130.0, 128.9, 128.6, 127.8, 127.4, 127.1, 126.9, 125.9, 125.5 (d, JC-F = 3.0 Hz), 123.1, 122.9 (d, JC-F = 2.7 Hz), 120.9 (d, JC-F = 17.8 Hz), 110.2, 109.1, 91.4 (d, JC-F = 201.9 Hz), 80.3, 66.2 (d, JC-F = 23.1 Hz), 44.5, 44.3, 28.2. 19F NMR (376 MHz, CDCl3): δ = -167.1. HRMS (ESI-TOF) m/z: [M + Na]+ Calcd for C35H32FN3O4Na 600.2275; Found 600.2267.</p><!><p>Compound 23 was obtained as a white crystalline solid in 99% yield (106 mg, 0.20 mmol) from 3-fluoro-1-phenylindolin-2-one (45 mg, 0.20 mmol) and 1,1-bis(phenylsulfonyl)ethene (65 mg, 0.20 mmol) after stirring in isopropyl alcohol for 30 minutes as described above. Mp. 127-128 °C. 1H NMR (399 MHz, DMSO-d6): δ = 7.99 – 7.87 (m, 4H), 7.84 – 7.76 (m, 2H), 7.72 -7.56 (m, 7H), 7.54 – 7.41 (m, 4H), 7.23 (dd, J = 7.5, 7.5 Hz, 1H), 6.82 (d, J = 7.9 Hz, 1H), 5.69 (dd, J = 4.4, 4.4 Hz, 1H), 3.42 (ddd, J = 17.9, 14.1, 4.3 Hz, 1H), 3.02 (ddd, J = 32.4, 17.3, 4.5 Hz, 1H). 13C NMR (100 MHz, DMSO-d6): δ = 170.4 (d, JC-F = 23.0 Hz), 143.1 (d, JC-F = 5.2 Hz), 137.8, 136.9, 135.1, 134.9, 132.9, 132.2 (d, JC-F = 2.9 Hz), 129.8, 129.5, 129.4, 129.4, 129.0, 128.7, 126.4, 125.3, 124.1, 123.9 (d, JC-F = 2.1 Hz), 110.1, 89.3 (d, JC-F = 188.9 Hz), 76.1, 30.3 (d, JC-F = 30.6 Hz). 19F NMR (376 MHz, DMSO-d6): δ = -155.2 (dd, J = 32.4, 13.9 Hz). HRMS (ESI-TOF) m/z: [M + Na]+ Calcd for C28H22FNO5S2Na 558.0821; Found 558.0816.</p>

PubMed Author Manuscript

Dialumenes – aryl <i>vs.</i> silyl stabilisation for small molecule activation and catalysis

Main group multiple bonds have proven their ability to act as transition metal mimics in the last few decades.However, catalytic application of these species is still in its infancy. Herein we report the second neutral NHC-stabilised dialumene species by use of a supporting aryl ligand (3). Different to the trans-planar silyl-substituted dialumene (3 Si ), compound 3 features a trans-bent and twisted geometry. The differences between the two dialumenes are explored computationally (using B3LYP-D3/6-311G(d)) as well as experimentally. A high influence of the ligand's steric demand on the structural motif is revealed, giving rise to enhanced reactivity of 3 enabled by a higher flexibility in addition to different polarisation of the aluminium centres. As such, facile activation of dihydrogen is now achievable. The influence of ligand choice is further implicated in two different catalytic reactions; not only is the aryl-stabilised dialumene more catalytically active but the resulting product distributions also differ, thus indicating the likelihood of alternate mechanisms simply through a change of supporting ligand.

dialumenes_–_aryl_<i>vs.</i>_silyl_stabilisation_for_small_molecule_activation_and_catalysis

Introduction<!>Synthesis of aryl-stabilised dialumene<!>Computational discussion of aryl-stabilised dialumene<!>Reactivity of dialumenes<!>Small molecule activation<!>Catalysis<!>CO 2 hydroboration<!>Conclusions<!>Conflicts of interest

<p>The ability to isolate and stabilise complexes containing metalmetal bonds is of fundamental interest, providing both experimental and theoretical insights into the intrinsic nature of the metal centre. 1 Since the discovery that the so-called 'double bond rule' could be broken in the beginning of the last quarter of the 20th century, 2-5 efforts within main group chemistry have strived towards isolating a plethora of both homo-and heteromain group element multiply bonded compounds, which have been the subject of numerous reviews. 6,7 Aside from curiosity, one of the driving forces behind this research area is the ability to use main group multiple bonds as transition metal mimics. [8][9][10] This is possible due to similarly energetically accessible frontier molecular orbitals. Thus, reduction of small molecules, such as dihydrogen, under ambient conditions by sustainable main group metal centres is achievable. 11 Whilst the ability to mimic transition metals is now possible in regard to oxidative addition reactions, main group elements still fall short in terms of catalytic activity due to the resulting stability of the higher oxidation state complexes, i.e. the rst step in a redox based catalytic cycle. In order to truly compete with transition metals that are currently employed in industry, the ability to inuence the stability, and thus reactivity, of main group metal centres is paramount. One method of inuencing stability is through choice of stabilising ligand. If you consider disilenes, the choice of silyl, aryl and nitrogen-based ligands has been shown to inuence the structural parameters around the double bond, 12,13 with silyl groups tending towards transplanar geometries 13 and aryl groups promoting trans-bent character. It was not until the use of an N-heterocyclic imine (NHI) based ligand, which results in a highly trans-bent and twisted geometry, that dihydrogen activation was achieved. 14 An electropositive silyl supporting ligand was used to stabilise the rst neutral aluminium-aluminium double bond, namely dialumene. 15 DFT calculations found the HOMO to consist of a p-bond formed from almost pure Al p-orbitals and as such a planar geometry was observed. As predicted, the dialumene behaved as a transition metal mimic towards a variety of small molecules, as well as enabling catalytic reduction of CO 2 . 16 Prior to the isolation of the rst neutral dialumene, several compounds with Al-Al bond orders greater than 1 were isolated. 17 These can be classed as radical monoanionic species, one electron p-bonded compounds, a dianionic complex and masked dialumenes. The stick with latter, reported independently by Power 18 and Tokitoh, 19 proposed the intermediacy of aryl-stabilised dialumenes, with the masked species being a result of [2 + 4]-cycloaddition reaction due to the use of aromatic solvent. This was additionally accounted for through a series of [2 + 2]-cycloaddition reactions with internal alkynes. Tokitoh further showed that the benzene derived masked species was capable of activating dihydrogen; 20 however, upon switching to an anthracene derived masked species no reactivity towards dihydrogen was observed.</p><p>On descending group 13, heavier digallenes and dithallenes have been isolated which show notable trans-bent character and have been known to dissociate to their corresponding monomers in hydrocarbon solutions. [21][22][23][24][25] However, digallanes have been shown to react as the double bonded species, rather than the monomer with regards to cycloadditions of unsaturated C-C bonds and even dihydrogen activation. [26][27][28] Motivated by our group's previous efforts in dialumene chemistry, we targeted the isolation of a neutral aryl-stabilised dialumene to compare the intrinsic nature of the aluminiumaluminium double bond through the inuence of ligand stabilisation. Whilst silyl and aryl groups have been routinely used in main group multiple bond chemistry, no direct comparisons of their inuence on multiple bonds as reactive species have been drawn. As such, we proposed a systematic study of both dialumenes towards activation of a range of small molecules and their use in catalysis, with the aim of providing experimental and theoretical insight into the inuence of these ligand classes on main group multiple bond reactivity.</p><!><p>Following on from the successful isolation of the rst neutral dialumene, we focused our attention on expanding the scope of this class of compounds towards aryl stabilised systems. As such, we targeted the use of the Tipp ligand (Tipp ¼ 2,4,6-tri-isopropylphenyl) for the stabilisation of a new dialumene. In keeping with the previous dialumene, the choice of Nheterocyclic carbene (NHC) remained the same, I i Pr 2 Me 2 (I i Pr 2 Me 2 ¼ 1,3-di-iso-propyl-4,5-dimethyl-imidazolin-2ylidene). Direct reaction of I i Pr 2 Me 2 AlH 3 and LiTipp at À78 C resulted in formation of the monosubstituted aluminium dihydride complex I i Pr 2 Me 2 Al(Tipp)H 2 (1) (Scheme 1) in good yield (66%, 27 Al: d 112.9 ppm). 29 The identity of compound 1 was conrmed upon inspection of the 1 H NMR spectrum wherein three resonances for the iso-propyl groups were identied in a 2 : 2 : 1 ratio (NHC : o-Tipp : p-Tipp iso-propyl signals) as well as a characteristic broad signal for the Al-H 2 protons ( 1 H: d 5.11 ppm). Additionally, a sharp IR stretching band at 1711 cm À1 (Al-H) was observed in the IR spectrum.</p><p>Conversion of 1 towards formation of I i Pr 2 Me 2 Al(Tipp)I 2 (2) could be achieved through reaction with BI 3 $dms (dms ¼ dimethyl sulde) or with a small excess of methyl iodide, with the latter resulting in higher and cleaner conversion; moreover, the concomitant formation of methane allows for facile reaction monitoring. Loss of signals relating to Al-H were observed in both the 1 H NMR and IR spectra, and further characterisation by single crystal XRD conrmed the identity of 2 (Fig. S54 †). Compound 2 is structurally analogous to the corresponding silyl supported complex (2 Si ) with Al-C NHC bond lengths essentially the same (2: 2.0645(18) Å; 2 Si : 2.0673(17) Å), indicating the dative nature of the NHC ligand. This is additionally conrmed on comparison with the Al-C Tipp bond length (1.9887(19) Å), which is smaller than the sum of the covalent radii (R Al-C ¼ 2.01 Å). 30 Following the analogous synthetic protocol to the silyl dialumene, compound 2 was stirred vigorously with KC 8 at room temperature (Scheme 1). Through monitoring the reaction by 1 H NMR, it was found that this reaction requires 72 hours rather than the 24 hours required for the previous case. Compound 3 was isolated as a black solid, and in contrast to the silyl stabilised dialumene (3 Si ), 3 is highly soluble in a broad range of aromatic, alkyl and ethereal solvents. Both dialumenes are stable in the solid state in an inert atmosphere for prolonged periods; however, they decompose in solution aer 24 hours. The 1 H NMR spectrum of 3 shows a large broad signal at room temperature ($7.0-5.5 ppm) which resolves into distinct signals at 228 K for the iso-propyl groups, indicating a degree of rotational uxionality in this system (Fig. S11 †).</p><p>Single crystals were grown from a concentrated n-hexane solution at 5 C and revealed a trans-bent and twisted geometry of the aryl stabilised dialumene (compound 3, Fig. 1) (q ¼ 17.25 , 23.70 , s ¼ 12.06 ), which contrasts with the trans-planar geometry observed previously. Furthermore, in 3 Si the NHC groups were found to be parallel to each other, whilst in 3 they are found to be almost perpendicular (85 ). The change from a planar to a trans-bent and twisted geometry has also been observed in disilene chemistry on switching between aryl and silyl-based ligands. 12,13 The Al-Al bond length is 2.4039(8) Å which is fractionally longer than that in the previous dialumene (3 Si : 2.3943(16) Å). Another notable difference between the two systems lies in the Al-C NHC bond length (3: 2.0596(16), 2.0422(17); 3 Si : 2.073(3) Å). The shorter bond length in the case of aryl stabilisation likely indicates a decrease in dative character and thus an increase in the covalent nature of the Al-C NHC bond (which is also supported by the calculated bond dissociation energy, see below).</p><!><p>To gain a deeper insight into the differences between these two classes of dialumenes, we performed density functional theory (DFT) calculations at the B3LYP-D3/6-311G(d) level of theory (for detailed information see the ESI †). The optimised geometry of 3 is in good agreement with experimental values, with the addition of the dispersion required to account for the trans-bent and twisted geometry. For comparison, all calculated values for 3 Si including dispersion are given in the ESI. † Analysis of the frontier orbitals of 3 revealed similar features to 3 Si , in which the HOMOÀ1 and HOMO contain the Al-Al sand p-bonds, respectively, as well as the LUMO representing the Al-C NHC p bond (Fig. 2). The main difference to 3 Si (see Fig. S57 † for the corresponding orbitals) is the loss of uniform arrangement of the HOMO on the two aluminium centres as well as additional p-incorporation of the NHC present in 3. We attribute this to the different orientation of the NHCs in 3, enabling overlap with the p-orbital of the carbene carbon atom, which is experimentally observed as a shortened Al-C NHC bond in the SC-XRD structure and further evidenced by an increased Gibbs free energy of bond dissociation of 26.0 kcal mol À1 (cf. 3 Si ¼ 16.9 kcal mol À1 ). The conjugation towards the Al-C NHC p-bond in 3 is also observed on inspection of the monomers (for further details see ESI Fig. S62 †), which also gives rise to the decreased HOMO-LUMO gap in 3 compared to 3 Si (3 ¼ 1.86 eV, 3 Si ¼ 2.24 eV) based on decreased overlap of the monomers being possible. TD-DFT calculations corroborated the experimental UV/vis spectrum of 3. This showed an intense absorption band at 833 nm (3 ¼ 6273 L mol À1 cm À1 ) (calc. value 794 nm), which can be assigned to the HOMO to LUMO transition and is responsible for the highly coloured compound. 31 Natural bond orbital (NBO) analysis provided electronic insight into the nature of the Al-Al double bond. The Al-Al p-bond of 3 bears reduced pcharacter compared to 3 Si . Moreover, this NBO orbital has a lower occupancy based on partial population of the p*orbitals of the C-N bonds of the NHC, rationalising the increased interaction of the NHC for 3. This is based on its different orientation, which we mainly attribute to the reduced steric demand of the ligand. Furthermore, this is reected in the decreased Wiberg bond index (WBI) of the Al-Al bond of 1.67 to 1.53 going from silyl to aryl (Fig. 3), yet still indicating a high degree of multiple bonding character in both systems.</p><p>Analysis of NPA charges clearly reects the silyl effect (Fig. 3): the aluminium centres in 3 Si bear a nearly neutral charge of +0.08, while in 3 they account for +0.48/+0.49. We attribute this to the silyl substituents, with their strong s-donating properties, possessing a more effective orbital overlap with the aluminium centres in the s(Al-Si) bonds. This also becomes evident upon examination of the results of NBO analysis for the Al-C Tipp /Al-Si bonds: the Al-C Tipp bonds are highly polarised (17% Al, 83% C Tipp ) compared to Al-Si bonds in 3 Si (36% Al, 64% Si). This difference is also rationalised upon comparison of Al-C and Al-Si Pauling electronegativities (Dc Al-C 0.94; Dc Al-Si 0.29), thus resulting in less polarised Al-Si bonds.</p><p>To elucidate the effect of sterics around the aluminium centre, we initially compared the steric demand of the Tipp and Si t Bu 2 Me ligands, which revealed similar percentages of buried volume (% V bur ) of 29.9% (3) and 30.7% (3 Si ) (Fig. S58 and S59 †). However, the shape and thus distribution of kinetic stabilisation vary. Further calculation and comparison of reduced model systems were performed with the I i Pr 2 Me 2 carbene replaced by IMe 4 ( IMe4 3 and IMe4 3 Si , Fig. S60 †). 32 For IMe4 3 Si the most stable isomer exhibits a strongly transbent and twisted geometry (q ¼ 42.1 , 30.4 , s ¼ 11.7 ) with the NHC planes orientated almost parallel and a substantially elongated Al-Al bond length of 2.43 Å. In the Tipp-substituted IMe4 3 the trans-bent character is decreased compared to 3, accompanied by a small increase of the Al-Al bond length due to further rotation of the NHC planes towards the Al-Al plane, enabling more effective p-interaction of NHC and the AlAl moiety. This also becomes more apparent upon examination of the corresponding frontier orbitals with IMe4 3. This features enhanced delocalisation of the HOMO onto the NHC moiety, as a consequence of further rotation of the NHC planes towards the Al-Al bond (angle between NHC planes: 49 ). In contrast, the HOMO in IMe4 3 Si exhibits contributions from the silyl groups, as conjugation towards the NHC p-system is not possible due to the different orientation. Moreover, the HOMO-LUMO gap decreases for aryl and increases for the silyl case, attributed to the decreased/increased trans-bent geometry.</p><p>The smallest possible model systems, by reducing I i Pr 2 Me 2 to IH 4 as well as Tipp/Si t Bu 2 Me to phenyl/TMS, were calculated and yield comparable results: S 3 and S 3 Si both possess transbent but no twisted conguration. In S 3 Si a slightly shorter Al-Al bond length and a decreased trans-bent angle (21.2 vs. 31.8 for S 3) are observed; however, in each case the NHC planes are rotated towards the Al]Al bond (see Fig. S61 †). Hence, transbent structures are obtained for the aryl and the silyl substituted dialumenes bearing minimal steric effects. Thus, it is clearly demonstrated that the steric effects of both NHC and the ligands govern the binding motif of dialumenes. The shape of the ligand inuences the interaction with the NHC: either only a weak and purely s-donating type of interaction, as observed in planar 3 Si , or more exible coordination of the NHC, with the porbital of the C carbene able to form a slipped p-bond with the AlAl core, as observed in 3. The trans-bent and twisted structure obtained for 3 is therefore a result of the difference in steric demand of the Tipp ligand compared to Si t Bu 2 Me.</p><p>From the different aspects, steric as well as electronic, discussed above we thus conclude that the structural difference between 3 and 3 Si is caused by the different steric demand of the ligands. From the electronic point of view the change of silyl to Tipp ligand in the dialumene changes the orbital situation at the central AlAl core, which is accompanied by a reduced HOMO-LUMO gap. Moreover, the polarisation of the aluminium centres is different, based on differences in electronegativity between C and Si. We thus anticipate differences in reactivity with respect to activation of strong bonds, such as those in small molecules, as well as an increased accessibility towards a bigger range of reagent molecules of 3, based on the increased exibility of this system.</p><!><p>Further differences between these two systems were sought experimentally. Firstly, reactivity towards a series of C-C multiple bonds was examined (Scheme 2). In the case of ethylene, compound 3 underwent formal [2 + 2]-cycloaddition to yield the dialuminacyclobutane compound 4, akin to the reactivity observed with 3 Si . 15 Upon reaction with 1 equivalent of phenylacetylene, clean formation of a single species by NMR spectroscopy was noted to occur to form compound 5. This is in contrast to the reactivity of 3 Si where both [2 + 2]-cycloaddition (5 Si ) and C-H activation were observed. Varying the number of equivalents of phenyl acetylene (2 : 1 and 3 : 1 with respect to 3) did not result in further incorporation of phenyl acetylene into the complex even at elevated temperatures. However, compound 5 was found to decompose in solution to yield styrene (see ESI Fig. S37 and S38 †). Monitoring a C 6 D 6 solution of 5 showed that this occurs intramolecularly, with the additional protons required to make styrene likely the result of C-H activation. In further support of an intramolecular C-H activation, addition of a hydrogen source, e.g. dihydrogen, phenyl silane, pinacol borane or amine borane, failed to provide any notable increase in the rate of styrene formation. Unfortunately, attempts to identify the fate of the resulting aluminium containing species were unsuccessful. It is proposed that initially [2 + 2]-cycloaddition occurs to form compound 5, followed by C-H activation of the iso-propyl groups of the Tipp ligand, as this was not observed with the analogous silyl complex. Intramolecular C-H activation of the Mes* ligand (Mes* ¼ 2,4,6-tri-tert-butylphenyl) has been previously observed by thermolysis of (Mes*) 2 AlH, 33 Further reactivity towards C-C multiple bonds was trialed with diphenylacetylene (PhCCPh). Addition of 1 eq. of PhCCPh to 3 Si failed to cause a reaction, and aer prolonged heating only decomposition of 3 Si was observed. In contrast, PhCCPh was observed to react readily with 3, notably through the instant colour change from the dark black solution of 3 to a yellow solution of compound 6. This difference in reactivity was surprising, considering that both 3 and 3 Si reacted cleanly with both non-polar (ethylene to form 4 and 4 Si ) and polar (phenylacetylene to form 5 and 5 Si ) C-C multiple bonds. This difference in reactivity is thought to be a direct result of the choice of stabilising ligand. The exibility of the Tipp ligand, due to the rotational iso-propyl groups, makes the central AlAl core more accessible for reactant molecules, thus enabling reactivity with more sterically demanding reagents. Moreover, the positive NPA charges of 3 make it more electrophilic in comparison to 3 Si , thus implying higher reactivity towards nucleophilic C-C multiple bonds.</p><p>Compounds 4 and 6 were crystallised from concentrated pentane solutions at À30 C. The XRD structures revealed addition of the C-C multiple bonds to the dialumene, resulting in the formation of 4-membered rings (Fig. 4). Loss of double bond character from the dialumene was conrmed due to elongation of the Al-Al bond (4 2.6035(13), 6 2.5918(6) vs. Extension of this work towards C-N triple bonds focused on the use of 2,6-dimethylphenylisocyanide (XylNC). Previously, Tokitoh and co-workers had shown that reaction of their masked dialumene species resulted in homocoupling of isocyanides. 35 Reactions of varying equivalents of XylNC to 3 Si all resulted in an ill-dened mixture of species; unfortunately, attempts to separate species through fractional crystallisation failed. In contrast, reaction of 2 eq. of XylNC with 3 resulted in a clear colour change from black to red and produced a well-dened but complex 1 H NMR spectrum of compound 7 (Scheme 3). This complex contains bridging CNXyl units due to the observed downeld signal in the 13 C NMR spectrum at d 303.4 ppm. This was similar to the previously observed bridging carbonyl fragment observed with 3 Si , in the rearrangement of CO 2 (d 276.0 ppm) 16 and the bridging isocyanide intermediate reported by Tokitoh (d 294.7 ppm). 35 Single crystals of 7 were grown from a 2 : 1 (toluene : hexane) mixture at 5 C, revealing a buttery conguration with two m-CNXyl units (Fig. 5).</p><p>The central Al-C Xyl -Al-C Xyl core in compound 7 is puckered (34. 4) Å), which is in line with average C]N bond lengths. [36][37][38][39] Additionally, the change in angle around the nitrogen in XylNC from linear to bent (126.3 (2) ) conrms reduction of the C-N triple bond. This buttery conguration has been previously observed with transition metal complexes; [40][41][42][43][44][45][46][47] however, they all contain a M-M bond, and those without M-M bonds contain a planar central ring. [48][49][50][51][52] To conrm the nature of the bonding within compound 7 DFT studies were performed again, at the B3LYP-D3/6-311G(d) level of theory. The optimised structure is in good agreement with the one obtained experimentally by SC-XRD, including the calculated C]N IR stretching frequencies (experimental: 1545 cm À1 vs. calculated: 1568 cm À1 ). Orbital analysis (Fig. 6)</p><!><p>Further reactivity differences were sought through investigation towards small molecules (Scheme 4). Previously, reaction of 3 Si towards carbon dioxide (CO 2 ) resulted in an initial CO 2 xation complex. 16 This subsequently underwent C-O cleavage reaction, in the absence of additional CO 2 through rearrangement to a bridging carbonyl complex, whilst in the presence of CO 2 , formation of a carbonate species with elimination of CO was observed. On reaction of 3 with CO 2 immediate loss of the black colour and formation of a colourless solution was observed. On inspection of the 13 C NMR spectrum, the presence of CO (d 184.4 ppm) and CO 3 (d 159.12 ppm) was observed, indicating the formation of the carbonate complex compound 9. In contrast to 3 Si , attempts to isolate the CO 2 xation product were unsuccessful as it rapidly converted to compound 9. Use of the labile I i Pr 2 Me 2 -CO 2 species allowed for the formal [2 + 2]cycloaddition product (compound 8) to be observed due to its characteristic 13 C resonance at d 207.7 ppm (8 Si d 209.9 ppm). However, this reaction resulted in multiple species as well as compound 9, owing to the higher reactivity of the Tipp dialumene (compound 3), thus indicating that formation of 9 proceeds through the CO 2 xation species in a similar manner to 3 Si . Reaction of 3 with O 2 resulted in the expected dioxo product, compound 10, same as the previously reported reaction of 3 Si . In a similar manner to 10 Si , compound 10 can also be reacted with CO 2 resulting in carbonate complex 9. In a notable difference to the silyl supported reactivity, addition of N 2 O to compound 3 resulted in a dark red solution at room temperature (3 Si yielded colourless compound 10 Si ). This red solution was observed to slowly fade to colourless over a few hours and the formation of compound 10 was conrmed by 1 H NMR spectroscopy. Use of 1 eq. of an oxygen donor reagent, namely N-methylmorpholine-N-oxide, with 3 allowed for clean isolation of the red species, compound 11. Compound 11 is stable in the solid state for up to two months in a glovebox freezer; however, at room temperature and in solution, further oxidation to compound 10 occurs. Whilst 1 H NMR showed similar environments for both 10 and 11 (Fig. S39 †), compound 11 is intensely coloured (UV/vis ¼ 512 nm, 3 ¼ 1155 L mol À1 cm À1 ) whilst 10 is colourless. As such compound 11 was tentatively assigned as a bridging aluminium(II) mono-oxide species, rather than a terminal aluminium(III) mono-oxide complex. Unfortunately, SC-XRD analysis did not provide clear structural parameters for the mono-oxide species due to superposition with compound 10 (Fig. S55 †). To provide further insight, calculations were also performed on compounds 10 and 11. The optimised structure of 10 is symmetric relating to the Al-O bonds, as previously observed for the analogous silyl compound (10 Si ). 16 TD-DFT calculations revealed the highest transition at 259 nm, in line with the experimental colourless appearance. In contrast, compound 11 bears substantial p-electron density between the two aluminium centres in the HOMO as depicted in Fig. 7, reminiscent of the disilaoxirane reported by our group. 53 The LUMO represents the unoccupied p(Al-C NHC ) bond. TD-DFT calculations veried the experimentally observed red colour (UV-vis 512 nm) with good accordance (calc. 519 nm), assigned to the HOMO to LUMO transitions of 11.</p><p>Extension of this small molecule reactivity towards dihydrogen was investigated. Firstly, a J-Young NMR tube containing a purple solution of 3 Si was freeze-pump-thaw degassed and then backlled with approximately 1 atm of H 2 . Aer 24 hours at room temperature no reaction was noted to have occurred; increasing the temperature to 60 C and regular monitoring only resulted in the observed decomposition of 3 Si .</p><p>Repetition of this reaction with the aryl stabilised dialumene, compound 3, also resulted in no reaction at room temperature. Aer 16 h at 50 C, however, the black colour of 3 had faded to a dark brown/yellow solution (Scheme 5). On inspection of the 1 H NMR spectrum, no Al-H signals could be observed owing to the quadrupolar nature of the Al centre. Additionally, three distinct iso-propyl signals similar to that observed for compound 1 were identied. These, however, were not identical and therefore complete hydrogenation and cleavage of the Al-Al bond can be ruled out. Thus, it is likely that compound 12 consists of either terminal or bridging hydrides.</p><p>IR spectroscopy was utilised to differentiate between the two likely structures; two broad but distinct peaks at 1593 and 1634 cm À1 were observed. Compounds containing no Al-Al bond but both terminal and bridging hydrides are found at approximately 1880 cm À1 and 1350 cm À1 , respectively, 20,54 whilst terminal hydrides within complexes containing Al-Al bonds are found within 1680-1835 cm À1 , 55 thus pointing more in the direction of a terminal hydride with Al-Al bonds. Additionally, for the previous terminal hydride in the related silyl system, from C-H activation of phenyl acetylene, this Al-H was found at 1666 cm À1 . 15 Unfortunately, attempts to grow crystals suitable for SC-XRD were unsuccessful. Therefore, additional insight for this structure was sought computationally. Different possible isomers of product 12 were calculated, including bridging, terminal, and combinations of both as well as different rotational isomers (H: cis or trans; NHC and Tipp ligands: cis or trans).</p><p>The two lowest lying isomers were found to possess terminal hydrides in the cis and trans congurations (Fig. 8). The Al-H stretching frequencies were calculated to be 1634 and 1676 cm À1 , respectively, which is in good agreement with the experimentally obtained values (for detailed information see the ESI †). It is, therefore, suggested that the activation of hydrogen by 3 results in both the cis and trans isomers of compound 12.</p><!><p>Further comparisons between the two dialumenes examined their use in catalytic applications. Two archetypal catalytic reactions (hydroboration and dehydrocoupling) were studied due to their prevalence in main group catalysis, as well as the implication of metal-hydrides in facilitating turnover. 56,57 With the ability to form dialuminium-hydrides in the case of 3 and not for 3 Si , differences in activity and mechanistic pathways are anticipated.</p><!><p>Previously, 3 Si was found to selectively catalyse the reduction of CO 2 to a formic acid equivalent (product A, Scheme 6) with pinacol borane (HBpin). 16 Whilst this reaction does proceed at room temperature, it required up to 1 week and 10 mol% of 3 Si (Table 1, entry 1); use of higher temperatures allowed for reduced catalyst loadings and decreased reaction times (Table 1, entry 2). As 3 has so far shown increased reactivity, a trial reaction with 5 mol% of 3 towards hydroboration of CO 2 at room temperature was carried out (Table 1, entry 3). On regular monitoring through 1 H and 11 B NMR spectroscopy the consumption of HBpin was noted to occur along with the formation of new B-O containing species. The corresponding 1 H NMR spectrum showed the presence of further reduced species (A-D, Scheme 6), indicating that 3 is not only more catalytically active, but also proceeds through an alternate mechanism due to the presence of B-C.</p><p>Again, through use of a higher temperature (60 C), the catalyst loading could be decreased down to 1 mol% (Table 1, entry 5). This resulted in the same consumption of HBpin aer 24 h (at RT) as with 5 mol% (Table 1, entry 4); however, the resulting product distribution differs, with higher temperatures favouring the formation of the triply reduced methanol equivalent (product C, Scheme 6).</p><p>The formation of more highly reduced species indicates a likely change in the mechanism. Previously, 3 Si showed no reactivity towards HBpin and as such a non-hydridic mechanism based on the initial formation of 9 Si was proposed. From computational analysis, coordination of HBpin and subsequent reduction of the exocyclic carbonyl of 9 Si was found to be rate determining. Turnover was achieved through coordination/ insertion of an additional CO 2 on the opposite side of the Al/Al plane resulting in formation of an 8-membered ring which collapses to reform 9 Si with release of the formic acid equivalent. This mechanism also further supports the observed selectivity towards product A. 16 In this instance, use of 3 results in the formation of products B-D in notable amounts; therefore, an alternative mechanism for the hydroboration of CO 2 is highly likely. As such, 3 was reacted with 1 eq. of HBpin; the 11 B NMR spectrum showed complete consumption of HBpin and formation of a new upeld doublet at d 2.57 ppm (J HB ¼ 112.18 Hz). The same signal and coupling were observed from the reaction of HBpin and I i Pr 2 Me 2 ; therefore it is proposed that the stoichiometric reaction of 3 and HBpin results in NHC abstraction. Notably, this does not result in H-B bond cleavage and formation of an Al(H)-Al(Bpin) type species, which was observed with diborene 58 and disilyne 59 chemistry. Addition of CO 2 to this I i Pr 2 Me 2 -HBpin adduct did not result in formation of any reduced CO 2 species, or any reaction aer 24 h at room temperature; therefore it is unlikely that this is the catalytically active species. It is of note that NHCs have been shown to catalyse hydroboration (with HBpin) of carbonyl compounds, in acetonitrile. 60 Whilst these experimental observations preclude denitive mechanistic analysis, it is proposed that the aryl stabilised dialumene (3) acts as a pre-catalyst, with CO 2 hydroboration occurring through an initial hydroalumination of CO 2 and subsequent Al-O/B-H s-bond metathesis, in line with other previously reported main group hydroelementation of CO 2 mechanisms. [61][62][63][64][65][66][67][68][69][70] Amine borane dehydrogenation Main group catalysts (largely group 1, 2, and 13) have also been shown to be viable dehydrocoupling catalysts. 56,57,71,72 These reactions largely proceed through formation of M-H and M-E Scheme 6 Catalytic hydroboration of CO 2 mediated by dialumene (3). 2, entry 5). As aluminium-hydrides have been used in amine borane catalysis previously, 73 and to rule out complete hydrogenation and Al-Al bond cleavage during the reaction, compound 1 was tested for dehydrocoupling activity. Aer 24 h at room temperature (Table 2, entry 6) no conversion of Me 2 NHBH 3 was observed; on increasing the temperature to 60 C (Table 2, entry 7), some formation of H 2 and products A-D was observed. Due to the increased temperature and prolonged reaction times required for compound 1, it is proposed that the retention of an Al-Al bond accounts for the increased catalytic activity.</p><p>Comparable to hydroboration reactions, the aryl stabilised dialumene (3) was found to be more catalytically active than the silyl-stabilised counterpart (3 Si ). Mechanistically speaking, amine-borane dehydrocoupling reactions generally occur through formation of M-H and M-E bonds. 57 As such, it has been shown that formation of Al-H bonds is more accessible from 3 compared to 3 Si , therefore accounting for the difference in catalytic activity. Both reactions show initial formation of a catalytic equivalent of HB(NMe 2 ) 2 (product B, Scheme 7) which then remains constant throughout the catalysis. It has previously been shown by Wright and co-workers that formation of B is the result of the formation of the catalytically active Al-H containing species from Al(NR 3 ) 3 (R ¼ Me, iPr). 74 Furthermore, Braunschweig and co-workers recently showed that Me 2 NHBH 3 can be used to isolate hydrogenated diborenes; thus, analogous reactivity is anticipated. 75 However, in our hands, stoichiometric reactions of 3 and Me 2 NHBH 3 resulted in a mixture of species, whilst reaction with a higher number of equivalents of Me 2 NHBH 3 resulted in the dehydrocoupling products. We therefore conclude that the dialumene acts as a pre-catalyst in this reaction and the active catalyst is generated in situ.</p><!><p>In conclusion, we have shown the fundamental differences between aryl and silyl supporting ligands for the stabilisation of dialumenes and their subsequent inuence on reactivity. The increased exibility of the trans-bent and twisted structure for the aryl dialumene (3) enables reactivity with more sterically demanding substrates, and in addition is now able to activate dihydrogen. Further differences are observed in the catalytic ability of the two dialumenes, with the latter exhibiting higher activity. This is likely due to different mechanisms in the catalytic cycle and the ability of the aryl dialumene to stabilise a metal-hydride intermediate in contrast to the silyl ligand.</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Mechanism of the Intramolecular Claisen Condensation Reaction Catalyzed by MenB, a Crotonase Superfamily Member\xe2\x80\xa0

MenB, the 1,4-dihydroxy-2-naphthoyl-CoA synthase from the bacterial menaquinone biosynthesis pathway, catalyzes an intramolecular Claisen condensation (Dieckmann reaction) in which the electrophile is an unactivated carboxylic acid. Mechanistic studies on this crotonase family member have been hindered by partial active site disorder in existing MenB X-ray structures. In the current work the 2.0 \xc3\x85 structure of O-succinylbenzoyl-aminoCoA (OSB-NCoA) bound to the MenB from Escherichia coli provides important insight into the catalytic mechanism by revealing the position of all active site residues. This has been accomplished by the use of a stable analogue of the O-succinylbenzoyl-CoA (OSB-CoA) substrate in which the CoA thiol has been replaced by an amine. The resulting OSB-NCoA is stable and the X-ray structure of this molecule bound to MenB reveals the structure of the enzyme-substrate complex poised for carbon-carbon bond formation. The structural data support a mechanism in which two conserved active site Tyr residues, Y97 and Y258, participate directly in the intramolecular transfer of the substrate \xce\xb1-proton to the benzylic carboxylate of the substrate, leading to protonation of the electrophile and formation of the required carbanion. Y97 and Y258 are also ideally positioned to function as the second oxyanion hole required for stabilization of the tetrahedral intermediate formed during carbon-carbon bond formation. In contrast, D163, which is structurally homologous to the acid-base catalyst E144 in crotonase, is not directly involved in carbanion formation and may instead play a structural role by stabilizing the loop that carries Y97. When similar studies were performed on the MenB from Mycobacterium tuberculosis, a twisted hexamer was unexpectedly observed, demonstrating the flexibility of the interfacial loops that are involved in the generation of the novel tertiary and quaternary structures found in the crotonase superfamily. This work reinforces the utility of using a stable substrate analogue as a mechanistic probe in which only one atom has been altered leading to a decrease in \xce\xb1-proton acidity.

mechanism_of_the_intramolecular_claisen_condensation_reaction_catalyzed_by_menb,_a_crotonase_superfa

<!>Experimental Procedures<!>Ligand synthesis<!>Preparation of wild-type and mutant MenB enzymes<!>apo-ecMenB and OSB-NCoA:ecMenB<!>mtMenB<!>Enzyme kinetics<!>Active site disorder<!>The OSB-NCoA substrate analogue<!>Structure of the ecMenB:OSB-NCoA complex<!>Conformation of the A-loop<!>Binding mode of the substrate<!>Intramolecular proton transfer<!>The tetrahedral oxyanion hole<!>Structure of the mtMenB:OSB-NCoA complex<!>Novel mtMenB hexameric assembly<!>Active sites of mtMenB and ecMenB<!>Substrate analogues as mechanistic probes<!>The roles of D163 and S161<!>Mechanism of the MenB-catalyzed reaction<!>Conclusion

<p>Menaquinone (vitamin K2; Figure 1) is a polyisoprenylated naphthoquinone that functions as a redox active cofactor in the electron transport chain of most Gram positive and some Gram negative bacteria (1–2). Although humans utilize menaquinone and the related naphthoquinone vitamin K1 (phylloquinone; Figure 1) for the γ-carboxylation of glutamate residues (3–4), mammalian cells are unable to undertake the de novo synthesis of menaquinone, and thus bacterial enzymes in the menaquinone biosynthesis pathway are potential targets for antibacterial drug discovery (5–8).</p><p>The biosynthesis of menaquinone from chorismate was originally elucidated in Escherichia coli, Bacillus subtilis and Mycobacterium phlei (9–10) and recently refined by Jiang et al. (11–12) (Figure 1). A key step in this pathway is the reaction catalyzed by the 1,4-dihydroxynaphthoyl-CoA synthase (MenB) in which the second naphthoquinone aromatic ring is formed through an intramolecular Claisen (or Dieckmann) condensation involving the succinyl side chain of O-succinylbenzoate (OSB) (8, 13–14). In Claisen condensations, such as that catalyzed by the β-ketoacyl-ACP synthases, normally both nucleophile and electrophile are activated through the formation of thioesters (15–16). However, the MenB reaction is an unusual one since only the nucleophile is activated (8).</p><p>MenB is a member of the crotonase superfamily in which a common theme is the stabilization of a CoA thioester oxyanion intermediate by an oxyanion hole (16–20). This structural feature is conserved in MenB where it plays a critical role by acidifying the OSB-CoA α-protons and promoting carbanion formation (8). However the identity of the base that abstracts the α-proton has still not been fully resolved. The mechanism originally proposed by our group involved an intramolecular proton transfer from C2 to the OSB carboxylate resulting in carbanion formation and also leading to protonation of the acid, thus making it a better electrophile (8). In contrast, more recently it has been suggested that an active site Asp or a bicarbonate cofactor functions as the base (21). In addition, by analogy with enzymes such as the β-ketoacyl-ACP synthases (16), a second oxyanion hole must be present in the active site to stabilize the tetrahedral oxyanion intermediate formed by carbon-carbon bond formation. However the identity of this second oxyanion hole, which is not normally a feature of crotonase superfamily members, is an open question.</p><p>Our ability to fully elucidate the mechanism of MenB and address the questions raised above has been hindered by the lack of structural data in which the MenB active site is intact. Currently structures exist of the MenB enzymes from Mycobacterium tuberculosis (mtMenB, 1Q51, 1RJN; (8, 22)), Staphylococcus aureus (saMenB, 2UZF; (23)), Salmonella typhimurium (stMenB 3H02; (24)) and Geobacillus kaustophilus (gkMenB, 2IEX; (25)). However in each case a portion of the MenB active site is disordered. This region displays variability in sequence even within the MenB family and also little conservation in structure throughout the crotonase superfamily, which has hindered our attempts to use sequence homology to predict the function of amino acids in this part of the active site. Although several of these enzymes were crystallized in the presence of acyl-CoA ligands, including the product of the reaction, only in the case of acetoacetyl-CoA can the acyl group be visualized. We hypothesized that a stable analogue of the substrate that retained all enzyme-substrate interactions would make an ideal structural probe and consequently we used a chemoenzymatic approach to synthesize OSB-aminoCoA (OSB-NCoA) in which the thioester sulfur is replaced by a nitrogen. The resulting decrease in α-proton acidity resulting from conversion of the CoA thioester into an amide reduces the stability of the carbanion sufficiently so that the Claisen condensation reaction is prevented. Subsequent structural studies revealed that the OSB-NCoA successfully traps the previously disordered active site region in a well-defined conformation, providing valuable information on substrate recognition and the catalytic mechanism of this intriguing reaction.</p><!><p>Chemicals were purchased from commercial suppliers (Sigma-Aldrich, Acros Organics, Alfa Aesar) and used without further purification. All solvents were purchased from Fisher Scientific. 1H-NMR spectral data were recorded on a Varian Gemini-2300 or Varian Inova-400 NMR spectrometer. Mass spectral data were obtained using an Agilent 1100 LS-MS electrospray ionization single quadrupole mass spectrometer. HPLC analysis was performed using a Shimadzu LC-10AVP chromatography system with an XTerra MS C18 reverse-phase column (4.6×100 mm, 3.5 μm) and by running a linear gradient of 0–100% solvent B (acetonitrile) in solvent A (5% acetic acid/H2O) over 20 min at a flow rate of 1ml/min.</p><!><p>OSB-aminoCoA (OSB-NCoA; Figure 2) was synthesized chemoenzymatically according to the route shown in Scheme 1 (Figure S1). This method is based on the strategy employed for the synthesis of acyl-CoA analogues initially described by Drueckhammer (26–27) and employed by us for the synthesis of crotonyl-oxyCoA (28) in which the OSB-aminopantetheine is initially synthesized chemically and then converted to the final product using enzymes from the CoA biosynthetic pathway. OSB-CoA methyl ester and OCPB-CoA (Figure 2) were synthesized from the respective acids and CoA. A detailed description of the synthetic methods together with compound characterization is given in the supplementary information.</p><!><p>The MenB enzyme from Mycobacterium tuberculosis (mtMenB) was expressed and purified as described previously (8). In order to obtain the corresponding enzyme from Escherichia coli (ecMenB), the E. coli menb gene b2262 (858 bp) was cloned into the pET-15b plasmid (Novagen) and placed in frame with an N-terminal His-tag sequence. Protein expression was performed using BL21 (DE3) E. coli cells essentially as described for mtMenB. A 1 l culture of cells was induced with 1 mM isopropyl-β-D-thiogalactopyranoside (IPTG) at an OD600 of 0.8 and harvested by centrifugation after shaking for 12 h at 25°C. The cell pellet was then resuspended in 30 ml of His binding buffer (5 mM imidazole, 0.5 M NaCl, 20 mM Tris HCl, pH 7.9) and lysed by 3 passages through a French Press cell (1000 psi). Cell debris was removed by centrifugation at 33,000 rpm for 60 min at 4 °C. ecMenB was purified using His-tag affinity chromatography. The supernatant was loaded onto a His-bind column (1.5 cm × 15 cm) containing 4 ml of His-bind resin (Novagen) that had been charged with 9 ml of charge buffer (Ni2+). The column was washed with 60 ml of His-binding buffer and 30 ml of wash buffer (60 mM imidazole, 0.5 M NaCl, 20 mM Tris HCl, pH 7.9). Subsequently, the protein was eluted using a gradient of 20 ml elution buffer (60–500 mM imidazole, 0.5 M NaCl, 20 mM Tris HCl, pH 7.9). Fractions containing ecMenB were collected and the imidazole removed using a Sephadex G-25 chromatography column (1.5 cm × 55 cm) with a buffer containing 20 mM NaH2PO4, 0.1 M NaCl at pH 7.0 as eluent. The protein was found not to be stable with the His-tag, and therefore it was removed by treating the protein with biotinylated thrombin overnight at RT. After the biotinylated thrombin was captured with streptavidin agarose, the protein was concentrated using a Centricon-30 (Amicon) concentrator and stored at −80 °C. The concentration of ecMenB was determined by measuring the absorption at 280 nm and using an extinction coefficient of 36,040 M−1cm−1 calculated from the primary sequence. The purified protein was >95% pure on SDS-PAGE which gave an apparent MW of ~30 kDa.</p><p>Quikchange mutagenesis was used to prepare the D185E, D185G and S190A mutants of mtMenB and the Y97F and G156D mutants of ecMenB. These mutant proteins were expressed, purified and stored as described for the wild-type enzymes. The primers used to generate the mutants are given in the supporting information.</p><!><p>Apo-ecMenB was crystallized using the sitting drop vapor diffusion technique. 0.5 μl of 350 μM protein solution was mixed with 0.5 μl of reservoir solution (200 mM sodium malonate at pH 7.0 and 20% PEG 3350, Hampton Research) and equilibrated against 75 μl of reservoir solution. Plates of 0.3 mm length in the longest dimension appeared in one day. The crystals were cryo-protected using a solution that contained 200 mM sodium malonate at pH 7.0, 21% PEG 3350, 25% glycerol and 20 mM NaH2PO4 at pH 7 and cryo-cooled in liquid nitrogen.</p><p>ecMenB in complex with OSB-NCoA was crystallized similarly using a sitting drop comprising 0.5 μl of 350 μM protein solution containing 1.7 mM of OSB-NCoA and 0.5 μl of reservoir solution (100 mM Bis-tris at pH 6.5, 200 mM NaCl and 25% PEG 3350, Hampton Research). Small bipyramids appeared in one day, and a long rod (0.6 mm in the long dimension) with a hollow core appeared in two days. The bipyramids did not improve and were not used for the diffraction experiment. A portion of the long rod was cryo-protected in a solution containing 100 mM Bis-Tris at pH 6.5, 200 mM NaCl, 26% PEG 3350, 25% glycerol, 20 mM NaH2PO4 at pH 7 and 200 μM OSB-NCoA, and cryo-cooled in liquid nitrogen.</p><p>Data were collected at beamline X29 at the National Synchrotron Light Source (NSLS) in Brookhaven National Laboratory, indexed, integrated and scaled using HKL2000 (29). The binary structure was solved by MolRep (30) using the structure of MenB from Salmonella typhimurium (stMenB) as a search model (PDB code 3H02). Clear densities for OSB-NCoA and the missing residues 89–103 in the search model were revealed and built into the model. Residues in ecMenB inconsistent with the stMenB structure were fixed. Restraints for OSB-NCoA were generated by eLBOW (31) using the appropriate SMILES string (32) (see Supporting Information), and coordinates were refined in Phenix (33). Manual model building was performed in Coot (34). The density adjacent to G156 and the succinyl group of OSB-NCoA could not be simply accounted for by water. Modeling of a chloride ion present in the crystallization buffer eliminated the majority of the difference density. Several cycles of refinement followed by manual model building reduced both the working and free R factors significantly to below 20%. Densities for part of a PEG 3350 molecule (essentially three units of ethylene glycol) and glycerol from the cryo solution were found on the surface and were included in the structure. Protein geometry and all-atom contacts including added hydrogens were analyzed by MolProbity (35). Some Asn, Gln and His residues were subsequently flipped following this analysis. Although MolProbity suggested clashes between the OSB C2 and the oxygen attached to C7 in some monomers, the density map suggests that these atoms are indeed brought into close proximity. Statistics from diffraction data processing, model refinement and validation are summarized in Table 1.</p><!><p>A solution of 280 μM mtMenB was incubated with 3.7 mM OSB-NCoA for 1 h on ice. One μl of this protein solution was then mixed with 1 μl of reservoir solution containing 100 mM HEPES pH 8.0, 300 mM NaCl and 19% PEG 6000 and set up for hanging drop, vapor diffusion crystallization against 500 μl of reservoir solution at RT. The crystal grew into an irregular rod, 0.2 mm in the long dimension, and was cryo-cooled in liquid nitrogen on day 6 after stepwise transfer into a cryo solution containing 100 mM HEPES pH 8.0, 20 mM NaH2PO4 pH 7.0, 1 mM OSB-NCoA, 100 mM NaCl, 20% PEG 6000, and 22% glycerol. In a separate setup, 280 μM mtMenB was incubated with 1 mM OSB-NCoA for 40 min at RT after which 1 μl of this solution was mixed with 1 μl of reservoir solution containing 100 mM Tris pH 8.0, 200 mM Li2SO4 and 19% PEG 3350 and set up for hanging drop, vapor diffusion crystallization against 500 μl of reservoir solution at RT. Crystals of various shapes were obtained and cryo-cooled in liquid nitrogen on day 14 after soaking in a cryo solution containing 100 mM Tris pH 8.0, 200 mM Li2SO4, 23% PEG 3350, 22% glycerol, 20 mM NaH2PO4 pH 7.0 and 1 mM OSB-NCoA.</p><p>Diffraction data were collected at beamline X29 at the NSLS, indexed, integrated and scaled using HKL2000. Structure solutions were found by MolRep or Phaser (36) molecular replacement using the mtMenB structure 1Q51 as the search model (8). The same hexagonal crystal form was observed from both crystallization conditions, but an additional rhombohedral crystal form was obtained from the second condition. The rhombohedral structure was solved with two monomers in the asymmetric unit, but the second monomer was found by molecular replacement only after removing the C-terminal domain from the 1Q51 search model.</p><!><p>Steady-state kinetic parameters for ecMenB and mtMenB were determined in 20 mM Na2HPO4, 150 mM NaCl, 1 mM MgCl2, pH 7.0 buffer at 25 °C using a coupled assay (8). The formation of DHNA-CoA at 392 nm was monitored using a CARY-300 spectrophotometer, and reactions were initiated by addition of MenB to solutions containing OSB, ATP (120 μM), CoA (120 μM) and ecMenE (4 μM). The final assay volume was 500 μl. Kinetic parameters were calculated by fitting the initial velocity data to the Michaelis-Menten equation and using an extinction coefficient of 4, 000 M−1cm−1 for DHNA-CoA at 392 nm.</p><!><p>MenB catalyzes an intramolecular Claisen condensation reaction in which the electrophile is an unactivated carboxylic acid. Apart from the oxyanion hole that stabilizes the carbanion (enolate) and which is a common feature of crotonase superfamily enzymes, insight into other aspects of the mechanism including α-proton abstraction, carbon-carbon bond formation and stabilization of the resulting tetrahedral oxyanion requires specific information on how the acyl portion of the substrate interacts with active site residues. Based on previous structures of mtMenB in complex with acetoacetyl-CoA and DHNA-CoA, L134, I136 and L137 have been suggested to make hydrophobic contacts with the aromatic ring of OSB while D185, A192, S190 and Y287 are potential proton donors and acceptors involved in the MenB reaction (8, 22). However the exact role that each residue plays in the reaction is difficult to determine given the active site disorder, which is normally observed in MenB X-ray structures and which, for mtMenB, includes residues 108–125 (the A-loop). Although the acyl group for acetoacetyl-CoA can be observed, this is a poor mimic of the natural substrate. In addition, the acyl group of the product, DHNA-CoA, cannot be observed most likely due to disorder. Nevertheless, we noticed that in the saMenB structure with acetoacetyl-CoA, only 8 residues (residues 79–86) were missing from the A-loop (23) presumably due to its shorter sequence in this nonconserved region. We therefore speculated that an acyl-CoA ligand that better mimicked the native substrate combined with a MenB enzyme with a shorter loop might increase the chance of revealing an intact active site together with details of the enzyme-substrate interactions.</p><!><p>We speculated that replacing the thioester in OSB-CoA with an amide would reduce α-proton acidity sufficiently to prevent formation of the carbanion required for carbon-carbon bond formation. This approach has previously been utilized in structural studies of succinyltransferase (37), while an acyl-CoA amide analogue has also been used to probe the mechanism of substrate recognition and catalysis by the crotonase superfamily member dihydroxyphenylglyoxylate synthase (DpgC) (38–40). In addition the amide analogue will be more stable to hydrolysis than the thioester counterpart, and so we prepared OSB-NCoA using the chemoenzymatic route described here. As anticipated, no reaction could be detected when OSB-NCoA was incubated with ecMenB or mtMenB even at high (100 μM) enzyme concentrations. We thus used OSB-NCoA as a ligand for co-crystallization with the two enzymes.</p><!><p>While apo-ecMenB crystallizes in the same space group (P212121) as apo-stMenB (3H02), co-crystallization of ecMenB with OSB-NCoA resulted in a different crystal form with space group P21212. Both structures were refined to a similar resolution of 2 Å with R factors below 0.2 (Table 1). The asymmetric unit contains a hexamer in both cases with the same tertiary and quaternary structure observed for other MenB enzymes. The crotonase fold and hexameric assembly are shown in Figure 3a. The three C-terminal helices (H14–H16, the C-loop) fold across the trimer-trimer interface and contribute to part of the active site in the opposing trimer, a characteristic of all known MenB hexamers (8, 22–23) (Figure 3a, 3b).</p><!><p>In the structure of OSB-NCoA bound to ecMenB, the ligand can be observed in all six active sites of the hexamer. Significantly, there is no active site disorder and thus the entire active site of MenB is revealed for the first time (Figure 3c). The A-loop, comprising Q88 to L106 in ecMenB, is locked in the same conformation for all six monomers, forming an additional α coil followed by a loop leading to a β turn and a short β hairpin (the A-loop, Figure 3d). This extensive β-like secondary structure is apparently only trapped by substrate binding since secondary structure prediction in the absence of ligand only infers a disordered loop or α-helical structure (41). The A-loop not only covers the active site, but also packs against the C-terminal helices from two neighboring monomers (yellow and cyan monomers, figure 3d), contributing to the integrity of the MenB hexameric assembly. This includes the C-terminus of a monomer from the opposing trimer which, together with the A-loop, forms part of the active site (C-loop, yellow monomer, figure 3d). In contrast, the A-loop remains disordered for apo-ecMenB as observed in other known MenB structures, and part of the C-loop is also less ordered or displays higher B factors. Placing the hexamer for the enzyme-ligand complex in the lattice of the apo structure generates clashes between the A-loop and an adjacent apo hexamer, indicating incompatibility of this A-loop conformation in the apo crystal form. Apparently the crystal form is altered for the binary complex due to the change in A-loop location upon binding of OSB-NCoA.</p><!><p>OSB-NCoA adopts the same conformation in each of the 6 active sites. The CoA portion of the ligand is bound in the U-shaped conformation that is seen in the structures of other crotonase family members (8, 38, 42–48). In addition, the OSB portion is bound in such a way that the C7 carboxylate and C4 carbonyl are clearly out of the plane of the benzene ring, which is also the case when OSB is bound in OSB synthase from Amycolatopsis sp. (1SJB; (49)) and OSB-CoA synthase from Thermobifida fusca (2QVH; (50)). In the MenB reaction carbon-carbon bond formation occurs between the OSB C2 and C7 atoms which are within 3.5 Å of each other in the OSB-NCoA structure. In contrast, the distance between the C2 and C7 atoms is > 5.3 Å in the OSB and OSB-CoA synthases where C-C bond formation does not occur (1FHV, 1SJB and 2QVH (49, 51)). The OSB-NCoA benzoate is surrounded by Y97, F48, L106, V108, L109, Q112, A163 and F162 from the same monomer, Y258 and T254 from the opposing monomer, and an array of eight ordered water molecules. The side chains of L106, V108, L109 and T254 provide favorable hydrophobic interactions with the benzene ring, while the hydroxyl groups from Y97, Y258, and an ordered water molecule provide hydrogen bonding interactions to the carboxylate (Figure 3e). Two additional water molecules extend the hydrogen bonding network to the backbone carbonyl of F48. Other ordered water molecules in the binding pocket mediate a second hydrogen bonding network that involves the backbone carbonyl groups of F162 and G133, and the side chains of T254, D163 and Q112. In addition, S161, an ordered water and a chloride ion are located adjacent to the OSB succinyl moiety. The chloride ion is modeled instead of a water molecule because the electron density is larger than that expected for water. In addition, the negatively charged chloride also interacts favorably with the side chain of Q154 and the backbone NH group of T155. The water molecule is adjacent to the OSB C2 and makes polar interactions with the chloride ion, the oxygen atom of the C4 carbonyl on OSB and the side chain of S161. Finally, the OSB-NCoA amide carbonyl oxygen is hydrogen bonded in the oxyanion hole formed by the backbone NH groups of G86 and G133 (Figure 3e), a feature that is characteristic of the crotonase superfamily. These interactions orient the OSB moiety into the conformation required for carbon-carbon bond formation, and also prevent the OSB carboxylate from attacking the OSB C-4 carbonyl, which is the first step in the uncatalyzed decomposition of OSB-CoA to spirodilactone.</p><!><p>Compared with the structure of OSB determined by energy minimization (52), the bound OSB in the MenB active site adopts a reactive conformation in which the C7 carboxylate is positioned significantly closer toward C2 (Figure 3f). In the unbound structure the oxygen atom on the C7 carboxylate is more than 3.3 Å away from C2 whereas in the bound OSB this distance is between 2.7 and 2.9 Å. Although this is considered an unfavorably close approach of the two atoms by MolProbity, the density map supports the observed interaction which, for the natural substrate, will facilitate the transfer of the pro-2S proton from C2 to C7. This proton transfer is likely facilitated by two nearby Tyr residues, Y97 and Y258 (Figure 3e), which are expected to have pKa values intermediate between the α-proton and the OSB-carboxylate. Instead of direct transfer from C2 to C7, it is possible that Y97 acts as a proton shuttle given its syn position with respect to the carboxylate (53) and its orientation with respect to the C2-Hs bond. In addition, the hydrogen bonding pattern in which Y97 and Y258 donate two in-plane hydrogen bonds to one oxygen atom of the C7 carboxyl group and an ordered water donates one out-of-plane hydrogen bond to the second oxygen suggests that the C7 carboxylate is deprotonated (54). Therefore the C7 carboxylate remains capable of accepting a proton in this binding environment. Thus, intramolecular proton transfer from C2 to C7 not only leads to carbanion formation but also protonates the carboxylate thus making it a better electrophile. In this regard, we note that the involvement of a substrate carboxylate as an acid/base catalyst has also been suggested for 3(S)-methylglutaconyl-CoA hydratase, another member of the crotonase superfamily (55).</p><!><p>By analogy to the Claisen condensation reactions catalyzed by the β-ketoacyl-ACP synthases in fatty acid biosynthesis, a second oxyanion hole is required to stabilize the tetrahedral oxyanion that results from carbanion attack on the protonated OSB carboxyl group (15–16). The two Tyr residues, Y97 and Y258, are ideally positioned to fulfill this function. Sequence alignment demonstrates that these residues are conserved in the MenB family despite significant variability in the A-loop that carries Y97 (Figure 4). The two Tyr residues are also conserved in BadI, a crotonase superfamily member that catalyzes a retro-Dieckmann condensation presumably via an analogous tetrahedral oxyanion intermediate (56). The alignment with Y97 is not straightforward without the present structure given that additional Tyr residues are present in the A-loop of other MenB enzymes and also because of the active site disorder that characterizes other MenB structures. Once Y97 is aligned properly, the conservation of G96 is also revealed. G96 is adjacent to Leu-106 in space, another conserved residue making direct hydrophobic contacts with the aromatic ring of OSB. Replacement of Y97 with a phenylalanine in ecMenB leads to an inactive enzyme (Table 2) that preserves the overall structure of the enzyme (Figure S5), and previously we demonstrated that the homologue of the second Tyr in mtMenB was essential (Y287) (8). These observations strongly suggest that the two Tyr residues play a critical role in the MenB reaction. A similar strategy is employed by hydroxycinnamoyl-CoA hydratase–lyase (HCHL), another crotonase superfamily member that uses two Tyr residues as a molecular "pincer" to recognize the substrate, initiate deprotonation and exert strain on the substrate. The two Tyr residues in HCHL are located on analogous loops to those found in MenB (Figure 4), one of which is also only observed when the analogous A-loop in HCHL becomes ordered (48).</p><!><p>We also attempted to co-crystallize OSB-NCoA with mtMenB which has an A-loop that is 9 residues longer than in ecMenB. The resulting structure is in space group P6122 and contains three MenB monomers in the asymmetric unit (Table 1). The same hexameric assembly observed in existing MenB structures can be generated by a symmetry operation, and the RMSD by aligning the Cα atoms in the three monomers with the equivalent monomers in the hexamer of mtMenB (1Q51) is 0.376 Å. However, in contrast to ecMenB, the A-loop is still disordered in all three monomers. Density for OSB-NCoA can be observed but is weak in chain C possibly due to disorder or low occupancy. In chain B, the density for the CoA portion is improved and there is more residual density for the acyl portion, but the conformation for OSB cannot be determined unambiguously. There is little evidence for the presence of OSB-NCoA in chain A. Instead, the CoA binding site is occupied by the N-terminus of a monomer from a neighboring MenB hexamer in the crystal lattice that prevents the ligand from binding, and hence full occupancy cannot be achieved as in the ecMenB structure. Although the longer A-loop might be responsible for the disorder in the mtMenB structure, it is also plausible that the A-loop only adopts a productive conformation when all six active sites are occupied with the substrate. Such a mechanism might exist to ensure that the MenB hexamer utilizes all its active sites efficiently in catalysis.</p><!><p>In order to improve the occupancy of OSB-NCoA in mtMenB we attempted to identify a different crystal form in which the N-terminal tail from one monomer did not block the CoA binding site in an adjacent hexamer. We subsequently found a rhombohedral crystal with high diffraction quality, which belongs to space group R3 and contains two monomers in the asymmetric unit. The RMSDs between each monomer and that in 1Q51 are 0.627 Å and 0.364 Å over 211 and 197 Cα atoms, respectively. However, upon symmetry operation the asymmetric unit generates a "staggered" hexamer in striking contrast to the eclipsed configuration in all other known MenB structures (Figure 3a). In this new crystal form, the two trimers in the hexamer are rotated 60° with respect to each other along their three-fold axis (Figure 5a). Consistent with this change in quaternary structure, there is local disruption to the tertiary structure. While the A-loop is disordered, there is also significant disorder in the C-terminal region. In chain A, the C-loop corresponding to residues 273–314 is disordered, and the six preceding residues fold in a different direction resulting in a shift of 16 Å for the Cα of L272 compared to its position in 1Q51, suggesting a large-scale dislocation of the C-loop. In addition, the B loop, which is comprised of residues 183–199 and also forms part of the active site, displays a different conformation in chain A so that D187 travels 9 Å from the protein surface into the oxyanion hole (Figure 6b). The flexibility of these loops is further reflected in chain B where the B-loop, the C-loop and the preceding helix (residues 255–314) give little electron density. As a result, the normal active site seen in other known structures is severely disrupted, and OSB-NCoA is not found in the structure.</p><p>The disorder of the A-loop is a common observation among crotonase superfamily members (enoyl-CoA hydratase (ECH) (46, 57–58), methylmalonyl CoA decarboxylase (MMCD) (45), Δ3- Δ2-enoyl-CoA isomerase (ECI) (59), and hydroxycinnamoyl-CoA hydratase-lyase (HCHL) (48)), while in MenB the flexibility of the B-loop and C-loop has also been observed (8, 22). These loops together form the interface between the two trimers in the hexamer that buries more than 3450 Å, or 24% of the total surface area, and which is likely the reason for the stability of the mtMenB structure (22). However, the novel hexameric structure reported here demonstrates that the flexibility of these loops can actually lead to a trimer-trimer rotation which establishes new contacts between two A-loops and between the B-loop and A-loop from the two trimers (Figure 5b). While the functional relevance of this rotation is unclear at present, the observation is consistent with the versatility of these loops in the controlling function within the superfamily (60). These loops comprise the active site (Figure 5c), and share little similarity amongst superfamily members. The C-loop is known to be involved in domain swapping that results in variation of the hexameric assembly (8, 45, 61). However, variation of the hexameric assembly within the same enzyme is less well known. Two forms of hexamers have been observed for the yeast peroxisomal Δ3- Δ2-enoyl-CoA isomerase (Eci1p) where it was speculated that the hexamer might dissociate into trimers and associate with a different partner for entry into peroxisomes (59). While lower oligomeric states have been reported for saMenB (23), there is little evidence for the presence of trimeric mtMenB. In solution mtMenB is found exclusively as a hexamer (22), and in the present rhombohedral crystal form the mtMenB monomers clearly form discrete hexameric units. However, only 10% of the total surface area is buried upon trimer-trimer association in contrast to the 24% that is buried in the normal MenB hexamer. Thus the staggered hexamer is likely less stable than the hexameric structure usually adopted by MenB.</p><!><p>Although the A-loop and acyl portion of the ligand are not observed in mtMenB, conservation of active site residues identified from the ecMenB structure, including those involved in OSB binding and the two oxyanion holes (Figure 4), indicates that mtMenB is capable of using the same catalytic mechanism as ecMenB. The non-conserved regions, including the 9 extra residues in the A-loop of mtMenB, are expected to be outside the active site while catalysis takes place. One exception, though, is D185 of mtMenB which is located next to the OSB succinyl group. This residue is replaced by G156 in ecMenB, and a water/chloride ion replaces the D185 side chain (Figure 3e). Throughout the MenB family, this residue is either an Asp or a Gly (Figure 4). Although G156 or the water molecule does not appear to play a major role during α-deprotonation or stabilization of the two oxyanion intermediates based on our ecMenB structure, a glutamate or water in a similar position has been proposed to perform acid/base catalysis in a number of crotonase superfamily members including ECH (62), dienoyl-CoA isomerase (63), ECI, (64), HCHL, (48) and DpgC (39). The bicarbonate dependence in the MenB activities of E. coli, S. aureus and B. subtilis and the presence of bicarbonate in the crystal structure of stMenB also has led to a proposal that D185 is used for α-deprotonation in mtMenB and that a bicarbonate cofactor performs the same function when the Asp is replaced by a Gly as in ecMenB, saMenB and bsMenB (21). Our structural analysis of ecMenB, however, does not support this role for bicarbonate, and bicarbonate is also not observed in the structures of saMenB and gkMenB (23, 25).</p><p>Nevertheless, both the ordered water molecule in ecMenB and D185 in mtMenB are positioned so that they could aid in the recognition of the OSB C4 carbonyl and assist in the final tautomerization step that leads to DHNA-CoA. D185 in mtMenB clearly plays a critical role in the reaction since kcat for the D185E and D185N mtMenB mutants is reduced 200 and 2000-fold, respectively (Table 2). In addition, neither the D185G mtMenB mutant nor the G156D ecMenB mutant have detectable activity, indicating that the roles of these residues in the two enzymes cannot be simply reversed. Detailed comparison of the two active sites reveals that this result can be attributed to the disruption of the respective hydrogen bonding network optimized for each enzyme when the mutation is introduced (Figures S6 and S7).</p><!><p>The importance of the OSB carboxylate in α-proton abstraction is substantiated by the observation that the methyl ester analogue of OSB-CoA is inactive (Table 2). If the carbanion can be generated without intramolecular proton transfer to the OSB carboxylate, the OSB-CoA methyl ester is expected to be a good substrate for MenB since methanol and water have similar leaving group abilities. In addition, the Kd for the OSB-CoA methyl ester (11.5 ± 1.2 μM; data not shown) is similar to the Km value for OSB-CoA (22.4 ± 2.1 μM), suggesting that the loss of activity for the methyl ester is not simply due to an inability to bind to MenB. In contrast, OCPB-CoA which lacks the C4 carbonyl is still able to undergo ring closure, albeit with lower efficiency than OSB-CoA, indicating that MenB retains the ability to abstract the substrate α-proton when the OSB carboxylate is not modified (Table 2). These results support our original mechanism for mtMenB in which the OSB carboxylate abstracts the C2 α-proton.</p><!><p>ECH contains two active site glutamates, E144 and E164 (62). While E164 is the structural homologue of D185/G156, a second Asp is present in the ecMenB (D163) that is conserved amongst MenB enzymes (D192 in mtMenB) and that is in a similar location in the active site as E144 in ECH. While we have previously shown that the D192N mtMenB mutant was inactive (8), our structural data indicates that D192/D163 points away from the substrate and is involved in a conserved hydrogen bond network so that it cannot directly participate in acid/base catalysis. A similar example is found for MMCD, where E113 is hydrogen-bonded to an arginine and points away from the substrate, preventing it from direct involvement in catalysis (45). Here D192 is hydrogen-bonded to Q140 at the C-terminal end of the A-loop and is apparently important in maintaining the shape of the substrate binding pocket.</p><p>Finally, previous studies also demonstrated that S190 in mtMenB was important but not essential for catalysis (Table 2). The structures of mtMenB and ecMenB reveal that the side chain of S190 (S161 in ecMenB) can interact with Y287, D185, the sulfur atom of the thioester moiety and the oxygen atom of the C4 carbonyl group. Its location in the active site suggests that this residue is involved in the tautomerization step.</p><!><p>The mechanism of the MenB-catalyzed reaction based on these new observations can be described as follows (Figure 6). Two active site Tyr residues from the A-loop and C-loop play a central role in orientating the OSB C7 carboxylate group so that it can abstract the pro-2S proton in either ecMenB or mtMenB. The resulting enolate oxyanion is stabilized in the oxyanion hole formed by two backbone amides, and the C7 tetrahedral intermediate generated by C-C formation is stabilized by the second oxyanion hole formed by the two Tyr residues. The intramolecular proton transfer leads to protonation of the C7 carboxylate, which increases the electrophilicity of this group while the surrounding hydrogen bond network assists in elimination of water from the tetrahedral oxyanion. The two active site Asp residues in mtMenB or the Asp and water in ecMenB together with the active site serine are involved in correctly positioning the substrate for the reaction and are also likely involved in substrate tautomerization.</p><p>Although the X-ray structure of ecMenB in complex with OSB-NCoA strongly suggests that the substrate pro-2S proton is transferred to C7, Igbavboa et al (65) previously reported that MenB catalyzed the exchange of the pro-2R OSB-CoA proton with solvent more rapidly than the pro-2S proton. Although we cannot rationalize this discrepancy, it is possible that other enzymes could be present in the cell extract used for the labeling experiments that might catalyze the exchange of the pro-2R proton with solvent, while the instability of OSB-CoA, which decomposes readily to spirodilactone in solution, could also complicate measurements of stereospecificity. In addition, it is also plausible that the interaction between the OSB carboxylate and the pro-2S proton reduces the propensity of this proton to exchange with solvent. Interestingly, however, the pro-2S stereochemistry agrees with that determined for BadI, which catalyzes a retro-Dieckmann, ring-opening reaction, that is essentially the reverse of the MenB reaction (66). BadI is also a member of the crotonase superfamily and sequence analysis reveals that many active site residues including Y97 and Y258 are conserved between the two enzymes. If MenB and BadI share a common mechanism, then the pro-2S proton in the BadI product could be derived from the Tyr residues or from the carboxylic acid of the substrate which is generated following ring opening.</p><!><p>We have successfully trapped the ecMenB active site in a catalytically relevant conformation using OSB-NCoA, a stable substrate analogue. This structure reveals the positions of all the catalytic residues for the first time, and shows the substrate poised for proton abstraction and carbon-carbon bond formation. Coupled with site-directed mutagenesis and studies with additional substrate analogues, the mechanistic studies reveal how this crotonase superfamily member has adapted to catalyze an intramolecular Claisen condensation reaction. Common or similar strategies are likely employed by other members that catalyze Claisen-like reactions, including BadI, 6-oxocamphor hydrolase and Anabaena β-diketone hydrolase. The serendipitous finding of a novel MenB hexameric assembly also highlights the tight connection between evolution, catalysis and oligomerization within the crotonase scaffold.</p>

PubMed Author Manuscript

CO2 and Water Activation on Ceria Nanocluster Modified TiO2 Rutile (110)

Surface modification of TiO2 with metal oxide nanoclusters is a strategy for the development of new photocatalyst materials. We have studied modification of the (110) surface of rutile TiO2 with ceria nanoclusters using density functional theory corrected for on-site Coulomb interactions (DFT+U). We focus on the impact of surface modification on key properties governing the performance of photocatalysts, including light absorption, photoexcited charge carrier separation, reducibility and surface reactivity. Our results show that adsorption of the CeO2 nanoclusters, with compositions Ce5O10 and Ce6O12, is favourable at the rutile (110) surface and that the nanocluster-surface composites favour non-stoichiometry in the adsorbed ceria so that reduced Ce ions will be present in the ground state. The presence of reduced Ce ions and low coordinated O sites in the nanocluster lead to the emergence of energy states in the energy gap of the TiO2 host, which potentially enhance the visible light response. We show, through an examination of oxygen vacancy formation, that the composite systems are reducible with moderate energy costs. Photoexcited electrons and holes localize on Ce and O sites of the supported nanoclusters. The interaction of CO2 and H2O is favourable at multiple sites of the reduced CeOx-TiO2 composite surfaces. CO2 adsorbs and activates, while H2O spontaneously dissociates at oxygen vacancy sites.

co2_and_water_activation_on_ceria_nanocluster_modified_tio2_rutile_(110)

INTRODUCTION<!>METHODOLOGY<!>The singlet-triplet excitation energy:<!>Stoichiometric CeO2-modified TiO2 structures<!>Reduction of CeO2-rutile by oxygen vacancy formation<!>Modelling charge separation upon photoexcitation.<!>CO2 adsorption at the reduced nanocluster-surface composites.<!>H2O adsorption at the reduced nanocluster surface composites.<!>CONCLUSIONS

<p>Since the seminal paper by Fujishima and Honda in 1972, 1 titanium dioxide, TiO2, has remained at the forefront of photocatalysis research due to its abundance, low-cost, nontoxicity and robustness under operating conditions. The large bandgap (>3 eV) means that TiO2 is UV active so that extending light absorption to the visible range is necessary to maximize solar energy absorption for large-scale implementation of photocatalytic technologies.</p><p>Strategies to induce visible light absorption in TiO2 have included substitutional cation or anion doping at Ti or O sites respectively [2][3][4][5][6][7][8][9][10][11][12][13] and co-doping, where multiple dopants are incorporated in the TiO2 host. [12][13][14][15][16][17][18][19][20] Doping introduces impurity energy states into the band gap of the TiO2 host, facilitating electronic transitions that have energies in the visible range. However, localized defect states have been shown to act as recombination centres, impeding carrier migration and reducing photocatalytic activity 9,12,13 and practical issues with reproducibility, solubility and stability persist with doped metal oxides.</p><p>Extending the absorption edge to longer wavelengths should not be the sole research focus as efficient separation of photoexcited charge carriers and molecular activation are essential to the performance of photocatalysts. The development of the dye sensitized solar cell (DSSC) 21 can inspire similar strategies in photocatalysis; dyes simultaneously promote visible light absorption and charge separation but do suffer from degradation. 13 Noble-metal loading of TiO2 has been reported to improve photocatalytic efficiency in the UV and visible through plasmon resonance in the metal. [22][23][24][25][26] However, the use of precious metals such as Ag, Au and Pt drives up costs.</p><p>Surface modification of TiO2 with dispersed metal oxide nanoclusters of non-precious metals has been investigated experimentally via chemisorption-calcination cycle (CCC) 27,28 and atomic layer deposition (ALD). 29 These studies reported both band gap reduction and enhanced visible light photocatalytic activity for FeOx-modified TiO2. Photoluminescence spectroscopy revealed that the modification suppressed carrier recombination 27 and the observed red shift was due to cluster derived states above the valence band maximum (VBM) as identified by X-ray photoelectron spectroscopy (XPS) and confirmed with density functional theory (DFT) simulations. 27,28,30 DFT has been used in combination with experiment to examine these and similar systems. 28,[30][31][32][33][34][35][36][37][38][39][40][41][42][43] Our previous work 28, 31, 34-40, 43, 44 has indicated the potential for metal oxide modifiers to induce a bandgap reduction over bare TiO2. In addition, an enhanced separation of photoexcited electrons and holes has been reported to result from nanocluster surface modification of TiO2. 34,36,37,40,45 We have further highlighted the role of low-coordinated nanocluster metal and/or oxygen sites in trapping and separating charge carriers 34,36,37,40 and this suggests that modification of TiO2 promotes electron and hole separation. Initial work on CO2 activation at metal oxide modified TiO2 has been presented. 31 In this paper, we present a DFT study of TiO2 rutile (110) modified with sub-nm nanoclusters of CeO2, with specific compositions Ce5O10 and Ce6O12. CeO2 is an interesting modifier as Ce 4f states are crucial in optical properties, reducibility and reactivity. 46,47 In particular, the facile conversion between Ce 4+ and Ce 3+ oxidation states has important implications for catalytic performance and metal/CeOx/TiO2 composites with Ce 3+ cations have displayed enhanced activity for the water gas shift (WGS) reaction. 42,[48][49][50] We focus in particular on the impact of nanocluster modification on (1) the interfacial atomic structure, (2) the valence or conduction band edges of rutile (110), (3) charge localization after excitation, (4) the reducibility of the composite system and (5) the interaction of feedstock molecules, such as H2O and CO2, with the reduced CeOx-TiO2 composite. Reducibility and interactions with molecules are crucial for catalysis. A more reducible catalyst could use a combination of photocatalytic and thermal catalytic effects. 51 Electrons and holes can be produced by light absorption and thermally produced defects, such as oxygen vacancies, can provide sites for the adsorption and activation of feedstock species.</p><p>Transition metal oxides have been widely studied as catalysts for the oxygen evolution reaction (OER). 52,53 Nørskov and colleagues studied water oxidation at the rutile TiO2 (110) surface using DFT 54 and found that the most difficult step was the dissociation of a H2O molecule at a vacancy site to form an adsorbed hydroxyl group (OH*). Other DFT studies have examined water adsorption at extended surfaces of both rutile TiO2 (110) 55 and CeO2 (111) 56,57 and found that molecular adsorption of water is more favourable than dissociative adsorption, albeit marginally so for the latter system (0.01-0.03 eV depending on exchange-correlation functional and separated by an energy barrier of 0.1 eV). A recent study compared water adsorption at the (101) (Eads = 0.89 eV) and (001) (Eads = 0.29 eV) surfaces of anatase TiO2. 58 The authors attributed the greater activity of the (001) surface for water oxidation to hydrogen bonds between H2O and terminal hydroxyls which facilitate rapid hole transfer. In general, the adsorption configuration of water molecules at TiO2 surfaces depends on the crystal form, termination, stoichiometry and degree of coverage. 33,59 However, an important first step, consistent across mechanisms describing water oxidation, is the dissociative adsorption of H2O at the catalyst surface. 60-62 DFT+U studies examining ceria nanoclusters, of composition Ce2O3, supported on rutile (110) found that water dissociation is exothermic (Eads = -0.7 eV) with a small energy barrier (0.04 eV). 42,48 In addition, a number of studies have highlighted the role played by dissociated H2O, in particular surface hydroxyls, in trapping holes at catalyst surfaces, 58,61,[63][64][65] which is important for subsequent steps in the water oxidation reaction.</p><p>The CO2 reduction reaction (CO2RR) competes with the hydrogen evolution reaction (HER) in the presence of water and in general H2O adsorption at catalyst surfaces is preferential to CO2 adsorption. 66 It is therefore necessary to promote selectivity for the desired reactions. The adsorption of CO2 molecules at titania surfaces has been studied using DFT and a crucial role has been ascribed to oxygen vacancies in the activation process. 67,68 The presence of excess electrons and holes was shown to affect adsorption and activation of CO2 at rutile (110), with implications for binding energies, structure and reactivity of adsorbed CO2; both bent CO2anion (excess electrons) and CO2 + cation (excess holes) configurations were identified with energy barriers of 1.12 eV and 0.75 eV respectively. 69 Yang and colleagues showed that subnm Pt clusters at the anatase (101) surface enhanced CO2 activation through provision of additional adsorption sites at the edge of the Pt cluster, reporting increased adsorption strength and, in some instances, the spontaneous formation of a CO2anion due to accumulation of negative charge on the C atom. The authors also reported transfer of electron density from the cluster to the TiO2 substrate which facilitated adsorption at surface sites away from the supported Pt octamer. 70 Bismuth pyrochlore oxides have been shown to have a high CO2 chemisorption capacity as identified through FTIR and attributed to the Bi2O3 motif with a Bi 3+ lone pair. 71 Cu2O has emerged as a potential candidate for CO2RR due to its favourable band gap position and width 72 and studies have focussed on the interaction of CO2 molecules with various cuprous oxide surfaces and terminations. [72][73][74][75][76][77] Wu and colleagues studied the adsorption of CO2 at the Cu2O (111): O terminated surface with oxygen vacancies, 75 finding that oxygen vacancies have a negative impact on the interaction energy; the most stable adsorption configuration at the perfect surface was more favourable by 0.15 eV than adsorption at the O vacancy surface. However, the authors also reported the formation of a stable CO2 δradical anion species upon adsorption at the O vacancy surface, but this has an adsorption energy of ~0 eV. Another study examined the adsorption of CO2 at Cu2O (111) using Hybrid DFT 77 and found adsorption only in non-activated form. Physisorption of a linear CO2 molecule is favoured over adsorption in activated form at Cu2O (111), 73,76 however strong chemisorption, with energy gains of as much as 1.76 eV, was reported for CO2 adsorption at the Cu-O terminated (110) surface. 73 Activation, with bending and elongation of bonds, upon exothermic (Eads = -0.96 eV) adsorption of CO2 at the (011) surface of CuO has been reported. 74 The conversion of CO2 to methanol on Cu2O nanolayers and clusters 72 was studied using Hybrid DFT with water as the source of H atoms for hydrogenation steps. Other theoretical studies have been conducted into reaction pathways involving the hydrogenation of CO and CO2 at a variety of catalytic surfaces, including Cu/CeO2 and Cu/CeO2/TiO2, 46 Cu/ZnO/Al2O3 78 and copper surfaces. 79,80 Enhanced photoreduction of CO2 with H2O vapour has been reported for dispersed CeO2 on anatase TiO2, prepared using a one-pot hydrothermal method; 47 the role of Ce 3+ in visible light absorption, photogenerated charge separation and strengthening CO2surface bonding was highlighted. The adsorption and activation of the CO2 molecule at the catalyst surface is an important first step in subsequent reactions.</p><p>In the following we will present results of DFT studies of Ceria nanocluster modified rutile (110). Our clusters have compositions Ce5O10 and Ce6O12 and compliment earlier work on Ce2O3 reduced nanoclusters supported on rutile (110). 42,48,50 These nanoclusters allow us to examine composition effects on stability, band gaps, charge localization and reducibility. We show that adsorption of ceria-nanoclusters at the rutile (110) surface is favourable and that the nanocluster-surface composites favour non-stoichiometry so that reduced Ce ions will be present in the ground state. This off-stoichiometry leads to the emergence of Ce-derived occupied states in the band gap and low coordinated oxygen sites in the supported nanoclusters which contribute to the density of states (DOS) at the TiO2-derived valence band maximum (VBM), potentially increasing the visible light response.</p><p>Results using a photoexcitation model show that the excited electron and hole prefer to localize onto the supported CeO2 nanocluster. We will also present results which indicate that the interaction of CO2 and H2O is favourable at multiple sites of the reduced CeOx-TiO2 composite surfaces. CO2 adsorbs and activates, forming a bent complex with elongated C-O distances.</p><p>Finally, H2O spontaneously dissociates at oxygen vacancy sites to generate surface bound hydroxyls.</p><!><p>All calculations were performed using periodic plane wave density functional theory (DFT) as implemented in the VASP5.2 code. 81,82 The valence electrons are described with a plane wave basis set with an energy cut-off of 396 eV. Projector augmented wave (PAW) potentials account for the core-valence electron interaction, 83,84 with 4 valence electrons for Ti, 6 for O, 12 for Ce, 4 for C and 1 for H. The exchange-correlation functional is approximated by the Perdew-Wang (PW91) functional. 85 Γ-point sampling is used for the (2 × 4) surface expansion of the rutile (110) surface with a supercell consisting of 18 monolayers (6 neutral trilayers) and a vacuum gap of 20 Å. The computed bulk lattice constants of rutile TiO2 are = = 4.64 Å and = 2.97 Å. The convergence criteria for the energy and forces are 10 eV and 10 eV Å respectively. All calculations are spin polarized.</p><p>To consistently describe the partially filled Ti3d and Ce4f states a Hubbard U correction is applied. 86,87 We use values of U(Ti) = 4.5 eV and U(Ce) = 5.0 eV with these values chosen from previous work on CeO2 and TiO2. 37,38,40,48,88,89 For calculations involving the model excited state and valence band hole formation we apply an additional +U correction to the O2p state with U(O) = 5.5 eV. Previous work has highlighted the necessity for such a correction in obtaining a correctly localized oxygen hole state in metal oxides. 33,[35][36][37]40 The ceria nanoclusters were adsorbed in different adsorption configurations at the rutile (110) surface which, for the purposes of this work, is free of the point defects and surface hydroxyls which can be present on real surfaces. 90,91 The adsorption energies are computed using:</p><p>where , and are the energies of the adsorbate-surface composite system, the bare rutile (110) surface and the gas phase nanocluster respectively.</p><p>Once a stable adsorption configuration was identified we examined the energies associated with oxygen vacancy formation in the adsorbed CeO2 nanocluster. One oxygen ion is removed from the adsorbed CeO2 cluster and the vacancy formation energy is calculated as:</p><p>where the first and third terms on the right hand side of the equation are the total energy of the cluster-surface composite with and without an oxygen vacancy and the energy is referenced to half the total energy for molecular O2. The calculation was performed for each oxygen site of the supported nanoclusters (see Table S1 Supporting Information) to determine the most stable non-stoichiometric composite. Once this is identified, we remove a second and third oxygen atom, as required, to describe situations in which multiple oxygen vacancies are present in the nanocluster (vide infra). The oxidation states were determined through Bader charge analysis 92 and computed spin magnetizations and the corresponding values are quoted in the following sections.</p><p>We also investigated the adsorption and activation of H2O and CO2 at the CeO2-modified rutile (110) composites, taking into particular account the presence of oxygen vacancies in CeO2.</p><p>The adsorption energies for the molecules adsorbed at the nanocluster are calculated as:</p><p>where , and refer to the energies of the molecule and modified surface in interaction, the modified surface and the gas phase molecule (H2O or CO2) respectively.</p><p>We model photoexcitation by imposing a triplet electronic state on the system. 93 This promotes an electron to the conduction band, with a corresponding hole in the valence band, and enables an evaluation of the energetics and charge localization associated with photoexcitation. The following energies are computed:</p><p> The ground state energy of the system, yielding .</p><p> A single point energy calculation at the ground state geometry with the triplet state imposed, yielding .</p><p> An ionic relaxation of the triplet electronic state which gives . From the results of these calculations we compute:</p><p>1. The singlet-triplet vertical excitation energy:</p><p>This is the difference in energy between the ground (singlet) state and the imposed triplet state at the singlet geometry and corresponds to the simple VB-CB energy gap from the computed density of states.</p><!><p>= − . This is the difference in energy between the relaxed triplet state and the relaxed singlet state and gives a crude approximation of the excitation energy.</p><p>3. The triplet relaxation (carrier trapping) energy:</p><p>This difference in energy between the unrelaxed and relaxed triplet states is the energy gained when the electron and hole are trapped at their metal and oxygen sites upon structural relaxation. This energy relates to the stability of the trapped electron and hole.</p><p>These quantities are summarized schematically in Figure 1.</p><!><p>We focus on ceria nanoclusters of two compositions, namely Ce5O10 and Ce6O12, and we first examine the stoichiometric nanocluster adsorption energies and structures shown in Figures 2(a) and 2(d). The adsorption energies were computed using Eq. 1 and are -4.75 eV for Ce5O10 and -2.47 eV for Ce6O12 adsorption on rutile (110). The negative adsorption energies show that the interaction between the nanocluster and the surface is favourable, with the magnitude of the energy indicating the strength of the interaction. The larger adsorption energy for the Ce5O10 nanocluster is reflected in the larger number of surface-to-nanocluster bonds; 7 compared with 6 for the adsorbed Ce6O12 nanocluster. Another reason for the smaller adsorption energy of the Ce6O12 cluster may be due to the presence of under-coordinated terminal oxygen ions and this idea will be expounded upon in the next section. From the adsorption energies we expect the nanoclusters to be stable at the surface without desorbing or migrating over the surface to form aggregates. Henceforth, the composites will be denoted as Ce5Ox-rutile-( 110) and Ce6Ox-rutile- (110), where the subscript x will vary according to the stoichiometry. The interfacial bonding between the nanocluster and the surface results in an appreciable distortion of the local atomic structure at the surface. Where a bridging surface oxygen is bound to a nanocluster cation the Ti-O bond involving this oxygen elongated by up to 10% compared with a typical unmodified bond length of 1.88 Å. Surface titanium atoms that bind with oxygen in the nanoclusters migrate out of the surface plane towards the cluster by as much as 0.92 Å, lengthening the subsurface Ti-O distance.</p><!><p>From our relaxed stoichiometric nanocluster-surface composites we remove oxygen ions from CeO2 and examine the energies involved in the formation of these vacancy sites. Previous work on small CeO2 structures on rutile (110) has shown that these prefer to be reduced, with loss of oxygen in the ground state, giving composition Ce2O3. 46,48 It is not known if a similar composition would be found for larger but still sub-nm ceria clusters. The oxygen vacancy formation energies are important as their stability determines the stoichiometry of the composite. If the composite is then reduced, the formation energy can be a further important factor in determining if feedstock species will interact with the CeOx-rutile composites. If the energy cost to form a reducing vacancy is low, the system favours non-stoichiometry and fixation and activation of molecular species, via a redox or Mars van Krevelen process, may not occur and no reactions can take place. On the other hand, while large vacancy formation energies can promote reoxidation via feedstock reduction, these require a large initial energy input and may also result in too strong interaction with molecular species, leading to poisoning of the surface.</p><p>Table 1 presents the computed oxygen vacancy formation energies in each supported ceria nanocluster. The most stable oxygen vacancy in Ce5O10-rutile- (110), which results in formation of Ce5O9-rutile- (110), has a small cost of 0.18 eV. A formation energy of this magnitude suggests that an off-stoichiometric ground state will be present. For a second oxygen vacancy, giving a composition Ce5O8-rutile- (110), the most stable vacancy site has an energy cost of 1.48 eV, relative to Ce5O9-rutile- (110). Thus the second oxygen vacancy is the reducing oxygen vacancy and this has a moderate cost.</p><p>For the Ce6O12-rutile composite, the first two oxygen vacancies have negative formation energies, of -0.46 eV and -0.16 eV, which means that the ground state is highly offstoichiometric as the vacancies will form spontaneously at = 0 K. The ground state therefore has the composition Ce6O10-rutile- (110). This instability of the stoichiometric Ce6O12 nanocluster adsorbed on the rutile (110) surface sheds light on its small adsorption energy relative to the Ce5O10 nanocluster. Computing the adsorption energy of an off-stoichiometric Ce6O10 nanocluster on rutile (110), yields a value of -3.45 eV, suggesting a stronger interaction at the surface and enhanced stability. The energy cost required to produce the third oxygen vacancy in the most stable cluster site of the larger nanocluster-surface composite is +0.30 eV. This is a moderate cost and we consider the Ce6O9-rutile-( 110) composite as being in a reduced state. Thus, for the CeO2-rutile composites, with rutile modified by a sub-nm ceria nanocluster, we expect a highly non-stoichiometric system with multiple potential activation sites at moderate temperatures, consistent with the work of Graciani et al. In these non-stoichiometric nanocluster-surface composites we expect to find two electrons released for each neutral oxygen vacancy and the spin density plots are used to determine the location of the electrons after relaxation. The spin density plots for the ground and reduced states of CeOx-rutile are presented in Figure 3 and show that electron localization occurs at Ce atoms in each nanocluster, which results in the formation of reduced Ce 3+ cations. Ce 3+ form in preference to Ti 3+ cations and this has also been seen in DFT+U studies of Ce-doped TiO2 [94][95][96] and some surfaces. 42,50 For the non-stoichiometric ground state structures, the smaller nanocluster has a Ce5O9 configuration and two Ce atoms are reduced as shown in Figure 3 These results are further confirmed through Bader charge analysis, the results of which are included in 2. The spin polarized projected electronic density of states (PEDOS) for the stoichiometric, offstoichiometric ground state and reduced nanocluster-surface composites described above are presented in Figure 4. Panels (a) and (d) of Figure 4 show the stoichiometric configurations where the most obvious feature is the presence of states due to cluster oxygens at the top of the valence band for the Ce6O12 nanocluster. These states are due to the singly coordinated oxygen ions described previously. However, the nanocluster-derived oxygen 2p states above the TiO2 VB persist even after removing these oxygen sites. In panels (b), (c), (e) and (f), which correspond to the off-stoichiometric CeOx-rutile composites, we can see that the presence of reduced Ce 3+ cations in the nanoclusters after formation of oxygen vacancies introduces states into the TiO2-derived band gap. These states arise due to the singly occupied 4f 1 orbital configuration of the reduced Ce 3+ cations. The modification of rutile with CeOx nanoclusters will result in a red shift of the TiO2 adsorption edge; this is due to a combination of 2p states of low coordinated O sites of the cluster pushing the VBM to higher energy and the emergence of mid-gap states associated with reduced Ce 3+ ions in the off-stoichiometric composites. Insets in the top panels show the mid-gap Ce-derived states in the range -0.5 eV -2.0 eV.</p><!><p>We apply the photoexcited model to the ground state CeOx-TiO2 systems which consist of the off-stoichiometric composites, Ce5O9-rutile-( 110) and Ce6O10-rutile- (110). Table 3 presents the computed vertical and singlet triplet energies and the electron-hole localization (relaxation) energies, as discussed in Section 2. Firstly, we note the underestimation of the bandgap inherent in approximate DFT is present in our DFT+U computational set-up. The +U corrections used herein are chosen to consistently describe the localization of electrons and holes rather than to reproduce the bandgap of bulk TiO2, which is not advised. This underestimation is clear in the computed values for E vertical and E excite which are clearly smaller than the experimental values.</p><p>However, what is important for our study is the change in these quantities with modification of the rutile (110) surface. We note that E excite is always smaller than E vertical and the simple valence-conduction band energy difference, as the former energy includes the ionic relaxations and polaron formation in response to "exciting" the electron which then lowers the energy of the triplet electronic state.</p><p>Comparison of these computed energies across different structures yields useful qualitative information about the effect of surface modification. In particular, a reduction in E excite for a composite structure relative to the unmodified metal oxide will correspond to a red shift in light absorption for the surface modified system. The energies presented in Table 3 show that modification of the ( 110) surface of rutile TiO2 with nanoclusters of CeO2 leads to a red shift in light absorption whether we use the vertical or excitation energies. This effect is stronger for the larger nanocluster, consistent with the PEDOS. Relaxation energies of 0.8 eV upon charge localization in each heterostructure indicate high stability of the photogenerated electron-hole pairs.</p><p>We can also examine the localization of the electron-hole pair through analysis of computed</p><p>Bader charges, spin magnetizations and excess spin density plots. 2, and spin magnetizations of 0.97 µB were computed for these sites. the hole localizes at a singly coordinated terminal oxygen site; the Ce-O distance increases from 1.9 Å in the ground state to 2.3 Å after excitation. Hole localization is accompanied by a change in the computed Bader charge of the oxygen by 0.4 electrons, from 7.1 to 6.7 electrons, in each case. For the Ce5O9-rutile-( 110) composite there is some spreading of the hole to neighbouring two-fold coordinated oxygen sites of the nanocluster but this spreading is typical for this DFT+U set-up and is accompanied by changes of < 0.1 electrons in the computed Bader charges, so that we can conclude the hole predominantly localizes on one oxygen site in the nanocluster. This is confirmed by a computed spin magnetization of 0.73 µB for the oxygen hole on Ce5O9-rutile-( 110) and compares with a value of 0.78 µB for the singly terminated oxygen site at which the hole localizes in Ce6O10-rutile- (110).</p><p>For the CeOx-rutile-( 110) composites we can see that both the electron and hole localize on the nanocluster modifiers, which may have consequences for recombination. However, in looking at Figure 5 we see that the spatial separation of the charges is maximal, given that both electrons and holes localize at nanocluster sites. In addition, the large relaxation or trapping energies act to impede migration of the charges and thus the impact on recombination should be minor. We also note that our photoexcited model, which involves the imposition of a triplet state to induce a transition from the VB to the CB, precludes transitions from the highest occupied, Ce 4fderived states of the off-stoichiometric ground states (see Figures 4(b) and 4(e)). Such transitions would amount to electron hopping between Ce sites of the nanocluster with no change in electronic configuration after "excitation". Rather, our model with a triplet electronic state (in addition to the unpaired electrons on reduced Ce 3+ ) will induce transitions from OC 2p-derived states, which sit at the top of the titania-derived VB, to the unoccupied Ce 4f states.</p><!><p>With the motivation that O vacancies in reduced metal oxides can act as sites for the adsorption and activation of CO2, as found in other studies, 75,[97][98][99][100] we have examined the adsorption of CO2 at various sites on our reduced Ce5O8-and Ce6O9-rutile-( 110)); the computed adsorption energies for the most stable configurations are -1.36 eV on Ce5O8-rutile-(110) and -1.09 eV on Ce6O9-rutile- (110). The relaxed geometries for these configurations are shown in Figure 6. The Supporting Information shows additional adsorption structures and energies for the CO2-CeOx-TiO2 interaction.</p><p>The most stable CO2 adsorption sites have negative adsorption energies and the magnitudes of these adsorption energies are indicative of a strong exothermic interaction between CO2 and the oxides. Our results follow the trend that CO2 interaction is stronger at vacancy sites with a higher formation energy, as previously reported. 31 A DFT+U study of CO2 activation on CeO2 (110) found that the most stable O vacancy had a formation energy of +1.65 eV; 101 the authors reported that CO2 adsorption at this site, with a bent geometry and Eads = -1.22 eV, was the most stable adsorption configuration. A DFT+U study of CO2 reduction on CeO2 (111) also found that interaction was strongest at the O-defective surface; 102 the O vacancy formation energy was +2.78 eV and CO2 adsorbed in a bent geometry with Eads = -1.12 eV. While the adsorption energies are comparable across these studies, the vacancy formation energy is not sufficient in predicting the strength of interaction of adsorbed CO2. Previous work on Ce3O6rutile-( 110) 31 found that this composite was reducible with an O vacancy formation energy of +0.31 eV; CO2 was calculated to adsorb exothermically with Eads = -0.20 eV. This compares with an adsorption energy of -1.09 eV for CO2 interacting at the reduced Ce6O9-rutile- (110) composite of the present work in which oxygen vacancies are produced with similar energy costs (see Table 1). This would suggest that, in the case of ceria nanocluster modifiers, the degree of non-stoichiometry, which is related to the number of reduced Ce cations in the cluster, may play a role in stabilizing adsorbed surface species. Future work, involving larger ceria nanocluster modifiers, can shed further light on the nature of the trade-off between interaction strength and reducibility. This means that the interaction leads to an activated, chemisorbed CO2 species and the formation of a carbonate species can be ruled out.</p><p>The Ce-O bonds established with the adsorbed species are comparable in length to those within the nanocluster which are typically in the range of 2.2-2.6 Å. The calculated Bader charges show that charge transfer is qualitatively consistent across the various adsorption sites.</p><p>Between 0.1 and 0.2 electrons are transferred from the CO2-derived O atoms to the cluster while the cluster oxygen site with which the CO2 interacts gains between 0.4 and 0.6 electrons through the interaction.</p><!><p>We also examined how water interacts at the vacancy sites in the reduced CeOx-rutile (110) composites. We compute the adsorption energies of H2O interacting at a range of sites of the reduced Ce5O8-and Ce6O9-rutile-(110) surfaces using Eq. 2. We find that adsorption of water is favourable at multiple sites on the CeOx nanocluster. Adsorption energies for the most stable adsorption configurations of water are -1.8 eV on Ce5O8-rutile-( 110) and -0.9 eV on Ce6O9rutile- (110); the corresponding geometries displayed in Figure 7. The Supporting Information shows additional adsorption sites and energies for the H2O-CeOx-TiO2 interaction.</p><p>In the interaction of H2O at the reduced composites, starting from an initial water adsorption in molecular form, the most stable adsorption mode is that in which the water molecule dissociates spontaneously upon relaxation. This dissociation involves the transfer of an H atom to an O site of the supported nanocluster and the hydroxyl from the water molecule bridges two cluster Ce sites. On the larger CeOx nanocluster, the moderate adsorption energy means that hydroxyls should not be overstabilized and could be active in catalysis. Thus, water dissociation and activation can be promoted on these ceria-rutile composites. Despite this distortion of the larger nanocluster upon H2O adsorption, the interaction is strong and favourable as shown by an adsorption energy of -0.9 eV. Similarly to the smaller nanocluster, there is a redistribution of charge with water oxygen transferring 0.3 electrons to the nanocluster and this charge is donated to the nanocluster oxygen that binds with hydrogen from water.</p><p>These results compare with studies of water dissociation at Ce2O3-TiO2. 48,106 In these studies the authors followed the energy pathway from water adsorbed in molecular form to dissociation, finding that the dissociation process was exothermic (-0.70 eV) with a small energy barrier of 0.04 eV. We found that dissociation of molecular water occurred spontaneously, suggesting that the size of the supported CeOx nanocluster and the number of Ce 3+ sites play a role in the ability of the composite to dissociate water.</p><p>While the ability of metal oxides to dissociate H2O is well established, the mechanism which promotes dissociation upon adsorption remains of interest. A number of studies have looked at CeO2 surfaces as model systems for the study of water dissociation. [107][108][109][110] Defects, step edges and terraces in surfaces play a role as such features provide low-coordinated adsorption sites.</p><p>CeO2 (111) with O vacancies and Ce 3+ ions shows a preference for dissociative water adsorption, relative to the pristine surface, where there is little energetic difference between adsorption in molecular and dissociated form. 111 surface promotes dissociation of H2O over molecular adsorption. 113 For the reduced Ce6O9rutile-(110) composite, the Ce-O distances, at the sites of H2O adsorption (see Figures 7(c) and (d)), are longer by ~1% relative to typical distances (~2.37 Å) in the pristine CeO2 (111) surface. This suggests that tensile strain may indeed contribute to promoting the dissociation of water. In Ce5O8-rutile-( 110), Ce-O distances are shorter (~2.2 Å), due to the lower coordination of the cluster O sites, and elongate after the dissociative adsorption of H2O.</p><p>However, the Ce-Ce distance prior to water adsorption is 4.2 Å, which is considerably longer than neighbouring Ce-Ce distances (~3.9 Å) in CeO2 (111). After the dissociative adsorption of water, this Ce-Ce distance decreases to 3.6 Å, further indicating that tensile strain may play a role in driving the dissociation.</p><p>Figure 8 shows the PEDOS of the H2O molecule and reduced CeOx-rutile-( 110) composites in the non-interacting case (H2O + surface) and after dissociative adsorption (H2O-surface). For the non-interacting systems the molecule and surface are relaxed in the same unit cell with sufficient spatial separation such that they do not interact. In the non-interacting cases (left panels of Figure 8), the water-derived OW 2p states are well defined peaks at energies of -2.9</p><p>eV and -0.8 eV (Figure 8 Despite these differences, some trends are consistent across both composites. In both cases the interaction increases the gap between the occupied Ce 4f-derived states and the CBM of the TiO2 host (see insets of panels in Figure 8); i.e. the occupied Ce 3+ states are pushed to lower energy after interaction. In addition, integrating the OC and OW-derived DOS lying above the TiO2 VBM in both the non-interacting and interacting cases shows that after interaction the occupied states are driven to lower energies. For both composites the number of states lying above the TiO2 VBM is reduced by 2 in the interacting cases relative to the non-interacting systems; this suggests that passivation of high lying O 2p states is a factor driving the interaction of water with the reduced CeOx-rutile-(110) composite surfaces.</p><!><p>We have studied the (110) surface of rutile TiO2 modified with ceria nanoclusters of compositions Ce5O10 and Ce6O12 using first principles DFT+U analysis. Our results show that the ground state of the nanocluster-surface composites is off-stoichiometric with one or more oxygen vacancies forming spontaneously or at very low energy cost, so that under typical experimental conditions, there will be oxygen vacancies present. The consequence of this is that Ce 3+ ions will be present in the nanoclusters in their ground state (with no Ti 3+ species) and this leads to the emergence of occupied Ce 4f-derived states in the TiO2-derived bandgap.</p><p>Together with CeOx-derived O 2p states above the TiO2 VB, this may induce a red shift in light absorption making these systems visible light active. It is low-coordinated oxygen atoms in the supported nanoclusters that contribute to these new states above the valence band edge.</p><p>In our model of the photoexcited state, in which an electron is promoted from the O 2p derived valence band, we found that electron and hole localization occur at Ce and low-coordinated oxygen sites on the supported nanocluster respectively. The consequence of this for charge recombination may not be detrimental as the electron-hole pair has a large trapping energy of 0.8 eV so this can reduce the migration of charges over the nanocluster. Verification of both the predicted red shift and the charge recombination effects would be welcome.</p><p>In terms of activity, the CeO2-rutile composites are more reducible compared to the unmodified rutile (110) surface and moderate energy inputs are required to produce multiple oxygen vacancies. Electrons released after forming the oxygen vacancies localize on Ce sites in the supported nanoclusters. We have examined the interaction of oxygen vacancies in the reduced composites with CO2 and H2O to determine how CeOx-rutile-(110) activates these molecules.</p><p>We find that CO2 adsorption is favourable at multiple sites on the nanocluster-modified surface, with exothermic adsorption energies up to 1.36 eV. This strong adsorption is accompanied by a distortion from the linear gas phase CO2 geometry, in which the molecule bends, with O-C-O angles of 125⁰-128⁰, and the C-O bonds in CO2 show an elongation of ~0.10 Å. In combination with some transfer of charge between the adsorbed species and the nanocluster, this suggests the formation of activated CO2 which is the crucial first step in the transformation of CO2 to more useful molecules. We welcome attempts to study these materials for their ability to activate and convert CO2, although the actual conversion process may be limited by other factors. Nevertheless, the finding that these ceria-modified TiO2 systems can activate CO2 is a promising first step.</p><p>Finally, the interaction of H2O at the ceria-modified rutile composites was investigated. This is important for a number of reactions, such as water gas shift or water oxidation and one of the limiting steps in these reactions is water dissociation which usually has an energy cost and an activation barrier. On both reduced ceria-TiO2 systems, water adsorption is exothermic and favourable and, importantly, this leads to spontaneous dissociation of water to form surface bound hydroxyls.</p><p>The results of this paper show that ceria-modified rutile TiO2 composites can (1) have reduced Ce 3+ cations, (2) show red shift in light absorption, (3) adsorb and activate carbon dioxide and (4) adsorb and activate water. This makes these composites interesting materials for the activation and conversion of CO2 and water.</p>

ChemRxiv

NF-\xce\xbaB as a Therapeutic Target in Inflammatory-Associated Bone Diseases

Inflammation is a defensive mechanism for pathogen clearance and maintaining tissue homeostasis. In the skeletal system, inflammation is closely associated with many bone disorders including fractures, nonunions, periprosthetic osteolysis (bone loss around orthopedic implants), and osteoporosis. Acute inflammation is a critical step for proper bone-healing and bone-remodeling processes. On the other hand, chronic inflammation with excessive proinflammatory cytokines disrupts the balance of skeletal homeostasis involving osteoblastic (bone formation) and osteoclastic (bone resorption) activities. NF-\xce\xbaB is a transcriptional factor that regulates the inflammatory response and bone-remodeling processes in both bone-forming and bone-resorption cells. In vitro and in vivo evidences suggest that NF-\xce\xbaB is an important potential therapeutic target for inflammation-associated bone disorders by modulating inflammation and bone-remodeling process simultaneously. The challenges of NF-\xce\xbaB-targeting therapy in bone disorders include: (1) the complexity of canonical and noncanonical NF-\xce\xbaB pathways; (2) the fundamental roles of NF-\xce\xbaB-mediated signaling for bone regeneration at earlier phases of tissue damage and acute inflammation; and (3) the potential toxic effects on nontargeted cells such as lymphocytes. Recent developments of novel inhibitors with differential approaches to modulate NF-\xce\xbaB activity, and the controlled release (local) or bone-targeting drug delivery (systemic) strategies, have largely increased the translational application of NF-\xce\xbaB therapy in bone disorders. Taken together, temporal modulation of NF-\xce\xbaB pathways with the combination of recent advanced bone-targeting drug delivery techniques is a highly translational strategy to reestablish homeostasis in the skeletal system.

nf-\xce\xbab_as_a_therapeutic_target_in_inflammatory-associated_bone_diseases

1. INTRODUCTION<!>2.1 Inflammation<!>2.1.1 Acute vs Chronic Inflammation<!>2.1.2 Proinflammatory and Antiinflammatory Functions of Macrophages<!>2.2 Acute Inflammation-Associated Bone Disorders<!>2.3.1 Fracture Nonunion<!>2.3.2 Periprosthetic Osteolysis<!>2.3.3 Senile Osteoporosis<!>3. INFLAMMATION AND NF-\xce\xbaB SIGNALING<!>3.1 The NF-\xce\xbaB Protein Family<!>3.2 Activators and Targets of Canonical Pathway<!>3.3 Activators and Targets of the Alternative Pathway<!>4.1 Bone Remodeling<!>4.2 NF-\xce\xbaB in Osteoclasts<!>4.3 NF-\xce\xbaB in MSCs/Osteoblasts<!>5. PHARMACEUTICAL APPROACHES TO MODULATE NF-\xce\xbaB ACTIVITY<!>6.1 Classification<!>6.2 Drug Delivery to the Skeletal System<!>6.2.1 Local Drug Delivery<!>6.2.2 Systemic Delivery (Bone-Targeting Vehicle)<!>7. CONCLUSION<!>

<p>Bone is the major component of the skeletal system and provides physical support and protection of the body, calcium metabolism, and endocrine regulation, and it facilitates the hematopoietic system in bone marrow. Bone remodeling is a dynamic process that continues throughout life and involves bone formation and bone resorption activities. The common path-ophysiological event in bone disorders is the disruption of bone homeostasis (Theoleyre et al., 2004). Bone homeostasis depends on the functional balance between bone-forming cells (osteoblasts, OBs) and bone-resorptive cells (osteoclasts, OCs). A functional imbalance between these two arms determines either osteosclerotic bone-forming diseases (i.e., osteopetrosis) or osteolytic bone-resorptive diseases (Theoleyre et al., 2004).</p><p>Inflammation is a protective mechanism involving the activation of innate and adaptive immune systems in response to exogenous (bacteria, virus, etc.) or endogenous (necrotic cells) stimuli. Immune cells recognize the inflammatory stimuli to activate several cellular signaling including nuclear factor-κB (NF-κB) (Cordova et al., 2014). NF-κB is a master transcriptional factor in regulation of the inflammatory response and bone-remodeling process (Lin, Tamaki, et al., 2014; Novack, 2011). The proinflammatory cytokines driven by NF-κB are powerful signals to modulate OB and OC activities (Purdue, Koulouvaris, Potter, Nestor, & Sculco, 2007). Activation of NF-κB signaling in OCs is crucial for their differentiation and activation (Boyle, Simonet, & Lacey, 2003), whereas the activation in OBs inhibits bone formation (Chang et al., 2009). These unique characteristics imply the great potential of NF-κB as a therapeutic target for the treatment of inflammatory-associated bone disorders.</p><p>Acute inflammation is an essential step to initiate tissue repair processes including bone healing (Alexander et al., 2011; Raggatt et al., 2014). Unresolved inflammation progresses into chronic inflammation and leads to pathological conditions in affected organs. This review will focus on the biological significance and therapeutic potential of NF-κB in bone disorders with acute (fracture healing) or chronic (fracture nonunion (FNU), per-iprosthetic osteolysis (see Section 2.3.2), and senile osteoporosis) inflammation. Tumor, osteoarthritis, rheumatoid arthritis, bone infection, and metabolic bone disorders are excluded because of their complicated pathogenesis involving (in some instances) systemic factors, the adaptive immune system, and factors beyond innate immunity and NF-κB signaling.</p><!><p>The major functions of inflammation are clearance of pathogens and reestablishment of tissue homeostasis. In addition to pathogen infection, sterile inflammation is defined as inflammatory responses induced by trauma, ischemia-reperfusion injury, or chemical-induced injury (Chen & Nunez, 2010). The acute inflammatory response in damaged tissue initiates the release of chemical mediators that increase vascular permeability and leukocyte infiltration via activation of the local endothelium. The infiltrated leukocytes, including neutrophils and macrophages, can recognize necrotic cell debris and secrete proinflammatory cytokines and chemokines to further enhance immune cell infiltration. The infiltrated cells engulf the damaged tissue and cell debris, and secrete proteinases and growth factors to facilitate tissue remodeling and reconstruction. Successful clearance of inflammatory stimuli is accompanied by increased antiinflammatory and reparative cytokines to resolve the inflammatory response and reestablish tissue homeostasis (Serhan & Savill, 2005). However, if unresolved, these events may progress to chronic inflammation when inflammatory stimuli persist in damaged tissue. This results in continuous secretion of cytokines that enhance tissue destruction and impair the homeostasis.</p><!><p>Acute inflammation is initiated by recognition of inflammatory stimuli including microorganisms or damaged cell debris via the pattern-recognition receptors (PRRs). There are several classes of PRRs that recognize a variety of stimuli and trigger downstream inflammatory responses, including toll-like receptors (TLRs), NOD-like receptors (NLRs), RIG-I-like receptors (RLRs), C-type lectin receptors (CLRs), and absence in melanoma 2 (AIM2)-like receptors. PRRs can recognize pathogen-associated molecular patterns (PAMPs) from microorganisms. In sterile inflammation, PRRs can recognize damage-associated molecular patterns (DAMPs) from damaged tissue. The recognition of PAMPs and DAMPs and the activation of proinflammatory responses have been well documented by Takeuchi and Akira (2010) and Chen and Nunez (2010). DAMPs are intracellular proteins such as heat-shock proteins (Quintana & Cohen, 2005), nucleic acid (Cavassani et al., 2008; Imaeda et al., 2009), and intracellular cytokines (Eigenbrod, Park, Harder, Iwakura, & Nunez, 2008). Release of DAMPs from necrotic cells with impaired membrane integrity is an indicator of tissue damage. Recognition of DAMPs via PRRs in tissue macrophages leads to the secretion of chemoattractants and local recruitment of neutrophils and circulating monocytes/macrophages.</p><p>The inflammatory response may switch from acute to chronic inflammation when the stimuli persist (tissue damage, infection, etc.). Chronic inflammation is marked by infiltration of macrophages and lymphocytes, as well as ongoing attempts at repair. Excessive production of inflammatory cytokines from macrophages during chronic inflammation may cause tissue damage and fibrosis. For example, in patients with joint replacement surgery, continued release of wear particles from implanted biomaterials induce chronic inflammation and periprosthetic osteolysis in confined regions (Lin, Tamaki, et al., 2014).</p><!><p>Macrophages are crucial regulators of initiation, progression, and resolution of inflammation (Martinez, Sica, Mantovani, & Locati, 2008). Polarized macrophages may acquire distinct phenotypes with proinflammatory (M1) or antiinflammatory (M2) behaviors (Mantovani, Biswas, Galdiero, Sica, & Locati, 2013; Martinez et al., 2008). Classical activation of macrophages with interferon-γ and/or lipopolysaccharide leads to M1 macrophage polarization. M1 macrophages secrete proinflammatory cytokines (tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), etc.) and chemokines (monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1α (MIP-1α), etc.) in a NF-κB-dependent pathway, which can result in tissue damage with additional leukocytes infiltration. Alternatively, macrophages exposed to IL-4 or IL-13 are polarized into M2 macrophages, marked by increased arginase-1 and antiinflammatory cytokines such as IL-10 and IL-1 receptor antagonist (IL-1Ra). The interaction between the NF-κB pathway and M2 macrophage polarization remains unclear. M2 or M2-like macrophages are capable of modulating and terminating the inflammatory response and are crucial for tissue remodeling and repair. Crosstalk between polarized macrophages and bone remodeling has been reviewed comprehensively elsewhere (Loi et al., 2016).</p><p>Thus, the biological roles of inflammation are to eliminate pathogens and foreign bodies, as well as initiate tissue repair and remodeling. The crosstalk of macrophages and others cells in the tissue microenvironment via modulation of inflammatory status and tissue remodeling may determine the status of inflammatory-associated conditions such as bone remodeling and repair.</p><!><p>Traumatic fracture and fragility fracture secondary to osteoporosis are closely associated with acute inflammatory responses. Infiltration of immune cells, especially macrophages, is critical for bone-healing processes (Loi et al., 2016). Fracture healing involves four consecutive phases: (a) acute inflammation, (b) cell proliferation and progenitor recruitment, (c) a stabilization step characterized by the consecutive formation of a fibrous, cartilaginous, and immature bony callus, and then (d) remodeling of the immature callus (Loi et al., 2016). The acute inflammation phase is driven by phagocytic cells including macrophages and polymorphonuclear neutrophils (PMNs), which are recruited from the hematopoietic niche and then attracted to the fractured site (Purdue et al., 2007). Macrophages and PMNs recognize DAMPs and PAMPs through TLRs and other receptors (see Section 2.1.1) and mediate NF-κB-dependent induction of proinflammatory and pro-osteoclastogenic cytokine secretion including TNF-α and IL-1β (Lin et al., 2015; Lin, Tamaki, et al., 2014). Transient elevated TNF-α levels during the acute inflammatory stage (d1–d3) are critical to the mediation of mesenchymal stem cell (MSC) migration into the fracture site and the differentiation into osteoblastic lineage cells (Karnes, Daffner, & Watkins, 2015). Supplementation of TNF-α (1 ng/ml) accelerates fracture healing rate and mineralization of callus (Glass et al., 2011). Nevertheless, persisted proinflammatory responses at the callus formation stage (days 3–7) could impair fracture healing. Martensson et al. reported that TNF-α and IL-1β synergistically decrease chondrocyte proliferation and survival at fracture callus, leading to reduction of bone formation in a rat model (Martensson, Chrysis, & Savendahl, 2004).</p><!><p>FNU consists in incomplete consolidation of the fracture, with an absence of progressive radiographic signs of healing over three consecutive months (Loi et al., 2016; Panteli, Pountos, Jones, & Giannoudis, 2015). Based on the radiographic findings, FNU can be classified into either hypertrophic, exhibiting an oversized soft callus around the fracture site; or atrophic, featured by the absence of visible soft callus (Marsell & Einhorn, 2011). While hypertrophic FNU is associated with mechanical instability, atrophic FNU involves an intrinsic deficit of host immune and/or bone-healing responses (Karnes et al., 2015). Histologically, FNU demonstrates persistence of disorganized fibrous tissue, woven bone, and cartilage at the nonunion site (Karnes et al., 2015).</p><!><p>Total joint replacement (TJR) is an effective surgical procedure to treat patients with end-stage arthritis. In 2011, approximately 1 million of TJRs were performed in the United States (AAOS, 2013). Wear particles and other orthopedic byproducts generated from the bearing surfaces of TJRs induce chronic inflammation and bone loss around the implant, leading to aseptic loosening, and revision surgery in nearly 10% of TJR patients (Purdue et al., 2007). Wear particles less than 10 μm are either phagocytized by macrophages, or enclosed by foreign body giant cells (FBGCs) (if >10 μm) (Cobelli, Scharf, Crisi, Hardin, & Santambrogio, 2011). Recognition of wear particles or DAMPs adhering to the particles via TLR2 and TLR4 induces the secretion of proinflammatory cytokines in the NF-κB-dependent pathway (Pearl et al., 2011). The proinflammatory cytokines including TNF-α and IL-1β further activate NF-κB in macrophages as a positive regulatory loop during the chronic inflammation, leading to OC activation, and osteolytic processes (Lin, Pajarinen, et al., 2016; Lin, Tamaki, et al., 2014). Inhibition of NF-κB activity suppresses PMMA and UHMWPE wear particle induced OC activation in vitro and in vivo, suggesting the therapeutic potential of targeting NF-κB pathway in the particle disease (Clohisy, Hirayama, Frazier, Han, & Abu-Amer, 2004; Lin, Pajarinen, et al., 2016).</p><p>Exposure of wear particles also impairs osteoblastic phenotypes and paracrine regulation functions in MSCs and OB-lineage cells. Reduced expression of collagen type 1, bone sialoprotein, and decreased bone mineralization was found in human and murine MSCs exposed to titanium or polyethylene wear particles (Chiu, Ma, Smith, & Goodman, 2009; Lin et al., 2015; Wang et al., 2002). Inhibition of NF-κB activity in the MSCs exposed to wear particles mitigated the reduced bone formation (Lin et al., 2015). The paracrine regulators including IL-8, GM-CSF (Haleem-Smith et al., 2012), M-CSF, and RANKL (Pioletti & Kottelat, 2004) are also upregulated in OB or MSC exposed to wear particles, which could further enhance inflammation and the osteolytic process.</p><!><p>Aging is associated with chronic inflammation and increased reactive oxygen species. The concept of "inflamm-aging" has been suggested to accelerate the aging process (Franceschi et al., 2000). Aging-associated bone loss is marked by reduced bone formation ability (compared to increased OC activity in postmenopause osteoporosis) and is often referred to as "senile osteoporosis" (Dobbs, Buckwalter, & Saltzman, 1999). Senile osteoporosis is associated with increased risk of fracture in 44–65% of women and 25–42% of men during the lifetime (Nguyen, Ahlborg, Center, Eisman, & Nguyen, 2007).</p><p>Though NF-κB activation could be associated with inflamm-aging process (Salminen et al., 2008), direct evidence of a correlation with senile osteoporosis in humans remain unclear. In one study using a murine model, NF-κB activation (increased phosphorylation of RelA) has been reported in the trabecular bone in natural aging mice (Yu et al., 2014). Furthermore, increased NF-κB activity was found in the MSCs isolated from aged mice (15 months) compared with younger mice (Lin, Gibon, et al., 2016). Inhibition of the NF-κB pathway partially rescued the reduction of osteogenesis in aged MSCs. Increased RANKL and decreased OPG expression (thus leading to increased RANKL/OPG ratio and OC activation) was observed in aged MSCs. Further investigation is essential to clarify the correlation of NF-κB pathway in the process of senile osteoporosis.</p><!><p>NF-κB is one of the best characterized transcription factors that regulate inflammation and innate and adaptive immune reactions (Hayden & Ghosh, 2011; Lawrence, 2009). NF-κB signaling is activated by a variety of proinflammatory and danger signals as well as cell stress sensed by multiple receptors expressed on the cell membrane, endosomal compartment, and cytoplasm. Activation of NF-κB signaling leads to the production of various inflammatory cytokines, chemokines, adhesion molecules, transcription factors, and antimicrobial effector molecules that initiate and module the inflammatory reaction, and orchestrates the immediate host response against pathogens and tissue damage. NF-κB signaling is also involved in lymphoid organogenesis; activation and proliferation of CD4+ T cells; T cell polarization into various different effector T cell populations; and to the maturation of B cells. The role of NF-κB signaling in these adaptive immune functions has comprehensively been reviewed elsewhere (Hayden & Ghosh, 2011). In the context of bone, NF-κB signaling is directly involved in the differentiation and activation of bone resorbing OCs (Novack, 2011; Soysa & Alles, 2009). Chronic NF-κB activation has also been shown to impair both the differentiation of MSCs along the osteogenic pathway and OB-mediated bone formation (Lin, Tamaki, et al., 2014). Thus NF-κB signaling plays a role both in physiological bone remodeling as well as pathological bone loss occurring in such inflammatory conditions as rheumatoid arthritis and periimplant osteolysis of TJRs. Indeed, blocking the chronic NF-κB signaling in these and other inflammatory conditions limits inflammation and prevents bone loss (Lin, Tamaki, et al., 2014; Xu et al., 2009).</p><!><p>The NF-κB transcription factor family consists of five members p50 (NF-κ B1), p52 (NF-κB2), RelA (p65), RelB, and c-Rel (Huxford, Hoffmann, & Ghosh, 2011; Lawrence, 2009). All of the NF-κB subunits share a structurally conserved N-terminal sequence spanning 300 amino acid residues called the Rel homology domain (RHD) (Ghosh, May, & Kopp, 1998; Huxford et al., 2011). The RHD is responsible for DNA binding, dimerization, and nuclear translocation of the NF-κB subunits (Courtois & Gilmore, 2006; Huxford, Huang, Malek, & Ghosh, 1998). As described by Huxford, Hoff-man, and Ghosh, the RHD can be divided into three structural components—the N-terminal domain (NTD), dimerization domain (DD), and the nuclear localization sequence (NLS) polypeptide—all of which mediate the various activities of the RHD and subsequent NF-κB signaling (Huxford et al., 2011). At the C-terminal end of the RHD, the DD folds so that two antiparallel β-sheets form an immunoglobulin-like (Ig-like) structure; one of the sheets forms an interface for subunit dimer formation while the other mediates nonspecific DNA contacts (Chen & Ghosh, 1999). Similarly, the NTD contains an Ig-like fold that binds DNA both base-specifically and backbone nonspecifically. Subunits RelA, RelB, and c-Rel are produced as a mature protein while the p50 subunit is produced from an inactive precursor p105 and the p52 from precursor p100 via posttranslational processing in proteasome (Courtois & Gilmore, 2006; Gilmore, 2006; Lawrence, 2009). The production of p50 is constitutive while the production of p52 is regulated and induced upon the activation of the noncanonical NF-κB pathway (Fig. 1). In addition, the NF-κB p105 and p100 proteins are distinguished from Rel proteins by IκB-like inhibitory domains that play a role in the binding of inhibitory IκB proteins (Karin, Yamamoto, & Wang, 2004).</p><p>In resting state, NF-κB subunits reside in the cell cytoplasm non-covalently bound by a group of IκB proteins that maintain the NF-κB subunits in inactive form (Huxford et al., 2011; Whiteside & Israel, 1997). The mechanism underlying the inhibitory effects of IκB binding has been elucidated by determining the X-ray crystal structure of IκB α bound to p50:RelA dimers (Jacobs & Harrison, 1998). It is thought that the long-range electrostatic interactions between the C-terminal PEST region of IκB α and the NTD of RelA causes a conformational change that does not allow for RelA to bind DNA (Huxford et al., 1998; Jacobs & Harrison, 1998). Moreover, IκB α conceals the NLS peptide of p65, preventing its nuclear localization.</p><p>The degradation of these inhibiting proteins is regulated by a group of IκB kinase complexes IKK1 (IKKα), IKK2 (IKKβ), and IKKγ (NEMO) (Chen, 2005; Karin & Ben-Neriah, 2000). Once activated by upstream signaling cascades, IKKs phosphorylate the inhibitory IκB proteins leading to their ubiquitination by E3 ubiquitin-protein ligase followed by degradation in 26S proteasome. Once released the NF-κB subunits home to the nucleus as hetero- or homodimers and regulate the transcription of multitude of genes by binding to the gene promoter regions know as B sites; currently more than 500 NF-κB target genes have been recognized (Boston_University). The dimers bind to DNA via 10 flexible loops that extend from the Ig-like fold; this mechanism is unlike most transcription factors, which utilize alpha helices (Chen & Ghosh, 1999). Beyond this unique DNA-binding scheme, the NF-κB dimer arranges along the major groove for a full turn to create a "butterfly" structure.</p><p>Depending on the composition of the NF-κB dimer, the NF-κB can either induce or inhibit gene transcription; complexes containing RelA, RelB, and c-Rel function as transcription promoters while p50 and p52 lack the C-terminal transcription activation domains necessary to induce gene reading and can activate transcription only when paired with other NF-κB family members (Hayden & Ghosh, 2011); correspondingly p50 homodimers lacking activation domains function as transcription suppressors (Bohuslav et al., 1998). The signaling pathway leading to the degradation of IκB and the subsequent release of NF-κB subunits is known as the canonical (classical) NF-κB pathway, while the pathway culminating to the cleavage of p100 to active p52 is known as noncanonical (alternative) NF-κB pathway (Fig. 1).</p><!><p>The canonical NF-κB signaling pathway is primarily involved in the sensing of danger due to tissue damage or infection, and is followed by rapid initiation and progression of an inflammatory reaction and antimicrobial functions (Huxford et al., 2011; Lawrence, 2009; Lin, Tamaki, et al., 2014). In the context of innate immunity, the pathway is activated by signals originating from two broad groups of receptors; the receptors for proinflammatory cytokines and the PRRs for various danger signal molecules (Hayden & Ghosh, 2014; Kawai & Akira, 2010). Downstream signals from these receptors convene to active a kinase complex formed by IKK1, IKK2, and IKKγ, with IKK2 playing the key role, leading to the release and nuclear translocation of mainly p50-RelA and p50-cRel dimers (Hayden & Ghosh, 2011). These factors promote the transcription of multiple proinflammatory cytokines, prostaglandins, chemokines, endothelial and leucocyte adhesion molecules as well as proteinases leading to recruitment and activation of further inflammatory cells, mainly neutrophils and macrophages. Antimicrobial effector molecules, such as defensing and reactive oxygen and nitrogen species, are also produced and the antigen presenting machinery induced for the subsequent activation of the adaptive immune system. In addition to transcription of proinflammatory signals, antiinflammatory cytokines such as IL-10 and IL-1rA as well as multiple inhibitors of NF-κB pathway, e.g., IκB proteins, are produced thus limiting the inflammatory reaction in a manner of an autocrine feedback loop (Lawrence, 2009).</p><p>Proinflammatory cytokines including TNF-α and IL-1 are among the best-known inducers and also target of the canonical NF-κB pathway (Hayden & Ghosh, 2014). These archetypal proinflammatory cytokines are abundantly produced during the inflammatory reaction and play a key role in multiple chronic inflammatory conditions. Binding of these cytokines to corresponding receptors TNF receptor 1 (TNFR1, widely expressed) and TNF receptor 2 (TNFR2, expressed on immune cells), and type I IL-1 receptor (IL-1R1) activates canonical NF-κB pathway signaling but also the MAP kinase/AP-1 pathway amplifying the inflammatory reaction.</p><p>The second set of receptors that activate the canonical NF-κB pathway are PRRs that sense danger signals originating from tissue damage and invading pathogens (Matzinger, 2002). The first recognized and the best-known PRR family is the TLRs (Kawai & Akira, 2010; Kumar, Kawai, & Akira, 2009). This set of receptors recognizes various evolutionally well-conserved molecular repeat structures expressed on various pathogens; the best-known examples include TLR2 ligand lipoteichoic acid (LTA) and TLR4 ligand lipopolysaccharide (LPS) both of which are fundamental structural components of Gram-positive or Gram-negative bacteria cell walls, respectively. TLRs also recognize conserved viral (e.g., single- and double-stranded RNA, recognized by TLR3, TLR7, and TLR8) and fungal (e.g., zymosan, recognized by TLR2) structures. In addition to these pathogen-derived molecules, or PAMPs, it has been suggested that several TLRs recognize endogenous ligands collectively known as alarmins (Bianchi, 2007; Kono & Rock, 2008). Other families of PPRs, including NLRs and RLRs, activate canonical NF-κB pathway and IRF3-mediated type 1 interferon production (Kawai & Akira, 2010, 2011). Unlike TLRs that are restricted to cell and endosomal membranes, NLRs and RLRs are located to the cell cytoplasm thus being optimally located to recognize viral structures and complementing the cells danger signal sensing machinery.</p><!><p>While the canonical NF-κB pathway is related to the rapid initiation and amplification of an inflammatory reaction, the best-known functions of the noncanonical pathway are related to lymphoid organogenesis and the activation and progression of adaptive immune response (Hayden & Ghosh, 2011; Lawrence, 2009). The activation of the pathway culminates in the induction of NF-κB-inducing kinase (NIK) and formation of IKK1 dimers. IKK1 phosphorylates p100 leading to its proteosomal processing into p52 and nuclear translocation of mainly p52/RelB dimers. The ligands that activate the noncanonical pathway include several TNF family members related to adaptive immune functions including lymphotoxin b, CD40 ligand, and B-cell activating factor (BAFF) but not TNF-α itself.</p><p>In the context of bone, the best-known function for the noncanonical NF-κB pathway is related to the bone resorption (Abu-Amer, 2013; Boyce, Yao, & Xing, 2010; Novack, 2011). The formation and function of bone resorbing OC are dependent on the receptor RANK expressed on circulating OC precursors (derived from monocytes) and its ligand, RANKL, produced by OBs, other MSCs, and activated T cells (Lacey et al., 1998; Suda et al., 1999). Both RANK and RANKL are necessary for OC formation. RANK signaling activates both the canonical and non-canonical NF-κB pathway via TRAF6 (Novack, 2011; Soysa & Alles, 2009). RANK signaling also activates the MAP kinase pathway with induction of the transcription factor c-Fos that is also necessary for OC formation (Grigoriadis et al., 1994). All of these pathways synergize to induce the expression of transcription factor NFATc1 that directly activates the transcription of OC-related genes and is considered as the master regulator of OC formation and sustained function (Kim & Kim, 2014; Takayanagi et al., 2002). The activity of RANKL is regulated on the one hand by a secreted decoy receptor, OPG that inhibits RANKL activity, and on the other hand by various inflammatory cytokines such as TNF and IL-1 and TLR ligands that enhance OC formation by synergizing with RANKL in activating the canonical NF-κB pathway (Osta, Benedetti, & Miossec, 2014; Simonet et al., 1997). Furthermore, the balance of RANKL and OPG production is regulated by these inflammatory signals typically increasing the RANKL/OPG ratio (Abu-Amer, 2013). Thus multiple mechanisms drive the increased OC formation and bone loss seen in the context of chronic inflammatory conditions.</p><!><p>Bone remodeling is a necessary process to repair damaged bone and involves the resorption and formation of hard tissue. OCs, OBs, and osteocytes are the cells maintaining bone matrix homeostasis in bone. Immune cells, especially macrophages, are critical in the bone-remodeling process in response to damage and other inflammatory stimuli (Alexander et al., 2011; Cho et al., 2014; Guihard et al., 2012; Lin, Tamaki, et al., 2014). Under normal physiological conditions, osteocytes secrete sclerostin (van Bezooijen et al., 2004) and transforming growth factor β1 (TGF-β1) (Heino, Hentunen, & Vaananen, 2002) to suppress the activities of OB and OC, respectively. Osteocyte apoptosis caused by damage or inflammation is associated with a reduction of the suppressive paracrine regulators and thus, initiates bone remodeling at the damaged site. The basic multicellular unit (BMU) is a specialized structure formed in the bone-remodeling process. In an active BMU, OBs and OCs line the bone surface, covered by a canopy-like structure consisting of bone resident macrophages (known as osteomacs) (Chang et al., 2008), and acting in bone resorption and bone formation by a coupling reaction. The process is then terminated when the bone homeostasis is reestablished.</p><p>The crosstalk between immune cells and bone cells is tightly associated with mineral homeostasis and tissue repair in bone. However, inflammation-associated NF-κB activation is not limited to immune cells. The signals can be activated in OBs and OCs via direct exposure to the stimuli like PAMPs or DAMPs, or indirect regulation by the immune cells (Xu et al., 2009; Chang et al., 2013; Lin, Tamaki, et al., 2014; Lin et al., 2015). The fundamental roles of NF-κB activation in OC differentiation and activation are well defined (Boyle et al., 2003). The biological functions of NF-κB activation in OBs and MSCs are recently being clarified (Chang et al., 2013, 2009; Cho et al., 2010; Lin et al., 2015), although the detailed regulation of their bone-forming ability remains unclear. In this section, we summarize the current findings of NF-κB activation effects on bone-remodeling process (Fig. 2), including the studies using transgenic animal models or the stimulation by proinflammatory cytokines such as TNF-α and IL-1β. In addition, several reports have indicated that the TLR agonists can modulate the biological activities in OC (Itoh et al., 2003; Takami, Kim, Rho, & Choi, 2002) and OB (Hwa Cho, Bae, & Jung, 2006; Lombardo et al., 2009; Mo et al., 2008).</p><!><p>OCs are terminal differentiated myeloid lineage cells, which can be characterized by the unique multinuclear morphology and the expression of OCs-specific markers including tartrate-resistant acid phosphatase (TRAP), cathepsin K, calcitonin receptor, and β3 integrin (Boyle et al., 2003). Myeloid precursor cells differentiate into macrophages when exposed to macrophage colony-stimulating factor (M-CSF), or differentiate into OCs in the presence of M-CSF and RANKL.</p><p>RANKL can induce both classical and alternative NF-κB activation in OCs and their precursors (Novack, 2011). Classical activation of NF-κB requires IKK2 to phosphorylate and degrade IκB, and releases RelA/p50 or cRel/p50 heterodimer to translocate into the nucleus. Deletion of IKK2 (IKK2−/−) in transgenic mice caused defective osteoclastogenesis in OC precursors in response to RANKL, TNF-α, or IL-1β, which results in osteopetrosis (excessive bone formation) and resistance to inflammatory-associated bone loss in vivo (Ruocco et al., 2005). In contrast, mutation of IKK1 (IKK1AA) shows a defect of osteoclastogenesis in OC precursors in response to RANKL but not TNF-α or IL-1β in vitro. Notably, the defect of osteoclastogenesis was not observed in IKK1AA mice in vivo, which could be explained by compensatory effects from the paracrine regulation of OB. The role of IKKγ in skeletal development remains unclear due to the lethal phenotypes of severe liver degeneration in IKKγ-deficient mice (Rudolph et al., 2000). No phenotypes in bone have been reported in the transgenic mice lacking IκB or cRel expression (Gerondakis et al., 1996; Klement et al., 1996). Further studies are required to clarify their roles in skeletal development and bone remodeling.</p><p>Osteopetrosis and impaired osteoclastogenesis were reported in the transgenic mice with p50/p52 deletion, and the phenotypes were rescued by bone marrow cell transplantation (Franzoso et al., 1997; Iotsova et al., 1997). The transgenic mice with the single deletion in p50 or p52 showed no significant phenotypes in bone, suggesting the redundant roles of p50 and p52 to regulate OC functions and bone homeostasis. The RelA-deficient mice are embryonically lethal (Beg, Sha, Bronson, Ghosh, & Baltimore, 1995), while the mice with deficiency in RelA and TNFR1 live for 2–3 weeks (Rosenfeld, Prichard, Shiojiri, & Fausto, 2000). In the radiated wild-type mice transplanted with bone marrow cells from RelA/TNFR1-deficient mice, the OC numbers at the basal level or upon RANKL induction are significantly decreased (Vaira, Alhawagri, et al., 2008). RANKL-induced significant cellular apoptosis in RelA/TNFR1-deficient precursor cells in vitro through JNK/Bid/caspase 3 pathway, and blocking of proapoptotic Bid signaling protect the cells from RANKL-induced cell deaths and rescued the defect of osteoclastogenesis in p65-deficient cells. Taken together, the results suggested that RelA is essential for the anti-apoptotic signaling in OC in response to RANKL stimulation, but is not required for OC activation.</p><p>The alternative NF-κB pathway can be activated by RANKL but not the proinflammatory cytokines. In this process, NF-κB-inducing kinase (NIK) is stabilized in response to the stimulation and activates IKKα, which then process p100 into p52 to form RelB/p52 heterodimer (Sun, 2011). The nuclear translocation of RelB is specifically regulated by p100, and thus unique downstream signaling of NIK. Mild increased trabecular bone volume and normal OC numbers at the basal line are observed in both NIK-and RelB-deficient mice (Novack et al., 2003; Vaira, Johnson, et al., 2008). Nevertheless, administration of RANKL failed to induce osteoclastogenesis in the OC precursors with the defect in NIK or RelB in vitro (Novack, 2011). Overexpression of RelA cannot rescue defective osteoclastogenesis in RelB-deficient precursor cells induced by RANKL, suggested that RelB may be the key regulator of OC differentiation (Vaira, Johnson, et al., 2008).</p><p>The proinflammatory cytokines including TNF-α and IL-1β induce osteoclastogenesis via direct activation of OC precursor cells, or indirect induction of RANKL secretion in bone marrow stromal cells. Nevertheless, the dependence of RANKL/RANK signaling in the OC activation process is still in debate. Kobayashi et al. (2000) first reported that murine bone marrow myeloid cells differentiated into TRAP+ OCs in the presence of M-CSF and TNF-α. The bone-resorption ability in OCs and RANKL secretion in OBs stimulated by TNF-α was dependent on IL-1β (Kobayashi et al., 2000; Wei, Kitaura, Zhou, Ross, & Teitelbaum, 2005; Zwerina et al., 2007). Antibodies against TNF-α receptors but not RANKL inhibited this process, suggesting that the TNF-α-mediated OC activation is independent of RANKL/RANK signaling (Kobayashi et al., 2000). Lam et al. showed that TNF-α and M-CSF-mediated OC activation and required a permissive level of RANKL (Lam et al., 2000). Inhibition of RANKL by OPG at an earlier stage of OC differentiation (exposed to M-CSF alone) augmented TNF-α-mediated OC activation. Interestingly, bone marrow myeloid cells deficient in RANK can differentiate into OCs by TNF-α stimulation; this demonstrated the existence of RANKL/ RANK-independent pathway of OC activation (Kim et al., 2005).</p><p>The classical NF-κB activation can be stimulated by TNF-α, whereas the alternative NF-κB activation could be inhibited in OC precursors. TNF-α induced the accumulation of p100 in OC precursors, which inhibited the alternative NF- B activation (Yao, Xing, & Boyce, 2009). A recent study further demonstrated that the limitation of TNF-α-mediated OC activation was only observed in macrophage/OC precursors stimulated by M-CSF but not in combination with TNF-α (Zhao et al., 2015). Mechanistic studies showed that TNF-α-induced RelB expression and enhanced OC activation, but this process was self-limited by suppression of NFATc1.</p><!><p>OBs are specialized bone-forming cells differentiated from MSCs, which have multilineage differentiation abilities including bone, cartilage, adipose tissue, etc. Runx2 is a master regulator of osteoblastogenesis which initiates the commitment of osteogenic differentiation into osteoprogenitors. The expression of Runx2, followed by osterix, induces alkaline phosphatase (ALP) and type I collagen secretion, and turn the cells into mature OBs located on the bone surface (Wu, Scadden, & Kronenberg, 2009). Mature OBs deposit the organic matrix for bone mineralization and, once surrounded by bone matrix, become osteocytes, which account for almost 95% of all bone cells. Osteoblastogenesis is guided by paracrine or endocrine factors including parathyroid hormone, bone morphogenic proteins (BMPs), Wnt signaling, and growth factors such as TGF-β1 (Novack, 2011). In addition, differentiated OBs secrete M-CSF, RANKL, and OPG to regulate OC activity in a coupling reaction during the bone-remodeling process.</p><p>The role of NF-κB in OC activation and differentiation has been well defined. However, the biological effects of NF-κB activation in OB differentiation and bone formation are still in debate. The first direct evidence for the suppressive role of canonical NF-κB signaling in osteogenesis was demonstrated by using transgenic mice expressing a dominant negative form of IKKγ in differentiated OBs as controlled by osteocalcin promoter. Inhibition of NF-κB activity in OBs increased trabecular bone mass and bone mineral density without affecting OC function in young (2–4 weeks old) mice. In addition, inhibition of NF-κB activity prevented ovariectomy-induced bone loss in adult mice by maintaining bone-forming ability in OBs. In a study using human, murine, and rat MSCs, inhibition of IKK2 by a small molecular inhibitor or gene deletion increased osteogenic ability at the basal level or in the presence of TNF-α or IL-17. Local administration of IKK2 inhibitor enhanced MSC-mediated bone repair in a murine calvarial bone defect model. This mechanistic study demonstrated that NF-κB activation induced the expression of Smurf1/2, the ubiquitin ligase controlling the degradation of β-catenin, and inhibits osteogenic differentiation (Chang et al., 2013). Expression of constitutive active IKK2 in OBs and cho-ndrocytes in transgenic mice controlled by Col2α1 promoter exhibits abnormal skeletal development with impeded bone formation and reduced bone mineral density. A heterozygous missense mutation on RelA in an osteopetrosis patient was revealed by trio-based whole exome sequencing, demonstrating the critical role of NF-κB signaling in human skeletal homeostasis.</p><p>In studies of noncanonical NF-κB signaling on bone formation, increased OB numbers and increased bone formation rate were found in the transgenic mice with NIK mutation. However, the effects of mutant NIK on osteogenesis had not been examined in MSCs and/or OBs. RelB-deficient mice developed age-related increased trabecular bone mass associated with increased bone formation. RelB-deficient MSCs had increased bone-forming ability in both in vitro studies and in the murine tibia defect model. These studies suggest that the noncanonical NF-κB signaling also plays a significant role in osteogenic differentiation.</p><p>Compared to the evidence in transgenic animal studies, the effects of NF-κB activation induced by extracellular stimulation in OB differentiation remain paradoxical (Osta et al., 2014). Bone mineral density and bone formation were elevated in the TNF-α or TNF-α receptor 1-deficient mice, whereas bone-resorption activity was not changed (Li et al., 2007). Direct injection of TNF-α into wild-type mice reduced osteogenic differentiation in MSCs, which was blocked in the ubiquitin ligase WWP1-deficient mice (Zhao et al., 2011). In vitro studies with primary bone marrow stromal cells or MC3T3 E1 (clone 14) cells demonstrated that 10 ng/ml TNF-α potently suppressed osteogenesis via suppressing Runx2 expression (Abbas, Zhang, Clohisy, & Abu-Amer, 2003; Gilbert, Rubin, & Nanes, 2005; Li et al., 2007). Interestingly, TNF-α-mediated inhibition of Runx2 is NF-κB dependent, whereas the suppression of osterix is depended on MEK1/ ERK1 signaling but independent of NF-κB (Lu, Gilbert, He, Rubin, & Nanes, 2006).</p><p>There is increasing evidence indicating an important induction role of TNF-α in osteogenic differentiation. Hess et al. demonstrated that treatment of 20 ng/ml TNF-α during osteogenic differentiation enhanced BMP2 expression, followed by Runx2 and osterix expression, and increased mineralization in human MSCs (Hess, Ushmorov, Fiedler, Brenner, & Wirth, 2009). Induction of constitutive active IKK2 by using retroviral vectors enhanced, whereas IκB impaired TNF-α-mediated osteogenesis induction. In studies of rat MSCs cultured in poly(ε-carprolactone) scaffold, the lower dose (0.1–5.0 ng/ml) inhibited, whereas the higher dose (50 ng/ml) of TNF-α enhanced mineralization in dexamethasone-pretreated cells (Mountziaris et al., 2013; Mountziaris, Tzouanas, & Mikos, 2010). The high dose of TNF-α mediating osteogenic induction was only observed with continuous (days 1–16) or early (days 1–4) treatments, but not with intermediate or later treated cells (Mountziaris et al., 2013). Early treatments of extracellular NF-κB stimulators including TNF-α, LPS, or peptidoglycan (the agonist for TLR2) enhanced osteogenesis in human adipose tissue-derived (Cho et al., 2010) or bone marrow-derived MSCs (Croes et al., 2015). Inhibition of NF-κB activity or silence of its downstream target TAZ impaired the induction of osteogenic differentiation, suggesting the direct regulation of NF-κB on TNF-α-mediated osteogenesis (Cho et al., 2010). In addition, Lu et al. demonstrated that human OBs and MSCs preconditioned with 1 ng/ml TNF-α for 1–3 days enhanced osteogenic differentiation via induction of BMP2 expression (Lu et al., 2013; Lu, Wang, Dunstan, & Zreiqat, 2012). Mechanistic studies have shown that inhibition of ERK1/2 or Wnt signaling impeded TNF-α-induced osteogenesis (Briolay et al., 2013; Lu et al., 2013); however, these studies did not address the role of NF-κB induced by TNF-α. In vivo studies have demonstrated that local injection of TNF-α at the early stage (24 h) augmented fracture healing by recruitment of muscle-derived stromal cells and infiltrated macrophages. Low and continuous levels of TNF-α were associated with proosteogenic effects, contributing to the formation of bone spurs (enthesis) by upregulating the activity of ALP (Ding et al., 2009; Lencel et al., 2011). However, the involvement of NF-κB signaling during the inflammation and healing processes remains unclear (Chan et al., 2015; Glass et al., 2011).</p><p>Taken together, although studies using transgenic animals demonstrated that NF-κB activation impairs normal skeletal development and bone-forming ability in OB-lineage cells, their effects on the osteogenic differentiation stimulated by extracellular signals are still in debate. The controversial finding in these reports could be due to the dose and the exposure times of NF-κB inducer, cell type used, and the conditions of osteogenic induction (DelaRosa & Lombardo, 2010; Osta et al., 2014).</p><!><p>In this section, we will broadly discuss the structural aspects of NF-κB transcription factors, their interactions with select regulatory proteins, and how this knowledge can help in targeting NF-κB signaling for therapeutic purposes.</p><p>As aberrant NF-κB signaling is implicated in many disease processes, the development of NF-κB inhibitors has been widespread. To date, there are over 800 inhibitors that have been reported with, undoubtedly, many more to come (Gilmore & Garbati, 2011). There are step-wise approaches to inhibiting the NF-κB transduction pathway by: receptor inhibition, adaptor inhibition, IKK inhibition, IκB stabilization, cytoplasmic retention, and transcription factor inhibition (Gilmore & Garbati, 2011).</p><p>Since ligand binding to cell-surface receptors activates NF-κB signaling, inhibition of receptor binding can be used to block NF-κB activation. Most notably, anti-TNF-α antibodies such as etanercept and infliximab have been used to block activation of the canonical NF-κB pathway and have been used in several chronic inflammatory diseases (Gilmore & Garbati, 2011; Taylor & Feldmann, 2009). Similarly, denosumab, an anti-RANKL antibody, has been used to treat osteoporosis, and its role in preventing osteolytic lesions following total hip arthroplasty is in Phase 2 clinical trial (Clinicaltrials.gov, 2012). Once receptors are engaged, adaptor proteins such as TRAF are recruited to the cell membrane. Though these receptor or adaptor inhibitors are effective, their off-target effects on multiple signaling pathways and the compensatory effects from other NF-κB upstream regulators have made them less desirable as specific NF-κB inhibitors.</p><p>Most of the developments in NF-κB inhibitors have focused on targeting the IKK protein family since they are the central integrator of the NF-κB pathway without involvement of other cellular signaling. There are a variety of inhibitors that exert their effects via different mechanisms (Gilmore & Herscovitch, 2006): (1) The ATP analog that specifically interacts with IKK. For example, β-carboline, a natural ATP analog, specifically binds IKK2 to inhibit NF-κB signaling (Karin et al., 2004). Similarly, NSAIDs provide COX-independent antiinflammatory effects by competitively inhibiting the ATP-binding site of IKK2 (Karin et al., 2004). (2) Compounds bind to IKK proteins and mediate conformational changes. The synthetic BMS-345541 has been shown to inhibit IKK2 activity through allosteric effects (Karin et al., 2004). (3) Compounds bind to the Cys-179 residue on the activation loop on IKK protein and blocking the kinase activity. Several thiol-reactive compounds were shown to interact with IKK2 and inhibit the kinase activity, although the detailed mechanism remains unclear (Kwok, Koh, Ndubuisi, Elofsson, & Crews, 2001). In the canonical NF-κB pathway, NEMO and IKK1 are also comprised in the IKK complex. Therefore, dominant negative mutants or specific inhibitors to these proteins could also result in NF-κB signaling inhibition (Gilmore & Garbati, 2011; Scheidereit, 2006). For bone-related disease, the IKK inhibitor SAR113945 recently completed Phase 1 of clinical trials as a treatment for knee osteoarthritis (Clinicaltrials.gov, 2011). Notably, most of the current developed IKK inhibitors have targeted IKKβ and thus only inhibit the canonical NF-κB pathway. Inhibition of the noncanonical pathway via targeting IKK1 activity could be particularly important in osteolytic bone diseases, regarding the fact that IKK1 mutant in OC precursors showed defective osteoclastogenesis but normal TNF-α and IL1β signaling (Ruocco et al., 2005). As the IKK complex is not completely understood in itself, it is almost certain that more IKK inhibitors will be developed and/or discovered to match future understanding.</p><p>The next important step in the NF-κB signaling is the degradation of IκB. There are three main strategies for blocking IκB degradation: (1) promoting IκB synthesis, (2) blocking IκB ubiquitination, and (3) inhibition of the proteasome (Gilmore & Garbati, 2011). The most prominent proteasome inhibitor is bortezomib, which has shown efficacy in treating multiple myeloma as well as other hematologic and solid tumors (Gilmore & Garbati, 2011; Jagannath et al., 2010). Similarly, sulfasalazine, a medication used to treat inflammatory bowel disease, prevents NF-κB activation by blocking IκB degradation in response to TNFα and LPS (Karin et al., 2004; Wahl, Liptay, Adler, & Schmid, 1998).</p><p>Once IκB is degraded, the NF-κB dimer must translocate into the nucleus, so inhibitors of nuclear localization can block NF-κB signaling. As nuclear entry appears to be mediated by importin α, cell-permeable peptides with the NLS of p50 have been used to saturate importin α, and thus, block NF-κB dimer nuclear entry (Gilmore & Garbati, 2011; Letoha et al., 2005; Lin, Yao, Veach, Torgerson, & Hawiger, 1995; Torgerson, Colosia, Donahue, Lin, & Hawiger, 1998). However, these peptides were not specific to NF-κB and have not been used applied beyond the laboratory.</p><p>Finally, NF-κB signaling can be blocked at the level of DNA by directly blocking DNA binding or competitively inhibiting binding through the introduction of NF-κB decoy oligodeoxynucleotides (ODNs). For example, there are several compounds that target both IKK2 and NF-κB DNA binding such as parthenolide (Garcia-Pineres, Lindenmeyer, & Merfort, 2004; Gilmore & Garbati, 2011). However, these compounds likely affect other protein targets. Alternatively, NF-κB decoy oligonucleotides (ODN) specifically compete for binding of NF-κB dimers to their DNA targets, and could simultaneously inhibit both canonical and noncanonical NF-κB pathway. It has been shown that NF-κB decoy ODN significantly suppress cyto-kine and chemokine expression in macrophages, especially in the setting of periprosthetic osteolysis (Lin, Pajarinen, et al., 2016; Lin et al., 2015; Lin, Yao, et al., 2014). Moreover, there are several NF-κB decoy ODN-based therapies that have entered clinical trials for dermatitis and psoriasis (Gilmore & Garbati, 2011).</p><!><p>Over 800 NF-κB inhibitors have been reported, and the number continues to increase (Gilmore & Garbati, 2011; Gilmore & Herscovitch, 2006). These inhibitors can be broadly divided into three categories including (1) proteins and peptides, (2) small molecules, and (3) nucleic acids. Proteins and peptides inhibitors include antibodies and growth factors and are highly specific with less off-target side effects (Craik, Fairlie, Liras, & Price, 2013). The common limitations in protein-based treatment are instability when applied in vivo, high dose requirement, high cost of manufacturing, undesirable immunogenic effects, contamination, and the limitations for oral administration. Small molecules are natural or synthetic nonpeptide molecules with small molecular size (<1000 Da) and have several advantages in clinical application. These molecules are characterized by greater tissue penetration and are less immunogenic due to their smaller size compared to the protein-based compounds (Lo, Ashe, Kan, & Laurencin, 2012). Other advantages include lower manufacturing costs and application for oral administration. However, these compounds could be less selective compared to the protein or nucleic acid-based drugs, raising the concern of nonspecific toxicity, limiting their clinical application (Balmayor, 2015; Torchilin, 2000). Nucleic acid-based molecules include such as oligonucleotides, small interfering RNAs (siRNAs), and microRNAs (miRNAs). These approaches are highly specific and directly silence protein translation via siRNA or miRNA, or inhibit gene transactivation via decoy ODN. In particular, modulating the transcriptional process such as NF-κB by using the decoy ODN is an emerging approach due to the complexity of the signal transduction pathway (Rad et al., 2015). Synthetic decoy ODN is a short fragment of DNA which has the consensus sequence of the binding site of the target transcription factor, thus decoy ODN has the ability to bind to free target transcription factor subsequently preventing these factors from binding to the specific promoter regions (Bielinska, Shivdasani, Zhang, & Nabel, 1990). Like protein-based therapy, nucleic acids are also limited by low cellular uptake and rapid degradation in biological fluids (De Stefano, 2011).</p><!><p>Local drug delivery is applicable to many of the bone disorders in a confined region including fractures and periprosthetic osteolysis. Though local delivery strategy has the advantage of reduced systemic adverse effects, systemic drug delivery is still desired for the long-term management during the disease process, and treatment for systemic bone diseases such as osteoporosis. Recent developments in bone cell-specific targeting vehicles allow gene modulation and transcriptional regulation in OC, OB, or MSC in skeletal system. Thus, the adverse effects of NF-κB therapy to nontargeted cell populations (i.e., lymphocytes) in the bone marrow can be reduced and advance its translational application. Here we summarize the current advanced techniques for local and systemic drug delivery in the skeletal system (Fig. 3).</p><!><p>Local drug delivery systems are designed to keep the localized and controlled release of biomolecules in a confined region. The advantages of local drug delivery include reduced systemic toxicity; avoidance of the risk of overdose; and upholding effective concentrations at target regions. The aims of drug delivery in orthopedics are to improve bone-healing processes, increase osseointegration, mitigate inflammation, and prevent infection. Implantable devices with controlled drug release are some of the most commonly used strategies for local drug delivery in the orthopedic field, and the techniques have also been applied to other diseases including cardiovascular diseases, cancer, periodontal diseases, and ophthalmologic diseases (Arruebo, Vilaboa, & Santamaria, 2010). Orthopedic implants are widely used for fracture fixation, TJR, spinal reconstruction, and other orthopedic applications. Several different strategies have been developed for surface coating of local drug release of orthopedic implants (Goodman, Yao, Keeney, & Yang, 2013; Raphel, Holodniy, Goodman, & Heilshorn, 2016), including the use of hydrogel, immobilization (Maia, Bidarra, Granja, & Barrias, 2013), and layer-by-layer coating (de Villiers, Otto, Strydom, & Lvov, 2011).</p><p>The layer-by-layer coating method is based on the alternating deposition of positively and negatively charged polyelectrolytes onto the implant surface. Charged biomolecules can be loaded onto the surface, and the amount of encapsulated biomolecules and release rate can be tuned by changing the concentration of the biomolecules, the number of layers, and the type of polyelectrolytes. Coating can be performed onto any shape and dimension of different material surfaces. Furthermore, due to simple process of layer-by-layer coating, various biomolecules have been applied for drug release from implants including proteins (Keeney et al., 2013; Min, Braatz, & Hammond, 2014), nucleic acids (Miyake et al., 2014; Tahara et al., 2011), and small molecules (Min et al., 2014). The limitations of layer-by-layer coating techniques include the fact that many layers are required to prevent rapid diffusion and burst release of biomolecules. Thus, long production times are needed, which may lead high batch-to-batch variability. Also, the influence of the layers on the mechanical stability after a press fit implantation into bone must be considered. Further studies are required to address such limitations.</p><p>Combination of drug delivery systems have been used to overcome the instability of target drugs such as ODN. De Rosa and La Rotonda reviewed the details of delivery systems including cationic liposomes, poly-ethylenimine (PEI), chitosan, and poly(lactide-co-glycolide) (PLGA) nanospheres which have the ability to increase the cellular uptake of ODN, prolong their stability, and localize the effect of ODN to target cells and tissues (De Rosa & La Rotonda, 2009). Furthermore, coating with chitosan showed a positive charge, which can penetrate easily through the negative charged cell membrane and enhance cellular uptake of ODN (Mao et al., 2001). Additionally, PLGA is thought to have the proton sponge mechanism to escape from the endosomal pathway (Panyam, Zhou, Prabha, Sahoo, & Labhasetwar, 2002). Taken together, combinations of multiple drug delivery systems could improve the drug release profile and keep the biological stability of target drugs in a confined region.</p><!><p>Early development of drug delivery to the skeletal system was focused on targeting the bone environment. The synthetic compounds including bis-phosphonates and tetracycline have high affinity for calcium ions and hydro-xyapatite (Pazianas & Abrahamsen, 2011; Russell, 2011). Therefore, the concept of bone-targeted delivery system is the use of biomolecules conjugated with bisphosphonates as ligands targeting bone mineral (Cole, Vargo-Gogola, & Roeder, 2016). Clinical applications investigating bisphosphonates as a targeting ligand include metabolic bone diseases such as osteoporosis (Bhandari, Newa, Chapman, & Doschak, 2012; Fujisaki et al., 1997; Morioka et al., 2010), bone infection (Houghton et al., 2008), rheumatoid arthritis (Hirabayashi et al., 2001), osteosarcoma, and cancer metastases to bone (Klenner et al., 1990; Reinholz et al., 2010; Torres Martin de Rosales, Finucane, Mather, & Blower, 2009). Intravenous injection or oral administration of bisphosphonate-conjugated vehicle delivered the desired compounds to bone due to their high affinity for calcium crystals (Widler, Jahnke, & Green, 2012). Also, bisphosphonates can regulate calcium homeostasis and inhibit OC activity, further enhancing the clinical application for several bone disorders. Conjugation of bisphosphonates with PLGA nanoparticles (Thamake, Raut, Gryczynski, Ranjan, & Vishwanatha, 2012) or N-(2-hydroxypropyl)methacrylamide (HPMA) (Miller et al., 2011) successfully delivered the small molecule compounds and siRNA to bone. However, recent reports suggested that long-term treatment of bisphosphonates-induced OB apoptosis (Orriss, Key, Colston, & Arnett, 2009), and can cause osteo-necrosis of the jaw (Favus, 2007). Although the direct link between bisphosphonates and jaw osteonecrosis remains unclear, preventive treatment for jaw osteonecrosis is important during bisphosphonates therapy. An alternative delivery strategy is to conjugate the therapeutic compounds with tetra-cycline, an antibiotic with high affinity to calcium ions and thus have bone-targeting ability (Neale et al., 2009). The development of tetracycline and its derivative to conjugate with drug carrying vehicles could be an efficient strategy to deliver agents to the skeletal system without induction of jaw osteonecrosis (Dang et al., 2016).</p><p>Recent development of drug delivery models for the skeletal system has advanced to cell-specific targeting vehicles to avoid the toxic effects on nontargeted cells. The bone-forming surface is characterized by low crystallized hydroxyapatite and amorphous calcium phosphate compared to the high crystallized hydroxyapatite in bone-resorption surface (Dang et al., 2016). The differences of chemical and physical properties enable the design of OC- or OB-targeting vehicles. For example, the tripeptite asparate–serine–serine (DSS) binds to bone formation sites preferably than bone-resorption site in vivo (Zhang et al., 2012). On the other hand, the acid octapeptide with aspartic acid has high affinity to hydroxyapatite and accumulated at bone-resorption surfaces (Wang et al., 2007). Conjunction of the bone formation or bone-resorption selective peptide with dio-leoyltrimethylammonium propane (DOTAP)-based cationic liposomes or HPMA nanoparticles successfully delivered siRNA, protein, or small molecule compounds to the desired region (Wang et al., 2007; Zhang et al., 2012).</p><p>A new developed technique, named as cell-SELEX (Gold, 1995), was able to screen and identify cell-specific molecules and target OB, OC, and even MSC, specifically (Dang et al., 2016). A random pool of 1013–1016 of ssDNA or ssRNA is used to screen for the cell-specific targeting molecule. CH6 is an OB-specific aptamer screened from cell-SELEX system (Liang et al., 2015). Conjugation of CH6 with lipid nanoparticles was able to deliver siRNA to OB at cellular level in vivo. Antagomir-188 is another example of MSC-specific aptamer screened from cell-SELEX system (Li et al., 2015), which can specifically regulate miRNA-188 in bone marrow MSCs in vivo. Taken together, the advanced techniques enable the NF-κB-targeting therapy in the skeletal system at the cellular level, reduce the potential toxic effects to the immune system, and advance the translational application in inflammatory bone disorders.</p><!><p>Despite direct evidence from transgenic animal studies demonstrating the essential roles of NF-κB in the activation of OC and the suppression of OB differentiation, bone-remodeling processes are sensitive to the timing, duration, dose, and composition of upstream NF-κB stimulators (Fig. 4). Acute inflammation or low dose inflammatory cytokines are indispensable and beneficial for bone defect healing processes. Therefore, temporal modulation or delayed inhibition could optimize the therapeutic effects of targeting NF-κB pathway in bone diseases associated with acute inflammation. Alternatively, overwhelming inflammatory signals (e.g., infection) or unresolved chronic inflammation (e.g., periprosthetic osteolysis) alters the balance of bone remodeling toward osteolytic processes, thus effective inhibition of NF-κB signaling is required to mitigate these inflammation-associated bone diseases.</p><p>There are many modalities to target the canonical or noncanonical NF-κB signaling cascades. In many cases, the strategy of NF-κB inhibition focuses on suppressing IKK2 kinase activity or maintaining IκB protein stability. These approaches have proved to be effective in blocking the canonical pathway; however, they cannot modulate noncanonical signaling and consequent osteoclastogenesis (Ruocco et al., 2005). Although the strategic use of NF-κB decoy ODN could simultaneously target both canonical and noncanonical signaling, the stability of the decoy ODN in vivo, or the potential toxic effects induced by chemically modified ODN, remain an obstacle to their translational application (Osako, Nakagami, & Morishita, 2012). Most likely, the best approach will be a combination of inhibitors that have specific activity, broad activity, and are synergistic, and provide a multistep inhibition of the inflammatory cascade. Enhanced understanding of situation-specific NF-κB activation and unique structural changes may also allow for the development of increasingly refined NF-κB target strategies.</p><p>The central roles of NF-κB as a master regulator of macrophages, OC, and OB make it possible to manipulate both the inflammation and bone-remodeling processes. Nevertheless, the critical functions of NF-κB in the immune system also raise concerns of toxicity with systemic treatment. Local delivery with controlled drug release systems is an efficient strategy for long-term manipulation of the NF-κB pathway with minimal side effects and can be applied to many bone diseases including fracture healing, per-iprosthetic osteolysis, osteoarthritis, etc. The discovery of bone-targeting drug delivery vehicles further advances the possibility to deliver siRNA, decoy ODN, or even small molecular inhibitors with minimal impacts on the patient's immune function.</p><p>Taken together, the in vitro and in vivo evidence strongly suggest that NF-κB-targeting therapy has great potential to restore impaired bone-remodeling processes. The natural differences in pathogenesis between acute and chronic inflammation suggest that the optimal timing, dose, and targeting strategy to modulate NF-κB pathways are critical in order to achieve the desired therapeutic effects. Temporal modulation of NF-κB activity with advanced drug delivery strategies could efficiently mitigate osteolytic processes and enhance bone formation in the patients with inflammation-associated bone diseases.</p><!><p>Canonical (left) and alternative (right) NF-κB pathway and the target strategies: (1) inhibition of cell-surface receptor binding, (2) inhibition of receptor adaptor proteins, (3) IKK inhibition, (4) blocking IκB degradation/upregulating IκB /inhibiting proteasome, (5) inhibit nuclear translocation, and (6) block DNA binding/transcriptional activation.</p><p>The roles of NF-κB pathway in OC and OB/MSC biological activity. The upstream NF-κB stimulators (TNFα, IL-1β) can enhance OC activity. The effect of NF-κB activation to OB/MSC is associated with timing, dose, duration, and the composition of the stimulators (TNFα, LPS, etc.). The table at the bottom summarized the specific role of NF-κB protein family reported in the studies using transgenic mice or pharmacological inhibitors. *IKKγ- and RelB-deficient mice are embryonic lethal, and their roles in OC have not been reported. The specific role of IKKγ in OB was identified using OB-specific transgenic mice model.</p><p>The strategies of drug delivery to the skeletal system. (A) Three surface coating procedures of the implants. (B) Systemic drug delivery conjugated with bone-targeting vehicle. OB, osteoblast; OC, osteoclast; BMSC, bone marrow mesenchymal stem cell.</p><p>Temporal modulation of NF-κB activity in inflammatory-associated bone diseases. Blue line represents optimal condition of NF-κB signaling for bone-healing/bone-remodeling process. Red dash line represents the impaired inflammatory response at acute phase and/or persistent response at chronic phase. The arrows indicate the optimal bone regeneration conditions by either induction of NF-κB signaling at acute phase of inflammation (Red arrow), or suppression at chronic phase with unresolved inflammation (Green arrow).</p>

PubMed Author Manuscript

Probing Protein Shelf Lives from Inverse Mean First Passage Times

Protein aggregation is investigated theoretically via protein turnover, misfolding, aggregation and degradation. The Mean First Passage Time (MFPT) of aggregation is evaluated within the framework of Chemical Master Equation (CME) and pseudo first order kinetics with appropriate boundary conditions. The rate constants of aggregation of different proteins are calculated from the inverse MFPT, which show an excellent match with the experimentally reported rate constants and those extracted from the ThT/ThS fluorescence data. Protein aggregation is found to be practically independent of the number of contacts and the critical number of misfolded contacts. The age of appearance of aggregation-related diseases is obtained from the survival probability and the MFPT results, which matches with those reported in the literature. The calculated survival probability is in good agreement with the only available clinical data for Parkinson's disease.

probing_protein_shelf_lives_from_inverse_mean_first_passage_times

<p>Most proteins have been evolved to spontaneously fold to their native states, which determine their functional specificity and diversity. 1,2 Any phenotypic or genotypic variations may induce abnormal amino acid modifications and cause protein misfolding. [3][4][5] Misfolded proteins disrupt normal cellular functions and may be potentially toxic. 6 The spontaneous self-assembly of misfolded proteins often lead to the formation of aggregates, which are associated with a wide variety of debilitating disorders like Alzheimer's, Parkinson's, Creutzfeldt-Jakob's, Huntington's, Amyotrophic lateral sclerosis (ALS) and dementia. 2,[7][8][9] The Protein Quality Control (PQC) system present in the cell manages these misfolded proteins and helps them to either refold back to their respective native conformations via chaperones or degrades them to amino acids and eventually replaces them with their newly synthesized replicas. 10,11 This phenomenon known as protein turnover, is a highly specific and precisely regulated process that involves a constant renewal of the functional proteins by allowing the damaged or non-functional ones to be eliminated from the cell. 10 The underlying link among protein folding, misfolding, aggregation and degradation equilibria implies that a change in any one of these components would directly/indirectly affect the others. 12 External factors like aging, genetic mutation, oxidative stress, pH and temperature results in the failure of the protein turnover process and leads to the formation of aggregates/fibrils. 13,14 These aggregates are typically highly organized hydrogen-bonded structures that are more stable compared to the native protein, 6,7 kinetically-trapped in the lowest free energy state. Thus once formed such aggregates are extremely stable for long time periods and acts as a nucleus for further propagation. This work analyzes the folding outcome of a protein through protein turnover followed by misfolding, aggregation and degradation. The rate of formation of proteins from the amino acids follows a zero-order kinetics, 15,16 which is an input for the subsequent P ⇀ ↽ M equilibrium, that is governed by the time evolution of the misfolded contacts. The Chemical Master Equation (CME) for this equilibria is derived from the splitting probabilities of the misfolded contacts at a particular time instant. The misfolded proteins self-associate to form aggregates as described by a first order differential equation. The Mean First Passage Time (MFPT) required for the protein to form aggregates from the misfolded proteins is calculated from both CME and the first order differential equation under appropriate boundary conditions. The rate constants of aggregation of different disease causing proteins are evaluated from the inverse MFPT, which show an excellent match with the experimentally reported rate constants [17][18][19][20][21][22] and those extracted from the ThT/ThS fluorescence data. The age of appearance of these diseases are directly evaluated from the MFPT and the survival probability results, which agrees well with those reported in literature. The survival probability result is in good agreement with the only available clinical data for Parkinson's disease. begins from a pool of amino acids via protein turnover. 24 The synthesized native proteins may misfold and the misfolded proteins subsequently self assemble to form aggregates. 8,10,12 Both misfolded proteins and aggregates may degrade to by-products, which is eliminated from the system. 10 The misfolded state represents the ensemble of misfolded proteins, where each one is characterized by a critical number of misfolded contacts, q M C . For a given protein, all chains in the native conformational ensemble are assumed to be of equal lengths with equal number of contacts that are in equilibrium with the misfolded state.</p><p>The number of proteins, n, present at time t may be calculated assuming zero order kinetics 15,16 with the rate constant k n . The solution of this rate equation is n = k n t. The total number of contacts present at time t is given by: q(t) = n P n = n P k n t, where n P is the number of contacts present in each protein.</p><p>The number of misfolded contacts present in the native protein at time t + ∆t is q M (t).</p><p>The protein acquires a misfolded conformation M at time t M when the number of misfolded contacts reaches a critical value, q M C . The rate of increase/decrease of a misfolded contact at an infinitesimal time interval, ∆t, may be given by rate(q M (t)→q</p><p>where, k pm denotes the rate constant for the conversion of a native contact into a misfolded one, while k mp is the rate constant for the backward reaction. The transition probabilities for the gain and loss of a misfolded contact at time ∆t are represented as W (q M (t) + 1, q M (t))∆t and W (q M (t) − 1, q M (t))∆t respectively. Thus the probability to remain in a given misfolded state with q M (t) misfolded contacts at time ∆t is 25 Thus the probability, P (M, t M | q M , t) to acquire the misfolded conformation, M , at time t M may be expressed as a difference equation. 25,26 P (M,</p><p>The Chemical Master Equation (CME) 25,[27][28][29] for the native conformational ensemble may be obtained from Eqn (1) in the limit ∆t→0 as</p><p>The probability P (M, t M | q M , t) follows the reflecting boundary condition for the number of misfolded contacts, q M (t) < q M C . The MFPT may be obtained from Eqn (2) as (refer to the Supporting Information (SI))</p><p>The equation 25,29 holds true for all values of q M (t) ranging from 1 to q M C . Since τ (0) = 0 and τ (q M C + 1) is not required, this equation may be solved to obtain the MFPT, τ M , of the misfolded proteins in terms of the Gauss hypergeometric function 2 F 1 (α, β; γ; z) (refer to SI).</p><p>where r = k mp /k pm < 1. 30 The generalized equation of MFPT is simplified using the integral identity as 26</p><p>Degradation of the misfolded proteins follow first order kinetics. 15,16,31 The rate equation for degradation may be defined in terms of the evolution of q M (t) with time as:</p><p>where k d is the rate constant for the degradation of misfolded proteins calculated from the half-life 31 of a protein as, k d = 0.693/t 1/2 . This first order differential equation may be solved as</p><p>Protein aggregation may be viewed as the self-assembly of misfolded proteins. 17,32 The rate equation for aggregation followed by degradation of the aggregates is given by (refer to</p><p>where, n As and n M are the number of aggregates and the number of misfolded proteins present in an aggregate respectively. The ratio R is defined as R = n As /n M . k agg denotes the pseudo first order aggregation rate constant, whereas k da is the degradation rate constant of the aggregates. Eqn (7) may be solved by using absorbing boundary condition defined by</p><p>n As ; t = τ agg ; absorbing boundary condition</p><p>The solution of Eqn ( 7) is given for n As as</p><p>The time required for the aggregation of misfolded proteins, τ agg , may be obtained by rearranging Eqn (8) as</p><p>where the ratio of rate constants, K is defined as K = k da /k agg . Thus the MFPT of aggregation may be expressed as [17][18][19][20][21][22]26,33 and half-lives [34][35][36][37][38][39][40] for a specified value of the rate constant k da = 10 −3 k agg . Inset figure depicts the MFPT at initial times.</p><p>with time followed by the formation of aggregates. The MFPT of each protein reaches a plateau with time marking the age of appearance of the aggregation-related diseases. The MFPT of the selected proteins are calculated from Eqn (10) using the respective values of the reported rate constants [17][18][19][20][21][22]26,33 and half-lives [34][35][36][37][38][39][40] as listed in Table 1.</p><p>The MFPT of the aggregate remains constant for fixed values of R for a given n As . This affirms that protein aggregation is independent of the number of aggregates, n As for fixed values of k n , k pm , k mp , k agg , t 1/2 and R. To the best of our knowledge there are no reported literature values of the rate constants or half-lives for the degradation of aggregates. The rate of degradation of these aggregates is much slower compared to the rate of their formation, as the aggregated proteins are very stable. 6,7 For the given range of K = 10 −1 − 10 −5 , the values of R are tuned to match the MFPT with the age of appearance of aggregation-related diseases as given in S2 of SI. The rate constant of aggregation is proportional to the inverse MFPT, which may be calculated as</p><p>where C is the proportionality constant equal to R. Thus, Eqn ( 11) is recast as</p><p>Table 1 displays the values of MFPT of the selected proteins by varying K and R. Table 1 also shows a comparison between the calculated and experimental values of the rate constants of aggregation of these proteins. The calculated values of k agg show an excellent match with the rate constants extracted from the ThT/ThS fluorescence data (refer to Figures S1(a), (b) and (c) of SI) and those obtained from experiments. [17][18][19][20][21][22] Protein aggregation is found to be practically independent of the number of contacts (n P )</p><p>and the critical number of misfolded contacts (q M C ) (refer to SI). The MFPT is independent of the rate constant, k mp for fixed values of k n , k pm and k agg . 26 The survival probability is calculated by assuming that the distribution of proteins in the conformational ensemble is Gaussian 26 at time t. The average number of proteins at an infinitesimal time interval ∆t may be estimated as</p><p>The survival probability of the proteins is given by</p><p>where σ 2 is the variance of the Gaussian distribution.</p><p>Table 1: MFPT of the selected proteins (calculated from Eqn (10)) and a comparison of the experimentally obtained rate constants of aggregation, k agg with those calculated from our theory for k mp 26 = 10 −12 s −1 .</p><p>Proteins Diseases Figure 3(a) shows the survival probability of the selected aggregation-prone proteins for reported values of the rate constants [17][18][19][20][21][22]26,33 and half-lives. [34][35][36][37][38][39][40] All proteins are initially present in their respective native states. Thus, the survival probability of these proteins shows a maximum that remains constant upto a threshold time, after which it exhibits a slow decrease with time due to the initiation of misfolding. The survival probability decreases monotonically with time and reaches zero after a long time, marking the formation of aggregates. The zero value of the survival probability corresponds to the age of appearance of the aggregation-related diseases. Figure 3(b) displays a comparison of the survival probability obtained from our theory with the only available clinical data of Killinger et al. 23 for Parkinson's disease. The calculated survival probability is in good agreement with this clinical data. 23 Table 2 provides a comparison of the age of appearance of the aggregationrelated diseases from our results of MFPT and survival probability with the respective values reported in the literature.</p><p>In this work, protein aggregation is investigated theoretically via protein turnover, misfolding, aggregation and degradation. The rate of formation of proteins in turnover follows a zero-order kinetics, which is used in the P ⇀ ↽ M equilibrium, that is governed by time evolution of the misfolded contacts. The Chemical Master Equation for this equilibria is derived from the splitting probabilities of the misfolded contacts at a particular instant of Corresponding Author:</p><p>*E-mail: pbiswas@chemistry.du.ac.in</p>

ChemRxiv

A fluorescence-based assay for N-myristoyltransferase activity

N-myristoylation is the irreversible attachment of a C14-fatty acid, myristic acid, to the N-terminal glycine of a protein via formation of an amide bond. This modification is catalyzed by myristoyl-CoA : protein N-myristoyltransferase (NMT), an enzyme ubiquitous in eukaryotes that is up-regulated in several cancers. Here we report a sensitive fluorescence-based assay to study the enzymatic activity of human NMT1 and NMT2, based on detection of coenzyme A by 7-diethylamino-3-(4-maleimido-phenyl)-4-methylcoumarin. We also describe expression and characterization of NMT1 and NMT2, and assay validation with small molecule inhibitors. This assay should be broadly applicable to NMTs from a range of organisms.

a_fluorescence-based_assay_for_n-myristoyltransferase_activity

<p>Myristoyl-coenzyme A : protein N-myristoyltransferase (N-myristoyltransferase, NMT) is a ubiquitous enzyme in eukaryotes that catalyzes co- and post-translational transfer of a C14 saturated fatty acid (myristic acid) from myristoyl-coenzyme A (myristoyl-CoA) to the N-terminal glycine residue of target proteins [1] (Fig. 1A). NMT was first identified in yeast [2], and subsequently characterized in fungi, parasitic protozoa, insects, plants, humans and other mammals. N-myristoylation of proteins can promote reversible protein-protein interactions, enhance interactions of the protein with the membrane and change protein stability [1]. The role of myristoylation is still not entirely understood, and not all myristoylated proteins have been experimentally determined [3; 4]. However, in humans, protein myristoylation is connected with several diseases including cancer [5], genetic disorders [6] and infection [7]. In Homo sapiens, NMT is encoded by two distinct genes, Nmt1 and Nmt2, and RNA interference experiments suggest that Nmt1 knockdown inhibits tumor growth, making NMT1 a potential target for the development of novel anti-cancer therapies [8]. The host myristoylation is essential for the formation of HIV viral capsids, suggesting potential for mammalian NMT inhibitors as anti-viral agents [9]. Furthermore, NMT is established as a promising anti-fungal [10] and anti-parasitic drug target, for example in African sleeping sickness [11; 12], malaria [13] and leishmaniasis [14; 15]. An effective in vitro enzyme assay is required for drug discovery against NMT; the few assays reported in detail to date are based on detection of a radioisotopic label in a myristoylated peptide or protein [13; 16]. Such assays allow sensitive measurements, but are discontinuous, expensive, and require handling and disposal of radioactive materials.</p><p>Herein we report the development of a robust fluorogenic assay for NMT activity suitable for continuous reaction monitoring and end-point assays. This assay monitors coenzyme A (CoA) production in real time using a pro-fluorescent probe, 7-diethylamino-3-(4-maleimido-phenyl)-4-methylcoumarin (CPM), a commercially available coumarin derivative containing a thiol-reactive maleimide [17] (Fig. 1B). The maleimide quenches coumarin fluorescence, but the in situ reaction with CoA thiol generated during myristoylation results in release of fluorescence.</p><p>The proteins used for this study are the catalytic domains of human NMT isoforms 1 and 2. These proteins share 83% sequence identity over 388 amino acids and lack the long N-terminal extensions involved in NMT subcellular targeting [18] (Supplementary data, Fig S1). Details of gene constructs, protein production and purification may be found in Supplementary Data. The assay was developed in 96-well black polypropylene microplates (Greiner Bio-One, UK) and reagent solutions were prepared in a buffer containing 20 mM potassium phosphate (pH 7.9-8.0) with 0.5 mM EDTA, 0.1% (v/v) Triton® X-100 and a final concentration of 2.7% (v/v) DMSO. Thiol-containing reagents should be avoided as they react with CPM and interfere with the assay. Fluorescence readings were obtained on a SpectraMax M2e microplate reader (Molecular Devices, Canada) or an EnVision Xcite reader (Perkin Elmer, UK). The peptide H-Gly-Ser-Asn-Lys-Ser-Lys-Pro-Lys-NH2 (Hs pp60src(2-9)), derived from the N-terminal sequence of myristoylated Homo sapiens proto-oncogene tyrosine kinase pp60src [19], was used as substrate for both human NMTs.</p><p>10 μL of a 10% DMSO/water (v/v) solution, 25 μL of myristoyl-CoA solution, 50 μL of NMT (final concentration: 6.3 nM) and 10 μL of CPM solution (final concentration: 8 μM) were combined in an assay well. The enzymatic reaction was started by adding 15 μL of peptide substrate solution and fluorescence intensity was monitored over 30 minutes at 1 minute intervals (excitation 380 nm, emission at 470 nm) at 25 °C. The initial velocity was calculated over the first 4 minutes of the experiment after subtraction of the background fluorescence (measured in the absence of enzyme). The Michaelis-Menten (Km) constant of Hs pp60src(2-9) was determined using a saturating concentration of the co-substrate, myristoyl-CoA (30 μM). Under these conditions, the peptide Hs pp60src(2-9) displayed a Km of 2.76 ± 0.21 μM and 2.77 ± 0.14 μM for NMT1 and NMT2 respectively. Subsequently, the Km of myristoyl-Co A was determined in the presence of a saturating concentration (30 μM) of Hs pp60src(2-9) substrate. This experiment led to Km values of 8.24 ± 0.62 μM and 7.24 ± 0.79 μM for NMT1 and NMT2 respectively, which are in good agreement with previously reported data (7.6 μM for NMT1 using pp60v-src(2-17) as substrate) [20].</p><p>While continuous assays are generally preferred for analytical purposes, they are time-consuming and unsuitable for the screening of large compound libraries; we therefore investigated the feasibility of an endpoint assay. A suitable enzyme concentration (6.3 nM) was selected to give a linear reaction rate over 30 minutes at 25 °C. If necessary, this concentration can be reduced down to 2.1 nM which in these conditions gives a reasonable signal to background ratio of ~ 2. Then, we examined the possibility of quenching the reaction by acidifying the reaction mixture since the rate of the reaction between the coenzyme A and CPM is strongly pH-dependent [21] (Supplementary data, Fig S2). Screening a range of conditions, we found that addition of 60 μL of 0.1 M sodium acetate buffer pH 4.75 ('quenching solution') 30 minutes into the assay immediately decreased the pH of the reaction solution to pH 4.9-5.1. At this pH, quenching the fluorogenic reaction and giving a signal that remains stable over 8 hours (Supplementary data, Fig. S3).</p><p>To validate the assay, two known NMT inhibitors were evaluated against NMT1 and NMT2 (Fig. 2): 1, a pseudo-peptidic NMT inhibitor [22] and 2, a small molecule that has been recently described as an inhibitor with low-nM affinity for Trypanosoma brucei NMT and Homo sapiens NMT [11]. Inhibition assays were carried out using the endpoint method, with final concentrations of 4 μM Hs pp60src(2-9) and 4 μM myristoyl-CoA. Briefly, the inhibitor in 10% DMSO/water (10 μL), myristoyl-CoA (25 μL) and NMT (50 μL) solutions were combined in a 96-well plate as described above, and the enzymatic reaction was started by adding 25 μL of a solution containing 17.6 μM Hs pp60src(2-9) and 35.2 μM CPM in assay buffer. The reaction was stopped after 30 minutes at 25 °C by adding 60 μL quenching solution. Positive controls excluded inhibitor, negative controls excluded both NMT and inhibitor. Under these assay conditions, the average Z′ value was between 0.7 - 0.9. The apparent Km of the peptide was determined to be 2.66 ± 0.20 μM for NMT1 and 3.25 ± 0.22 μM for NMT2.</p><p>As expected, 1 behaved as an inhibitor of both human NMTs with IC50 values of 0.35 μM and 0.51 μM against NMT1 and NMT2 respectively, conforming to previously reported data (IC50 = 0.50 ± 0.37 μM against NMT1) from a radioactive HPLC-based assay [22]. Similarly, 2 was tested against both human NMTs and led to IC50 values of 13.7 nM (NMT1) and 14.4 nM (NMT2), similar to the result previously obtained against NMT1 with a scintillation proximity assay (4 nM) [11].</p><p>In summary, this fluorogenic assay constitutes an attractive alternative to radioactive assays in the search for NMT inhibitors. Moreover, the possibility of using it in either continuous or endpoint mode makes it suitable both for kinetic/mechanistic studies and for high-throughput screening. Whilst strongly nucleophilic reagents or inhibitors should be avoided as they lead to increased background fluorescence, thiols in the enzyme are tolerated. Although this assay was developed on human NMT1 and NMT2 it depends only on the generation of CoA-SH, and could be readily adapted to the study of parasitic or fungal NMT activity.</p>

PubMed Author Manuscript

From machine learning to transfer learning in laser-induced breakdown spectroscopy analysis of rocks for Mars exploration

surface asperity on the hydrogen emission line has been investigated 11 . Our recently published work 12 observed and analyzed the performance of a machine learning-based model 13 , trained with a set of pressed rock powder pellets for total alkali-silica (TAS) classification 14 of rocks in their natural state. A significant degradation of the model prediction performance compared to the prediction for pellet samples has been observed. Such degradation prevents the models trained with laboratory standards from reliable predictions with LIBS spectra acquired on raw rock samples, a situation that can lead to misinterpretations for in situ LIBS analysis of rocks on Mars, since we are not yet able to bring materials back from Mars.In order to search a solution for the issue raised, this work introduced transfer learning in LIBS spectral data treatment to more specifically overcome the physical matrix effect. Transfer learning is considered in machine learning when the knowledge gained while solving one problem is required to be applied to a different but related problem 15 . Its necessity comes from the fact that a major assumption in machine learning data processing is that the training and the model-targeted samples to be analyzed should share the same feature space and have the same distribution 16 . It is unfortunately not the case for the application scenario that we consider. Moreover, transfer learning has recently emerged as a new learning framework to address the problem of insufficient training data in an application (target domain) with the help of the knowledge learnt from a related application having the capability to get sufficient training data (source domain) 17 . Such strategy fits well the requirement of LIBS analysis of rocks on Mars, where sufficient laboratory standards can be prepared as the source domain, whereas real Mars rock samples are not yet available as the target domain. Simulation of their chemical as well as physical properties by terrestrial materials, whether natural or artificial, appears therefore a suitable solution. According to the specific contents of the "knowledge" to be transferred, we can distinguish feature-representation-transfer, where parts of relevant features respectively from the both source and target domains are merged and selected for their low sensitivity to the difference between the two domains, to form a common set of features contributing to the training of a transfer learning model 18,19 . Instance-transfer is another specificity of transfer learning where data of the samples from the both source and target domains participate in the model training, with a conditional testing on the relevance of each sample from the source domain for its effectiveness in improving the performance of the model in a cross-validation process with the data from the target domain 18,19 . A weight is then applied to each source domain sample participating the training, according to its contribution in improving the performance of the model for predicting with target domain data. We note that algorithms belonging to transfer learning, low rank alignment of manifolds or feature-based transfer learning for example, have been used respectively for calibration transfers between different LIBS instruments 20 or metallic samples with different temperatures 21 .More specifically, in our experiment, on the basis of the LIBS spectra acquired from a set of laboratory standard samples in the form of pressed powder pellet, machine learning-based multivariate models were trained, validated and then used to predict the concentrations of major oxides necessary for TAS classification of rocks, SiO 2 , Na 2 O and K 2 O, with LIBS spectra acquired from natural rocks. The purpose was first to observe the physical matrix effect due to the difference in surface states between pressed powder pellets and rocks. Since for a LIBS measurement, such difference can be in particular due to the surface hardness, heterogeneity or roughness of a rock, the rock was thus measured in its raw state and with a polished surface, in such way that the different contributions to the physical matrix effect can be investigated separately. Transfer learning-based models were trained with the implementation of feature-representation-transfer and instance-transfer to effectively correct the physical matrix effect in the concentration prediction for rocks in their raw state or prepared with a polished surface, allowing their satisfactory TAS classifications. The correct TAS classification rate increases from 25% for polished rocks and 33.3% for raw rocks with a machine learning model, to 83.3% with a transfer learning model for the both types of rock samples.

from_machine_learning_to_transfer_learning_in_laser-induced_breakdown_spectroscopy_analysis_of_rocks

<!>OPEN<!>Samples, experimental setup and measurement protocol<!>Experimental setup.<!>Data treatment method<!>Data pretreatment.<!>Transfer learning-based calibration model training. A transfer learning model training algorithm<!>Results and discussion<!>Conclusions

<p>Although the matrix effects correspond to a general issue in LIBS, they become accentuated in the case of rock analysis for Mars exploration, because of the large variation of rock compositions leading to the chemical matrix effect, and the difference in surface physical properties between laboratory standards (in pressed powder pellet, glass or ceramic) used to establish calibration models and natural rocks encountered on Mars, leading to the physical matrix effect. The chemical matrix effect has been tackled in the ChemCam project with large sets of laboratory standards offering a good representation of various compositions of Mars rocks. The present work more specifically deals with the physical matrix effect which is still lacking a satisfactory solution. The approach consists in introducing transfer learning in LIBS data treatment. For the specific application of total alkali-silica (TAS) classification of rocks (either with a polished surface or in the raw state), the results show a significant improvement in the ability to predict of pellet-based models when trained together with suitable information from rocks in a procedure of transfer learning. The correct TAS classification rate increases from 25% for polished rocks and 33.3% for raw rocks with a machine learning model, to 83.3% with a transfer learning model for both types of rock samples.</p><p>It is generally considered that the matrix effects, both the chemical 1 and the physical 2 matrix effects, represent a critical issue in analysis with laser-induced breakdown spectroscopy (LIBS) for either qualitative classification or quantitative determination 3 . Suitable solutions with respect to such consideration become paramount for applications as important as LIBS analysis of rocks in Mars explorations 4 . The scientific goals, searching for present and past water activities and the traces of the life as well as studying the habitability of Mars [5][6][7] , rely, at least partially, on the reliability and the accuracy of the analytical data that one can extract from the LIBS spectra recorded by LIBS instruments embarked on Mars rovers 8 . The diversity of chemical compositions of Mars rocks has been studied in previous missions, the absence of real sample from Mars, except meteorites, requires a large number of laboratory rock standard samples in order to cover the expected chemical variety of Mars rocks. It was the purpose of the sets of laboratory standard rock samples prepared and used by the ChemCam team for training and validation of the Mars LIBS spectral data processing models. The number of the involved samples was first 69 9 , and was further increased to 408 in order to offer a more complete representation of the chemical and mineral compositions of Mars rocks 10 . It is important to point out that all the above mentioned laboratory rock standards were prepared in the forms of pressed powder pellet, glass, or ceramic to minimize the heterogeneity and the surface roughness of the samples in the scale of LIBS observations of typically several hundred μm. Such sample preparation leads to obvious differences in surface physical properties between laboratory standards and real rocks analyzed by LIBS instruments on Mars. From these differences, changes in the spectra can rise (physical matrix effect) which can impact the analytical results. With this concern, the effects of sample</p><!><p>School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China. * email: jin.yu@sjtu.edu.cn</p><!><p>Samples. In this work, 20 natural terrestrial rocks were used as samples for LIBS analysis. The rocks were first washed using alcohol and distilled water before any further treatment. All the rocks were prepared in 3 different forms. Raw rocks: LIBS measurements took place on the natural surface of each rock; Polished rocks: LIBS measurements took place on a polished flat surface of each rock (prepared using a 300-mesh sandpaper); Pellets: a part of each rock was crushed and ground into a powder by a laboratory mill and then sieved by a 300-mesh screen (grain size < 50 μm). A binder (microcrystalline cellulose powder) with a similar particle size was mixed into the rock powder at a weight ratio of 20%. One gram of the obtained mixture powder was pressed under a pressure of 850 MPa for 30 min to form a pellet of 15 mm diameter and 2 mm thickness. The composition, with especially the concentrations of major oxides, SiO 2 , Na 2 O, K 2 O, of each rock was determined with X-ray fluorescence spectroscopy (XRF) performed on the pellets with large enough analyzed area to get their bulk composition. The detailed compositions and the geological names of the rocks are presented in the section "Methods" (Table 4), which allows presenting the rocks in a TAS diagram as shown in Fig. 1. The short notations of the 15 fields (surrounded by circles) are according to Reference 22 In order to better simulate an application where the samples to be characterized are not available as in the case of Mars exploration, we first isolated 2 samples (S2 and S5) for model validation, they were excluded from the model training processes. Although these 2 samples were randomly selected as typical isolated validation samples, later, for the model performance evaluation, we will involve other pairs of validation samples excluded from the model training process in order to obtain average model performances independent on the choice of validation samples. The corresponding pellets of these 2 samples were used to validate the machine learning model trained using the rest 18 pellets, while the rock forms of these 2 samples joined the rock validation samples in the validation of the transfer learning models, without counterpart pellet in the training sample set. Among the 18 remaining samples, 8 rocks were selected as training samples (S3, S7, S8, S11, S13, S14, S18 and S19). They joined the 18 pellet samples in the training process of the transfer learning models. The rest 10 rocks, together with the above 2 isolated rocks, ensured the validation of the transfer models. In Fig. 1, the 2 isolated samples are shown in green stars, the 10 additional validation samples in blue dots, and the 8 training rocks samples in red crosses.</p><!><p>A detailed description of the used experimental setup can be found elsewhere 12 .</p><p>Briefly as shown in Fig. 2, a Q-switched Nd:YAG laser operated at a wavelength of 1064 nm with a pulse duration of 7 ns and a repetition of rate of 10 Hz, was used to ablate the samples with a pulse energy of 8 mJ. A lens of 50 mm focal length focused laser pulses about 0.86 mm below the surface of a sample. The diameter of the www.nature.com/scientificreports/ laser spot on the sample surface was estimated to 150 μm, leading to a laser fluence on the sample surface of about 45 J/cm 2 , or an irradiance of about 6.5 GW/cm 2 . The emission from a generated plasma was collected by a combination of two quartz lenses with a same focal length of 75 mm into an optical fiber of 50 μm core diameter. The output of the fiber was connected to the entrance of an echelle spectrometer equipped with an ICCD camera (Mechelle 5000 and iStar, Andor Technology) which provided a wide spectral range from 230 to 900 nm with spectral resolution power of 5000. The ICCD camera was triggered by laser pulses and set with a delay and a gate width of respectively 500 ns and 2000 ns. A lateral CCD camera (not shown in the figure) allowed capturing time-integrated plasma images as shown in the inset of Fig. 2. Samples were mounted on a 3D translation stage allowing recording replicate spectra on a sample surface with an ablation crater matrix, while keeping a constant distance between the focusing lens and the sample surface (approximately for a raw rock).</p><p>We can see in Table 1 that the mean intensities exhibit different values for different sample forms even though the same sample were concerned, which correspond to biases introduced by the physical matrix effect. In addition, for a given emission line, the RSD value generally increases from the pellet to the corresponding polished and raw rocks. This observation indicates that starting from an initial spectral intensity fluctuation of a pellet sample, the fluctuation increases for the corresponding polished and raw rocks due to heterogeneity and then surface asperity. The most important information from the table is that the RSDs calculated over all the 3 sample forms are significantly larger than the values calculated for a given sample form. This means that the physical matrix effect due to change of sample form represents the dominant variability of spectral intensity, much more important than usual fluctuations observed when measuring a heterogeneous material such as a rock, confirming the above observation of the biases on the mean intensities.</p><!><p>The general data treatment flowchart used in this work is shown in Fig. 3. It was respectively applied to pairs of sample types, pellets/polished rocks and pellets/raw rocks. Several steps can be distinguished: data pretreatment, feature selection, machine learning (ML) and transfer learning (TL) model trainings, as well as model validation. Such flowchart allowed a comparative study between the performances of a machine learning (ML) model and those of a transfer learning (TL) model. As mentioned above, for the machine learning model, the 18 training pellets were used as the training samples set. The resulted model was validated by the 2 isolated pellets as well as the 12 validation rocks including the 2 isolated rocks without counterpart pellet in the training sample set. For the transfer learning models, the training sample set was composed by the 18 training pellets and the 8 training rocks. The resulted models were validated by the 12 validation rocks including the 2 isolated rocks without counterpart pellet in the training sample set.</p><!><p>The pretreatment consisted in the following operations. (i) Average in order to reduce experimental fluctuations and the influence of sample heterogeneity: For each sample, the 50 raw replicate spectra on each sample were averaged in a procedure where an averaged spectrum was calculated with a first group of randomly selected 30 spectra. The remaining 20 spectra then replaced one by one, a spectrum in the first group, each time the new group of 30 spectra was averaged to generate 20 other average spectra. 21 average spectra were generated for each sample. (ii) Baseline correction: an average spectrum was decomposed into a set of cubic splines of undecimated wavelet scales, the local minima were found, then the spline function was interpolated through the different minima to construct the spectral baseline which was removed 23 . (iii) Normalization: baseline-corrected average spectra were normalized with their respective total intensity (the area under the spectrum). (iv) Standardization: standard normal variate (SNV) transformation was respectively applied to the normalized and baseline-corrected average spectra of the training set of the pellet samples (18 × 21 = 378 spectra) and the training set of the rock samples (8 × 21 = 168 spectra). Within a given sample set, for each channel in a spectrum (22,161 channels in total), the variation range of the intensity value over all the samples was transformed into a range with a mean value equal to 0 and a standard derivation (SD) equal to 1. The parameters determined in the standardization of the training sets of the pellet and rock samples (the means and the SDs) were respectively applied to the 2 isolated pellet samples (2 × 21 = 42 spectra) and the validation rock samples (12 × 21 = 252 spectra) by assuming a same statistical distribution of the data for all the pellets or rock samples. The ensemble of the above operations generated pretreated spectra.</p><p>Table 1. Mean value, standard derivation (SD) and relative standard deviation (RSD) of the intensities of the Si I 251.6 nm, Na I 589.0 nm, and K I 766.5 nm lines, recorded from sample S1 in the 3 the forms of pressed pellet, polished and raw rocks, as well as calculated over all the replicate spectra of the 3 sample forms. www.nature.com/scientificreports/ Spectral feature selection. SelectKBest (SKB) algorithm [24][25][26] was respectively applied to the pretreated spectra of the training pellet and training rock sample sets, and successively for the 3 concerned oxides. Within a sample set, for each spectral channel, covariance was calculated between the channel intensity and the concentration of the concerned compound in the corresponding sample, over all the spectra of the sample set. A score was then calculated as a function of the covariance according to the definition given in Reference 13 . A ranking index, ρ i,j , was thus associated to each spectral channel according to its obtained score, with 2 indexes (i, j) and a value varying from 1 to 22,161, which ranks the channels from the lowest score to the highest one. Such procedure was applied to the 2 sample sets ( i = 1 : training pellets, i = 2 : training rocks) and the 3 concerned oxides ( j = 1 : SiO 2 , j = 2 : Na 2 O, j = 3 : K 2 O). A feature selection procedure identified 100 highest ranked spectral channels respectively for each of the 3 oxides in each of the 2 training sample sets. Pearson's correlation coefficient 27 related to the above mentioned covariance was calculated for the 6 groups of 100 selected features.</p><p>The results showed that all the selected features had a Pearson's coefficient larger than 0.75.</p><p>As we can see in the Fig. 3, the 3 groups of 100 features selected for the 3 oxides for the training pellet sample set were directly used to respectively train the calibration models for the 3 oxides base on a back-propagation neural network (BPNN). The training algorithm that involved stochastic gradient descent (SGD) and mini-batch stochastic gradient descent (MSGD) optimization iterations, as well as cross-validations with randomly generated statistically equivalent data configurations, has been presented in detail in Reference 13 .</p><p>For transfer learning model training, and according to the principle of feature-representation-transfer discussed above, an ensemble of common selected features was identified between the training pellet and the training rock sample sets, by calculating a total ranking index ρ j = ρ 1,j + ρ 2,j . One hundred highest ranked features according to the value of ρ j from the highest one to the lowest one, were retained as the common selected features, respectively for the 3 oxides. These groups of features were then fed into the transfer learning model training algorithm. The results of feature selection for Na 2 O for the pair of sample types pellet/raw rock, are shown in Fig. 4. Similar behaviors can be observed in the feature selections for the other 2 oxides and with the 2 pairs for the sample types pellet/raw rock and pellet/polished rock, the corresponding results are shown in the section "Methods" in Figs. 10 and 11.</p><p>In Figs. 4a, we can see that for the training pellets, the spectral channels with high SKB scores are clearly concentrated around the several Na emission lines: Na I 330.24 nm and 330.30 nm lines, Na I 588.99 nm and 589.59 nm lines (with 2 groups of ghost lines around 572.1 nm and 606.9 nm), Na I 818.33 nm and 819.48 nm lines. For the training raw rocks in Fig. 4b, the selected features are distributed also among other channels with a significant decrease of the scores for all the important features. This means that the physical matrix effect perturbs the inherent correlation between the emission line intensities of an element and its concentration in the material, and reduces therefore the importance of the line intensities in the concentration determination. At the same time, other spectral channels, such as those around 275 nm and between 410 and 460 nm, get relatively higher scores. This means that they become important in the determination of elemental concentration when using a model based on the training set of the rock samples. These features, representative of the rock samples, www.nature.com/scientificreports/ are thus included in the common selected features for transfer learning model training. Figure 4c shows in red dots, the total ranking index of the 100 common selected features for Na 2 O. These features are indicated in a typical spectrum in Fig. 4d in red dots. We can see that, beside the features related to the Na emission lines, some features important for the rock samples are included. A more detailed peak identification using the NIST database 28 , shows the contributions from Fe II 268.475 nm and 275.57 nm lines, Si II 385.366 nm and 385.602 nm lines, and the probable contributions from K I 404.414 nm and 404.721 nm lines, Ca I 409.85 nm lines, and Si II 412.807 nm and 413.089 nm lines. A selected feature around 461 nm cannot have easy interpretation.</p><p>In the insets of Fig. 4d, 2 parts of the spectrum are enlarged. The inset around 589 nm shows the sodium D lines together with the selected features in red dots. We can see that the selected features are located in the side parts of the line profiles, whereas the central parts of the lines are not retained by the feature selection algorithm. This might be due to self-absorption of the strong resonant Na D lines, which affects much more the central part of the spectral lines. It would also be the reason for the higher scores observed for the weaker Na emission lines around 330 nm. This observation would show the ability of the feature selection process to reduce the influence of self-absorption by selecting the most suitable features inside of a line profile. The second inset in Fig. 4d shows an enlarged part of the spectrum around 820 nm, where we can see the selected features related to the Na I 819.5 nm line in red dots. Due to the spectral interference with the N I 820.0 nm line, only the short wavelength part of the spectral profile around 820 nm is included in the selected features, showing the effectiveness of the feature selection to avoid the influence of spectral interference.</p><!><p>was developed in this work on the basis of that used for machine learning model training presented in detail in our previous publication 13 and used for various application scenarios 12,[29][30][31][32][33] Data formatting. According to the above discussed principles of feature-representation-transfer and instance transfer in transfer learning, spectra from the 18 training pellet samples (the source domain) and those from the 8 training rock samples (the target domain), with their 100 common selected features, participated in the training process. These spectra were organized in a given data configuration where the replicate spectra for each sample were arranged in an arbitrarily given order. The effectiveness of each training pellet was tested within an iteration loop where the RETs with and without the spectra from the pellet were compared in order to decide the exclusion or the definitive inclusion of the pellet in the final transfer learning model training sample set. It was why the ensemble of pretreated replicate spectra associated to one of the 18 training pellets was indexed with k that went from 1 to 18 (Fig. 5a). The 8 training rock samples contributed to the transfer learning model training and in particular, were used in a cross-validation process during the optimization of the neural network. It was why the corresponding spectra were first organized in different data configurations where each configuration j corresponded to a certain arrangement of pretreated replicate spectra for each training rock (Fig. 5a). The data configurations were all statistically equivalent since the order of a replicate spectrum of a sample was a dummy www.nature.com/scientificreports/ index. The number of different data configurations were limited to 3 in this work because more configurations did not bring further improvement of the model as tested in the experiment. For a given configuration j, the pretreated replicate spectra of each sample were further organized into 5 groups containing respectively 4, 4, 4, 4 and 5 spectra, respectively. A new index i was introduced to designate ensemble of the groups of pretreated replicate spectra of all the training rocks as shown in Fig. 5a. In the model training process, the index i went from 1 to 5 within an iteration loop of cross-validation, indicating each time the validation ensemble of the groups of pretreated replicate spectra.</p><p>Model training by optimization. A 3-layer back-propagation neural network (BPNN) similar to that used in Reference 13 was employed in this work for the transfer learning model. The network was composed of an input layer of 100 neurons corresponding to the 100 common selected features of each input spectrum; a hidden layer 5 neurons and an output layer with a single neuron corresponding to the targeted compound concentration. The function of the network was therefore to map an input spectrum (a vector of 100 dimensions) to a scalar which can be considered as the module of a vector in a hyperspace of 100 dimensions. The accuracy of the mapping was improved during the training process through different iteration loops under the supervision of the targeted concentration and using the model performance indication parameters specified above.</p><p>As shown in Fig. 5b, 3 hierarchized iteration loops, i, j, k , among them i, j are doubled loops for a given k ( ±k ) surrounding the BPNN optimization loop performing the supervised optimization of the model.</p><p>-A doubled inner loop for i = 1 to 5: for the double cases of a given sample k among the pellet samples being excluded ( −k ) or included ( +k ) in the training data set, and a given data configuration j of the rock spectra, the network was optimized within a cross-validation process where the model was trained using 4 ensemble of groups of replicate spectra, of for example, i = 2, 3, 4, 5 with respectively 4, 4, 4 and 5 spectra for each sample. The resulted REC(ij − k) and REC(ij + k) were calculated for the respectively optimize d models for test (ij − k) and (ij + k) . These models were then tested using the rest ensemble of groups of replicate spectra, i = 1 for instance, generating RET(j − k) and RET(j + k) , together with the optimized models for test (j − k) and (j + k). -A doubled intermediate loop for j = 1 to 3: in this loop, the above discussed loop i was executed with 3 independent training rock data configurations for the 2 cases of a given sample k among the pellets being excluded from or included in the training data set. The model was further optimized. Corresponding calculation of RET resulted in RET(−k) and RET(+k). -An outer loop for k = 1 to 18: in this loop the above discussed loop i and loop j were executed for each of the 18 training pellet samples successively assigned as the pellet k. For a given pellet k, RET(−k) and RET(+k) were compared. If an improvement was observed with the sample, it was kept in the final training sample set, otherwise it was rejected. This loop generated a model for test (k) for each considered pellet sample with the corresponding RET(k) . The optimization process finally generated a model for validation with a minimized RET and RMSET.</p><p>Model validation. The resulted transfer learning model was validated by the pretreated spectra from the 12 validation rock samples including the 2 isolated rocks without counterpart pellet in the training sample set, with the identified features according to the common selected features between the training pellets and the training rocks. The parameters assessing the performance of the model for prediction, REP, RMSEP and RSD were calculated. These parameters indicate the performance of the model when used for predictions with LIBS spectra from rock samples, including unseen rocks, simulating thus a real application scenario. Remark that some of the training pellets, counterparts of the validation rocks and initially included in the model training sample set, were later rejected by the model training process (see Table 5 in the section "Methods") and did not participate to the final model optimization process. Such configuration of validation provided the assessments of the transfer learning model in the both cases of rocks with counterpart pellets more or less seen during the model training and rocks totally unknown by the model.</p><!><p>Analytical performances with the machine learning model. In order to emphasize the improvement with transfer learning, we first present the results obtained with the machine learning models trained using the 18 training pellet samples and validated using the 2 isolated pellets and the 12 validation rocks respectively for the 3 concerned oxides, SiO 2 , Na 2 O and K 2 O. Such double validations allowed the correction of chemical matrix effect being explicitly checked with independent pellets before the check of physical matrix effect with rock samples. The training method described in Reference 13 was implemented in this work to train a neural network. The training procedure was similar to the inner (loop i) and the intermediate (loop j) iteration loops used in the transfer learning model training (Fig. 5b) with a similar neural network structure. As shown in Fig. 3, the input variables were the 100 selected features in a pretreated spectrum of a training pellet sample for the training, and the 100 identified features in a pretreated spectrum of an isolated pellet sample or a validation rock sample for the validation. www.nature.com/scientificreports/ nals are plotted in the figures as a reference for the models. The extracted parameters for assessment of model performances are presented in Table 2 according to the definitions provided above. Although in Fig. 6, the results are presented with a given typical pair of isolated validation samples (S2 and S6), in Table 2 the validation performances are calculated as average values of those obtained with 6 different pairs of isolated validation samples (S2 and S5; S1 and S6; S4 and S12; S15 and S16; S10 and S17; S9 and S20), which ensures the independence of these performances on the choice of validation samples. For validation with rocks, we make the distinction between the 2 isolated rocks and the 10 rocks with counterpart pellets. In Fig. 6 and Table 2, we can see that the machine learning models trained with the training pellet samples present good calibration performances in terms of the usual assessment parameters including r 2 , LOD , REC , RET , and RMSE . In addition, the validation with the 2 isolated pellet samples also show satisfactory results. This indicates an effective correction of the chemical matrix effect with machine learning regression, as we also observed in our previous works 12,13 . Whereas, we can remark an obvious degradation of the performance when the models were tested using the validation rock samples, in terms of REP , RMSEP and RSD due to the influence of the physical matrix effect. In Fig. 6, the 2 isolated rocks do not show a particularly "bad" behavior with respective to the other validation rocks with counterpart pellets in the training sample set, which would indicate the fact that the absence of bulk chemistry of a rock for the model training does not particularly further influence its prediction by the model. This remark is confirmed by Table 2. Moreover, Fig. 6 shows that the use of a model trained with pellet samples for prediction with the spectra from rock samples can lead to bias, with a shift of the linear regression of the validation data with respect to that of the training data, as well as variance, with a rotation of the linear regression of the validation data with respect to that of the training data. We can also remark that the model performance degradation observed with polished rock samples is in general, further aggravated for raw rock samples, as also indicated by Table 2 where we can see increased average REP and RMSEP when one passes from polished rocks to raw rocks. This means that the physical matrix effect arises due to different surface hardness and heterogeneity of a polished rock with respect to its corresponding pressed powder pellet. Surface roughness of a raw rock introduces additional perturbations leading to in general, larger prediction uncertainties. A detailed look on the validation performances in Table 2 however shows that the influence due to surface roughness (raw rocks) remains smaller than that due to surface hardness and heterogeneity (polished rocks), which contributes to the largest part of the physical matrix effect.</p><p>As a consequence of the influence of the physical matrix effect, the TAS classification of the validation rock samples with the pellet machine learning models led to an unsatisfactory result as shown in Fig. 7. In this figure, the reference positions in the TAS diagram of the validation rock sample determined by their compositions measured using XRF (as shown in Fig. 1 and Table 4) are indicated with solid green stars for the 2 isolated rocks, and solid blue circular points for the rest of the validation rocks. The position predicted by the pellet machine learning models for the same sample is represented by a cross of the same color with error bars. More precisely, the Analytical performances with the transfer learning model. Calibration models resulting from transfer learning are shown in Fig. 8 with a similar format as those resulting from machine learning presented in Fig. 6, in order to review the improvements by comparison. The extracted parameters for assessment of the model performances are presented in Table 3 with validation performances calculated as average values of those obtained with the 6 different pairs of isolated validation samples. In Fig. In Fig. 8, we do not remark particular behavior for the 2 isolated rocks with respect to the other validation rocks as in Fig. 6. In Table 3, we can see that although the transfer learning models present in general, slightly lower calibration performances in terms of r 2 , LOD , REC , RET and RMSE compared to the machine learning models, the prediction performance for polished and raw rock samples are much improved, especially for REP and RMSEP . This means that the participation of the 8 rock samples in the training data set together with the retained pellet samples with common selected features, effectively takes into account the physical matrix effect and reinforces the robustness of the models for prediction for rock samples, including isolated rocks totally unknown by the models. We remark in particular, the prediction performances for both polished and raw rocks are simultaneously improved, showing the effectiveness of the transfer learning models in the correction of physical matrix effects of different origins.</p><p>The calibration models shown in Fig. 8 were used to present the validation rock samples in a TAS diagram. The obtained results are shown in Fig. 9a for polished rock samples and Fig. 9b for raw rock samples using the same symbols as in Fig. 7. We can see a much improved result conforming the good performances of the transfer learning models shown in Fig. 8 and Table 3. A detailed counting shows 10 correctly classified validation samples for the both polished and raw rocks, including the 2 isolated rocks. Only two samples were classified into a wrong field (S12 and S15 for polished rocks, S4 and S6 for raw rocks). The rate of correct classification can thus be determined to be 83.3% in the both cases. These results show the effectiveness of the developed method to www.nature.com/scientificreports/ correct the physical matrix effect. Confirming the observation in Fig. 8, no particular behavior can be observed for the 2 isolated rocks in the both cases of polished and raw rocks with respect to the other validation rocks.</p><!><p>In this work, within a given application of classification of rocks using the TAS diagram, we have introduced transfer learning in LIBS spectral data treatment to improve the performance of the models trained using laboratory standard samples in the form of pressed powder pellet, when used for prediction with LIBS spectra acquired www.nature.com/scientificreports/ from natural rocks with a polished surface or in a raw state. Such scenario corresponds to the important application of analysis of rocks with LIBS on Mars, although the used experimental configuration compared to the current rovers on Mars remains still quite different, concerning the ambient gas, the laser excitation, as well as the spectrum detection. The purpose was therefore to work on a general method that can be later implemented according to specific experimental conditions into particular applications. More precisely, feature-representationtransfer and instance-transfer as the two important processes of transfer learning were implemented in the LIBS spectral data treatment. The performances of the resulted transfer learning models were compared with those of the machine learning models. Significant improvements have been realized for prediction with LIBS spectra acquired on polished and raw rock samples for the 3 concerned compounds involved in the TAS classification, SiO 2 , Na 2 O and K 2 O. The rate of correct TAS classification has been improved from 25% for polished rocks and 33.3% for raw rocks with the machine learning models to 83.3% for the both types of rock samples with the transfer learning models. The obtained results therefore demonstrate the effectiveness of transfer learning to overcome the physical matrix effect due to the change of sample physical state in LIBS analyses.</p><p>There are still steps forward to realize in research and development to apply the method developed in this work to Mars explorations with LIBS. Such steps should involve a larger set of samples, with the possibility to isolate more rock samples for the independent validation of the transfer learning models, although the results shown in this work do not reveal obviously different behavior of the isolated validation rocks with respect to the other validation rocks that can have a counterpart pellet in the model training set. This would indicate a dominant physical matrix effect in the given configuration of study. It is also to be taken into account the experimental conditions, including the measurement environment (ambient gas and its pressure), the used laser parameters and the spectrum detection, in order to reduce the dissimilarities between a laboratory simulation experiment and the in situ LIBS measurements on Mars to a strict minimal related to the lack of complete knowledge about a real sample to be analyzed on Mars. Beyond analysis of rocks with LIBS in Mars explorations, our findings in this work can also have more general interests in the development of LIBS technique for various applications involving sets of samples with different surface physical properties.</p>

Scientific Reports - Nature

Recent Progress in Decarboxylative Oxidative Cross‐Coupling for Biaryl Synthesis

The beginning of the 21st century has seen tremendous growth in the field of decarboxylative activation. Benzoic acid derivatives are now recognised as atom‐economic alternatives to traditional cross‐coupling partners, and they also benefit from being inexpensive, readily available and shelf‐stable reagents. In this microreview we discuss recent developments in the coupling of benzoic acid derivatives either with an arene or with a second benzoic acid derivative, a process often termed decarboxylative oxidative cross‐coupling. These procedures offer great promise for the development of highly selective and atom‐economic cross‐couplings.

recent_progress_in_decarboxylative_oxidative_cross‐coupling_for_biaryl_synthesis

1. Introduction<!>1.1. Brief History of Decarboxylative Oxidative Coupling<!><!>2. Protodecarboxylation: Trends in Decarboxylation Aided by Transition Metals<!>2.1. [Cu] Systems<!><!>2.2. [Pd] Systems<!><!>2.2. [Pd] Systems<!>2.3. [Ag] Systems<!><!>2.3. [Ag] Systems<!><!>2.4. ortho Effect in Transition‐Metal‐Catalysed Decarboxylation<!><!>2.4. ortho Effect in Transition‐Metal‐Catalysed Decarboxylation<!>3. Decarboxylative C–CO2H/C–H Coupling<!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.1. [Pd]/[Ag] Systems<!><!>3.2. [Pd]/[Cu] Systems<!><!>3.3. Cu‐Catalysed Procedures: [Cu]/[Ag] Systems and [Cu]‐Only Systems<!><!>3.3. Cu‐Catalysed Procedures: [Cu]/[Ag] Systems and [Cu]‐Only Systems<!><!>3.3. Cu‐Catalysed Procedures: [Cu]/[Ag] Systems and [Cu]‐Only Systems<!><!>3.4. [Ni]/[Ag] Systems<!><!>3.5. [Ag]‐Only Systems<!><!>3.6. Summary<!>4. Decarboxylative C–CO2H/C–CO2H Couplings<!>4.1. Homocoupling<!><!>4.1. Homocoupling<!><!>4.2. Cross‐Coupling<!><!>4.2. Cross‐Coupling<!><!>4.3. Summary<!>5. Conclusions

<p>The advent of traditional cross‐coupling reactions – coupling between aryl halides and organometallic reagents – revolutionized thoughts relating to the construction of C–C bonds.1 More recent developments in the areas of C–H activation and decarboxylative activation have looked to improve the atom economy of these procedures by using more simple and readily available reagents.2, 3 The field of C–H activation has provoked considerable interest, because – ideally – it would allow for the construction of complex molecules from the simplest starting materials in an elementary fashion. In reality, this methodology faces the significant challenge of selective activation of one C–H bond in the presence of many others. Decarboxylative activation is a complementary strategy that can overcome some of the inherent difficulties of C–H activation, because the carboxyl group can provide a handle for selective transformations. The ready availability of benzoic acid derivatives also makes these processes comparable to C–H activation in terms of cost and atom efficiency.</p><!><p>The ability of transition metals to promote the decarboxylation of benzoic acid derivatives was first observed in 1930, when Shepard and co‐workers noted that furan‐2‐carboxylic acid derivatives were more prone to protodecarboxylation in the presence of copper than upon heating alone.4 Significant advancements were made during the 1970s by the groups of Nilsson,5 Sheppard6 and Cohen,7 who provided a more detailed study of copper‐mediated protodecarboxylation and began demonstrating its generality (Scheme 1). The field remained relatively quiet during the following years, and it was not until 2002 that Myers et al. reported Heck‐type decarboxylative coupling between benzoic acid derivatives and olefins, which – although catalytic in palladium – required a super‐stoichiometric loading of a silver salt additive.8 The seminal report in the field of decarboxylative biaryl synthesis was made by Gooßen and co‐workers, who developed direct decarboxylative cross‐coupling between benzoic acid derivatives and aryl iodides.9 Most importantly, the group discovered a dimetallic system that used only catalytic amounts of both palladium and copper salts, therefore firmly establishing benzoic acid derivatives as alternative aryl donors in cross‐coupling procedures. In recent years, the coupling of benzoic acid derivatives either with arenes or with other benzoic acid derivatives has attracted much interest. The first reports on C–CO2H/C–H and C–CO2H/C–CO2H couplings were made by the groups of Crabtree10 and Larrosa,11 respectively. Here we provide a comprehensive review of the current state of decarboxylative oxidative coupling for biaryl synthesis and the successes therein. We also discuss current limitations and the desired goals for the future of this field.</p><!><p>Timeline of significant advancements in decarboxylative oxidative couplings for biaryl synthesis.</p><!><p>Before discussing decarboxylative oxidative cross‐coupling, we first summarize transition‐metal‐promoted protodecarboxylation. Trends in transition‐metal‐promoted decarboxylation can thus be established, allowing informed prediction on which transition metal is operative in the decarboxylation step of the coupling process. An extensive summary of protodecarboxylation is not the aim of this section, and we only discuss representative procedures. In addition, we restrict our discussion to copper‐, palladium‐ and silver‐catalysed protodecarboxylation, because these metals have been used for decarboxylative cross‐coupling. Other metals, such as gold12 and rhodium,13 can also promote protodecarboxylation, but we have not included these examples because of their current absence in decarboxylative coupling procedures.</p><!><p>We have already mentioned that copper was one of the earliest metals found to promote decarboxylation (Section 1.1); however, it was not until the report of a decarboxylative arylation by Gooßen et al. that copper‐catalysed decarboxylation was fully recognised. To assess copper's ability to effect decarboxylative transformations further, the Gooßen group subsequently developed a copper‐catalysed protodecarboxylation procedure (Scheme 2).14 This study revealed that benzoic acid derivatives bearing electron‐withdrawing substituents and/or ortho substituents were particularly susceptible to decarboxylation. Electron‐rich substrates were generally less reactive than electron‐deficient substrates (compound 2a vs. 2d). Also, non‐ortho‐substituted benzoic acid derivatives were less reactive than ortho‐substituted benzoic acid derivatives; however, good reactivity was still achieved with use of a modified phenanthroline ligand (see 2e). Copper‐mediated decarboxylation is more general than other transition‐metal‐catalysed procedures, because the latter are limited to acids bearing ortho substituents. The main disadvantage is that high temperatures (>170 °C) are required to effect decarboxylation.</p><!><p>Copper‐catalysed protodecarboxylation of aromatic acids. [a] 3a (10 mol‐%). [b] 3b (10 mol‐%).</p><!><p>Investigations by Kozlowski and co‐workers led to a method for palladium‐catalysed protodecarboxylation (Scheme 3).15 This procedure represents one of the lowest‐temperature transition‐metal‐catalysed protodecarboxylations to date; however, the scope is severely limited to highly electron‐rich benzoic acid derivatives bearing two ortho substituents (Scheme 3, i).16 The procedure can be extended to mono‐ortho‐substituted and less electron‐rich benzoic acid derivatives, but a stoichiometric amount of palladium is then required (Scheme 3, ii).</p><!><p>Palladium‐catalysed/promoted protodecarboxylation of aromatic acids.</p><!><p>Larrosa and co‐workers have also shown that Pd can mediate the protodecarboxylation of biarylcarboxylic acids in the context of a tandem process.17</p><!><p>In 2009 the groups of Gooßen18 and Larrosa19 concomitantly revealed methods for silver‐catalysed protodecarboxylation (Scheme 4).20 The decarboxylation is applicable to both electron‐rich and electron‐deficient benzoic acid derivatives (e.g., 2a, 2d); however, an ortho group is mandatory (2d vs. 2e). The dependence on ortho substitution is the key limitation of this procedure over copper‐catalysed processes; however, the decarboxylation of ortho‐substituted substrates occurs at somewhat lower temperatures when silver is used (120 vs. 170 °C).</p><!><p>Silver‐catalysed protodecarboxylation of aromatic acids. [a] 160 °C. [b] AcOH (5 mol‐%).</p><!><p>A unique system for decarboxylation was reported by Greaney and co‐workers (Scheme 5).21 This system employs a silver catalyst, but – because the process takes place in the presence of a strong one‐electron oxidant – a radical pathway for the decarboxylation was proposed (Scheme 6). In this manner, the silver(I) catalyst in combination with K2S2O8 can provide the carboxyl radical 4 from carboxylate 3. A radical decarboxylation of 4 expels CO2 and forms the aryl radical 5, which can then abstract hydrogen from the solvent to form the arene 2. Whether the silver salt is a true catalyst or simply an initiator for a radical chain process has not been confirmed. The required temperature is slightly lower than those for other silver‐catalysed procedures, and ortho substituents are not a necessity in this system. Electron‐deficient substrates are preferred (e.g., 2a–c) and methoxy‐substituted acids display poor reactivity (compounds 2t, 2e). Most impressive is the decarboxylation of unsubstituted benzoic acid to afford 2v, which is unsuccessful in other procedures.</p><!><p>Silver‐catalysed protodecarboxylation of aromatic acids under radical conditions. [a] AgOAc (40 mol‐%).</p><p>Proposed mechanism for the silver‐catalysed protodecarboxylation of aromatic acids under radical conditions.</p><!><p>Many groups have made efforts to understand the mechanism(s) of transition‐metal‐mediated decarboxylation.22 This has resulted in the general mechanism shown in Scheme 7. DFT studies suggest that the transition states for Ag‐ and Cu‐mediated decarboxylation are similar and involve the metal atom inserting into the aryl–carboxyl bond (intermediate 7) with concomitant loss of CO2. The transition state for Pd‐mediated decarboxylation (intermediate 8) is slightly different from that for Ag and Cu; in this case the carboxyl group is positioned perpendicular to the plane of the aryl group, rather than simply bent out of the plane. This results in a four‐membered transition state in which the palladium atom is bonded solely to the carboxyl oxygen atom, and there is no interaction with the carboxyl carbon atom.</p><!><p>(i) General mechanism for the transition‐metal‐promoted decarboxylation of benzoic acid derivatives. (ii) Primary ortho effect (steric destabilisation). (iii) Secondary ortho effect (steric destabilisation + coordination).</p><!><p>In general, the transition‐metal‐mediated protodecarboxylation shows improved reactivity with ortho‐substituted benzoic acid derivatives. DFT studies have shown that the steric destabilisation imparted by an ortho substituent is the primary cause for this ortho effect. For example, the transition‐state energies of species bearing the same ortho, meta and para substituent are similar; however, the energy of the substrate bearing an ortho substituent is higher than that of the meta and para isomers. Overall this causes the barrier of decarboxylation to be lowered (Scheme 7, ii). This effect is apparent in all transition‐metal‐mediated procedures (Pd, Ag, Cu) and is in agreement with experimental results.</p><p>It has also been shown that, in the cases of copper and silver, some ortho substituents [e.g., NO2, C(O)H, C(O)NMe2] can lower the barrier to decarboxylation through coordination of the metal atom in the transition state. This causes a pronounced ortho effect, because the ortho group cannot only destabilise the substrate, but also stabilise the transition state, therefore leading to a greater decrease in the barrier to decarboxylation (Scheme 7, iii).</p><p>Finally, the electronic nature of the substituent also affects the decarboxylation barrier. For example, electron‐rich substituents are preferred for palladium‐mediated decarboxylation, whereas electron‐withdrawing substituents are preferred for copper‐ and silver‐mediated decarboxylation. DFT studies by Larrosa et al. revealed that, in the case of silver, electron‐withdrawing substituents lower the barrier to decarboxylation by minimising the build‐up of negative charge on the carbon atom ipso to the carboxyl group in the transition state.[22h] This stabilises the transition state and therefore lowers the barrier to decarboxylation. Because of the similarities between copper and silver decarboxylation a similar effect is likely in copper protodecarboxylation, though this has not been studied. No analogous DFT investigation into palladium protodecarboxylation has been performed; however, Hammett plot analysis suggests that a build‐up of positive charge occurs in the transition state in this case.[22f] This experimental study highlights the preference for electron‐donating substituents in palladium protodecarboxylation.</p><p>Overall, the factors that favour decarboxylation are threefold: (1) ortho substituents destabilise the starting benzoic acid/carboxylate through steric factors (Scheme 7, ii), (2) in some cases the ortho substituent can stabilise the transition state through coordination of the transition metal atom (Scheme 7, iii), and (3) depending on the metal employed, electron‐withdrawing or electron‐donating substituents stabilise the transition state by minimising the build‐up of negative/positive charge.</p><!><p>Coupling between benzoic acid derivatives and arenes is highly appealing, due to the ready availability of each set of substrates and the potential for developing atom‐economic procedures. Generally, these systems use palladium catalysts and stoichiometric silver salts as oxidants that, more often than not, also assist in the decarboxylation event. The couplings have been organised into sections on the basis of which transition metals are used in each procedure.</p><!><p>The first examples of C–CO2H/C–H biaryl coupling were reported by Crabtree and co‐workers, who revealed that 2,6‐dimethoxybenzoic acid could be coupled with anisole to afford 12aa or with arenes substituted with directing groups to give 12ba–12da (Scheme 8).10 However, the yields of these reactions were generally low and led to the formation of significant amounts of protodecarboxylated products. The scope of the benzoic acid coupling partner was also not investigated, although they did report the intramolecular decarboxylative coupling of 2‐phenoxybenzoic acid to provide 13aa.</p><!><p>Scope of the decarboxylative oxidative coupling of 2,6‐dimethoxybenzoic acid with simple arenes. [a] From 2‐phenoxybenzoic acid.</p><!><p>Soon after, Glorius et al. reported an improved method for the decarboxylative cyclisation of 2‐aryloxybenzoic acid derivatives 14 (Scheme 9).23 This method provided better yields (85 % vs. 44 %) and lower levels of undesired protodecarboxylation (Ar–Ar/Ar–H = 1.0:1.2 vs. 1.0:0.01) for product 13aa (Scheme 8 vs. Scheme 9). Electron‐rich and electron‐deficient substituents were tolerated on the C–H ring, but only one example of a substituent on the C–CO2H ring was reported (compound 13ab). The cyclisation can occur at sterically hindered C–H bonds, though – if given the choice – the sterically less hindered C–H bond will undergo functionalisation preferentially (compounds 13da, 13ea).</p><!><p>Scope of the intramolecular decarboxylative oxidative coupling of 2‐aryloxybenzoic acid derivatives. [a] Asterisk marks position of minor cyclised regioisomer.</p><!><p>Larrosa and co‐workers then looked to expand the cross‐coupling to incorporate electron‐deficient benzoic acid derivatives (Scheme 10).24 Under the optimised conditions, benzoic acid derivatives that are capable of undergoing silver‐mediated decarboxylation were reactive; however, 2,6‐dimethoxybenzoic acid was unreactive in this case and did not afford 12ga. Also, the procedure was only applied to indole derivatives as the C–H coupling partners.25</p><!><p>Scope of the decarboxylative oxidative coupling between indole derivatives and electron‐deficient benzoic acid derivatives.</p><!><p>Su and co‐workers further optimised this methodology, with the resulting catalytic system being able to arylate both electron‐rich and electron‐deficient benzoic acid derivatives (Scheme 11).26 It seems that the choice of solvent (dioxane vs. DMF) and the addition of an aliphatic carboxylic acid (EtCO2H) were vital for obtaining reactivity with electron‐rich benzoic acid derivatives. Interestingly, the position (C2 vs. C3) of indole C–H arylation was determined solely by the electronic nature of the benzoic acid coupling partner: electron‐rich benzoic acid derivatives preferentially gave the C3‐arylated products, whereas electron‐deficient benzoic acid derivatives provided the C2 products, in accord with the Larrosa group's report. The reason for this switch in selectivity has not been investigated. Whereas acyl‐protected indole derivatives were preferred for coupling with electron‐rich benzoic acid derivatives, pivaloyl‐protected indole derivatives were required in order to obtain good reactivity with electron‐deficient coupling partners; however, the regioselectivity of the reaction was unaffected by the choice of protecting group (12ge vs. 12he).</p><!><p>Scope of the decarboxylative oxidative coupling between indole derivatives and electron‐rich or electron‐deficient benzoic acid derivatives.</p><!><p>Now that more general methods for the decarboxylative arylation of benzoic acid derivatives had been developed, studies then looked to expand the scope of the arene coupling partners. Continuing from their work on decarboxylative indole arylation, Su and co‐workers also reported that thiophene, furan, benzofuran and pyrrole derivatives could couple with a range of electron‐rich and electron‐deficient benzoic acid derivatives (Scheme 12).27</p><!><p>General schematic for the decarboxylative oxidative coupling between benzoic acid derivatives and heteroaromatics. [a] Ag3PO4 (1.5 equiv.), K3PO4 (2.0 equiv.).</p><!><p>Luo et al. realised that simple arenes could also be used as coupling partners (Scheme 13).28 Unfortunately, the arene component was required in solvent quantities and the benzoic acid component was limited to highly activated polyfluorinated substrates. In addition, the selectivity of the C–H activation was poor. Nevertheless, this represents one of the few examples in which simple benzene has been used as a coupling partner, affording 12pf, 12pg and 12ph. It is possible that the C–H activation occurs through an SEAr‐type process; however, it is difficult to suggest this with confidence, because no detailed mechanistic studies have been performed.</p><!><p>General schematic for the decarboxylative oxidative coupling between benzoic acid derivatives and simple arenes.</p><!><p>Su and co‐workers reported coupling between polyfluorinated arenes and electron‐rich or electron‐deficient benzoic acid derivatives (Scheme 14). The reactivity of the arene coupling partner correlated with its acidity: thus, pentafluorobenzene was the most effective arene coupling partner, whereas 1,3‐difluorobenzene was poorly reactive.29 It is presumed that bis(arylation) is not observed in cases in which more than one acidic C–H bond is present (e.g., synthesis of 12td or 12ud); however, the authors do not comment on this possibility.</p><!><p>General schematic for the decarboxylative oxidative coupling between benzoic acid derivatives and polyfluorinated arenes.</p><!><p>Similarly, Tan et al. also showed that polyfluoroarenes could couple with benzoic acid derivatives (Scheme 15).30 They also revealed that heteroarenes, such as benzoxazoles and benzothiazoles, could be used in this reaction with both electron‐rich and electron‐deficient benzoic acid derivatives.</p><!><p>General schematic for the decarboxylative oxidative coupling between benzoic acid derivatives and arenes bearing acidic C–H bonds.</p><!><p>Another group of arenes that have proved to be reactive in C–H activation processes are pyridine N‐oxides. Muthusubrumanian and co‐workers employed these substrates in decarboxylative coupling with heteroaromatic carboxylic acid derivatives (Scheme 16).31 Unfortunately, the use of simple benzoic acid derivatives was not reported. In some cases, a significant amount of bis(arylated) product was observed resulting from two C–H activation events (e.g., 12zm′).</p><!><p>General schematic for the decarboxylative oxidative coupling of benzoic acid derivatives with arenes bearing acidic C–H bonds.</p><!><p>Decarboxylative coupling between benzoic acid derivatives and aryl halides generally requires a system consisting of [Pd]/[Cu] salts;3 however, this type of system is hard to come by in oxidative couplings. In fact, the cross‐coupling between azolecarboxylic acid derivatives and simple azoles described by Greaney and co‐workers represents the only report in which a [Pd]/[Cu] dimetallic system is employed (Scheme 17).32 Although silver salts can be employed in this reaction, the authors preferred to use CuCO3 to aid the coupling of a range of substituted oxazoles with oxazole‐ and thiazolecarboxylic acid derivatives.</p><!><p>Scope of the decarboxylative oxidative coupling between azolecarboxylic acids and azoles in the presence of a [Pd]/[Cu] system.</p><!><p>A [Cu]/[Ag] system analogous to the [Pd]/[Ag] system used in the coupling between benzoxazole derivatives and benzoic acid derivatives (Scheme 15) has been described (Scheme 18).33 The benzoxazole core can be substituted with electron‐donating or electron‐withdrawing groups at various positions; however, the procedure is limited to 2‐nitrobenzoic acid derivatives as coupling partners.</p><!><p>Scope of the decarboxylative oxidative coupling between 2‐nitrobenzoic acid derivatives and benzoxazole derivatives in the presence of a [Cu]/[Ag] system.</p><!><p>It was found that this coupling also proceeds on removal of the silver salt and its replacement with O2 as the sole oxidant (Scheme 19).34 Under these conditions, copper is the only transition metal present, and in catalytic quantities. The procedure shows a scope similar to – if not better than – that of the [Cu]/[Ag] system: polyfluorobenzoic acid derivatives can also be used in this procedure along with a wider range of heteroarenes such as thiophene, furan and imidazole derivatives. The use of only a catalytic quantity of an abundant transition metal is highly appealing; however, the procedure is only applicable to coupling between highly activated benzoic acid derivatives and heteroarenes. It would be of great interest if a more general procedure employing lower loadings of the catalyst were to be developed.</p><!><p>Scope of the decarboxylative oxidative coupling of heteroarenes in the presence of a [Cu]‐only system.</p><!><p>A [Cu]/[Ag] system has also been used for the decarboxylative arylation of benzamide derivatives through directed C–H functionalisation (Scheme 20).35 High loadings of CuOAc and super‐stoichiometric amounts of AgNO3 are required. The benzamide can be decorated at various points with electron‐donating or electron‐withdrawing groups; however, the authors only describe the decarboxylative coupling of thiophenecarboxylic acid derivatives. In some cases, such as those of 12Js and 12Ls, significant levels of bis(arylation) are observed.</p><!><p>Scope of the directed decarboxylative oxidative coupling between benzamide derivatives and thiophenecarboxylic acid derivatives in the presence of a [Cu]/[Ag] system. PIP = (pyridin‐2‐yl)isopropyl. [a] Yield of bis(arylated) product. Asterisk marks the position of bis(arylation).</p><!><p>We have already discussed the fact that [Pd]/[Ag], [Cu]/[Ag] and [Cu] alone (Schemes 15, 18 and 19) can promote decarboxylative coupling between benzoic acid derivatives and benzoxazole derivatives. In addition, an [Ni]/[Ag] procedure has been developed (Scheme 21).36 The scope is comparable with those of other procedures, showing good reactivity with electron‐deficient and electron‐rich benzoxazole derivatives and nitro/fluoro‐substituted benzoic acid derivatives.</p><!><p>Scope of the decarboxylative oxidative coupling between 2‐nitrobenzoic acid derivatives and (benz)oxazole derivatives in the presence of an [Ni]/[Ag] system. [a] Ag2CO3 (3.0 equiv.); no BQ added.</p><!><p>The Minisci reaction – coupling between alkanecarboxylic acid derivatives and pyridine derivatives assisted by a silver catalyst – is well known; however, the extension of this procedure to incorporate aromatic carboxylic acids has been a longstanding challenge. Inspired by the Greaney group's report on the silver‐catalysed decarboxylation of benzoic acid derivatives under radical conditions (Scheme 5),21 Su and co‐workers used this methodology for an aromatic Minisci‐type reaction (Scheme 22).37 As mentioned in the discussion of the analogous protodecarboxylation, the beauty of this procedure is its ability to decarboxylate non‐ortho‐substituted benzoic acid derivatives. Because of the radical nature of the decarboxylation, a large excess (22.5 equiv.) of the arene is required, and the regioselectivity with respect to the C–H coupling partner is hard to control. The formation of biphenyl (12pw) is a nice addition to the reaction scope, because unsubstituted arenes and benzoic acid derivatives are poorly reactive in many C–H and decarboxylative arylations.</p><!><p>Scope of the decarboxylative oxidative coupling under radical conditions in the presence of an [Ag]‐only system.</p><!><p>Coupling between ortho‐substituted benzoic acid derivatives and a variety of arenes has attracted increasing attention in recent years. The generality and economy of these procedures are slowly improving; however, there is still much room for investigation. For example, all the procedures, barring a report by Su and co‐workers (Scheme 22), are strictly limited to ortho‐substituted benzoic acid derivatives. The protodecarboxylation of non‐ortho‐substituted benzoic acid derivatives is possible (see Section 2), and coupling between non‐ortho‐substituted benzoic acid derivatives and aryl (pseudo)halides has also been intensely studied. Therefore, cross‐coupling of non‐ortho‐substituted benzoic acid derivatives is a realistic possibility. In terms of atom economy, decarboxylative oxidative couplings generally require the addition of stoichiometric amounts of transition metals (usually silver), and there are only two reports that do not require stoichiometric amounts of transition‐metal additives (Schemes 19 and 22). In the wider field of decarboxylative cross‐coupling, significant progress has been made in avoiding the need for stoichiometric amounts of transition metals, especially in coupling between benzoic acid derivatives and (pseudo)halides; therefore, it is hoped that similarly efficient procedures can be achieved for C–CO2H/C–H couplings.</p><!><p>Coupling between benzoic acid derivatives and arenes through decarboxylation is highly appealing, because both reagent classes are readily available; however, because of the abundance of C–H bonds in the starting materials regioselectivity issues can be troublesome (cf. Schemes 13 and 22). Alternatively, if both coupling partners are benzoic acid derivatives the regioselectivity can be controlled by the position of the carboxyl group, whilst still achieving high atom economy. This field is still very much in its infancy, and only a handful of coupling procedures have been reported.</p><!><p>Reports in this field were begun by Larrosa et al., who performed homocoupling of (hetero)aromatic acid derivatives in the presence of a [Pd]/[Ag] system (Scheme 23).11 From examination of the reaction scope it is likely that silver is responsible for promoting the decarboxylation and that, upon transmetallation, palladium then can mediate the coupling of the aryl units.</p><!><p>Scope of the double decarboxylative homocoupling of benzoic acid derivatives in the presence of a [Pd]/[Ag] system.</p><!><p>More recently, a system for homocoupling catalysed solely by copper has been reported, but high loadings (30 mol‐%) of the copper catalyst are required (Scheme 24).38, 39 Remarkably, the coupling does not appear to require the addition of an oxidant, and it is performed under N2, so O2 is also excluded. Possibly DMSO is acting as the oxidant in this case; however, the authors do not comment on this peculiarity. The procedure is limited to ortho‐nitrobenzoic acid derivatives; sterically congested benzoic acid derivatives are unreactive (cf. 12EE). Methods that can couple a wider range of benzoic acid derivatives in the presence of a similarly cost‐effective system would be highly interesting.</p><!><p>Scope of the double decarboxylative homocoupling of benzoic acid derivatives in the presence of a [Cu]‐only system.</p><!><p>A much more valuable procedure would be the selective cross‐coupling of benzoic acid derivatives; however, differentiating between two benzoic acid components is a considerable challenge. The first attempt to tackle this problem was made by Tan, Deng and co‐workers, who found that electron‐rich or (poly)fluorinated benzoic acid derivatives can provide moderate to good yields in cross‐coupling with ortho‐nitrobenzoic acid derivatives (Scheme 25).40, 41 However, the chemoselectivity of this procedure is low, with at least 20 % of the homocoupled product of the 2‐nitrobenzoic acid (compound 12FF, 12ee or 12qq) being observed in each case.</p><!><p>Scope of the double decarboxylative cross‐coupling of benzoic acid derivatives in the presence of a [Pd]/[Ag] system.</p><!><p>Remarkably, by employing a different phosphine ligand and a slight adjustment of the solvent, Su et al. reported a similar system that could be applied to a wider range of benzoic acid derivatives, including benzoic acid derivatives that have similar electronic properties (Scheme 26).42 The chemoselectivity is certainly improved for product 12de in comparison with the previous report; however, the cross‐coupling/homocoupling selectivity is still less than 7:1. Furthermore, the authors did not reveal the levels of homocoupling in each case, so the chemoselectivity of the procedure over a wide range of benzoic acid derivatives could not be assessed.</p><!><p>Scope of the double decarboxylative cross‐coupling of benzoic acid derivatives in the presence of a [Pd]/[Ag] system: an improved system.</p><!><p>Selective coupling between two benzoic acid derivatives is an intriguing possibility. Although there are few reports in this area, they provide only a proof‐of‐principle for this transformation. Currently, these methods suffer from limitations similar to those described for cross‐coupling between benzoic acid derivatives and arenes. Namely, the procedures are limited to benzoic acid derivatives bearing ortho substituents, and the coupling of non‐ortho‐benzoic acid derivatives has not been reported. The need for the use of stoichiometric amounts of transition metals is also necessary in these procedures, and it is only in the homocoupling of ortho‐nitrobenzoic acid derivatives that catalytic amounts of copper can be used (Scheme 24). Finally, the levels of chemoselectivity for such cross‐couplings are very low, so strategies to allow better distinction between the benzoic acid derivatives are highly sought‐after. Despite these drawbacks, the initial reports in this area are beginning to display the potential of double decarboxylative couplings for biaryl synthesis.</p><!><p>Decarboxylative oxidative couplings are attractive procedures for three key reasons: (1) the carboxyl group offers a handle for selective couplings through decarboxylation, (2) the substrates are both inexpensive and readily available, and (3) they hold potential for the development of atom‐economic coupling procedures. This microreview describes the developments in this field from the early reports in 2008 to the present day.</p><p>The most intensively studied procedure has been the coupling between ortho‐substituted benzoic acid derivatives and a wide variety of arenes. A number of strategies have been adopted for this transformation, and it is hoped that future studies can continue to improve the generality and atom economy of these procedures.</p><p>Currently, there are only a handful of examples for the coupling of two benzoic acid derivatives. Many of the challenges associated with C–CO2H/C–H couplings are also apparent in C–CO2H/C–CO2H couplings, but with the added difficulty of distinguishing between the two benzoic acid derivatives in order to obtain good yields of cross‐coupled product. This point has been met with limited success, but it remains an important obstacle to be overcome in order to establish this strategy as a viable route for biaryl synthesis.</p><p>The field of decarboxylative oxidative cross‐coupling has developed significantly over the past decade. Current methods have already revealed some of the advantages of cross‐coupling of this type, and we are confident that future developments will continue to reveal the full potential of this reactivity.</p>

PubMed Open Access

Photonic Crystal-Enhanced Fluorescence Imaging Immunoassay for Cardiovascular Disease Biomarker Screening with Machine Learning Analysis

When myocardial walls experience stress due to cardiovascular diseases, like heart failure, hormone N-terminal pro-B-type natriuretic peptide (NT-proBNP) is secreted into the blood. Early detection of NT-proBNP can assist diagnosis of heart failure and enable early medical intervention. A simple, cost-effective detection technique such as the widely used fluorescence imaging immunoassay is yet to be developed to detect clinically relevant levels of NT-proBNP. In this work, we demonstrate photonic crystal-enhanced fluorescence imaging immunoassay using diatom biosilica, which is capable of detecting low levels of NT-proBNP in solution with the concentration range of 0~100 pg/mL. By analyzing the fluorescence images in the spatial and spatial frequency domain with principle component analysis (PCA) and partial least squares regression (PLSR) algorithms, we create a predictive model that achieves great linearity with a validation R2 value of 0.86 and a predictive root mean square error of 14.47, allowing for good analyte quantification. To demonstrate the potential of the fluorescence immunoassay biosensor for clinical usage, we conducted qualitative screening of high and low concentrations of NT-proBNP in human plasma. A more advanced machine learning algorithm, the support vector machine classification, was paired with the PCA and trained by 160 fluorescence images. In the 40 testing images, we achieved excellent specificity of 93%, as well as decent accuracy and sensitivity of 78% and 65% respectively. Therefore, the photonic crystal-enhanced fluorescence imaging immunoassay reported in this article is feasible to screen clinically relevant levels of NT-proBNP in body fluid and evaluate the risk of heart failure.

photonic_crystal-enhanced_fluorescence_imaging_immunoassay_for_cardiovascular_disease_biomarker_scre

Introduction<!>Diatom-based NT-proBNP Sensor Fabrication<!>Fluorescence Image Preprocessing and Processing<!>Statistical Regression Calibration Curve Creation<!>Qualitative Screening Procedure<!>Cardiovascular Disease Biosensing Mechanism<!>Average Intensity Analysis<!>Quantitative Statistical Regression<!>Qualitative Classification of NT-proBNP in Plasma<!>Conclusion

<p>According to the American Heart Association, in 2009, one in nine deaths cited heart failure (HF) as a contributing cause and in 2016, about 5.7 million Americans suffered from HF (Mozzafarian et al., 2016). Total direct medical costs of HF in the US are projected to be $42.9 billion by 2020 (Heindenreich et al. 2011). The need for accurate, inexpensive and early detection of HF is of critical importance. When an individual has HF, the myocardial wall experiences stress and the prohormone B-type natriuretic peptide (proBNP) is cleaved releasing N-terminal proBNP (NT-proBNP) and BNP. Both are recommended by the European Society of Cardiology (ESC) as analytes to aid in the diagnosis of HF (Ponikowski et al. 2016). However, the half-life-time of NT-proBNP is nearly 6× longer than that of BNP, making it a better biomarker for detection (Weber and Hamm 2006). The ESC directs that the upper limit of normal levels of the biomarker is 125 pg/mL and values lower than this can be used to rule out the possibility of HF (Ponikowski et al. 2016). Levels of NT-proBNP >450 pg/mL can be used to "rule in" HF (Januzzi 2005).</p><p>The most common method of detecting NT-proBNP is by performing electrochemiluminescence (ECL) paired with an immunoassay. This method is recommended and used by respected institutions such as the Mayo Clinic (Cobas 2017; Mayo 2017). ECL is effective, but it also requires expensive, sophisticated instrumentation and highly trained personnel. Fluorescence imaging, often paired with an immunoassay, is a biosensing technique that could be used in place of ECL. The immunoassay allows for high degrees of specificity due to the specific antibody-antigen interaction, allowing capture or separation of the analyte from the surrounding sample matrix. Fluorescence imaging sensors are rationally designed such that the presence of the analyte induces a change in fluorescence intensity, which is caused by specific analyte labeling with a fluorophore (Golden and Ligler 2002; Lee et al. 2019; Song et al. 2015) or quenching inherent sample fluorescence (Huang et al. 2016; Liu et al. 2010).</p><p>Fluorescence imaging employs imagers, either consumer or laboratory grade, to monitor the change in fluorescence intensity. The intensity depends on the concentration of analyte present, and in some applications, detection and quantification can be achieved even down to single molecule levels (Agrawal et al. 2006; Cai et al. 2006). Furthermore, fluorescence imaging can perform large area measurements while maintaining spatial information, thus allowing parallel sensing of multiple sensors for high-throughput applications. This powerful sensing technique has been applied to the detection of NT-proBNP (Lee et al. 2010; Wilkins et al. 2018). However, Lee et al. (2010) achieved detection of the biomarker only to 5 ng/mL, which is significantly above clinically relevant levels. Wilkins et al. (2018) successfully detected NT-proBNP down to 50 pg/mL but required high efficiency quantum dots containing toxic cadmium sulfide to achieve this level of detection. Therefore, safe detection of NT-proBNP at clinically relevant levels of detection still requires further fluorescence signal enhancement.</p><p>In recent years, plasmonic structures such as nanoparticles, nanorods and other nanostructures have been employed to enhance the local electromagnetic field resulting in enhanced fluorophore excitation (Bek et al. 2007; Mohamed et al. 2000; Parfenov et al. 2003). These techniques provide fluorescence enhancement but often suffer highly localized effects. Uniform photonic crystals have also been used as suitable fluorescence enhancing substrates due to their optical field enhancement and large sensing area-to-volume ratio (Chakravarty et al. 2012; Ganesh et al. 2007; Hou et al. 2014, Pokhriyal et al. 2010). However, rationally designed photonic crystals generally require cleanroom technologies to fabricate and often experience issues with surface functionalization (Campbell et al. 2000; Cheng and Scherer 1995). Engineered fluorophores, such as quantum dots, have been fabricated and used to achieve higher quantum efficiencies and stronger fluorescence, but these often require toxic materials such as cadmium (Buffet et al. 2014; Larson et al. 2003).</p><p>Other than the concern of sensitivity, random fluctuation of the fluorescence signals brings a great challenge for analyte quantization. Feature extraction, statistical regressions and classifications are the main tasks of statistical machine learning with each algorithm being used to improve the clarity of a dataset for quantitative and qualitative analyses. Feature extraction techniques, such as principle component analysis (PCA), reduce the dimensionality of data, enabling more effective visualization and analysis. Regression analyses, like the partial least squares regression (PLSR) or support vector regression, are common analytical techniques that have been applied to fluorescence biosensing and allow for the creation of accurate calibration curves to quantitatively predict the concentration of an analyte (Diez et al. 2008; Divya and Mishra 2006; Yan et al 2015). Classification techniques such as the linear discriminant analysis, k-nearest neighbors (kNN) or support vector machines (SVM) can be used to train a model capable of accurately grouping data points by similar characteristics and are effective for qualitative and semi-quantitative classification. Implementation of classification techniques have enabled successful analyte detection with fluorescence biosensing (Kurachi et al. 2008; Moshou et al. 2014; Zhang et al. 2007).</p><p>In this work, we demonstrated a photonic crystal-enhanced fluorescence imaging immunoassay biosensor capable of detecting clinically relevant levels of NT-proBNP and implemented machine learning-assisted analyte quantization. Different than artificial photonic crystals made by top-down nanofabrication techniques, our cardiovascular biomarker sensor employs diatom biosilica to enhance the fluorescence signal. Diatoms are single-celled microalgae that biologically fabricate porous silica shells called frustules. The periodic, nanostructured pore arrays of diatom frustules can enable natural photonic crystal behavior. Our group has proven that diatom biosilica is capable of enhancing Raman and fluorescence signals due to their photonic crystal structure as well as their large and super-hydrophilic surface, thus offering exclusive advantages for biosensing, particularly for immunoassay (Kong et al. 2016; Kong et al. 2017; Ren et al. 2013; Squire et al. 2018). The biosensor fabrication begins with cost-effective algae cultivation to grow diatoms. Cellular organic matter is removed, and the isolated biosilica shells are deposited onto a glass slide as a dispersed monolayer thin film. A typical sandwich immunoassay process is performed to functionalize the substrate with antibodies, selectively capturing the analyte NT-proBNP and tagged with fluorophore-labeled antibodies. The diatom biosilica integrated with our sensor offers significant fluorescence signal enhancement for clear imaging. Following the data acquisition, a simple arithmetic average fluorescence intensity analysis is performed, resulting in the detection of NT-proBNP to clinically relevant levels but with difficulty in differentiation at lower concentrations. To improve this, feature extraction and regression analyses obtain an excellent calibration curve for the NT-proBNP concentration with good linearity and differentiation. When challenged by 24 test images, a validation R2 value of 0.86 and a predictive root mean square error of 14.47 was achieved, allowing for good analyte quantification. Lastly, we detect NT-proBNP in human plasma and use feature extraction and classification to qualitatively distinguish between high and low concentrations of NT-proBNP, creating a screening mechanism for diagnostically ruling in or out heart failure. The classification model was trained using 160 fluorescence images and when applied to 40 test images, achieves excellent specificity of 93%, and decent accuracy and sensitivity of 78% and 65% respectively. Therefore, the synergistic integration of the photonic crystal-enhanced fluorescence imaging immunoassay with machine-learning analysis techniques has led to effective detection of cardiovascular biomarker NT-proBNP, which can play a key role for screening individuals with heart failure risk.</p><!><p>The fabrication follows our earlier work with minor modifications (Squire et al. 2018). Diatom culturing and isolation techniques as well as populating a coverslip are described in the Supporting Information. Scanning electron microscopy (SEM) images of the coverslips are shown in Fig. 1(a–b) and discussed in the Supporting Information. The process of the sandwich type immunoassay is outlined in the schematic in Fig. 1(c) below.</p><p>Briefly, a 2.2 × 2.2 cm glass coverslip with diatom frustule mass coverage of 5 μg/cm2 was first submerged in a mixture of 10 mL methanol, 500 μL of 99% acetic acid and 150 μL of 99% (3-Aminopropyl)-triethoxysilane (APTES) for 30 minutes at room temperature to populate the surface with free amine groups. The sample was rinsed with acetone and ethanol and dried with nitrogen. The sample was then submerged in 2% glutaraldehyde (GA), a homobifunctional crosslinker, in phosphate buffered saline (PBS) for 2 hours at room temperature to react with the free amine group and to cover the surface with aldehyde groups. Following a rinsing with 20 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) and deionized water, the glass coverslip was dried with nitrogen gas flow and diced into multiple 5 × 5 mm sensors. Each sensor then had 1 μL of 0.1 mg/mL of the antibody, anti-proBNP, dropcast onto its surface. It was left at 4° C for 6 hours to allow the surface to be functionalized with the antibody. The sample was again rinsed with HEPES and water and dried with nitrogen gas. Next, the sample was submerged in 1 mg/mL bovine serum albumin (BSA) in PBS for 6 hours at 4° C to block all the remaining aldehyde groups. This decreases nonspecific binding and enhances the detection specificity of the immunoassay sensor. Again, the sample was rinsed with HEPES and water, and dried by nitrogen gas. At this point, the functionalized immunoassay sensor was ready for detection. The detection was performed by submerging the sample in a solution of NT-proBNP analyte in either PBS or human plasma. This step was performed in solution volumes of 900 mL and 400 μL for the buffer and plasma respectively. The sensor was kept in the solution for 2 hours at room temperature to allow for immune-recognition of the antibody-antigen pair. After another rinsing with HEPES and water, the sample had 1 μL of 0.25 mg/mL anti-NT-proBNP conjugated with fluorescein dropcast onto the surface, where it was left for 4 hours at 4° C, thus labeling the bound antigens with fluorophore labeled antibodies and completing the immune-sensing process.</p><!><p>The details about the fluorescence microscope, light source, and image capture parameters are described in the Supporting Information. The acquired optical and fluorescence images were saved as .tiff files and imported into Matlab to be prepared for processing, following the similar approach outlined in our previous work (Squire et al. 2018), which is described in Fig. 2. Optical and fluorescence images were first superimposed on top of one another and aligned. Frustules in the image were then circled and a mask was created in the shape of the diatom shell. This mask was applied to the original fluorescence image, leaving just the frustule with the remainder of the background zeroed out. Once the fluorescence image was masked, it was cropped to a uniform size with the frustule in the center. Another set of images were constructed from the original image with the frustules zeroed, leaving only the fluorescence information on glass. These spatial domain images were used to analyze the fluorescence signal on glass and compare it to that found on diatom frustule.</p><p>After the diatom frustules from the fluorescence image were masked and cropped, the power spectral density (PSD) of each image was obtained by performing the two-dimensional fast Fourier transform (FFT) and taking the square of the absolute value in the spatial frequency domain. The image was shifted to move the zero-frequency component to the middle of the image and the natural log-scale was taken.</p><!><p>To create the calibration curve for solution-based NT-proBNP sensing, PCA was paired with PLSR. The model was created by first, using Matlab to find the average fluorescence intensity for each concentration by finding the average intensity of each PSD of the frequency domain image and taking the total average. Once the average intensity for each concentration was determined, 30 images with average intensities closest to the concentration's average fluorescence intensity were selected. This was done for each concentration to remove any outliers and resulted in a dataset of 30 images from each concentration. Using the built-in Matlab functions, the principle components (PCs) were determined and the first three were used in PLSR. A 5-fold cross-validation was used where 80% of the images were used to train a model and 20% were used to test the model.</p><p>From the training and test regressions, the coefficient of determination (R2) and the root mean square error (RMSE) were calculated from the 5-fold cross-validations and were averaged. The equations for these values are shown in the Supporting Information. The RMSE is a measure of the average error predicted within the dataset and explains how spread out the data is and the R2 is a measure of how good of a fit the regression gives. Generally, higher R2 (but no more than 1) and lower RMSE values means better regression performance. Discussion of our created model is given in section 3.3.</p><!><p>To perform the qualitative screening of NT-proBNP in human plasma, the data preparation was similar to that of the regression analysis but 100 frequency domain images at high and low concentrations were chosen instead of 30 due to our larger plasma-based measurements dataset. PCA was performed on the images and classification algorithms including kNN and SVM were used in this analysis. kNN was achieved using Matlab's built-in function and SVM classification was performed using a common SVM library, libSVM (Chang and Lin 2011). The accuracy, sensitivity and specificity for each classification algorithm were calculated for various numbers of PCs using a 5-fold cross-validation and the average of each statistic were compared and discussed in section 3.4 below. These metrics are defined thoroughly in our Supporting Information. Briefly, the model classifies the dataset into a positive and negative class, which correspond to the high concentration and low concentration, respectively. Accuracy is a measure of how many measurements the model correctly classified. Sensitivity is a measure of the number of correctly classified positive measurements, and specificity describes the number of correctly classified negative measurements. Each of these metrics range from 0 to 1 with 1 being perfect classification.</p><!><p>The sandwich immunoassay process used here is one that is fairly well understood and accepted. The diatom-populated glass slide is first aminated using the APTES, resulting in free amine groups on its surface. The homobifunctional crosslinker GA is then introduced. This molecule contains two aldehyde groups, one of which easily reacts with the free amine group, leaving the other free, thus populating the surface with free aldehyde groups. These aldehydes easily react with amine groups on the antibody, anti-NT-proBNP, and the protein BSA. The substrate is populated with capture antibodies, after which, BSA is used to block the remaining active aldehydes to reduce nonspecific binding. The analyte is then introduced and selectively binds with the capture antibody affixed to the substrate through immunorecognition. Lastly, antibodies labeled with a fluorescent tag (anti-NT-proBNP-FITC) are introduced, where they bind with the antigen and complete the sandwich structure. At this point, the sensing event has taken place and the fluorescence can now be measured. The characterization of this substrate is discussed in more depth in the Supporting Information.</p><!><p>To analyze the efficacy of our diatom-based fluorescence NT-proBNP biosensor, the immunoassay, image collection and preprocessing of the fluorescence images were performed as explained in sections 2.1 and 2.2 above, followed by an average intensity analysis. To begin, the average fluorescence intensity of each spatial domain image was calculated for a given concentration. The median average intensity was found, and images with an average fluorescence intensity greater than one standard deviation away from the median were excluded as outliers. The average and standard deviation of the remaining images' average fluorescence intensities were calculated for each concentration using the preprocessed spatial domain images of diatom frustules as well as the glass images. The results were plotted versus the analyte concentration as shown in Fig. 3(a). Figure 3 (b) shows the representative fluorescence images at those concentrations, which clearly highlights the enhanced fluorescence emission from the diatom biosilica due to the photonic crystal effect and surface effect. As can be seen in the figures, the fluorescence intensity on frustule is at least 2× higher than that on glass and validates the use of frustules for enhancing the fluorophore's signals.</p><p>Description of the fluorescence enhancing mechanism of frustules is explained in the Supporting Information. Using this average fluorescence analysis, NT-proBNP concentration of 100 pg/mL is distinct since the signal is clearly above the error bar of the negative test (zero analyte concentration). However, for lower concentrations of analyte testing, the fluorescence signals are comparable to the error bar of the negative test, making it difficult to differentiate. A more sophisticated method of analysis is required to achieve better sensitivity and quantization.</p><!><p>While the average intensity analysis is simple and straightforward, the calibration curve is nonlinear with large variation, either with or without diatom frustules, resulting in a high limit of detection. Random errors during the immunoassay process and the statistical nature of fluorescence emission are the main causes of the error bars, which are intrinsic to the fluorescence imaging immunoassay. More advanced statistical analytical methods must be employed to improve the sensing performance.</p><p>Statistical regressions were performed using spatial domain images as well as the PSD of the spatial frequency domain images of preprocessed diatom images. Figure 4(a) shows the spatial frequency domain images from the preprocessed diatom images. The central peak relates to the zero-frequency component of the zeroed-out background and the points in the image further from the center represent higher frequency components of the diatom fluorescence image. The spike lines radiating from the center represent fluorescence signals in the spatial domain corresponding to the geometric feature of diatom frustules. For example, the minor axis of the diatom in the spatial domain is represented by the prominent line radiating from the center of the spatial frequency domain image along the same axis.</p><p>The aim of the regression is to correlate the fluorescence intensity and the analyte concentration. Optimal results were achieved by implementing PCA feature extraction with PLSR. Comparing the regression results applied to the spatial and spatial frequency domain images, spatial frequency domain images gave superior results and were thus used in this analysis. This may be due to the fact that the intensity variation among different concentrations in the spatial domain is slight, as seen in Fig. 3(a). However, the spatial frequency domain is a more detailed image space and is heavily influenced by changes in the spatial domain. The slight change in fluorescence intensity in the spatial domain results in a much greater change in the spatial frequency domain. PCA and PLSR rely on variation to differentiate analyte concentrations and thus the greater change in the spatial frequency domain allows for greater sensitivity of PCA and PLSR.</p><p>The number of PCs to include in the regression step affects the quality of the model achieved. We swept the number of components to include and compared their R2 values. This analysis is shown in our Supporting Information. Optimal results were achieved using the first three PCs and the training data are plotted in Fig. 4(b). The PLSR algorithm creates a model which can then be applied to a test set. As explained in section 2.3, a 5-fold cross-validation was performed by training a model using 80% of the images and testing that model on the remaining 20% images. This allows verification of the utility of our model for future quantification. The calculated calibration curve from the training set was applied to the test dataset. The calibration fit, as well as that obtained when validating the model, are shown in Fig. 4(c) below. Applying this model to the test dataset, we achieved good linearity with a R2 testing value of 0.86 and a predicted RMSE (RMSEP) of 14.47. The high R2 value and the low RMSEP indicate accurate quantifications of NT-proBNP detection down to 19 pg/mL.</p><!><p>In real-world applications, the detection of NT-proBNP is performed in a real biological fluid with competing biomolecules like proteins that can obscure the signal. To prove the validity of our photonic crystal-enhanced fluorescence imaging immunoassay for future clinical usage, we performed the detection of NT-proBNP in human plasma. A qualitative classification screening was performed to determine the clinically relevant level of high or low concentration of NT-proBNP. According to the literature (Januzzi et al. 2005; Ponikowski et al. 2016), if the NT-proBNP concentration is below 125 pg/mL, it can be used to "rule out" heart failure. If the concentration is above 450 pg/mL, it can be used to "rule in" heart failure. For this classification, we combined measurements made at 10 and 50 pg/mL to be considered a low concentration class and measurements made at 500 pg/mL was a high concentration class. To ensure the same number of measurements were in each category, 50 images, with average intensities closest to the mean average intensity, were selected from each lower concentration. From the higher concentration, 100 measurements were taken, again, with average intensities closest to the total average intensity at this concentration.</p><p>The classification analysis was performed using PCA feature extraction combined with two classification techniques which were compared to find the best solution. The kNN and SVM are classification techniques that have been applied to both fluorescence imaging and spectroscopy biosensing (Kurachi et al. 2008; Moshou et al. 2014; Zhang et al. 2007). kNN is a non-parametric classification method. An unlabeled test sample is classified by a majority vote of its k-nearest neighbors and the most frequent label is assigned to the class of the output. SVM algorithm is a widely used supervised learning method which can efficiently perform a non-linear classification using the nonlinear kernel function and fitting the maximum-margin hyperplane in a transformed feature space.</p><p>The two classification algorithms were applied after PCA of the spatial frequency domain images and parameters were swept to find the optimal solution for each algorithm. A 5-fold cross-validation was again performed to enable training of the model and testing. The parameters for SVM were optimized and the results are shown in Fig. 5: (a) is the classification results from the training dataset and (b) is from the test dataset. Both are plotted with respect to the first three PCs. The color of each data point represents its actual concentration class and each point with an "X" represents measurements that were incorrectly classified.</p><p>From these classifications, the accuracy, sensitivity, and specificity were calculated as explained in Section 2.4 above. These are common metrics that indicate the quality of the classification model where the closer to 1 (but less than 1), the better the classification model. The calculated metrics for the optimal solution for each classification technique were obtained from each of the five cross-validations. The metric averages and standard deviations are displayed in Table 1 and the two classification methods were compared. It was found that using SVM with enough PCs to account for 55% of the sample variation gave the best results.</p><p>As can be seen above, the SVM model has a predictive accuracy and sensitivity that are slightly lower than desired. However, the specificity, of 93%, is excellent. The specificity is a measure of the model's ability to correctly classify negative measurements, in this case, the model can successfully determine low concentrations of NT-proBNP. As can be seen in Fig. 5 above, very few low concentration measurements were classified inaccurately. This allows us to confidently classify low concentration samples and rule out the heart failure diagnosis. While this is extremely useful, in our future work, we will continue to improve the sensitivity to allow for better ruling in of heart failure.</p><!><p>NT-proBNP is a clinically important cardiovascular disease biomarker. A photonic crystal-enhanced fluorescence imaging immunoassay biosensor has been created for this analyte, capable of detecting clinically relevant levels of NT-proBNP. Photonic diatom frustules achieve fluorescence signal intensity enhancement of fluorophores as high as 2× compared with those on the flat glass substrate. Furthermore, using PLSR, a predictive model has been extracted and validated on a test dataset showing excellent linearity with a R2 of 0.86 and a RMSEP of 14.47. This model can be applied to an unknown measurement and quantify the analyte concentration far surpassing the clinical detection requirement, with an excellent measurement accuracy. To prove the potential for clinical testing, the biosensor was employed to screen NT-proBNP in human plasma and we were able to successfully implement SVM classification with an excellent test specificity of 93% to rule out heart failure with further optimization being done to improve its ability to rule in heart failure. In short, we have successfully shown that diatom frustules can be used as fluorescence imaging immunoassay platform to detect NT-proBNP. The statistical regressions and classifications we have developed can be used for the detection and classification of NT-proBNP levels. This easy-to-use and cost-effective immunoassay can achieve clinically relevant levels of detection while avoiding the complexity of current ECL method of detection.</p>

PubMed Author Manuscript

Polymorphism, Structure, and Nucleation of Cholesterol·H2O at Aqueous Interfaces and in Pathological Media: Revisited from a Computational Perspective

We revisit the important issues of polymorphism, structure, and nucleation of cholesterol·H2O using first-principles calculations based on dispersion-augmented density functional theory. For the lesser known monoclinic polymorph, we obtain a fully extended H-bonded network in a structure akin to that of hexagonal ice. We show that the energy of the monoclinic and triclinic polymorphs is similar, strongly suggesting that kinetic and environmental effects play a significant role in determining polymorph nucleation. Furthermore, we find evidence in support of various O–H···O bonding motifs in both polymorphs that may result in hydroxyl disorder. We have been able to explain, via computation, why a single cholesterol bilayer in hydrated membranes always crystallizes in the monoclinic polymorph. We rationalize what we believe is a single-crystal to single-crystal transformation of the monoclinic form on increased interlayer growth beyond that of a single cholesterol bilayer, interleaved by a water bilayer. We show that the ice-like structure is also relevant to the related cholestanol·2H2O and stigmasterol·H2O crystals. The structure of stigmasterol hydrate both as a trilayer film at the air–water interface and as a macroscopic crystal further assists us in understanding the polymorphic and thermal behavior of cholesterol·H2O. Finally, we posit a possible role for one of the sterol esters in the crystallization of cholesterol·H2O in pathological environments, based on a composite of a crystalline bilayer of cholesteryl palmitate bound epitaxially as a nucleating agent to the monoclinic cholesterol·H2O form.

polymorphism,_structure,_and_nucleation_of_cholesterol·h2o_at_aqueous_interfaces_and_in_pathological

Introduction<!>Density Functional Theory (DFT) Optimization of the Triclinic Polymorph of Cholesterol·H2O<!><!>DFT Optimization of the Monoclinic Crystal Structure of Cholesterol·H2O<!><!>DFT Optimization of the Monoclinic Crystal Structure of Cholesterol·H2O<!>Comparison of the Two Computed Cholesterol·H2O Polymorphs with Experiment<!><!>Comparison of the Two Computed Cholesterol·H2O Polymorphs with Experiment<!><!>Comparison of the Two Computed Cholesterol·H2O Polymorphs with Experiment<!>Structure of Monoclinic Cholesterol·H2O on Early Growth and Its Preference as a Single Bilayer<!>Generality of the Ice-Like Motif in Sterol Crystal Structures Embodying the 10 × 7.5 Å2 Motif<!><!>Generality of the Ice-Like Motif in Sterol Crystal Structures Embodying the 10 × 7.5 Å2 Motif<!><!>Model of Induced Nucleation of Monoclinic Cholesterol·H2O via a Bilayer of Cholesteryl Palmitate<!>Cholesteryl Esters<!>Model of Induced Nucleation of Monoclinic Cholesterol·H2O via a Bilayer of Cholesteryl Palmitate<!><!>Transformation from the Monoclinic to the Triclinic Form of Cholesterol·H2O<!>Conclusions<!>Structure Construction<!>DFT Calculations<!><!>Accession Codes<!>

<p>Cholesterol, the most abundant sterol in mammalian cells, is a vital component of cell membranes and is essential for cell viability.1 The cholesterol molecule consists of one hydroxyl group attached to a rigid steroid tetracyclic moiety, terminating with a flexible hydrocarbon chain (Scheme 1A).2 Cholesterol is practically insoluble in water. In biological systems, it is mostly solubilized by incorporation in lipid membranes, bile salts, or with lipoproteins in the blood. In cells, most of the cholesterol is located in the plasma membrane,3 where the hydrophobic region is embedded alongside the fatty-acid chains of lipids (Scheme 1B), and the hydroxyl group points towards the water molecules surrounding the membrane.</p><p>High levels of cholesterol are, however, pathological. They may result in the formation of two-dimensional (2D) crystalline cholesterol domains in cell membranes (Scheme 1B) and ultimately in the precipitation of cholesterol monohydrate crystals.4,5 The precipitated cholesterol crystals can hardly be dissolved and therefore accumulate, leading to an increased inflammatory response and severe damage to the tissue.5−7 An unfortunate yet common outcome of this cholesterol deposition is atherosclerosis,8−10 a major cause of cardiovascular diseases and stroke.</p><p>The crystal structure of cholesterol·H2O was determined by Craven only as late as 1976,4 possibly due to its complexity: the space group is triclinic P1, with eight independent cholesterol·H2O units per cell, each containing 29 non-hydrogen atoms. We note, nonetheless, that the crystal structure has a high pseudo-symmetry, which was taken advantage of by Craven for structure determination.11 The habit of these cholesterol·H2O crystals is usually rhomboid plates, by virtue of the crystal pseudo-symmetry and the layer-like molecular packing of cholesterol.</p><p>A different cholesterol·H2O polymorph with a monoclinic structure was identified in cholesterol nucleation from monolayers and multilayers at the air–water interface.12,13 In this process, although the final multilayer structure is generally triclinic, the two leaflets of the first formed cholesterol bilayer are always related by a twofold screw symmetry in a 10 × 7.5 Å2 rectangular unit cell. After its initial determination, this polymorph was also detected in supported lipid bilayers composed of lipid mixtures of cholesterol with phosphoglycerolipids and sphingolipids.14−17 Two-dimensional monoclinic crystalline domains, formed by segregation of cholesterol from the phospholipids, can either grow into three-dimensional (3D) crystals of the monoclinic polymorph18 or transform into the triclinic polymorph.13,17 Surprisingly, the monoclinic polymorph was also identified in native bile solutions19 related to the formation of cholesterol gallstones and in an atherosclerosis-related cell culture model,20 highlighting its possible relevance to cholesterol crystallization in a biological lipid-rich environment, such as that found in cell membranes and bile.</p><p>The three-dimensional structure of the monoclinic polymorph was determined making use of thin cholesterol films ranging from 1 to 3 bilayers, in a study on the nucleation of cholesterol at the air–water interface.12 Their structures were characterized via synchrotron grazing incidence X-ray diffraction (GIXD), a method that has been applied to molecular assemblies of crystalline films.21,22 The single bilayer of cholesterol is of space-group symmetry p21, namely the two leaflets are related by twofold screw symmetry.11 The space group of the three bilayer film, with unit cell dimensions a = 10.2 Å, b = 7.6 Å, c = 68.2 Å, and β = 94.8°, was shown to be monoclinic A2 in a structure determined to near-atomic resolution.13 Details on the space group and structure elucidation at its basic level are presented in the Supporting Information S1. The X-ray structure refinement, based on the intensities of 48 (hkl) reflections, yielded a satisfactory fit between the observed and computed X-ray structure factors (Figure S1.2), indicating an overall correct structure,13 but clearly further refinement is called for in view of the structural assumptions made. Indeed, the H-bonded bilayer sandwiched between cholesterol bilayers shall be shown, in the present study, to have been ill-determined.</p><p>Beyond the ambiguous structural details, it is unclear why under some biological and/or chemical conditions, cholesterol grows as the monoclinic polymorph to form 3D structures,18−20,23 whereas under other conditions transformation into triclinic plates occurs at an early stage.13,17 Understanding this process should be relevant for clarifying critical stages in the pathological crystallization process.</p><p>We address these challenges by performing a comprehensive first-principles computational study of both crystal polymorphs of cholesterol·H2O, in particular that of the monoclinic form. We obtain a new, fully extended H-bonded network comprising sterol hydroxyl groups and water molecules in a structure akin to that of hexagonal ice. We show that the energy of the monoclinic and triclinic polymorphs is similar, strongly suggesting that kinetic and environmental effects play a significant role in determining polymorph nucleation. Furthermore, we find evidence in support of various O–H···O bonding motifs in both polymorphs that may result in structural disorder. We then rationalize what we believe is a single-crystal to single-crystal transformation of the monoclinic polymorph, on increased interlayer growth beyond that of a single cholesterol bilayer interleaved by a water bilayer. We are also able to explain why, as a single hydrated bilayer, cholesterol crystallizes in the monoclinic form rather than in its triclinic counterpart. We show that the ice-like structure is also relevant to the related cholestanol dihydrate (2H2O) and stigmasterol monohydrate (H2O) crystals. Finally, we posit a possible role for cholesterol esters in the crystallization of cholesterol·H2O in pathological environments, with a composite of a bilayer of cholesteryl palmitate bound epitaxially as a nucleating agent to the monoclinic form of cholesterol·H2O.</p><!><p>We begin our investigation with a dispersion-augmented DFT optimization of the known triclinic structure of the cholesterol·H2O crystal (Figure 1). As a starting point for geometry optimization, we use the structure originally determined by Craven,4,11 based on the computational refinement of this structure by Frincu et al.,24 in which sterol and water H atoms were introduced. There are, however, seven additional ways, beyond the motif originally reported by Frincu et al.,24 in which the O–H···O bonds may be arranged in the H-bonding layer. In all arrangements, the basic H-bonding motif is composed of four octagons and four tetragons (Figure 1C1), but they differ in the relative orientation of the water molecules and the cholesterol OH group (see Figure S2 for a detailed view of all arrangements). Therefore, crystal structure optimization was performed for all eight structures, with the optimized structural parameters reported in Table S2.1 and average O···O H-bond distances listed in Table S2.2. Computed total energies for the proposed structural motifs, relative to the lowest energy motif (which is found to be different from that of Frincu et al.24), are given in Table S2.3. Importantly, all eight H-bonding networks result in very similar energies, suggesting that the crystal structure may be composed of a disordered mixture of them. Furthermore, this structural disorder view agrees well with Craven's report,4 in which the H atoms participating in the H-bonded network were not found in electron density maps and were therefore not included in the X-ray structure factor calculations. Therefore, Figure 1C2 presents the disordered-mixture arrangement of the hydrophilic region for these eight H-bonding networks, with the partial occupation indicated by partial coloring of pertinent atoms.</p><!><p>Packing arrangement of triclinic cholesterol·H2O, viewed along the: a-axis (A), b-axis (B), and c-axis (C1,2). In (C1,2), the packing arrangement is limited to the hydrophilic region indicated in A. The atoms are color-coded in white, H; brown, C; and red, O. The different H-bonded rings in panel C1 are labeled in grey by ri and Ri, which refer to tetragons and octagons, respectively; the subscript i = 1···4 designates the unique polygons of each type. The arrangement in all panels, except for C2, is for the lowest energy pseudopolymorph of the triclinic cholesterol·H2O. The C2 panel arrangement is of the hydrophilic region of the disordered mixture of eight H-bonding networks with partial occupation indicated by partial coloring of pertinent atoms in white. Exclusively in C2, H atoms are colored in grey to avoid confusion with the color code used for partial occupation. OH···O bonds are represented as grey dashed lines. The unit cell is delineated by a black rectangle.</p><!><p>To extend our investigation to the structure of the monoclinic cholesterol·H2O polymorph, which incorporates the 10 × 7.5 Å2 bilayer motif, we based our initial model on the structure reported by Solomonov et al.,13 with H atoms introduced to the cholesterol and water molecules. The obtained structure has eight cholesterol molecules in the unit cell, as shown in Figure 2A,B1, and contains two nonequivalent molecules per asymmetric unit (labeled A and B in Figure 2B2). The c axis, which is ∼70 Å long, contains two cholesterol bilayers related by the twofold screw (21) symmetry, whereas the two cholesterol leaflets in each bilayer are related by the twofold (2) symmetry.</p><!><p>Packing arrangement of the monoclinic cholesterol·H2O unit cell, viewed along the: a-axis (A), b-axis (B1,2), and c-axis (C0,1,2) for the hydrophilic region indicated in (A). For panels (A,B1,C0,C1) the H, C, and O atoms are color-coded in white, brown, and red, respectively. Panels (B2,C2) present similar views as (B1,C1), respectively, but with different colors representing different symmetry-unrelated cholesterol and water molecules: grey, cholesterol molecule A (mol. A); orange, cholesterol molecule B (mol. B); and blue (W1) and green (W2), water molecules. The twofold and twofold screw symmetry axes are shown in black. Given that the exocyclic moieties of the non-symmetry related molecules A and B are part of a pseudo C-centered arrangement (see main text), the row of twofold axes along a are interleaved by pseudo twofold screw axes (indicated by black and white stripes). The hexagonal H-bonded rings in panel C2 are labeled by R1 and R2. The arrangement in all the panels except for C0 is for the lowest energy pseudopolymorph of the monoclinic cholesterol·H2O. The C0 panel arrangement is of the hydrophilic region of the disordered mixture of the three most stable H-bonding networks, with partial occupation indicated by partial coloring of pertinent atoms. Exclusively in C0, H atoms are colored in grey to avoid confusion with the color code used for partial occupation. OH···O bonds are represented as grey dashed lines. The unit cell is indicated by a black rectangle.</p><!><p>In order to construct a favorable H-bonding network composed of (cholesterol)-OH and H2O molecules in a 1:1 molar ratio, we need to modify the orientation in which the H atoms were originally introduced. To that end, we utilized a model that uses symmetry-related positions of the two asymmetric sterol O atoms, which belong to opposite leaflets of the bilayer (see Supporting Information, S3). These O atoms are separated by ∼3 Å and H-bonded to each other to generate the positions of the symmetry-related water O atoms (Figure S3). This model generates a hexagonal bilayer arrangement of O–H···O bonds, as in hexagonal ice, albeit distorted.</p><p>For dispersion-augmented DFT optimization based on the above motif, the monoclinic A2 unit cell was reduced to a primitive unit cell that contains half the number of molecular units. Both atomic coordinates and unit cell parameters were then fully optimized.a Finally, the conventional A2 unit cell was reconstructed from the global minimum solution, and the optimal H-bonded arrangement was found (see Methods for additional details). Overall, the computationally optimized structure of the monoclinic form given in Figure 2 is very similar to the experimentally determined one. Specifically, the overall atomic structure of the tetracyclic part of the molecules, as well as the molecular tilt relative to the (001) plane, remained essentially unaltered. Some conformational changes occur at the hydrocarbon tail.</p><p>The optimized H-bonding motif is composed of two differently shaped fused hexagons, with average O···O H-bond distances of 2.74 Å (Figure 2C2, labeled R1) and 2.87 Å (Figure 2C2, labeled R2). There are, however, three other ways in which the O–H···O bonds may be arranged by interchanging the donor and acceptor roles of the sterol oxygens and hydrogen bonding orientation of the acceptor hydrogens (see Figure S4). These three crystal structures were therefore also generated and optimized by the DFT, and their energies are listed in Table S4.1, compared to that of the first-generated motif. The optimized structural parameters thus determined are reported in Table S4.2. Two of these three H-bonding networks are almost as stable as the original motif, suggesting that the crystal structure may be composed of a disordered mixture of three H-bonding networks. Importantly, O···O H-bond lengths of these two motifs are also close to the original motif, while in the fourth motif they differ from the other three (Table S4.2). The hydrophilic region arrangement of the disordered mixture of the three most-stable H-bonding networks, with partial occupation indicated by partial coloring of pertinent atoms, is shown in Figure 2C0.</p><!><p>The total energy difference between the most stable pseudopolymorphs of the monoclinic and triclinic cholesterol·H2O, as computed using the pair-wise dispersion-augmented DFT (see Methods section), is found to be a small ∼2.25 kcal/mol per molecule, in favor of the triclinic polymorph. While the computed energy ordering is consistent with experiment, it is important to keep in mind that it is at the limit of accuracy of the computational approach.25,26 Furthermore, it may be washed out by entropic effects. Therefore, it is indeed reasonable that both polymorphs are accessible experimentally. Further gas-phase calculations of cholesterol molecules taken from the bulk (see Figure S5) reveal that the difference in energy between isolated (gas-phase) cholesterol molecules taken from the bulk of either polymorph without further relaxation is an insignificant ∼0.3 kcal/mol in favor of the triclinic form.b Therefore, the computed energy difference arises entirely from intermolecular interactions.</p><p>The optimized structural parameters of the most stable pseudopolymorphs of the monoclinic and triclinic cholesterol·H2O are given in Table 1. The results reveal that the computed lattice parameters are consistently smaller than the experimentally determined ones, such that the computed unit cell volume is smaller than the experimental one by ∼9%. This difference between experiment and theory is larger than that typically found with the pair-wise dispersion-augmented DFT for smaller, more rigid molecules (usually <3%,25,26 although larger volume discrepancies of ∼5% have been reported for flexible molecules).26 To test whether this is a consequence of the level of theory used, we performed further optimization using the more advanced many-body dispersion (MBD) approach, with27 and without28 non-local corrections (see Methods section), for the monoclinic polymorph. This, however, did not result in any significant improvement of agreement with the experiment (see Table S6).</p><!><p>Experimental parameters for these two forms were taken from Craven4 and Solomonov et al.13 We compare them to the corresponding lowest energy H-bonding motifs optimized by the DFT.</p><!><p>An alternative explanation for this discrepancy is that the exocyclic moiety of cholesterol in the monolayer at the air–water interface,12 as well as in the triclinic polymorph of cholesterol·H2O, is characterized by large thermal motion at room temperature.4,11 Specifically, the proposed trigonal lattice symmetry and packing arrangement of the cholesterol crystalline monolayer on water12 have been rationalized in terms of pronounced libration about the long molecular axis. This molecular motion is high enough to exclude the contribution of the exocyclic hydrocarbon moiety to the Bragg rod intensity profile as measured by GIXD.12 As for the thermal motion of the eight cholesterol molecules in the triclinic monohydrate,11 the ratio between the average atomic displacement parameter (ADP) of the flexible exocyclic group and of the rigid cyclic system is 2.5, with a maximum ratio of 4. Thus, libration of the molecule around its long axis, coupled with motion of the exocyclic hydrocarbon moiety, may induce increased intralayer packing distances in the monoclinic and triclinic polymorphs. In this view, the discrepancy between the theory and experiment then arises mostly from the comparison of room temperature experimental data with 0 K computational data. Theoretically, such thermal effects can be tested within DFT using first-principles molecular dynamics.29 However, for the large unit cells studied here, this would be prohibitively expensive. Instead, we address the issue from the experimental perspective by comparing the computed data against (hkl) (111) and (200) d-spacings, which are deduced from the electron diffraction (ED) measurements of Weihs et al.,19 corresponding to a temperature of 90 K, and from the GIXD data of Solomonov et al.13 taken at 278 K. Overall, this comparison, summarized in Figure 3 and Table S7, shows a reduction of ∼3.0–5.5% in the d-spacing with decreasing temperature. While a detailed temperature dependence is not available experimentally, this reduction in d-spacing is consistent with the difference between the theory and experiment.</p><!><p>Temperature dependence of the d-spacing of monoclinic cholesterol·H2O measured by electron diffraction (ED)19 and grazing incidence X-ray diffraction (GIXD)13 and compared to calculations at the PBE-TS level of theory.</p><!><p>We note that we have also compared the theoretical growth morphologies of the triclinic and monoclinic structures, determined using interatomic potential energy computations. The method and results are given in the Supporting Information (S8) and again reveal, by and large, a match to those of the observed morphologies of crystals grown in solution.</p><p>Taken together, the above comparison validates the computational approach, such that we can draw new insights from further calculations.</p><!><p>The two cholesterol leaflets are related by twofold screw symmetry for a single bilayer at the air–water interface or else hydrated at both sides of the film. However, as a triple bilayer crystal on the water surface, the cholesterol leaflets, in contact via their hydrocarbon tails, are related by twofold symmetry.13 At first sight, this is surprising since, in general, the twofold screw symmetry element lends itself to better molecular packing than the twofold symmetry.30</p><p>To rationalize this observation, we generated a series of hypothetical bulk P21 crystal structures of cholesterol·H2O (Figure S9.1) by first replacing the twofold axes of the A2 polymorph with twofold screw axes. This change in the space group was followed by offsetting adjacent cholesterol bilayers along the a-axis but maintaining the original H-bonded bilayer system, across which the corresponding cholesterol layers are related by the twofold screw symmetry. The DFT-computed energy profile of this series of generated crystal structures (Figure S9.2) revealed that the crystal structure with no offsetting of the adjacent cholesterol bilayers along the a-axis is the most stable. We then compared this hypothetical bulk P21 structure of cholesterol·H2O, after relaxation, with the above-obtained A2 polymorph. The comparison shows an energy difference between the two structures, at the MBD level of theory, of ∼1 kcal/mol per molecule in favor of P21. Note that the computations correspond to the structures at 0 K, such that this small difference is of the order of the energy associated with thermal fluctuations at room temperature. This consideration suggests that temperature may be a determining factor in the preferred stability of the A2 motif at room temperature. This preference is consistent with the crystal structure of stigmasterol monohydrate, which crystallizes at room temperature in the monoclinic P21 motif (a = 10.27 Å, b = 7.63 Å, c = 35.39 Å, and β = 94.4°).31 The exocyclic moiety of this sterol (see Figure S13A) contains a >C=C< double bond that makes it less flexible than the exocyclic group of cholesterol, which is in turn responsible for the contact between layers of the two non-symmetry-related cholesterol molecules A and B (see Figure 2B2). The vector distance between the centers of mass of the (terminal) atoms of the exocyclic moieties of molecules A and B is very close to 0.5(a + b) (Table S10.2), namely, it is a property of a pseudo C-centered arrangement of exocyclic groups. Therefore, the exocyclic groups make interlayer contact via a combination of alternating twofold (2) and pseudo twofold screw (21) axes along the a-axis, as shown in Figure 2B2. It is also noteworthy that in the cholesteryl ester crystal structures, which incorporate the monoclinic 10 × 7.5 Å2 motif, both types of cholesterol bilayer arrangements, namely interlayer contact via twofold or twofold screw symmetry, have been observed (see Table 6.1 in ref (2)).</p><p>The next question to examine concerns the energetics of a single cholesterol bilayer, because the symmetry of this bilayer at the air–water interface or hydrated at opposite sides is p21, as is also the trilayer of the stigmasterol hydrate.12 We therefore generated a bilayer in which the two leaflets are related by twofold screw symmetry, as opposed to a twofold axis (Figure S11A,B). The computed energy difference between both relaxed structures in vacuum of the p21 bilayer, compared to the bilayer with the original p2 symmetry, at the MBD level of theory, was found to be ∼0.85 kcal/mol per molecule, with p21 being consistently more stable.</p><p>The computed stability of the p21 cholesterol bilayer prior to growth beyond the single bilayer agrees with the experiment and our deduction of a single-crystal to single-crystal transformation on further growth beyond the first cholesterol bilayer. This change essentially involves an interlayer shift of b/2 such that the two cholesterol leaflets become related by twofold instead of twofold screw symmetry. This transition is consistent with the similarity of the Bragg rod data of the one, two, and three cholesterol bilayer films at the air–water interface (see Figure S1.1).</p><p>Finally, we tackled the question of why, as a hydrated single cholesterol bilayer, the monoclinic p21 form is always observed, as opposed to a single bilayer of the triclinic p1 counterpart (Figure S11C). The energy difference between the p21 and p1 structures in vacuum upon relaxation at the MBD level of theory is insignificant, at ∼0.15 kcal/mol per molecule in favor of the triclinic p1 polymorph. This result suggests that the observed preference for the monoclinic polymorph is not dictated by differences in the properties of the bilayer as such, but rather by hydration.</p><!><p>Clearly, the identification of an ice-like motif (Figure 4A) plays a major role in the above considerations for the monoclinic polymorph (Figure 4B). This arrangement is quite distinct from the hydrogen-bonded network in the triclinic system (Figure 4C), although in both each oxygen atom participates in three H-bonds of a proton-disordered network. The ice-like network can be rationalized in view of a partial lattice and stereochemical match to that of hexagonal ice. Specifically, the monoclinic motif incorporates a pseudo-centered 7.5 × 5 Å2 sub-lattice. Indeed, ice nucleation was promoted via monolayers of long-chain aliphatic alcohols, which are packed in a two-dimensional 7.5 × 5 Å2 lattice and whose OH groups are also arranged in a (pseudo) centered cell,32,33 as in the layer structure of hexagonal ice itself. It is therefore important to examine whether the above-suggested ice-like motif is unique to the monoclinic structure of cholesterol·H2O or is more general.</p><!><p>Views of the H-bonded bilayers of cholesterol·H2O and cholestanol·2H2O. Top and side views of (A) Hexagonal H-bonding bilayer in the structure of hexagonal ice, in which the O–H···O bonds are proton disordered36 and (B) disordered mixture of the three most stable H-bonding networks of monoclinic cholesterol·H2O. (C) Disordered mixture of the 8 H-bonding networks of triclinic cholesterol·H2O. (D) Model H-bonded network of cholestanol·2H2O. Also shown is a drawing of cholestanol·2H2O crystals taken from the PhD thesis of D. Hodgkin (1937),34 reproduced by permission of the Hodgkin family. The two crystals are elongated, twinned about the [010] direction, and show mainly the (001) face with minor (100), (010), and (110) side faces. The C and O atoms are color-coded brown and red, respectively, with partial occupation indicated by partial coloring of pertinent atoms. In panels (A–C), H atoms are colored in grey to avoid confusion with the color code used for partial occupation.</p><!><p>The 10 × 7.5 Å2 monoclinic motif is predominant in the two- and three-dimensional crystals of various sterols.13 Indeed, the 10 × 7.5 Å2 axial system is also found in the cholestanol·2H2O34,35 crystal, a close relative of cholesterol. In particular, the unit cell of cholestanol dihydrate, reported in the Ph.D. thesis of D. Hodgkin34 to be of triclinic P1 symmetry, can be transformed to a pseudo A2 cell similar to that of monoclinic cholesterol·H2O but with a c-axis longer by approximately 6 Å, which is consistent with a double ice-like bilayer (Table 2).32,33 To test this, we generated a model packing by inserting two additional H-bonded bilayers to the monoclinic structure of cholesterol·H2O, converting cholesterol to cholestanol, and optimizing the crystal structure by the DFT. A stable structure with A2 symmetry and dimensions close to the experiment (Table 2) were indeed found, lending further substantial support to the suggested ice-like structure and demonstrating its generality. The H-bonding motif and drawings of the crystal shape of cholestanol·2H2O are given in Figure 4D, with the energy-minimized structure provided in Figure S12.</p><p>We note that the ice-like motif also occurs in the three-dimensional crystal structure of stigmasterol·H2O31 alluded to above (Figure S13C) and, in all probability, in the trilayer film of stigmasterol hydrate (a = 10.2 Å and b = 7.7 Å, p21), as suggested in Figure 5. The results of a GIXD12,37 characterization of such a stigmasterol trilayer formed at the air–water interface are shown in Figure S14.</p><!><p>Model of the trilayer packing arrangement of stigmasterol hydrate on a water surface, based on an analysis of GIXD measurements thereof12,37 (Figure S14), on the sigmasterol·H2O crystal structure31 (Figure S13B,C), and on the model structure of cholestanol dihydrate (Figures 4D and S12). The trilayer structure viewed along the a-axis incorporates an ordered layer of water molecules whose ice-like hydration structure is probably a double bilayer similar to cholestanol dihydrate. Both structures embody the 10 × 7.5 Å2 monoclinic 21 motif.</p><!><p>Last but not at all least, we finally address the possible relevance of our results to the nucleation and growth of cholesterol crystals in atherosclerosis. In addition to cholesterol crystals, most atherosclerotic plaques develop calcifications of apatite (calcium phosphate) crystals. Lonsdale published a paper in 196838 in which she laid out possible epitaxial matches and, consequently, epitaxial growth of crystals in gallstones. Could the same apply to atherosclerosis? We consider here the possibility that epitaxy may play a role in the nucleation of cholesterol monohydrate crystals, not in relation to apatite, but to cholesteryl esters. Cholesterol crystal deposition occurs in atherosclerosis when cholesterol reaches super-saturation in the lipid environment because of the accumulation of unesterified cholesterol following hydrolysis of cholesteryl esters. The hydrolysis of cholesteryl esters is associated with the breakdown of lipid bodies inside lysosomal compartments or at extracellular locations following cell death.8,39,40 The major cholesteryl esters found in atherosclerotic lesions are cholesteryl palmitate, oleate, and linoleate5,41 (Scheme 2). Of these three molecules, the palmitate crystallizes in the rectangular 10 × 7.5 Å2 cholesterol-type monoclinic motif (as does the related myristate derivative, see Supporting Information S1); a crystal structure of the linoleate has not been reported, perhaps because of its doubly unsaturated chain; the oleate derivative has a crystal structure with no resemblance to that of monoclinic cholesterol·H2O.42</p><!><p>The palmitate derivative has a saturated aliphatic chain (C16H31); the chain of the oleate derivative (C18H33) contains a C=C double bond with a cis configuration; the linoleate has a chain (C18H31) with two C=C double bonds, both with the cis configuration.</p><!><p>According to surface pressure–area isotherms and grazing incidence X-ray diffraction measurements, cholesteryl tridecanoate (C13H25), palmitate (C16H31), and stearate (C18H35), each containing saturated aliphatic chains, self-assemble into crystalline single bilayer films in a unit cell of 10 × 7.5 Å2 at the air–water interface, where the two layers are interdigitated across their hydrocarbon ester chains.43 The cholesteryl moieties of the bilayer form a structure akin to the layer of cholesterol molecules in its monoclinic polymorph. Given the ease with which cholesteryl palmitate forms a single crystalline bilayer at the air–water interface,43 we propose a model by which the palmitate derivative forms a crystalline interdigitated bilayer inside lipid bodies or lysosomal compartments and acts as a nucleating agent of the monoclinic cholesterol form. We therefore set out to examine, by DFT, the possibility of epitaxial nucleation of cholesterol·H2O onto the cholesteryl surface of a cholesteryl palmitate bilayer. Making use of the crystal structure of cholesteryl myristate,44 we have been able to construct a model of the packing arrangement of a bilayer of cholesteryl palmitate, bound epitaxially as a nucleating agent to the monoclinic form of cholesterol·H2O (Figure 6). We have been able to converge this structure to atomic forces smaller than 10–2 eV/Å, meaning that it is at least locally stable, thereby lending support to the model hypothesis.</p><!><p>Simulation of a composite crystal in which the cholesteryl palmitate interdigitated bilayer is epitaxially bound to monoclinic cholesterol molecules across twofold axes. As a bilayer, cholesteryl palmitate is found to be sufficiently stable and could therefore nucleate the monoclinic crystals of cholesterol·H2O by epitaxy.</p><!><p>The different stages of cholesterol formation at the air–water interface are depicted in Figure S15. The final cholesterol transformation from monoclinic A2 to triclinic P1 space group symmetry, involving a lattice change from 10 × 7.5 Å2, γ = 90° to 12.4 × 12.4 Å2, γ = 101° has been modeled as a single-crystal to single-crystal layer transition, at least in its initial stages.13 Experimentally,12−16 for a single bilayer of cholesterol hydrated at both sides, the monoclinic p21 arrangement is more stable. Computationally, this bilayer is as stable as that of the triclinic p1 form, which suggests that hydration tips the balance in favor of the monoclinic bilayer. The unit cell of the triclinic polymorph contains eight non-symmetry-related molecules with essentially four different exocyclic group conformations, whereas the monoclinic structure contains two symmetry-unrelated cholesterol molecules with different conformations of their exocyclic moieties. Therefore, the greater stability of the triclinic polymorph at room temperature may be explained in terms of it having more degrees of freedom than the monoclinic polymorph to accommodate the large thermal motion of the exocyclic groups. In principle, such contributions to entropic stabilization can be addressed quantitatively based on a calculation of vibrational modes. Unfortunately, the computational cost of this calculation is at present prohibitive.</p><p>We may also address the greater stability of the triclinic polymorph via a different route by comparing the crystal structures of the monohydrates of cholesterol and stigmasterol and their thermal characteristics. As already discussed, stigmasterol, even in its early stage of formation of a trilayer on water, forms a monoclinic p21 structure analogous to the monoclinic A2 form of cholesterol. On further growth, stigmasterol retains its original 10 × 7.5 Å2 unit cell and space group, unlike the cholesterol monohydrate, which undergoes a transformation to a triclinic P1 cell. The atomic displacement parameters (ADPs) of the exocyclic group of stigmasterol appear to be about twice as large as those of the rigid steroid fragment, according to Figure 6b in ref (31). We suggest that the exocyclic moiety of cholesterol is more flexible than the corresponding group of stigmasterol that, as mentioned above, contains a rigid >C=C< system in order to pack effectively in the triclinic unit cell.</p><p>Importantly, 2D crystals of cholesterol bilayers, hydrated on both sides and segregating from mixed bilayers with phospholipids, always appear in the monoclinic polymorph.14−17 The monoclinic form segregated from mixed bilayers with phospholipids eventually transforms into the triclinic polymorph.17 The rate of transformation between the polymorphs depends on the phospholipid environment.23,45 Thus, as an example, only macroscopic 3D triclinic crystals are observed associated with sphingomyelin-containing mixed bilayers, whereas initial monoclinic crystals are retained and developed when they are formed from DPPC-containing mixed bilayers.18,23 Monoclinic helical crystals formed from solutions with bile acids are also relatively long-lived before transformation to the more stable triclinic polymorph.19 Helical triclinic crystals of cholesterol have also been characterized by synchrotron X-ray diffraction, yielding unit cell dimensions similar to that of the thermodynamically stable polymorph of cholesterol·H2O but with a c axis three times as long.46 In the above systems, the lipid environment determines the rate of transformation. Therefore, while cholesterol crystals found in atherosclerotic plaques were exclusively identified as the triclinic polymorph,5,47 it stands to reason that they could have formed as monoclinic crystals, having had years to transform prior to extraction. In this respect, we note that a model has been presented above for the induction of the monoclinic form via an epitaxial fit to a bilayer of cholesteryl palmitate, a molecule present in atherosclerotic lesions. The abundance of needle-like crystals in mature plaques is tantalizing in suggesting that this needle-like morphology may be a vestige of the initial formation of crystals in the monoclinic polymorph. This conclusion is further supported by the observation of monoclinic helical crystals in freshly fixed macrophage cells (the cholesterol scavengers in atherosclerosis) to which cholesterol was administered in excess.23</p><!><p>In conclusion, we presented a comprehensive computational study of the two crystal polymorphs of cholesterol·H2O, with an emphasis on the lesser-known monoclinic one. Using first-principles calculations based on the dispersion-augmented DFT, we confirmed the known features of the experimentally determined structures. Furthermore, we refined the structure of the monoclinic polymorph by obtaining a fully extended H-bonded network comprising the sterol hydroxyl groups and water molecules, in an arrangement akin to that of hexagonal ice. We further suggested that this network may exist in related structures, notably that of cholestanol·2H2O. The ice-like H-bonded network is found in the crystal structure of hydrated stigmasterol as a grown crystal and, in all probability, as a nucleus composed of three layers. The total energy of the newly refined monoclinic form of cholesterol·H2O was found to be similar to that of the triclinic one, suggesting that kinetic and environmental effects may play an important role in determining the polymorphic nucleation of cholesterol·H2O. We have also invoked the crystalline and thermal properties of stigmasterol hydrate to help rationalize the polymorphic and thermal properties of cholesterol·H2O. We have been able to rationalize a single crystal to single-crystal symmetry transformation of the monoclinic form of cholesterol·H2O on increased interlayer growth from one to several cholesterol bilayers. We have also discussed how our findings lend support to and rationalize the observation of nucleation of the monoclinic structure of cholesterol in hydrated lipid membranes, followed by transformation to the triclinic counterpart. Finally, we have found an epitaxial match between the cholesteryl surface of a single bilayer of the ester cholesteryl palmitate, which is found in atherosclerotic lesions, and the corresponding surface of monoclinic cholesterol·H2O, leading to its proposed nucleation.</p><!><p>The crystal structure of the monoclinic cholesterol monohydrate was taken from Solomonov et al.,13 with hydrogen atoms added using Materials Studio 6.1.48 The unit cell was then transformed to a primitive cell, containing half the atoms, with a single water-hydroxyl layer. We derived the primitive cell of monoclinic cholesterol using the phonopy package,49 which determines the transformation matrix from the input unit cell to the primitive one, Mp. For the monoclinic A2 unit cell, Mp based on the A2 conventional unit cell is given by:These values agree with those displayed in Table 5.1 of the International Tables for Crystallography.50 The primitive cell of cholestanol dihydrate was derived in a similar matter using the same transformation matrix.</p><p>For vacuum calculations of the p21 and p2 structures and the composite crystal, a layer of vacuum of ∼10 Å was added to terminate the periodicity in the c-axis. To study the contribution of inter- and intra-molecular forces on the molecular packing of cholesterol monohydrate crystals, isolated single cholesterol molecules of the triclinic and monoclinic polymorphs had a vacuum spacing of at least 10 Å in all three axes. The same vacuum spacing was also applied to the isolated infinite H-bonded networks, with the cholesterol C atoms connected to the cholesterol hydroxyl (OH) groups replaced with H.</p><p>Molecular structures were visualized using VESTA, a three-dimensional visualization system for electronic and structural analysis.51</p><!><p>Electronic structures, total energies, and geometries were calculated by solving the Kohn–Sham equations of DFT within the generalized gradient approximation (GGA), using the Perdew–Burke–Ernzerhof (PBE) exchange–correlation functional.52 The total energy was augmented by Tkatchenko–Scheffler van der Waals (TS-vdW) pair-wise dispersive terms.53 Most of the calculations were carried out using version 5.4.4 of the Vienna ab initio simulation package (VASP)54 plane-wave basis code,55,56 where ionic cores are described by the projected augmented wave (PAW) method.54,57 A plane wave energy cutoff of 920 eV was used in all calculations. Further calculations of the composite crystal, as well as MBD27 and MBD-NL28 based calculations, were performed using the Fritz Haber Institute ab initio molecular simulations (FHI-aims) package.58 FHI-aims is an all-electron, full-potential electronic structure code utilizing numeric atom-centered basis functions for its electronic structure calculations, which we used to speed up testing and address large system computations. We employed the "tight" settings, in which the tier 2 basis set is used for the light elements 1–10. It is considered to result in converged conformational energy differences at a level of a few meV.58 The Brillouin zone was sampled using a Gamma-centered Monkhorst–Pack k-point grid59 of 3 × 3 × 1 and 2 × 2 × 7 for the triclinic and monoclinic structures, respectively, and 2 × 2 × 8 for cholestanol dihydrate. With these numerical choices, structural parameters were found to be numerically converged to 0.01 Å. Total energies were converged to <1 meV/atom. Atomic forces in the system were relaxed to 10–4 eV/Å and stress was relaxed to 10–3 kB.</p><!><p>Details of crystal structure determination of monoclinic cholesterol monohydrate; eight H-bonding motifs of the triclinic cholesterol·H2O polymorph; generation of a H-bonding network in the monoclinic crystal structure of cholesterol·H2O; four H-bonding motifs of the monoclinic cholesterol·H2O polymorph; model structures used to study the contribution of intra-molecular forces on the molecular packing of cholesterol·H2O crystals; structural parameters of the monoclinic cholesterol·H2O optimized by DFT, compared to the experiment; temperature dependence of the d-spacing of monoclinic cholesterol·H2O; morphologies of the triclinic and monoclinic crystals of cholesterol·H2O; hypothetical P21 crystal structures of cholesterol·H2O: structure and energy profiles; atomic center of mass coordinates and the vector distance between the centers of mass of the atoms of the exocyclic moieties of molecules A and B of the monoclinic cholesterol·H2O; single cholesterol bilayers in which two leaflets are related by a twofold screw axis p21, as opposed to twofold axes p2 and p1; model for the packing arrangement of the monoclinic cholestanol·2H2O; packing arrangement of the stigmasterol·H2O; GIXD patterns and Bragg rods of the stigmasterol hydrate trilayer; and transformation of the monoclinic form on increased interlayer growth (PDF)</p><p>ja1c10563_si_001.pdf</p><!><p>CCDC 2157904–2157917 contain the supplementary crystallographic data for this paper. These data can be obtained free of charge via www.ccdc.cam.ac.uk/data_request/cif, or by emailing data_request@ccdc.cam.ac.uk, or by contacting The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK; fax: +44 1223 336033.</p><!><p>The authors declare no competing financial interest.</p>

PubMed Open Access

Catalytic Decarboxylative Radical Sulfonylation

Sulfones are not only important structural motifs in pharmaceuticals and agrochemicals but also versatile intermediates in organic synthesis. However, C(sp 3 )-sulfonyl bond formations remain underdeveloped. In this issue of Chem, Li and co-workers demonstrate that the merger of photo-organocatalysis and copper-catalysis enables the decarboxylative radical sulfonylation with organosulfinates at room temperature under redox-neutral conditions. The method leads to the improved synthesis of anti-prostate cancer drug bicalutamide and should find more important applications in drug discovery.

catalytic_decarboxylative_radical_sulfonylation

INTRODUCTION<!>RESULTS AND DISCUSSION<!>Conclusions<!>SUPPLEMENTAL INFORMATION

<p>Sulfones are ubiquitous in nature. They possess a wide variety of biological activities and thus serve as important structural motifs in pharmaceuticals and agrochemicals. For example, bicalutamide (CASODEX, AstraZeneca's blockbuster drug) is an orally active, nonsteroidal anti-androgen for the treatment of prostate cancer (Figure 1). 1,2 Certinib (Zykadia, Novartis) is a new drug approved by FDA (U.S. Food and Drug Administration) in 2014 to treat anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer. 3 Another example is oral drug apremilast (Otezla, Celgene), the only phosphodiesterase 4 (PDE4) inhibitor approved by FDA to treat active psoriatic arthritis and plaque psoriasis with an annual sales of over 1.2 billion US dollars. 4 In the meantime, sulfones are also versatile synthetic intermediates in organic chemistry. They serve as the key building blocks or reagents in many chemical transformations such as Julia-Lythgoe olefination [5][6][7] and fluoroalkylation. 8 As a consequence, the synthesis of sulfones has received a considerable attention and significant progress has been achieved in recent years. [9][10][11][12][13] However, recent advances focus mainly on C(sp 2 )-sulfonyl bond formations such as aromatic or vinylic sulfonylation, whereas C(sp 3 )-sulfonyl bond formations remain underdeveloped. Conventional C(sp 3 )-sulfonylation methods include (1) nucleophilic sulfonylation of electrophiles such as alkyl halides, epoxides, or Michael acceptors with organosulfinates or thiosulfonates under basic conditions 14 (Scheme 1A) and (2) electrophilic sulfonylation of sulfonic acid derivatives such as sulfonate esters or sulfonyl chlorides with organometallic reagents (Scheme 1B). However, the former suffers from the competing O-alkylation (to give sulfinate esters), while the latter often leads to the corresponding sulfoxides. 9 The recently developed sulfonyl radical addition to unsaturated bonds such as alkenes</p><p>The Bigger Picture Sulfones are not only important structural motifs in pharmaceuticals and agrochemicals but also versatile synthetic intermediates in organic chemistry. Despite the significant progress in the synthesis of sulfones in recent years, C(sp 3 )sulfonyl bond formations remain underdeveloped. In particular, there have been no reports to date of general methods for the sulfonylation of alkyl radicals. In this article, we introduce the copper-catalyzed cross coupling of sulfinates with alkyl radicals generated via photoredoxcatalyzed decarboxylation of redox-active esters derived from aliphatic carboxylic acids. This unprecedented protocol exhibits broad substrate scope and wide functional group compatibility, allowing the late-stage sulfonylation of complex molecules. The synthetic utility of the method is further demonstrated by the improved synthesis of anti-prostate cancer drug bicalutamide. provides a powerful means for C(sp 3 )-sulfonyl bond formations (Scheme 1C). This method can be extended to three-component condensation involving the fixation of SO 2 . 12,13 Nevertheless, the strategy is mainly limited to arenesulfonyl radicals (or aryl radicals plus SO 2 ), while examples [14][15][16][17] of alkyl radical addition to SO 2 (e.g., Reed reaction 17 ) are rare due to the fast desulfonylation of alkanesulfonyl radicals. In fact, there have been no reports to date of general methods for the sulfonylation of alkyl radicals. Given that alkyl radicals are common intermediates easily generated from various types of organic compounds, it is certainly highly desirable to develop efficient and general methods for the sulfonylation of alkyl radicals (Scheme 1D). In particular, the decarboxylative sulfonylation of aliphatic carboxylic acids should be an important transformation useful in organic synthesis. To meet the challenge, we propose the concept of ''RSO 2group-transfer from Cu(II)-SO 2 R to alkyl radicals,'' in accordance with our previous ideas of Cu(II)-assisted CF 3 -group-transfer [18][19][20] or F-atom-transfer. 21 Specifically, we target the copper-catalyzed cross coupling of sulfinates with alkyl radicals generated via photoredox-catalyzed [22][23][24][25][26][27] decarboxylation of redox-active esters [28][29][30][31][32][33] derived from aliphatic carboxylic acids. [34][35][36][37][38][39][40][41][42][43]</p><!><p>Carboxylic acids and sulfinates 44 are both attractive raw materials for chemical synthesis due to their ready availability, high stability, and low cost. Decarboxylative cross coupling of aliphatic carboxylic acids with sulfinates should therefore be an ideal method for sulfone synthesis. Given that sulfinates are much easier to be oxidized than the corresponding carboxylic acids, direct oxidative decarboxylative coupling is not feasible. Reductive decarboxylation of redox-active esters of carboxylic acids might provide the solution.</p><p>We then commenced our investigations with the redox-active ester of 4-phenylbutanoic acid (1a) and sodium 4-methylbenzenesulfinate (2a) as the model substrates. The redox-active ester was easily prepared by condensation of 4-phenylbutanoic acid with N-hydroxyphthalimide (NHPI). After extensive screening of reaction conditions (see Table S1 for details), we were pleased to find that, with 2 mol % 1,2,3,5tetrakis(carbazol-9-yl)-4,6-dicyanobenzene (4CzIPN) 45,46 and 20 mol % Cu(OTf) 2 as catalysts and 2 equiv of dibutyl hydrogen phosphate as the additive, the visiblelight-induced reaction of ester 1a and sulfinate 2a at room temperature (RT) for 12 h afforded the desired sulfone 3a in 95% yield (Table 1, entry 1). When the reaction was performed in the absence of (BuO) 2 P(O)OH, the yield dropped to 65% (Table 1, entry 2). Switching the additive to trifluoroacetic acid also led to a high product yield (Table 1, entry 3), while weak acids such as acetic acid showed no improvement (Table 1, entry 4). Interestingly, the addition of 2,2 0 -bipyridine (20 mol %) significantly inhibited the reaction (Table 1, entry 5). Control experiments revealed that photocatalyst 4CzIPN, copper catalyst, and visible light were all essential for the transformation (Table 1, entries 6-8). In addition, the redox-active ester could be prepared in situ without purification, providing the sulfonylation product in 85% yield (Table 1, entry 9). It is worth mentioning that the use of free 4-methylbenzenesulfinic acid in place of sodium 4-methylbenzenesulfinate resulted in a very low (7%) yield of 3a. However, the combination of 4-methylbenzenesulfinic acid with a weak base such as NaHCO 3 or CF 3 CO 2 Na increased the product yield to 51% and 89%, respectively (see Table S2). These experiments suggest that (BuO) 2 P(O)OH or trifluoroacetic acid might serve as a buffer to adjust the pH value of reaction solution. The use of (BuO) 2 P(O)OH or trifluoroacetic acid as the additive proved to be even more critical in the decarboxylative sulfonylation of secondary alkyl acids, resulting in a sharp increase in product yield by inhibiting the generation of the alkene byproduct (see Table S2). While the detailed mechanism remains unclear for the remarkable acid effect, it might be possible that the presence of an acid decreases the basicity of sulfinate and thus retards a-deprotonation of alkyl radicals (to give alkene radical anions and hence alkenes after electron transfer). Note that the CH groups adjacent to a carbon radical center are quite acidic as pointed out by Studer and co-workers. 47,48 With the optimized conditions in hand, we examined the scope of the method. As shown in Scheme 2, various NHPI esters derived from primary and secondary alkyl acids underwent smooth decarboxylative sulfonylation with sulfinate 2a to provide the corresponding sulfones 3a-3v in good to excellent yields. The presence of a wide range of functional groups was tolerated by the process. For example, terminal alkenes, alkynes, alkyl or aryl bromides, aldehydes, ketones, esters, amides, sunfonamides, ethers, and unprotected indoles all proved to be compatible with the reaction. Protected a-amino acids were also suitable substrates, as evidenced by the synthesis of sulfone 3m. The reaction could be operated in gram scale without the loss of efficiency. The method was also applicable to NHPI esters derived from tertiary alkyl acids, albeit in a lower efficiency (e.g., 3w) presumably because of steric hindrance.</p><p>The protocol has also shown a broad scope in terms of organosulfinates, as demonstrated in Scheme 3. A number of arenesulfinates with either electron-withdrawing or electron-donating substituents on the aromatic ring all underwent sulfonylation reactions furnishing the corresponding sulfones 4a-4d in satisfactory yields. Moreover, the protocol was also applicable to alkanesulfinates. Primary, secondary, and tertiary Article alkanesulfinates were all suitable partners in the cross coupling, as exemplified by the efficient synthesis of sulfones 4e-4k. An excellent chemoselectivity was observed in the reaction of 1-allylcyclopropanesulfinate furnishing sulfones 4j and 4k in which the allyl group remained intact. Nevertheless, the sulfonylation with pyridine-3-sulfinate afforded sulfone 4l in a low yield due to the competing Minisci alkylation, and no desired product could be observed in the sulfonylation with trifluoromethanesulfinate. The results also indicated that sulfonyl radicals were unlikely to be involved in the reaction given the fast desulfonylation of alkanesulfonyl radicals.</p><p>The above results clearly demonstrate the broad substrate scope and wide functional group compatibility of the method. In addition, the reactions were run at room temperature under redox-neutral conditions free from external reducing or oxidizing agents. These characteristics enabled the late-stage modification of complex natural products or drug molecules (Scheme 4). For example, steroids such as dehydrocholic acid or chenodeoxycholic acid were readily converted to the corresponding sulfones 5a or 5b in high to excellent yield. Drug molecules such as isoxepac, chlorambucil, mycophenolic acid, gibberellic acid, or indometacin were all transformed into the corresponding sulfones highly efficiently. The protocol was also applicable to carbohydrate-containing acids, as evidenced by the synthesis of 5f in 91% yield.</p><p>To further demonstrate the synthetic utility of the sulfonylation method, we chose the anti-prostate cancer drug bicalutamide as the target molecule. Bicalutamide and its analogs were achieved by multi-step synthesis starting from the commercially Article available and inexpensive (S)-malic acid (6). However, three steps were required for the installation of the sulfonyl group in bicalutamide consisting of (1) Barton decarboxylative bromination of acid 7 with CBrCl 3 , (2) nucleophilic substitution of the resulting bromide with 4-fluorobenzenethiol, and (3) subsequent oxidation with mCPBA (meta-chloroperoxybenzoic acid). With the newly developed decarboxylative sulfonylation method, the three steps could be shortened into one (Scheme 5). Specifically, the condensation of acid 7 with NHPI and DIC (diisopropylcarbodiimide) produced the corresponding NHPI ester, which, without purification, was subjected to the treatment with p-fluorobenzenesulfinate under the optimized Article conditions to provide sulfone 8 in 60% yield. The following hydrolysis of 8 with KOH in aqueous methanol at room temperature afforded cleanly compound 9, which, without purification, was subjected to the condensation with 4-cyano-3-trifluoromethylaniline according to the literature procedure, 49 furnishing (R)-bicalutamide in 91% yield based on 8. The new synthetic route offers a more concise and efficient entry to bicalutamide and avoids the use of toxic CBrCl 3 , odorous p-fluorobenzenethiol, and dangerous mCPBA.</p><p>To gain further insight into the sulfonylation, mechanistic studies were carried out (Scheme 6). The reaction of the NHPI ester derived from cyclopropylacetic acid (10) under the optimized conditions produced exclusively the ring-opening sulfonylation product 3i in 88% yield. When the NHPI ester of hept-6-enoic acid (11) was subjected to the treatment with sulfinate 2a under the optimized conditions, the cyclized product 3e was obtained in 50% yield along with the uncyclized product 12 isolated in 25% yield. These radical clock experiments unambiguously demonstrated the intermediacy of alkyl radicals. Additionally, radical trapping experiment with 1,1-diphenylethylene also suggested the involvement of alkyl radicals rather than sulfonyl radicals (see Scheme S1). Furthermore, copper(II) p-toluenesulfinate prepared from Cu(OH) 2 and sodium p-toluenesulfinate was treated with an equimolar amount of triethylborane (as the ethyl radical precursor) in acetonitrile at room temperature under aerobic conditions, and ethylsulfone 13 was achieved in 81% yield. This experiment provided a solid evidence for the proposed mechanism of Cu(II)-assisted RSO Article elimination. Given that uncomplexed copper(II) sulfinate is a mild oxidant rather than a reducing agent and the presence of 2,2 0 -bipyridine inhibits the sulfonylation, the direct RSO 2 group transfer seems more likely the case. More mechanistic studies are certainly required to provide a detailed understanding on the mechanism.</p><p>The ratio of cyclized product 3e versus uncyclized product 12 was 2:1 in the radical clock experiment shown in Scheme 6. The rate constant for the cyclization of hex-5-en-1-yl radical at 20 C is known to be approximately 2.3 3 10 5 s À1 , as determined by Ingold and co-workers. 50 By assuming that the active intermediate species responsible for sulfonylation is of the same concentration as the catalyst Cu(OTf) 2 (0.02 M) and remains constant throughout the reaction, the rate constant for the toluenesulfonyl group transfer from Cu(II)-SO 2 Tol to a primary alkyl radical can Article then be calculated to be around 2.3 3 10 7 M À1 s À1 , which is much larger than the rate constant for primary alkyl radical addition to an unactivated monosubstituted alkene (10 3 $ 10 4 M À1 s À1 ) 51 or to benzene (3.8 3 10 2 M À1 s À1 ). 52 This well explains the remarkable chemoselectivity in the reaction of 1-allylcyclopropanesulfinate (to give 4j and 4k). Furthermore, it may also account for the low efficiency in the reaction of pyridine-3-sulfinate (to give 4l), given that rate constants for radical addition to protonated 4-cyanopyridine (Minisci alkylation) range from 8.9 3 10 5 M À1 s À1 for n-butyl radical to 6.3 3 10 7 M À1 s À1 for t-butyl radical. 52 Thus, the rate constant for RSO 2 group transfer determined above offers a quantitative view on the reaction mechanism and sets the stage for the rational design of new synthetic methodology based on radical sulfonylation.</p><!><p>In conclusion, the merger of photo-organocatalysis and copper catalysis enables the successful development of a practical protocol for the sulfonylation of alkyl radicals generated from aliphatic carboxylic acids. As the procedure is operationally simple, catalytic in copper, broad in scope, free from external reducing or oxidizing agents, tolerant of sensitive functional groups, and utilizes cheap and stable sulfinates, the method should find widespread applications in sulfone synthesis. It is also conceivable that more new methods of radical sulfonylation will be developed given that alkyl radicals can be generated by many other ways (such as hydrogen atom abstraction, olefin radical addition, etc.). Furthermore, the proposed mechanism of Cu(II)-assisted RSO 2 group transfer should stimulate further research toward the cross coupling of alkyl radicals with nucleophiles other than sulfinates. The research in this direction is currently underway in our laboratory.</p><!><p>Supplemental Information can be found online at https://doi.org/10.1016/j.chempr. 2020.02.003.</p>

Chem Cell

Residue-Based Preorganization of BH3-Derived \xce\xb1/\xce\xb2-Peptides: Modulating Affinity, Selectivity and Proteolytic Susceptibility in \xce\xb1-Helix Mimics

We report progress toward a general strategy for mimicking the recognition properties of specific \xce\xb1-helices within natural proteins through the use of oligomers that are less susceptible than conventional peptides to proteolysis. The oligomers contain both \xce\xb1- and \xce\xb2-amino acid residues, with the density of the \xce\xb2 subunits low enough that an \xce\xb1-helix-like conformation can be formed but high enough to interfere with protease activity. Previous studies with a different protein-recognition system suggested ring-constrained \xce\xb2 residues can be superior to flexible \xce\xb2 residues in terms of maximizing \xce\xb1/\xce\xb2-peptide affinity for a targeted protein surface. Here, we use mimicry of the 18-residue Bim BH3 domain to expand the scope of this strategy. Two significant advances have been achieved. First, we have developed and validated a new ring-constrained \xce\xb2 residue that bears an acidic side chain, which complements previously known analogues that are either hydrophobic or basic. Second, we have discovered that placing cyclic \xce\xb2 residues at sites that make direct contact with partner proteins can lead to substantial discrimination between structurally homologous binding partners, the proteins Bcl-xL and Mcl-1. Overall, this study helps to establish that \xce\xb1/\xce\xb2-peptides containing ring-preorganized \xce\xb2 residues can reliably provide proteolytically resistant ligands for proteins that naturally evolved to recognize \xce\xb1-helical partners.

residue-based_preorganization_of_bh3-derived_\xce\xb1/\xce\xb2-peptides:_modulating_affinity,_select

Introduction<!>Development of a constrained \xce\xb2-amino acid with an acidic side chain<!>Binding of BH3-mimetic \xce\xb1/\xce\xb2-peptides to Bcl-xL and Mcl-1<!>Engagement of an apoptosis signaling network by BH3-mimetic \xce\xb1/\xce\xb2-peptides<!>Proteolytic susceptibilities<!>Discussion<!>Conclusions<!>Materials<!>Fmoc-APC(t-butylsuccinyl)-OH (1)<!>Peptide Synthesis<!>Competition fluorescence polarization (FP) assays<!>Circular dichroism<!>Proteolysis<!>Surface plasmon resonance<!>Cytochrome c release assays

<p>α-Helices play prominent roles in protein associations. In some cases, one partner's contribution to the binding interface is comprised entirely of an α-helical segment, while in other cases the α-helix is part of a more complex recognition surface, as documented in comprehensive structural surveys by Arora et al.1-3 The inherent regularity of helical secondary structure has inspired many efforts to mimic the information content encoded on α-helical surfaces with unnatural oligomers,4 including oligo-aryl compounds,5-8 peptoids,9 peptides comprised of D-α-amino acid residues,10 spiroligomers,11 and amide-sulfonamide oligomers.12 Efforts in a number of groups have focused on peptidic oligomers composed entirely of β-amino acid residues13,14 or containing mixtures of α- and β-amino acid residues.15 Collectively, these β-peptides and α/β-peptides can access diverse helical conformations that offer a variety of side chain display geometries;16,17 the specific conformation adopted can be controlled by modulating the β-amino acid substitution pattern, the arrangement of α and β residues along the backbone, and other molecular parameters.</p><p>We have used BH3 domain recognition by anti-apoptotic proteins in the Bcl-2 family, such as Bcl-xL and Mcl-1, as a testbed to compare the α-helix-mimetic competencies of alternative β- and α/β-peptide helices.15 The bioactive BH3 domain conformation is an α-helix with a minimum of four or five turns.18 A set of four hydrophobic side chains is displayed along one side of this helix, and these side chains are accommodated by pockets at the bottom of the BH3-recognition cleft on Bcl-2-family binding partners (Figure 1A). An Asp side chain projects from the opposite side of the BH3 domain helix, relative to the 'stripe' of hydrophobic residues; this carboxylate forms a key intermolecular salt bridge with an Arg side chain located on the rim of the BH3-recognition cleft. Our data revealed that neither β-peptide helices nor α/β-peptide helices resulting from a 1:1 α:β pattern are sufficiently faithful mimics of an α-helix to generate high-affinity ligands for Bcl-xL.19,20 α/β-Peptides with smaller β residue proportions, however, proved to be very effective.21-23 For example, homologues of an 18-residue Bim BH3 α-peptide containing α→β3 substitutions in three regular patterns, ααβ αααβ or ααβαααβ, which lead to α/β-peptides containing 25% to 33% β residues, displayed significant affinity for Bcl-xL, Mcl-1 or both (the Bim BH3 domain itself binds to both Bcl-xL and Mcl-1).23 This type of α/β-peptide retains the full complement of side chains relative to the prototype α-peptide, but the backbone contains an extra CH2 unit at the site of each α→β3 replacement (Figure 2). The regular occurrence of β residues along the peptidic backbone usually renders these α/β-peptides much less susceptible to proteolytic cleavage than are homologous α-peptides.15</p><p>Crystallographic data demonstrate that α/β-peptides generated via periodic α→β3 substitution, in the ααβ, αααβ or ααβαααβ pattern, can adopt helical conformations that are very similar to an authentic α-helix, despite the presence of at least one additional CH2 unit per helical turn relative to a pure α-peptide backbone (Figure 1B,C).24,25 However, each α→β3 substitution introduces an additional flexible backbone bond relative to the prototype α-peptide; therefore, the energetic cost of helix formation by α/β-peptides generated in this way should be larger than for α-helix formation by homologous α-peptides.26-28 This anticipated difference in helix stability may explain why the affinities for Bcl-xL or Mcl-1 of α/β3 18-mer homologues are uniformly lower than the affinity of the Bim BH3 18-mer α-peptide itself.23</p><p>β-Amino acid residues offer opportunities for conformational preorganization that have no parallel among α-amino acid residues, because a ring can be used to constrain the β residue without eliminating a backbone H-bonding site.16 In contrast, ring-based preorganization of an α residue comes at the expense of the H-bond donor site, as illustrated by proline. We have previously shown that β3→cyclic β residue replacements can enhance the affinity of an α-helix-mimetic α/β-peptide for a complementary protein surface when the β-amino acid residues bear a five-membered ring constraint and the amino and carboxyl groups are trans (Figure 3); this earlier work involved 38-residue α/β-peptides that mimic the CHR domain of HIV protein gp41.29,30 Complementary work from Reinert and Horne has demonstrated comparable stabilization effects from β3→cyclic β replacements in an α-helix within a defined tertiary structure.27,28</p><p>In the present study, we examine the impact of β3→cyclic β residue replacements on the affinities for Bcl-xL and Mcl-1 of α/β-peptides derived from an 18-mer Bim BH3 α-peptide (A; Figure 4).23 This BH3 mimicry testbed is more versatile than the gp41 CHR system for evaluation of alternative α/β-peptide designs because our Bim BH3 sequence is much shorter than the gp41 CHR sequence (18 vs. 38 residues). We have previously conducted a comprehensive survey of the ααβ3, αααβ3 and ααβ3αααβ3 registries (14 α/β variants in total) in terms of binding to both Bcl-xL and Mcl-1;23 in contrast, only a few ααβαααβ registries have been evaluated for mimicry of the much longer gp41 CHR domain.29 The comprehensive survey identified two α/β-peptides that retained the ability of the native Bim BH3 domain to bind to both Bcl-xL and Mcl-1. One of these dual-binding α/β-peptides featured the ααβ3αααβ3 pattern (B), and the other featured the αααβ3 pattern (C). The ααβ3αααβ3 pattern causes the β3 residues to align in a "stripe" upon formation of an α-helix-like conformation, while the αααβ3 pattern causes the β3 residues to spiral around the helix axis. Crystal structures of α/β-peptide+Bcl-xL complexes revealed all of the β3 residues of B to be oriented toward solvent (Figure 1B), while for C, side chains from two β3 residues make critical contacts with the BH3-recognition cleft on the protein (Figure 1C).23 (The small red dots over the sequence shown for A in Figure 4 indicate the positions of the four key hydrophobic side chains that are essential features of BH3 domains.)</p><p>Replacing an α residue with its β3 homologue is 'automatic' because the side chain is defined, but β3→cyclic β replacement requires careful design if the constrained residue is to mimic physicochemical properties of the original β3 residue. Our previous work has been based on just two cyclic β residues, one designated ACPC (Figure 3), which is appropriate for positions that originally had β3 residues with hydrophobic side chains, and another designated APC, which can be used to replace basic residues, β3-hArg or β3-hLys. The experiments described here introduce a new cyclic residue, designated "sAPC" (for "succinyl-APC"), which provides an acidic side chain and can therefore be used to replace β3-hGlu or β3-hAsp.</p><p>The BH3 domain mimicry testbed allows us to monitor variations in the responses of different members of the Bcl-2 protein family to specific β3→cyclic β replacement patterns in α/β-peptide binding partners. The data below are interpreted on the assumption that the new α/β-peptides retain the BH3 domain-like helical conformation and binding site established crystallographically for B and C, although altering a ligands structure can lead to changes in binding mode.31 Experiments based on α/β-peptide B involve replacements at sites that are exclusively solvent-exposed upon complex formation. In contrast, experiments based on C explore β3→cyclic β replacements at residues that make direct contact with the partner protein. Since the cyclic β residue cannot perfectly reproduce the steric qualities of the original side chain, replacements at direct contact positions might be highly deleterious to binding. Our data indicate that β3→cyclic β residue replacements at solvent-exposed sites generally improve α/β-peptide affinity for both Bcl-xL and Mcl-1, relative to the analogues that contain exclusively β3 residues. At sites expected to make direct contact, however, β3→cyclic β replacement elicits surprising protein-dependent responses, with high selectivity for Bcl-xL relative to Mcl-1 or vice versa.</p><!><p>Figure 5 summarizes the preparation of building block 1, which allows incorporation of sAPC residues into α/β-peptides via Fmoc-based solid-phase synthesis. Starting material 2 is used for incorporation of APC residues via solid-phase synthesis; the preparation of this compound in stereoisomerically pure form has been previously described.33 The subunit incorporated during solid-phase peptide synthesis via use of 1 bears a t-butyl ester in the side chain, which is stable during subsequent cycles of Fmoc deprotection and amide bond formation. The t-butyl protecting group is removed along with other side chain protecting groups under the acidic conditions used to detach the polypeptide from the solid support.</p><p>α/β-Peptide D (Figure 6) is the analogue of B in which each β3 residue has been replaced with an appropriate cyclic β residue, including two β3-hGlu→sAPC replacements. Preparation of D proceeded smoothly, which indicates that building block 1 is well-suited for solid-phase synthesis. Figure 7 compares far-UV circular dichroism (CD) data for α-peptide A with CD data for α/β-peptides B and D in aqueous buffer. The data for A, with a minimum at ~208 nm and a shoulder near 220 nm, are consistent with partial α-helix formation, which is common for α-peptides in this length range. Previous work has shown that formation of an α-helix-like conformation by α/β-peptides leads to a single CD minimum at ~208 nm.24 α/β-Peptide D manifests a strong minimum at this characteristic position, suggesting significant population of the helical state. In contrast, α/β-peptide B shows no evidence of helicity. The conformational difference between these two α/β-peptides presumably arises from the stronger local helical propensity of the ring-constrained β residues in D relative to the flexible β3 residues in B.26-28</p><!><p>For initial assessment of the impact of replacing β3 residues with cyclic analogues in BH3-mimetic α/β-peptides, we prepared the five derivatives of B in which a single β3 residue was replaced and the five derivatives of C in which a single β3 residue was replaced (Table 1). In each case, the cyclic residue was selected to mimic the properties of the side chain of the original β3 residue, i.e., ACPC (X) was used for hydrophobic side chains, APC (Z) for basic side chains and sAPC (U) for acidic side chains. Binding of these new α/β-peptides to Bcl-xL or Mcl-1 was evaluated with previously described competition fluorescence-polarization (FP) assays.33 Among the derivatives of B (ααβαααβ pattern), each single β3→cyclic β replacement has only a modest effect on affinity for either Bcl-xL or Mcl-1. Individual cyclic replacements are uniformly favorable in terms of binding to Mcl-1. Most replacements are moderately favorable in terms of binding to Bcl-xL, but β3-hGlu-6→sAPC (B-2) is slightly unfavorable.</p><p>For single β3→cyclic β replacement derivatives of C (αααβ pattern) involving sites that do not make intimate contacts with the partner protein, small and favorable effects on binding to Bcl-xL and Mcl-1 are observed, as for most single replacements in the context of B. However, β3→cyclic β replacements at the two sites in C that make direct contacts with partner proteins lead to larger and more selective effects. β3-hIle-10→ACPC (C-3) causes a substantial decline in affinity Mcl-1 but has little impact on affinity for Bcl-xL. In contrast, β3-hPhe-14→ACPC (C-4) causes a substantial decline in affinity for Bcl-xL but modestly improves affinity for Mcl-1. In the native Bim BH3 domain, the residues corresponding to β3-hIle-10 and β3-hPhe-14 contribute two of the four crucial hydrophobic side chains to the interface formed with a Bcl-2 family partner. The previously reported crystal structure of α/β-peptide C bound to Bcl-xL shows that the side chains of both β3-hIle-10 and β3-hPhe-14 are buried within the protein's BH3-recognition cleft, as expected (Figure 1C).23 The divergent responses of Bcl-xL and Mcl-1 to β3→cyclic β replacements at these sites suggest that the recognition pockets of these structurally and functionally related proteins differ in their capacity to accommodate local changes in side chain geometry within the α/β-peptide ligands. The pocket that accepts the side chain of β3-hIle-10 seems to be very discriminating in Bcl-xL but less so in Mcl-1, and the situation is reversed for the pocket that accepts the side chain of β3-hPhe-14. The intriguing results of β3→cyclic β replacements at contact residues 10 and 14 could not have been predicted.</p><p>Table 2 provides competition FP assay results for several α/β-peptides that contain multiple β3→cyclic β replacements. Two derivatives were examined for the ααβαααβ pattern of B. α/β-Peptide D, introduced above, contains β3→cyclic β replacements at all five sites. Analogue D* contains the same set of cyclic β residues and two variations among the α residues, Gln-5→Glu and Tyr-17→Lys. The α residue modifications in D* relative to D are based on a previous "hydrophile scan" analysis of the Bim BH3 18-mer sequence,33 which revealed that Gln-5→Glu and Tyr-17→Lys modestly increase α-peptide affinity for both Bcl-xL and Mcl-1. Analogous increases were observed when these two changes were made in α/β3-peptide B.34</p><p>The FP data for D (Table 2) indicate that replacing all β3 residues with cyclic analogues leads to higher affinity for Bcl-xL and for Mcl-1 than was observed for any of the α/β-peptides containing just a single cyclic residue (B-1 to B-5, Table 1). Small additional improvements are seen for α/β-peptide D* relative to D. α/β-Peptide D* is comparable to the Bim BH3 α-peptide 18-mer (A) in affinity for Bcl-xL and Mcl-1; D* binds moderately more tightly to Bcl-xL and slightly more weakly to Mcl-1 relative to A.</p><p>Comprehensive replacement of the β3 residues in C with cyclic residues, to generate E (Table 2) leads to substantial reduction in affinity for both proteins. This result can be rationalized based on data in Table 1, which show that binding to Bcl-xL is diminished by ACPC replacement for β3-hIle-10 (C-3), and binding to Mcl-1 is diminished by ACPC replacement for β3-hPhe-14 (C-4). We therefore examined α/β-peptides F and G, which each contain only four β3→cyclic β replacements relative to C; F retains β3-hIle-10 and G retains β3-hPhe-14. These α/β-peptides manifest the expected qualitative preferences based on results in Table 1, with F binding preferentially to Bcl-xL and G binding preferentially to Mcl-1. It is noteworthy that F binds to Bcl-xL with >100-fold selectivity relative to Mcl-1, which stands in contrast to the >100-fold selectivity of native Bim BH3 18-mer A for Mcl-1 relative to Bcl-xL.23</p><p>We conducted competition surface plasmon resonance (SPR) measurements to evaluate the binding of α/β-peptides B, D and D* to Bcl-xL and Mcl-1, as a complement to FP measurements. Previous SPR studies showed that B binds moderately to Bcl-xL and Mcl-1, which is consistent with FP results; α/β-peptide B was re-analyzed alongside D and D* to allow direct comparison. The results (Table 3) are consistent with the conclusion drawn from FP assays (Table 2) in that the α/β-peptides containing cyclic residues, D and D*, bind to both pro-survival proteins substantially more tightly than does B, the analogue containing β3 residues. In addition, the SPR data suggest a small increase in Mcl-1 affinity for D* relative to D.</p><!><p>Bcl-xL and Mcl-1, along with other members of the pro-survival Bcl-2 protein family, inhibit apoptosis by binding tightly to other family members, such as Bak and Bax, that can permeabilize mitochondrial membranes and thereby initiate the apoptotic signaling cascade. Wild-type mouse embryonic fibroblasts (MEFs) are protected from apoptosis by Bcl-xL and Mcl-1;35 therefore, molecules that bind tightly to both of these pro-survival proteins, such as α/β-peptides D and D*, should induce apoptotic signaling in this cell type by causing release of Bak and Bax. Conventional BH3 domain α-peptides and analogous α/β-peptides do not spontaneously cross cell membranes. However, the ability of such peptides to engage the MEF apoptotic control network can be assessed with well-established assays involving cells pre-treated with digitonin, which permeabilizes the plasma membrane but does not damage the mitochondrial membrane.20,23</p><p>Results obtained with wild-type and Bax/Bak-doubly deficient MEFs, after permeabilization, are summarized in Figure 8. A key step in the early stages of apoptosis signaling is the release of cytochrome c from mitochondria, a process that is mediated by proapoptotic proteins such as Bax and Bak. Thus, cells deficient in Bax and Bak do not possess the machinery to permeabilize the outer mitochondrial membrane, and these cells serve as negative controls that enable us to detect any non-specific effects that the peptides might exert on the mitochondrial membrane. Cytochrome c is normally not found in the cytoplasm, and this protein is therefore undetectable by western blot analysis in the soluble fraction from permeabilized MEFs that have not been treated with any of the peptides (see "DMSO" data at the right side of Figure 8; DMSO was the solvent used to prepare peptide stock solutions). However, when permeabilized MEFs are treated with Bim BH3 domain 18-mer A (10 μM), cytochrome c appears in the cytoplasm. Comparable cytochrome c release is observed upon treatment with α/β-peptide D or D*. In contrast, as previously reported, treatment with B does not lead to cytochrome C release from mitochondria; in this case, all of the cytochrome c remains in the insoluble fraction, which contains the mitochondria. The lack of cytochrome c release for B is presumably explained by inadequate affinity of this α/β-peptide for Bcl-xL and Mcl-1. α/β-Peptides D and D* can induce cytochrome c release because of their tighter binding to both pro-survival proteins, which enables them to displace Bak and Bax. As predicted, neither D nor D* induces cytochrome c release from permeabilized MEFs derived from embryos in which the bak and bax genes have been knocked out (Figure 8). This control study supports our conclusion that α/β-peptides D and D* induce cytochrome c release via a mechanism that requires Bak or Bax, rather than through a non-specific disruption of the mitochondrial membrane.</p><!><p>We have previously shown that α/β-peptides containing ≥ 25% β residues uniformly distributed along the sequence tend to be much poorer substrates for proteases than are comparable peptides comprised exclusively of α residues.22,23,29,30 Table 4 compares the effect of proteinase K, an aggressive and relatively non-sequence-selective enzyme, on three molecules: (1) the Bim BH3 18-mer (A); (2) α/β analogue B, which contains exclusively β3 residues; and (3) α/β analogue D, which contains exclusively cyclic β residues. Periodic α→β3 replacement significantly hinders proteinase K activity, as indicated by the 17-fold greater half-life of α/β3-peptide B relative to α-peptide A. However, cyclic β residues provide stronger protection from proteolysis than do β3 residues: the half-life of D is 120-fold greater than that of α-peptide A and 7-fold greater than that of α/β3-peptide B. The enhanced protection conferred by cyclic relative to acyclic β residues is consistent with previous observations in a different sequence context29,30 and presumably arises from differences in conformational propensities. Proteases generally bind substrates in extended conformations, while the cyclic β residues strongly favor helical conformations.</p><!><p>We previously explored the effects of β3→cyclic β replacements in the context of α/β-peptide inhibitors of HIV infection.29,30 This activity required mimicry of a long α-helix formed by the CHR domain of viral protein gp41. Fusion of the viral envelope with the target cell membrane, essential for HIV propagation, is mediated by gp41,36,37 and conventional CHR-derived peptides block fusion by interfering with helix-helix interactions within gp41 trimers.38 Efforts to optimize CHR-mimetic α/β-peptides revealed that replacing β3 residues with cyclic analogues enhanced affinity for the targeted protein surface.29,30 The BH3 domain mimicry testbed has now enabled us to test the generality of this beneficial effect and to broaden our evaluation of the impact of β3→cyclic β replacements. The gp41-based efforts were limited in scope because each candidate contained 38 residues, which prevented broad exploration of alternative α/β patterns. Thus, only the ααβαααβ backbone pattern was considered, and only registries that oriented the β residue 'stripe' toward the solvent were evaluated. This α/β arrangement is analogous to that in Bim BH3 analogue B. As with the Bim BH3 domain, the gp41 CHR-derived sequence we used contained hydrophobic, basic and acidic side chains at the positions selected for α→β substitution; however, we could evaluate β3→cyclic β replacements at only hydrophobic and basic sites because a cyclic β residue bearing an acidic side chain had not yet been developed.</p><p>The Bim BH3-based studies reported here complement the gp41 CHR-based findings in several important ways. First, we have now generated a β residue with the ring constraint appropriate for α-helix mimicry that contains an acidic side chain (sAPC), and we have shown that this residue can be used to generate α/β-peptides that bind tightly to a protein partner. Second, we have evaluated all possible single-site β3→cyclic β replacements in the context of the ααβαααβ pattern of Bim BH3 analogue B. These individual replacements (B-1 to B-5) almost always improve binding to protein partners Bcl-xL or Mcl-1, but the effects are generally modest. Global β3→cyclic β replacement (D), generates a very effective ligand for both proteins, as demonstrated not only by binding experiments (FP and SPR assays) but also by the ability of D to engage the apoptotic signaling network in permeabilized MEFs. Third, we have shown that replacing β3 residues with cyclic analogues enhances resistance to enzymatic degradation. In concert with previous findings in the gp41 CHR system,29,30 this observation suggests that proteolytic stabilization is a general benefit of β3→cyclic β replacement.</p><p>The Bim BH3 domain testbed has enabled the unexpected discovery that β3→cyclic β replacement at sites making direct contact with partner proteins can lead to highly selective ligands. Although α/β3-peptide C binds with comparable affinities to Bcl-xL and Mcl-1, β3→ACPC replacement at either of the positions that makes direct contact with the partner protein, β3-hIle-10 or β3-hPhe-14 (C-3 or C-4), generates a highly selective ligand. The binding preferences of C-3 and C-4 are complementary, with ACPC at position 10 causing >30-fold selectivity for Bcl-xL and ACPC at position 14 causing >30-fold selectivity for Mcl-1. These results suggest that β3→cyclic β replacement at different protein-contact sites has identified a subtle distinction between Bcl-xL and Mcl-1 in terms of local adaptability within these proteins' BH3-recognition grooves. Such variation is not evident from comparison of conventional structural data (e.g., crystal structures). Molecules with strong binding preferences among related proteins can be very useful from a biomedical perspective,39,40 and observations in the BH3 domain mimicry testbed encourage future studies to determine whether β3→cyclic β replacements at contact sites lead to comparable selectivities within other protein families. Our observations regarding Bcl-xL vs. Mcl-1 selectivity complement other recent reports of comparable selectivity in within different ligand families.41,42</p><!><p>Our results broaden understanding of an emerging methodology for α-helix mimicry and strengthen the prospect that this approach will prove to be of general utility. The strategy is based on peptidic oligomers that have unnatural backbones in which some residues are derived from β-amino acids. These α/β-peptides can be readily prepared via conventional solid-phase synthesis; many of the necessary β-amino acid building blocks are commercially available. Thus, it is straightforward to prepare sets of α/β-peptides based on a prototype α-helix-forming sequence via α→β3 replacement in patterns such as ααβαααβ or αααβ, and to evaluate these α/β-peptides for functional α-helix mimicry. The data provided here indicate that the α-helix-mimetic properties α/β3-peptides can be generally improved via replacement of some or all β3 residues, which are inherently flexible, with analogues containing a five-membered ring constraint and bearing appropriate side chain functionality. In addition to providing high affinity for protein partners, β3→cyclic β replacements can confer binding selectivity among related proteins. α/β-Peptides containing cyclic β residues benefit from improved helical stability relative to analogous α/β3-peptides and from decreased susceptibility to proteolysis relative the prototype α-helix-forming peptide and analogous α/β3-peptides. This combination of properties makes α/β-peptides containing cyclic β residues attractive for biological applications.</p><!><p>Fmoc-L-α-amino acids, O-(benzotriazol-1-yl)-N,N,N′,N′-tetramethyluronium hexafluorophosphate (HBTU), and NovaPEG Rink amide resin were purchased from NovaBiochem (San Diego, CA). Fmoc-L-β-amino acids were purchased from Peptech (Burlington, MA). 6-((4,4-Difluoro-1,3-dimethyl-5-(4-methoxyphenyl)-4-bora-3a,4a-diaza-s-indacene-2-propionyl)amino)hexanoic acid, succinimidyl ester (BODIPY-TMR-X-SE) was purchased from Invitrogen. Piperidine, 1-hydroxybenzotriazole hydrate (HOBt), trifluoroacetic acid (TFA), HPLC-grade acetonitrile (MeCN), dimethylformamide (DMF), dichloromethane (DCM), and all other chemical reagents were purchased from Sigma-Aldrich (Milwaukee, WI) or Fisher Scientific (Pittsburgh, PA).</p><!><p>(1S,2S)-Fmoc-APC(Boc)-OH43 (2) (298 mg, 0.66 mmol) was dissolved in 6.6 mL 25 vol %TFA in DCM without a stir bar in the flask. The reaction was allowed to proceed at r.t., with periodic flask agitation, for 4 h. TFA and DCM were removed by evaporation under a stream of N2 in a hood. The oily solid residue was dissolved in 5 mL DCM, and the solvent was evaporated again in a hood under a stream of N2. The product was dissolved in 3 × 5 mL DCM, each time removing solvent under rotary evaporation, until the brownish oil bubbled under vacuum during rotary evaporation (indicating that the TFA had been removed).</p><p>While DCM from the previous step was removed, the following materials were combined in 3 mL DCM: mono-tert-butylsuccinate44 (162.2 mg, 0.72 mmol), EDC·HCl (139.1 mg, 0.73 mmol), and HOBt (100 mg, 0.74 mmol). This solution was cooled to 0°C in an ice bath. Boc-deprotected Fmoc-APC (preceding paragraph) was dissolved in 3 mL DCM, cooled to 0°C, and 346 μL diisopropylethlamine (DIEA) was added. The preactivated succinate solution was transferred to the deprotected APC solution via syringe, and the reaction mixture was allowed to sit in the ice bath stirring overnight, during which time the mixture warmed to room temperature. The solvent was removed under rotary evaporation, and the residue was dissolved in 50 mL EtOAc. The organic layer was extracted with 2 × 50 mL 5% NaHSO4 and 1 × 50 mL brine. The organic layer was dried with MgSO4 and filtered, and the filtrate was concentrated. The residue was purified by column chromatography (column loaded in 1% MeOH/DCM + 1% HOAc, eluted with 1-4% MeOH/DCM + 1% HOAc). The fractions containing the product were combined, toluene was added to form an azeotrope with HOAc, and the solvents were removed under rotary evaporation. The oily product was dissolved in a small amount of EtOAc and precipitated with pentane. A white solid (173 mg, 51%) was obtained. Rf = 0.18, 4% MeOH/DCM + 1% HOAc. MS-ESI: m/z = 531.2102 (M+Na)+. mp 166-167°C; 1H-NMR (CD3OD, 300 MHz) δ 7.80 (d, JHH 7.2 Hz, 2H), 7.65 (d, JHH 7.5 Hz, 2H), 7.39 (t, JHH 7.4 Hz, 2H), 7.31 (t, JHH 7.4 Hz, 2H), 4.49-4.33 (m, 3H), 4.22 (t, JHH 6.4, 1H), 3.90-3.63 (m, 3H), 3.43-3.380 (m, 1H), 3.17-3.00 (m, 1H), 2.55 (s, 2H), 2.52 (s, 2H), 1.45 (s, 9H); 13C NMR (CD3OD, 75.4 MHz, 24 °C) δ172.81, 172.75, 171.531, 156.97, 144.10, 144.026, 141.448, 127.61, 126.97, 124.99, 124.92, 119.75, 80.58, 66.50, 53.79, 52.51, 50.87, 49.98, 31.05, 30.03, 29.67, 28.37.</p><!><p>Peptides were synthesized using standard Fmoc-solid phase methods in 4.0-mL solid-phase extraction tubes from Alltech (Deerfield, IL) on NovaPEG Rink Amide resin, to afford C-terminal amides upon cleavage from the resin. Microwave irradiation was used as previously described43-45 to synthesize all Bim-derived α/β-peptides. Briefly, Fmoc-amino acids were activated with HBTU and HOBt in the presence of DIEA in NMP for coupling reactions. Fmoc deprotection was accomplished with 20% (v/v) piperidine in DMF. Acetylation of the N-terminus was accomplished after the final Fmoc deprotection with 8:2:1 DMF:DIEA:Ac2O at room temperature. Peptides were cleaved from the resin with 95% TFA, 2.5% H2O, and 2.5% triisopropylsilane (TIS), except peptides containing β3-hTrp, which required 81.5% TFA, 5% thioanisole, 5% phenol, 5% H2O, 2.5% ethanedithiol (EDT), and 1% TIS. After the TFA was evaporated under a stream of nitrogen, the crude α/β-peptide was dissolved/suspended in TFA and precipitated with cold ether. α/β-Peptides were purified using preparative, reverse-phase HPLC performed with a C4 or C18 column (Vydac, Anaheim, CA) and eluting with gradients of MeCN w/0.1% TFA (B solvent) in water w/0.1% TFA (A solvent). MALDI-TOF mass spectrometry was used to establish α/β-peptide identity. The purity of the α/β-peptides was assessed by analytical HPLC; in all cases, purity was ≥ 95%.</p><p>All α/β-peptides to be tested for binding to a Bcl-2 family protein were dissolved in DMSO. The concentration of the DMSO stock solution was measured by UV spectroscopy, where the molar extinction coefficient at 280 nm for each α/β-peptide was calculated based on the chromophores present (Trp or Tyr).43 α/β-Peptides with a single tryptophan were predicted to have an extinction coefficient of 5690 M−1cm−1, and α/β-peptides with a single tyrosine were predicted to have an extinction coefficient of 1280 M−1cm−1.48 α/β-Peptides containing more than one chromophore were predicted to have an extinction coefficient corresponding to the sum of the single chromophore extinction coefficients.</p><!><p>Expression and purification of the proteins Bcl-xL and Mcl-1 were performed as previously described.49 FP assays were performed in a 384-well black polystyrene plate. A BODIPYTMR-Bak tracer peptide (Kd = 1.2 nM)49,50 was used for Bcl-xL binding assays, and a fluorescein-Bim tracer for Mcl-1 binding assays (Kd = 1.4 nM).51 Kd was recalculated for each new synthesis of tracers and proteins to account for slight variations between preparations. For Bcl-xL binding assays, wells of a 384-well plate contained 3 nM BODIPYTMR-Bak tracer, 2 nM Bcl-xL protein, and 2 μL DMSO solution of α/β-peptide (final concentration from 4.2 pM to 25 μM) in a final volume of 50 μL in FP Buffer (50 mM NaCl, 16.2 mM Na2HPO4, 3.8 mM KH2PO4, 0.15 mM NaN3, 0.15 mM EDTA, 0.5 mg/mL Pluronic; pH 7.4).52 For Mcl-1 binding assays, wells of a 384 plate contained 10 nM Flu-Bim tracer, 10 nM Mcl-1 protein, and 2 μL DMSO solution of α/β-peptide (final concentration from 4.2 pM to 25 μM) in a final volume of 50 μL in FP Buffer. Plates were read after a 5 h incubation at room temperature, the time necessary for complete equilibration. Experiments were performed in duplicate. The equilibrium dissociation constant (Ki)52,53 or IC50 was calculated using GraphPad Prism.54</p><!><p>All CD data were acquired using an Aviv 420 circular dichroism spectrophotometer. Peptide solutions were prepared in 10 mM phosphate buffer, pH 7, and the concentration was determined by UV absorbance. Data were acquired at 20 °C with a step value of 1 nm from 260 to 190 nm and an averaging time of 5.0 s. A 0.1-mm path length cell was used for all spectra. We used data only for wavelengths at which the dynode voltage was < 400 V. Mean residue ellipticity (θ) was calculated using the following equation. [θ]=[(δS−δR)∕(100∗n∗1∗c)]∕1000 where δS = sample signal, δR = reference signal, n = # amides in the backbone, l = path length (in cm) and c = concentration in dmol*cm−3.</p><!><p>Stock solutions of each peptide were prepared in a TBS solution, pH 7.5, with 10% DMSO (for solubility) at 100 μM peptide, as determined by UV absorbance. A 25 μg/mL stock solution of proteinase K was prepared in TBS. For each proteolysis reaction, 25 μL of peptide stock solution was mixed with 15 μL TBS. A 10 μL aliquot of proteinase K stock solution was added to the mixture, and the reaction was allowed to proceed at room temperature. A 100 μL aliquot of 1% TFA in 50:50 acetonitrile/H2O was added to quench the reaction at the desired time point. A 125 μL aliquot of the resulting solution was injected onto an analytical reverse-phase HPLC column, and the amount of full-length peptide remaining was quantified using the absorbance at 220 nm of this peptide. Duplicate reactions were run for each time point. Half-life values were determined by plotting the percent remaining peptide versus time and fitting the data to an exponential decay using GraphPad Prism. Amide bond cleavage sites were identified by MALDI-TOF-MS analysis of crude reaction mixtures at various time points.</p><!><p>All recombinant pro-survival proteins used for binding studies, which have N- and/or C-terminal truncations (Bcl-2ΔC22, Bcl-xLΔC24, Bcl-w C29S/A128EΔC29, Mcl-1ΔN170ΔC23), were expressed and purified exactly as described previously.55,56 SPR competition assays were performed using a Biacore 3000 instrument exactly as described previously.57 Briefly, pro-survival proteins were incubated with α/β-peptides for 2 hr prior to the solution being passed over a CM5 chip on which was immobilized either a wild-type 26-mer Bim BH3 peptide (DMRPEIWIAQELRRIGDEFNAYYARR) or an inert quadruple-variant peptide (Bim4E: DMRPEIWEAQEERREGDEENAYYARR; note that the four key hydrophobic residues necessary for binding to pro-survival proteins have been changed to glutamic acid residues). The signal from the Bim4E channel was subtracted from the signal from the wild-type channel to provide the binding fraction that arises from specific BH3-mediated binding.</p><!><p>The cytochrome c assay was performed as described previously.57 Briefly, wild-type or bax−/−/bak−/− MEFs were permeabilized in digitonin-containing buffer (20 mM HEPES pH 7.2, 100 mM KCl, 5 mM MgCl2, 1 mM EDTA, 1 mM EGTA, 1250 mM sucrose and 0.05% (w/v) digitonin) and then incubated with peptides (10 μM, dissolved in DMSO) for 1 hour at 30°C before pelleting via centrifugation. The supernatant was retained (soluble fraction), and the pellet was lysed in Triton-X100-containing buffer (20 mM Tris pH 7.4, 135 mM NaCl, 1.5 mM MgCl2, 1 mM EDTA, 10% (v/v) glycerol, 1% (v/v) Triton-X100 and protease inhibitors) to generate the pellet fraction. Both soluble and pellet fractions were analyzed for cytochrome c by Western blotting using an anti-cytochrome c antibody (clone 7H8.2C12; BD Biosciences).</p>

PubMed Author Manuscript

Downstream processing of Isochrysis galbana: a step towards microalgal biorefinery

An algae-based biorefinery relies on the efficient use of algae biomass through its fractionation of several valuable/bioactive compounds that can be used in industry. If this biorefinery includes green platforms as downstream processing technologies able to fulfill the requirements of green chemistry, it will end-up with sustainable processes. In the present study, a downstream processing platform has been developed to extract bioactive compounds from the microalga Isochrysis galbana using various pressurized green solvents. Extractions were performed in four sequential steps using (1) supercritical CO 2 (ScCO 2 ), (2) ScCO 2 /ethanol (Gas Expanded Liquid, GXL), (3) pure ethanol, and (4) pure water as solvents, respectively.The residue of the extraction step was used as the raw material for the next extraction. Optimization of the ScCO 2 extraction was performed by factorial design in order to maximize carotenoid extraction.During the second step, different percentages of ethanol were evaluated (15%, 45% and 75%) in order to maximize the extraction yield of fucoxanthin, the main carotenoid present in this alga; the extraction of polar lipids was also an aim. The third and fourth steps were performed with the objective of recovering fractions with high antioxidant activity, eventually rich in carbohydrates and proteins. The green downstream platform developed in this study produced different extracts with potential for application in the food, pharmaceutical and cosmetic industries. Therefore, a good approach for complete revalorization of the microalgae biomass is proposed, by using processes complying with the green chemistry principles. † Electronic supplementary information (ESI) available. See

downstream_processing_of_isochrysis_galbana:_a_step_towards_microalgal_biorefinery

Introduction<!>Chemicals and samples<!>2.2.1.<!>Conventional extraction method.<!>Total carotenoid and chlorophyll determination<!>Analysis of carotenoids and chlorophylls by HPLC-DAD<!>Identification of carotenoids by HPLC-APCI-MS/MS<!>Analysis of lipid class compositions by HPLC-evaporative light scattering detection<!>Antioxidant capacity assay<!>Protein analysis of PLE extracts<!>Sugar composition analysis of PLE extracts<!>Results and discussion<!>Optimization of supercritical CO 2 extraction of Isochrysis galbana (step 1)<!>Design of the conditions of sequential extraction of Isochrysis galbana (steps 2-4)<!>Concluding remarks

<p>A biorefinery involves biomass conversion processes and equipment to produce fuel, power, and added-value chemicals from organic materials 1 such as renewable resources or microalgae. Microalgae are among the most promising raw materials for the sustainable supply of commodities and the use of algae. 2,3 They use light energy, residual nutrients and carbon dioxide (that can be obtained from flue gas) with higher photosynthetic efficiency than plants for the production of biomass. 4 Moreover, these organisms may be grown on nonarable land, thus, not competing with food needs for biofuel production. Microalgae biomass is an excellent source of oils (including high amounts of long chain polyunsaturated fatty acids (LC PUFAs)), proteins, polysaccharides (such as starch, xylans, pectins, glucans, extracellular polysaccharides (EPS)) and other high-added value compounds such as carotenoids, pigments, antioxidants, sterols and minerals. The potential for the production of these different components may even be tuned by setting particular growing conditions. Therefore, the microalgae-based biorefinery concept relies on the complete process chain ranging from optimization of biomass production to the development of a platform able to generate a wide range of products, from bulk chemicals, food supply ( proteins, fibres), bioactive compounds, and oils with respect to its use as a biofuel.</p><p>Isochrysis galbana is a small marine flagellate (Phylum: Haptophyta) widely used in aquaculture as a PUFA-rich microalga. 5 It is commercially produced as feed for the early larval stages of mollusks, fish, and crustaceans. In fact, I. galbana cells produce antibacterial substances, which increase the toxicity of free fatty acids such as eicosapentanoic acid (EPA) to several pathogens, without the use of chemicals that might harm organisms under culture conditions or the environment. 6 Besides polyunsaturated fatty acids, I. galbana is a valu-able source of proteins, carbohydrates and photosynthetic pigments such as chlorophyll a and fucoxanthin. 7 Fucoxanthin, a major carotenoid present in the chloroplasts of brown seaweeds, contributes to more than 10% of the estimated total production of carotenoids in nature. Although fucoxanthin is clearly a valuable pigment with various health benefits, its use has been limited due to the low extraction efficiency from marine materials and the difficulty to synthesize it. In this respect, algae, such as I. galbana, can be considered as a potential source of fucoxanthin. 8 In order to fully develop the microalgae-based biorefinery concept, new aspects related to technologies for extraction, isolation and fractionation of the biomass into multiple products (lipids, proteins, polysaccharides, bioactives, etc.) should be studied. Also, steps into integrated approaches for multiproduct biorefinery should be taken into account to improve the efficiency and minimize the energy and resource consumption, 9 especially when green chemistry principles and sustainability issues are to be considered.</p><p>Traditionally, extraction of lipophilic compounds from algae, such as carotenoids and lipids, has been performed by means of toxic organic solvents like hexane. Nowadays there is a demand for fast, selective, efficient and greener processes able to provide extractions with high yields; besides, the costs associated have to be reduced, for instance, by minimizing the removal of solvent residues.</p><p>High-pressure extractions such as supercritical fluid extraction (SFE) and pressurized liquid extraction (PLE) using GRAS (generally recognized as safe) solvents such as CO 2 , ethanol or water, have emerged as promising alternatives to face these challenges. 10 This was the subject of a specifically devoted workshop on Supercritical Fluids and Energy that was conducted in Brazil in December 2013, 11 with the idea of assessing the potential of supercritical (pressurized fluids in general) technologies in the fields of energy, materials science, process technology, green chemistry and sustainable technologies.</p><p>SFE offers a fast extraction rate, high selectivity and is an ecofriendly technology with minimal or no use of organic solvents, although the low polarity of supercritical CO 2 (ScCO 2 ) limits its applications. ScCO 2 has been reported as an interesting approach for the extraction of lipids with antimicrobial activity from the microalgae Chaetoceros muelleri, 12 n-3 fatty acids from the seaweed Hypnea charoides, 1 lutein and β-carotene from Scenedesmus almeriensis 13 and fucoxanthin from the seaweed Undaria pinnatifida 14 and Sargassum muticum, 15 among others. In this latter application, the addition of ethanol as a co-solvent improved the yield of fucoxanthin in both algal species. 15,16 Ethanol is often used as a modifier or a co-solvent of ScCO 2 in order to overcome the CO 2 limitations towards the extraction of medium polarity bioactive compounds. For instance, CO 2 modified with ethanol has been applied for the extraction of astaxanthin from Haematococcus pluvialis 17 and various pigments from Spirulina platensis. 18 The use of a co-solvent at a higher concentration allows working in the region of gasexpanded liquids (GXLs), 19 which is a promising intermediate between PLE and SFE for the extraction of medium or highpolarity compounds. Carbon dioxide expanded ethanol (CXE) has been recently used to obtain astaxanthin enriched extracts from H. pluvialis. 20 Pressurized liquid extraction has demonstrated an interesting potential for extracting bioactive compounds from macroand microalgae. 10,20 This extraction technique allows obtaining higher yields than those achieved by conventional extraction techniques, in a shorter time and with less solvent consumption. 10 PLE using ethanol has been reported for the extraction of carotenoids from Neochloris oleoabundans, 22 Dunaliella salina 2 and Chlorella ellipsoidea. 3 In addition, 90% ethanol was used for the extraction of fucoxanthin from Eisenia bicyclis 23 and the mixture of ethanol/limonene (1 : 1, v/v) has been proposed as a green approach for PLE extraction of lipids from microalgae. 9 In the present study, we propose an integrated sequential extraction process based on the use of green compressed fluids, in increasing order of polarity, for the fractionation of bioactive compounds from the microalga I. galbana, as an approach to develop a microalgae biorefinery procedure. 21 The developed process comprises the sequential extraction with ScCO 2 , CO 2expanded ethanol, PLE using ethanol and subcritical water extraction. Finally, different tools are employed for the chemical and functional characterization of the obtained fractions.</p><!><p>HPLC-grade methyl tert-butyl ether (MTBE), methanol, acetone, and ethanol were from VWR (Leuven, Belgium). Sea sand (0.25-0.30 mm diameter) and potassium persulfate were from Panreac. Butylated hydroxytoluene (BHT), formic acid (LC-MS grade), triethylamine (99.5%) and standards of β-carotene, fucoxanthin, chlorophyll a (from Anacystis nidulans algae), ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)diammonium salt), D-methionine and Trolox (6-hydroxy-2,5,7,8tetramethylchromane-2-carboxylic acid) were obtained from Sigma-Aldrich (St Louis, MO, USA). The water used was Milli-Q water (Millipore, Billerica, MA, USA). Dichloromethane, chloroform, hexane, methanol, isooctane, and isopropanol were HPLC-grade and purchased from LabScan (Gliwice, Poland).</p><p>Freeze-dried samples of I. galbana (T-ISO) were obtained from Fitoplancton Marino S.A. (Cadiz, Spain), and stored under dry and dark conditions until further use. I. galbana was grown in outdoor vertical 400 L reactors. Air containing 2% CO 2 is injected into the reactors, while natural light-dark cycles and ambient temperature are used (10-11 h of light, temperatures ranging from 10 to 22 °C). These reactors are inoculated with cultures grown in growth chambers under the standard conditions of Fitoplancton Marino S.A.</p><!><p>High pressure extraction processes. All highpressure extractions were carried out in a Speed Helix super-critical fluid extractor from Applied Separations (Allentown, PA, USA). This equipment can be used to perform both SFE (with or without a co-solvent) and PLE. For each extraction, 10 g samples of I. galbana were mixed with 30 g of washed sea sand into a 300 mL basket sandwiched between filter paper. The basket was placed into the high-pressure stainless-steel extraction cell. The CO 2 pneumatic pump pressurizes the CO 2 to the required set value. In the experiments with CO 2expanded ethanol, ethanol was fed by using a liquid pump set at the required volumetric flow rate, and the solvent mixture in the feed tubing was preheated to the extraction temperature. In all experiments, a constant flow rate (5 L min −1 , CO 2 gas) of premier quality CO 2 (Carburos Metálicos, Madrid, Spain) was adjusted at the exit of the extraction cell using a CO 2 gas flow meter. CO 2 extracts were collected in a Falcon tube, while the rest of the extracts were collected in glass bottles.</p><p>Extractions were performed in four sequential steps using (1) supercritical CO 2 (ScCO 2 ), (2) ScCO 2 /ethanol (CXE), (3) pure ethanol (PLE), and (4) pure water (PLE) as solvents, respectively.</p><p>The different extraction steps were selected in increasing order of polarity (ScCO 2 < CXE < ethanol < water), to exhaust the microalgae biomass of extractable compounds, fractionating its components in order to give valuable isolated fractions.</p><p>Step 1: ScCO 2 extraction conditions were optimized using a response surface methodology (RSM) to reveal the functional relationship between the extraction responses (extract yield, total carotenoids and total chlorophylls of extracts) and independent variables (extraction pressure and extraction temperature). A three-level factorial design (3 2 ) was used. The studied factors were pressure (100-300 bar) and temperature (40-60 °C). To determine the extraction time of this step, a kinetic study was performed at the central point of the experimental design (200 bar, 50 °C), collecting the extract every 20 min and calculating the percentage of the extractable material. The parameters of the model were estimated by multiple linear regression using the Statgraphics Centurion XVI software (Statpoint Technologies, Warrenton, Virginia, USA), which allows both the creation and the analysis of experimental designs.</p><p>Step 2: The second step involved a carbon dioxide expanded ethanol (CXE) extraction in order to increase the polarity of the extracted fraction. This step was carried out in the residual biomass from the first step. The pressure was set at 70 bar, while the temperature was maintained at 50 °C to match the optimum temperature used in the first step in order to avoid unnecessary heating or cooling of the system and thus, minimizing operational costs. Three different percentages of ethanol were tested, 15%, 45% and 75%; the extraction time selected was 1 h. The extraction in the center point (45% EtOH) was performed in triplicate for the precision study.</p><p>Step 3: The residue from the previous extractions was extracted again using PLE at 100 bar and 80 °C for 30 min, using pure ethanol as an extracting solvent.</p><p>Step 4: In the fourth and last step, PLE was employed using water as a solvent under the same extraction conditions employed in step 3 (100 bar and 80 °C for 30 min).</p><p>All the collection recipients were protected from light and 0.1% (w/v) BHT was added to the extracts. Finally, the solvent (ethanolic extracts) was evaporated in a rotary evaporator (Buchi, Flawil, Switzerland) or the samples were freeze-dried (water extracts). The extracts were stored at −80 °C to prevent degradation until analysis.</p><!><p>Conventional acetone extraction was performed (in triplicate) to determine the total extractable compounds in I. galbana using the method of Reyes et al. 20 Briefly, 200 mg of lyophilized algae were mixed with 20 mL acetone containing 0.1% (w/v) BHT in a 50 mL Falcon tube and the mixture was shaken for 24 h in an orbital shaker (DOS-20L, Elmi Ltd, Riga, Latvia) at 250 rpm in the dark. Following the extraction, the exhausted substrate was precipitated out in a refrigerated centrifuge (Sorvall Evolution RC, Thermo Electron, Asherville, NC, USA) operating at 11 952g at 4 °C for 10 min. The supernatant was collected, and the solvent was removed using a stream of N 2 . Dry acetone extracts were weighed and stored at −20 °C.</p><!><p>A spectrophotometric method was used to determine the total carotenoid and total chlorophyll concentration, based on their characteristic absorbance. Extracts from steps 1 and 4 were dissolved in methanol at a concentration of 0.1 mg mL −1 , while extracts of steps 2 and 3 were dissolved in methanol at a concentration of 0.05 mg mL −1 . Absorbance of these solutions was recorded at two specific wavelengths, 470 and 665 nm, for carotenoids and chlorophylls, respectively. External standard calibration curves of fucoxanthin (0.5-10 µg mL −1 ) and chlorophyll a (0.5-7.5 µg mL −1 ) were used to calculate the total carotenoid and chlorophyll content. Total carotenoids were expressed as mg carotenoids per g extract, by interpolating the absorbance of the extract at 470 nm in the calibration curve of fucoxanthin. Total chlorophylls were expressed as mg chlorophyll per g extract, by interpolating the absorbance of the extract at 665 nm in the calibration curve of chlorophyll a.</p><!><p>The carotenoid and chlorophyll profile of I. galbana extracts was determined by HPLC-DAD (diode-array detector) according to a method previously described for N. oleoabundans by Castro-Puyana et al. 22 HPLC analyses of the extracts were conducted using an Agilent 1100 series liquid chromatograph (Santa Clara, CA, USA) equipped with a diode-array detector, and using a YMC-C 30 reversed-phase column (250 mm × 4.6 mm inner diameter, 5 μm particle size; YMC Europe, Schermbeck, Germany) and a pre-column YMC-C 30 (10 mm × 4 mm i.d., 5 μm). The mobile phase was a mixture of methanol-MTBE-water (90 : 7 : 3 v/v/v) (solvent A) and methanol-MTBE (10 : 90 v/v) (solvent B) eluted according to the following gradient: 0 min, 0% B; 20 min, 30% B; 35 min, 50% B; 45 min, 80% B; 50 min, 100% B; 60 min, 100% B; 62 min, 0% B. The flow rate was 0.8 mL min −1 while the injection volume was 10 μL. The detection was performed at 280, 450 and 660 nm, although spectra from 240 to 770 nm were recorded using the DAD ( peak width >0.1 min (2 s) and slit 4 nm). The instrument was controlled by LC ChemStation 3D Software Rev. B.04.03 (Agilent Technologies, Santa Clara, CA, USA). Extracts were dissolved in solvent A prior to HPLC analysis at a concentration of 1 mg mL −1 for the extract of steps 2 and 3; the extracts from the first (ScCO 2 ) and fourth steps were analyzed at 10 mg mL −1 (and filtered through 0.45 µm nylon filters).</p><p>For the calibration curve, twelve different concentrations of fucoxanthin in ethanol, ranging from 0.97 × 10 −4 to 0.2 mg mL −1 , were analyzed using the LC-DAD instrument.</p><!><p>LC-MS characterization of I. galbana extracts was performed according to the method previously described by Castro-Puyana et al. 22 An Agilent (Santa Clara, CA, USA) 1200 liquid chromatograph equipped with a diode-array detector was directly coupled to an ion trap mass spectrometer (Agilent ion trap 6320) via an atmospheric pressure chemical ionization (APCI) interface. The HPLC conditions employed for performing the analysis were the same as those described in the previous section. MS analysis was conducted with APCI in positive ionization mode using the following parameters: capillary voltage, −3.5 kV; drying temperature, 350 °C; vaporizer temperature, 400 °C; drying gas flow rate, 5 L min −1 ; corona current (which sets the discharge amperage for the APCI source), 4000 nA; nebulizer gas pressure, 60 psi. Full scan was acquired in the range from m/z 150 to 1300. Automatic MS/MS analysis was also performed, fragmenting the two highest precursor ions (10 000 counts threshold; 1 V Fragmentor amplitude).</p><!><p>Separation of lipid classes was done using the method described by Castro-Gómez et al. 24 The analysis was performed using an HPLC system (model 1260; Agilent Technologies Inc.) coupled with an evaporative light scattering detector (SEDEX 85 model; Sedere SAS, Alfortville Cedex, France) using prefiltered compressed air as the nebulizing gas at a pressure of 3.5 bar at 60 °C; the gain was set at 3. Two columns were used in series (250 × 4.5 mm Zorbax Rx-SIL column with 5 μm particle diameter; Agilent Technologies Inc.) and a precolumn with the same packing was used. Before analysis, samples were dissolved in CH 2 Cl 2 (5 mg mL −1 ) and 50 μL was injected. The autosampler temperature was maintained at 4 °C, while the column temperature was set at 40 °C. Solvent mixtures and gradients are detailed in ref. 24.</p><!><p>The TEAC (Trolox equivalent antioxidant capacity) value was determined using the method described by Re et al. 25 with some modifications. The ABTS •+ (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)diammonium salt) radical was produced by reacting 7 mM ABTS and 2.45 mM potassium persulfate in the dark at room temperature for 16 h. The aqueous ABTS •+ solution was diluted with 5 mM sodium phosphate buffer pH 7.4 to an absorbance of 0.7 (±0.02) at 734 nm.</p><p>Ten microliters of the sample (5 different concentrations) and 1 mL of the ABTS •+ solution were mixed in an Eppendorf vial and 300 μL of the mixture was transferred into a 96-well microplate. The absorbance was measured at 734 nm every 5 min for 45 min in a microplate spectrophotometer reader (Synergy HT, BioTek). "Trolox" (6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid) was used as the reference standard and the results are expressed as TEAC values (mmol Trolox equivalents per g sample). These values are obtained from five different concentrations of each sample tested in the assay giving a linear response between 20 and 80% of the blank absorbance. All analyses were performed in triplicate.</p><!><p>Protein analysis was performed according to the Dumas method 26 by using a FlashEA 1112 nitrogen analyzer (Thermo Fisher Scientific, Waltham, MA, USA). Ten milligrams of the dry extract were weighed in a cup of tin and tightly pelleted and subsequently analyzed. A calibration curve of D-methionine was used within the range 1-20 mg. A N-to-protein conversion factor of 4.68 was used to calculate total protein from total nitrogen. The N-to-protein conversion factor was obtained by determination of the amino acid composition of I. galbana according to ref. 27. Analyses were performed in duplicate.</p><!><p>The hydrolysis of algae extracts was performed according to Saeman et al. 28 75 mg of the extract was hydrolyzed for 1 h in 72% (w/w) H 2 SO 4 at 30 °C and subsequently water was added giving 1 M H 2 SO 4 and the mixture was incubated for 3 h at 100 °C. After hydrolysis the samples were cooled in ice and then centrifuged (3000g, 15 min, at room temperature). The supernatant of each sample was used for analysis of the sugar composition.</p><p>The neutral sugar composition was determined according to de Keijzer et al. 29 by high performance anion exchange chromatography (HPAEC) using an ICS-3000 ion chromatography HPLC system equipped with a CarboPac PA-1 column (2 × 250 mm) in combination with a CarboPac PA guard column (2 × 25 mm) and a pulsed electrochemical detector in pulsed amperometric detection mode (Dionex, Sunnyvale, USA). A flow rate of 0.3 mL min −1 was used and the column was equilibrated with 17 mM NaOH. Elution was performed in two steps: 0-0.5 min, 17-0 mM NaOH and 0.5-35 min, 0-35 mM NaOH in 0-350 mM sodium acetate. Detection of the monomers was possible after the post column addition of 0.5 M sodium hydroxide (0.2 mL min −1 ). Before analysis samples were diluted (1 : 3) in water and to a 1 mL sample, 2.5 µL 0.1% (w/v) bromophenol blue in ethanol was added. To adjust the pH, solid barium carbonate was added until a clear magenta color was obtained. Subsequently, the solution was filtered using a 0.45 µm PTFE filter. Fucose was used as an internal standard in the case where fucose was not present in the sample. Analysis was performed in duplicate.</p><!><p>The strategy has been selected considering the compounds of interest that can be found in I. galbana (such as lipids, proteins, carbohydrates and carotenoids, mainly fucoxanthin and its isomers), the need for re-extracting the residual biomass from the previous extraction step, and the use of green solvents with increasing polarity.</p><p>Experimental conditions of the different extraction steps were either optimized or selected according to the previous results obtained in our laboratory for the extraction of similar compounds in other microalgae samples. Moreover, minimization of operational and energy costs was also considered in the integrated process, thus minimizing heating/ cooling operations and collection or treatment of the microalgae biomass.</p><!><p>As mentioned above, SFE using CO 2 as a solvent is considered a green process for the extraction of non-polar compounds from natural sources. 30,31 With the objective of maximizing the extraction of the less polar fraction of I. galbana biomass, supercritical CO 2 extraction conditions were optimized using a three-level factorial design (3 2 ). Extraction time was selected after performing a kinetic study under the central conditions (200 bar, 50 °C) measuring the percentage of the extractable material vs. extraction time by collecting samples every 20 minutes (data not shown). An extraction time of 60 min was selected as the most appropriate since after that time the amount of extracted material did not increase. Table 1 shows the experimental design employed, together with the results of the different response variables measured, i.e. extraction yield and total carotenoids and total chlorophyll content. As shown in Table 1, extraction yields ranged from 0.31 to 5.00% while the carotenoid content can be as high as 16.15 mg per g extract at a pressure of 300 bar and medium temperature (50 °C). This is in agreement with the previous results obtained for the extraction of carotenoids from other microalgae such as D. salina. 32,33 After performing the ANOVA (evaluation of the experimental design with Statgraphics Centurion XVI software) for each of the responses (data not shown), the statistical model was fitted and optimized. Considering that the goal of the first step was to maximize the yield and carotenoid content, while minimizing chlorophylls, a desirability function was selected for meeting these goals and giving to all responses the same weight. As shown in Fig. 1, this function provided an optimum of 299 bar and 51 °C to increase the extraction yield and carotenoid content while minimizing the chlorophyll content. The optimization desirability was equal to 0.66, while the values predicted by the model under the optimum extraction conditions were 4.41% for extraction yield, carotenoid content of 16.4 mg carotenoids per g extract and 4.3 mg chlorophylls per g extract for total chlorophylls. Experiments under the optimum conditions provided experimental values close to that predicted by the statistical model (Table 1, experiment 300.50).</p><!><p>Following this first step, three sequential extractions were studied in order to further fractionate the biomass achieving extracts with different compositions. The second step was selected to increase the polarity of the solvent mixture while taking advantage of the intermediate conditions, such as those provided by GXLs that allow working at lower pressures than those of SFE and using smaller volumes of solvents (compared to PLE). This approach has already been successfully applied to the extraction of astaxanthin from H. pluvialis microalgae. 20 Thus, for the second step, a pressure of 70 bar was selected, which is lower than the CO 2 critical pressure (73.8 bar). The temperature was fixed at the optimum value of the first step (50 °C) in order to minimize energy consumption due to heating or cooling of the system. Three different percentages of ethanol, corresponding to low (15%), medium (45%) and high (75%) levels were tested to fully study the possible advantages offered by this intermediate process.</p><p>Steps 3 and 4 were performed under PLE conditions, using ethanol and water, respectively, which implies an increasing order of polarity. At this point, different bioactive compounds were sought such as polar lipids, proteins and carbohydrates. Moreover, the final objective was to extract all the valuable components contained in the microalgae biomass attaining different fractions and minimizing the leftovers. The extraction values selected included a pressure of 100 bar and a temperature of 80 °C. These values were maintained relatively low in order to avoid degradation of compounds.</p><p>The scheme of the overall extraction process, along with the target compounds expected in each step is depicted in Fig. 2. 2 and 3. These are corresponding to the pigments detected in steps 1 and 2, ScCO 2 extraction and CXE extraction using 45% ethanol, respectively. ScCO 2 extracted mainly carotenoids from I. galbana (see Table 2). Fucoxanthin isomers ( peaks 4-7) and diadinoxanthin derivatives ( peaks 11-13) could be tentatively assigned due to their UV and MS/MS spectra. Besides, pheophytin a′ ( peak 23) was tentatively identified in the extract in agreement with its [M + H] + ion. Other carotenoids also present in the extract could not be positively identified due to the lack of enough ionization efficiency. Chromatographic profiles are shown in Fig. S1 (ESI, † step 1).</p><p>Since the percentage of ethanol in the CXE step did not affect the chromatographic profile, the HPLC-DAD chromatogram obtained for 45% ethanol in CO 2 has been used to illustrate the identification of carotenoids and chlorophylls in the second step of the sequential extraction (see Fig. S1, step 2, ESI †). Fucoxanthin was again the main compound present in the extracts, but several chlorophylls and chlorophyll derivatives were also detected (see Table 3). The protonated molecule [M + H] + was not observed for any of the fucoxanthin isomers. Interestingly, E-and 13(′)Z-fucoxanthin isomers showed the same parent ions, corresponding to the dehydrated molecule ([M + H-H 2 O] + ) and a fragment corresponding to a loss of 78 Da consistent with the sequential losses of the C-3 carbomethoxy group (acetic acid) and a water molecule. MS/MS analyses of these ions exhibited a loss of 92 Da that could be attributed to the loss of toluene from the polyene chain. Fucoxanthin metabolite fucoxanthinol (Table 3, peak 3) was tentatively identified by its protonated molecule. MS/MS analysis of fucoxanthinol led to dehydration of the molecule.</p><p>Diadinoxanthin ( peak 11) was also identified in the extracts by the presence of its typical ions at m/z 583.6 ([M + H] + ) and m/z 565.6 ([M + H-H 2 O] + ). The same MS spectrum was obtained for peaks 12 and 13, but for these peaks, a hypso- chromic shift of 15-20 nm was observed in all UV maxima. Therefore, these compounds can be tentatively identified as 5,8-epoxy derivatives of diadinoxanthin, according to Crupi et al. 34 Chlorophyll a and its epimer chlorophyll a′ ( peaks 15 and 17) lost the phytyl group (C 20 H 39 ) 35 and showed the same fragment, m/z 615.5, which corresponds to the chlorophyllides a and a′, respectively. Besides, the loss of the phythyl group (C 20 H 39 ) can also be used for the identification of pheophytins a and a′ ( peaks 22 and 23). 36 The identification of chlorophyll a in the extract was confirmed by using a commercial standard, and thus peak 10 was assigned to chlorophyll a′. The same elution order was considered for pheophytins a and a′. Several chlorophyll c pigments were tentatively identified in the extracts, although no information could be obtained from the MS in this case. Nevertheless, they were grouped in chlorophyll c 1 -like ( peak 24) and chlorophyll c 2 -like ( peaks 26 and 28) compounds, on the basis of their UV-VIS spectra, since the band ratios (II/III) and the position of maxima are different. The ratios of band II (at ∼630 nm) to band III (at ∼580 nm) intensities are >1 for Chl c 1 -like chromophores, ≈1 for Chl c 2like chromophores and <1 for Chl c 3 -like chromophores. 37 3.3.2. Quantification of total carotenoids, total chlorophylls and fucoxanthin in the different extracts obtained (steps 1-4). Fig. S1 (ESI †) shows the chromatographic profile obtained for the analysis of pigments (carotenoids and chlorophylls) in the extracts obtained for the four different extraction steps. In general, the concentration of carotenoids (mainly fucoxanthin) in the second extraction step is higher compared to the first step, although the amount of chlorophylls (marked with an asterisk) is also higher. The main compounds determined correspond to carotenoids, most-notably fucoxanthin isomers, E-fucoxanthin being the most abundant compound by far. It is interesting to note that different bioactivities have been assigned to the fucoxanthin isomers, as 13Z and 13′Z isomers, which exert higher antiproliferative effects in various cancer cell lines, compared to the E isomer. 38 For this reason, the quantification of each isomer should be of interest. Bearing this in mind, the different fucoxanthin isomers were quantified for the different experimental conditions, in order to evaluate the difference (if any) in selectivity achieved under the different extraction conditions.</p><p>The vast majority of total fucoxanthin is formed by E-fucoxanthin, while the amount of the other isomers remains very low under the different extraction conditions, except for extractions at 300 bar and 60 °C (data not shown). Under these con-ditions, the sum of 13(′)Z isomer concentration is higher, although still extremely low compared to E-isomers, which could be due to an increase in their solubility under these extraction conditions. In general, the highest extraction of fucoxanthin occurred at 300 bar and 50 °C, over the experimental range that was explored.</p><p>Table 4 shows the quantification of fucoxanthin isomers, the total carotenoid amount and the total chlorophyll content of the extracts obtained after each step of the sequential integrated process. The highest total chlorophyll content (expressed as chlorophyll a) was found in the CXE extract obtained using 15% ethanol, while the highest content of total carotenoids (expressed as fucoxanthin) was obtained in the CXE extract containing 75% ethanol. In any case, total carotenoids and chlorophylls extracted with carbon dioxide expanded ethanol were higher than total carotenoids and chlorophylls extracted with acetone (146.58 vs. 57.19 mg per g extract and 96.56 vs. 44.48 mg per g extract, respectively, for carotenoids and chlorophylls). On the other hand, the highest content of E-fucoxanthin was found in the CXE extract containing 45% ethanol (40.69 ± 2.28 mg per g extract), and is comparable to the concentration of E-fucoxanthin obtained with acetone conventional solid-liquid extraction (44.60 ± 2.68 mg per g extract).</p><p>Regarding Z isomers, the sum of 13Z + 13′Z isomers, as well as the amount of 9(′)Z isomers, is higher in acetone extracts, compared to CXE extracts. The content of fucoxanthinol, however, is comparable between acetone and CXE extracts. On the other hand, pooling both ethanol containing extracts (steps 2 and 3), the content of fucoxanthin isomers surpasses acetone extractions, thus validating the use of this new type of green technology for extraction of high value-added compounds.</p><p>It is worth mentioning that the content of E-fucoxanthin in any of the CXE extracts (36-43 mg g −1 ) was higher than that previously reported for I. galbana using acetone extraction 39 and for Isochrysis sp., using conventional extraction with methanol. 34 3.3.3. Lipid profile at the different steps of the integrated process. The method employed for the analysis of all sequential extracts allows, not only the separation of lipid classes, but also further separation of polar lipidsas phospholipidsin the same run. An example of the chromatograms obtained for each sequential step is shown in Fig. 3, where it is clearly shown that different lipid profiles were achieved for each extraction step. Chromatograms have been divided in three segments in order to facilitate the discussion of the results. In the first segment, eluted triacylglycerides (TAGs); medium polar lipids as mono-(MAGs) and diacylglycerides (DAGs) eluted in the second segment, together with free fatty acids (FFAs), carotenoids and chlorophylls; finally, polar lipids eluted in the third segment of the chromatogram. In the first step of the sequential process, corresponding to ScCO 2 extraction, TAGs were mainly extracted, while polar lipids are not detected at all. In the second (CXE) and third (PLE with 100% ethanol) steps, a similar profile is observed: medium polar compounds and polar lipids were extracted, with a small residue of triacylglycerides. Finally, as expected, lipids were not found in the water extracts obtained in the last step. protein), thus confirming that the percentage of ethanol used in the previous step (CXE) did not affect the extraction, although a slightly higher amount of total protein is observed for CXE-75% ethanol compared to the others. These results are displayed in Fig. 4. As can be seen, the subsequent water PLE extracts showed approximately double the amount of total protein (14-18% (w/w)) than the PLE-ethanol extracts.</p><p>The sugar composition of ethanol and water PLE extracts was similar. Detailed results are shown in Table 5. Fucose, glucuronic acid, galacturonic acid, N-acetylglucosamine, N-acetylgalactosamine, glucosamine and galactosamine not detected. Xylose (only present in CXE75-water) and mannose were found only in water extracts. A slightly higher amount of total sugars can be observed in the extracts obtained after CXE-75% ethanol compared to the extracts obtained after 15% and 45% ethanol. In any case, the total amount of sugars did not exceed 10% of the extract weight (see Fig. 4). Galactose is the main sugar in ethanol extracts, ranging from 5.69 to 6.68% of dry weight. In water extracts, galactose is present in a smaller amount (1.44-2.83% dry weight), while glucose is the main sugar found (3.91-4.11% dry weight).</p><p>The results corresponding to the antioxidant capacity assay (expressed as TEAC, mmol of Trolox per g sample), are shown in Table 4. As can be seen, ethanol extracts contained twice the activity as water extracts. This observation cannot be directly related to the total content of sugars, which was similar in both water and ethanol extracts. However, a different composition of sugars in ethanol and water extracts can be expected. Since ethanol is commonly used to precipitate polymeric sugars, monomers or oligomers may be preferably present in ethanol extracts, while oligomeric and polymeric sugars can be expected in water extracts. The total content of protein was lower in ethanol extracts, but proteins extracted in ethanol can be different from proteins present in water extracts, and therefore the activity can be different, too. On the other hand, the amount of fucoxanthin and total carotenoids in ethanol extracts is more than two times higher than the concentration of carotenoids in water extracts. Consequently, despite the fact that there is no linear relationship between the carotenoid content and antioxidant activity, data seem to indicate that higher antioxidant activity in ethanol extracts might be related to the fucoxanthin and fucoxanthin isomer content; Zhang et al. 40 and Sachindra et al. 41 previously confirmed the potent antioxidant activity of these compounds by using different methods.</p><!><p>A downstream processing platform is described for the first time to extract bioactive compounds from the microalga I. galbana using GRASgenerally recognized as safesolvents and pressurized technologies. Extractions were performed in four sequential steps using (1) supercritical CO 2 (ScCO 2 ), (2) ScCO 2 /ethanol (Gas Expanded Liquids, GXLs), (3) PLE with pure ethanol, and (4) PLE with pure water as solvents, considering the residue of the previous extraction step as the raw material for extraction. The results obtained showed that the extraction process was partially selective according to the polarity of the solvent/mixture of solvents used. ScCO 2 extracts were rich in triacylglycerides and showed less carotenoid and chlorophyll contents than ethanolic extracts. The main carotenoid identified was fucoxanthin which was found in highest amount in CXE extracts obtained with 45% ethanol. Steps 3 and 4 provide with extracts enriched in proteins and carbohydrates. Further studies should be carried out to determine more in depth the composition of the obtained extracts and their relationships with the antioxidant activity. Also, from our point of view, a scaling up to the industrial level of the process will be of interest.</p>

Royal Society of Chemistry (RSC)

Effects of π-Extension on Pyrrole Hemithioindigo Photoswitches

The most red-shifted hemithioindigo photoswitches have been identified through systematic introduction of aryl units to a parent pyrrole hemithioindigo photoswitch. Increasing the size of the 5'-aryl substituent is ineffective at producing further redshifted chromophores. A second generation of 3',5'-diarylated photoswitches which possess increased tunability is reported. Experimental and computational evidence indicates the 4' position is electronically isolated from the bulk of the conjugated system.

effects_of_π-extension_on_pyrrole_hemithioindigo_photoswitches

Introduction:<!>Results and Discussion<!>Conclusion<!>General Experimental Procedure<!>Materials<!>Instrumentation<!>General Procedure for Suzuki coupling with solid aryl bromides<!>General Procedure for Suzuki coupling with liquid aryl bromides<!>General Procedure for synthesis of ArylPyrrole-HTI photoswitiches<!>Precursor Synthesis<!>5-(naphthalen-1-yl)-1H-pyrrole-2-carbaldehyde (SI-1):<!>Photoswitch 2e:<!>Photoswitch 3a:<!>Photoswitch 3d:

<p>Visible-light activated small molecule photoswitches comprise a class of molecular machines that are the subject of a great deal of interest in fields such as drug delivery, data storage, and photomechanical polymers. 1 Seminal advances in this field were accordingly recognized with the Nobel Prize in Chemistry in 2016. 2 A particular subclass of these compounds, E/Z-type photoswitches, are of particular interest for controlling biological systems due to the large geometric change conferred by double-bond isomerization. 3 Hemithioindigo photoswitches have recently received considerable attention in part due to their longer wavelength absorption relative to the more well explored azobenzenes. 4 Our laboratory has recently reported a new class of E/Ztype photoswitches which are designed to possess a key intramolecular hydrogen-bonding interaction in only one of the two isomeric states (Figure 1). 5 As a result of this interaction, these pyrrole hemithioindigo (PHTI) photoswitches can undergo quantitative photoisomerizations using visible light for both isomerization reactions. While the photoswitches we reported undergo quantitative isomerization using blue light for ZàE photoisomerization and red light for EàZ photoisomerization, it would be ideal to induce both isomerizations using light in the infrared window for subsurface drug delivery applications. 6 The amino-substituted photoswitches described in our previous report undergo isomerization at longer wavelengths than their oxygen-substituted analogs, however, they also undergo photobleaching upon repeated irradiation. Therefore, we decided not to test even more electron rich substrates due to photobleaching concerns. Rather, we chose to explore the effects of creating more conjugated π-systems as a strategy towards longer-wavelength photoswitches. 7 Upon reinvestigation of the previously described synthesis of arylpyrrole HTIs, it was found that the condensation of appropriate pyrrole-2-carboxaldehydes with benzothiophen-3-one was adequately catalyzed by piperidine, rather than using stoichiometric DBU. This obviated the need for removal of the DBU-water adduct and provided improved yields and purity (Figure 2). For example, while 2a was previously obtained in 44% using DBU as base, 2b-h were each obtained in yields not lower than 76%. If was found that replacement of the 5'-phenyl group (2a) with a 5'-(1-naphthyl) moiety (2b) provided a photoswitch with shorter wavelength absorption maxima. 4 The 2-naphthyl isomer 2c, proved superior, affording longer absorption maxima than 2a or 2b. Anthracyl derivatives 2d and 2e were prepared, and a similar trend was observed, with the longer end-to-end 2-anthracyl PHTI 2e absorbing at longer wavelength than the 9-anthracyl analog 2d (Z: 474 nm à 507 nm; E: 525 nm à 556 nm). This came at the cost of a reduced bathochromic shift and poor photostationary state selectivity. Further extension of the π-system with a pendant 1-pyrenyl moiety (2f) provided only a minimal redshift compared to the 5'-phenyl PHTI.</p><!><p>Considering the drawbacks of such polycyclic arenes, namely poor solubility and step-intensive routes for tuning polycyclic aromatic hydrocarbons via substituent effects, we decided against further exploration of these avenues of π-extension.</p><p>At this point instead of employing larger fused aromatics, we turned our attention to exploring biphenyl type moieties. In our previous report, we had previously observed that the introduction of an aromatic group at the 5'-position not only resulted in a redshift, but also an augmented bathochromic shift relative to a photoswitch without substitution on the pyrrole. It had been hypothesized that this increased bathochromic shift was the result of the increased change in geometry of the longer π-system. Therefore, 2g was synthesized to see if this effect would manifest itself further. However, 2g was found to possess a redshift of only 4-6 nm of either isomer was observed relative to the 5'-phenyl PHTI (2a). Introduction of an alkynyl linker (2h) led to a further small redshift, potentially due to diminished out-of-plane distortion of the two arenes. Unfortunately, these substantial increases in end-to-end distance change upon isomerization did not translate to a substantial increase in the bathochromic shift of the two isomers. Although some redshifting was observed with these compounds, the solubility and synthetic challenges associated with the fused arenes are still present, albeit to a somewhat lesser degree. Therefore, we hypothesized that instead of extending the 5'-substituent, installation of an additional arene moiety on the pyrrole could induce the desired redshift. Synthesis of the 4,5-diaryl photoswitches 4a-b was accomplished by double Suzuki-Miyaura coupling of 4,5dibromopyrrole-2-carboxaldehyde and then aldol condensation with benzothiophen-3-one. Diphenyl photoswitch 4a (Figure 3), however, showed no discernible redshifting over its monoarylated congener 2a. Installation of electron-donating methoxy substituents at the para position of both arenes also proved inferior to the single 5'-p-methoxy photoswitch. Steric distortion between the 4',5'-diaryl groups may lead to these poor properties, thus, a library of 3',5'-diaryl photoswitches was synthesized. The precursor diarylpyrrole-2carboxaldehydes are conveniently synthesized from a chalcone starting material, enabling the synthesis of differentially substituted diarylpyrrole photoswitches with complete regioselectivity. 8 Fortuitously, as shown in Figure 4, it was found that introduction of a 3'-aryl group (3a) provided a 10 nm redshift when compared to 2a (Z: 491 nm à 501 nm; E: 550 nm à 560 nm). In addition to this redshift, introduction of a methoxy to the 3'-arene (3b) substituent provides a 4 nm redshift, roughly half as large of the 10 nm shift induced by addition of a methoxy group to the 5'-arene (3c). Remarkably, these substituent effects appear to be additive, with bis-p-methoxy photoswitch 3d displaying a redshift of approximately 15 nm relative to the unsubstituted 3a. Like the previously disclosed first-generation 5'-aryl photoswitches, these compounds undergo highly selective photoisomerization in both directions using visible light. These photoswitches are also considerably more soluble in organic solvents. This increase in solubility is sufficient for convenient observation and quantitation of the photoisomerization via 1 H NMR (Figure 5). As described above, our initial hypothesis was that out-of-plane distortions between the pendant aryl groups in 4a and 4b lead to diminished conjugation such that two non-planar aryl groups provided similar redshifting to a single, more co-planar π-extension. Separating these groups as in the series 3a-d allowed their effects to be additive. However, when monoarylated photoswitches 5 and 6 were synthesized, we were surprised to observe that even in the absence of an out-of-plane distortion, 4'-phenyl switch 5 was markedly less redshifted than its 5'-phenyl isomer 2a (Figure 6). Photoswitch 6 was slightly redshifted relative to 5, although still substantially blueshifted relative to 2a. With these observations in mind, we turned to DFT calculations for insight into the origin of these electronic effects. Structures for photoswitches 5, 6, 2a, 4a, and 3a, were optimized at the B3LYP/6-31G* level of theory. While the out-of-plane distortions in 4a were apparent, another</p><p>striking trend was observed. Regardless of the presence of other arenes, the coefficients of the LUMO on the 4' aryl groups were minimal. This indicates that electronic insulation of the 4' position is responsible for the poor performance of photoswitches possessing aryl groups at this position. The extent of the LUMO on 3' phenyl groups was diminished but non-zero, in line with the reduced redshifts observed by introduction of electron-donating substituents at this position (3b, 3d). However, for PHTIs, TD-DFT calculations generally underestimate the absorbance maxima by around 60-70 nm.</p><!><p>In conclusion, we have mapped the effects of π-extension on the pyrrole moiety of pyrrole hemithioindigos. Previously reported 5'-arylated pyrrole hemithioindigos are a uniquely selective class of visible-light photoswitches. Substitution of the pyrrole unit with an aryl group leads to increasing conjugation in the following order: 4' < 3' < 5'. Experimental and computational</p><p>evidence suggests the 4' position is mostly electronically isolated from the system. Combining 3' and 5' aryl substitution results in a system with improved solubility that maintains the high selectivity of the first generation while providing more opportunities for tuning and derivatization. Importantly, the computational results described herein demonstrate that this system is amenable to redshift predictions based on DFT calculations.</p><!><p>All reactions were carried out under an inert nitrogen atmosphere with dry solvents under anhydrous conditions unless otherwise stated. All reactions were capped with a rubber septum, or Teflon-coated silicon microwave cap unless otherwise stated. Stainless steel cannula or syringe were used to transfer solvent, and air-and moisture sensitive liquid reagents. Reactions were monitored by thin-layer chromatography (TLC) and carried out on 0.25 mm Merck silica gel plates (60F-254) using UV light as the visualizing agent and potassium permanganate, an acidic solution of p-anisaldehyde, a solution of 2,4-dinitrophenylhydrazine, or vanillin as developing agents. Flash column chromatography employed SiliaFlash ® P60 (40-60 µm, 230-400 mesh) silica gel purchased from SiliCycle Inc.</p><!><p>All reaction solvents were purified using a Seca solvent purification system by Glass Contour, except for n-butanol. Anhydrous n-butanol was purchased from Sigma-Aldrich and degassed by bubbling N 2 through the solvent while sonicating for 30 minutes. Pd(OAc) 2 was purchased from Strem Chemical Inc. XPhos (CAS: 564483-18-7) was purchased from Oakwood Chemical. All other reagents were used as received without further purification, unless otherwise stated.</p><!><p>All new compounds were characterized by means of 1 H-NMR, 13 C-NMR, FTIR (thin film), and HR-MS. Copies of the 1 H-and 13 C-NMR spectra can be found at the end of each experimental procedure. NMR spectra were recorded using a Varian 400 MHz NMR spectrometer, Varian 500 MHz NMR spectrometer, or a Varian 600 MHz NMR spectrometer. All 1 H-NMR data are reported in δ units, parts per million (ppm), and were calibrated relative to the signals for residual dichloromethane in CD 2 Cl 2 (5.32 ppm), residual chloroform (7.26 ppm) in deuterochloroform (CDCl 3 ), or residual DMSO (2.50 ppm) in DMSO-d 6 . All 13 C-NMR data are reported in ppm relative to CD 2 Cl 2 (54.0 ppm), CDCl 3 (77.16 ppm), or DMSO-d 6 (39.52) and were obtained with 1 H decoupling unless otherwise stated. The following abbreviations or combinations thereof were used to explain the multiplicities: s = singlet, d = doublet, t = triplet, q = quartet, br = broad, m = multiplet, and a = apparent. All IR spectra were taken on an FT-IR/Raman Thermo Nicolet 6700. High resolution mass spectra (HR-MS) were recorded on a Bruker microTOF mass spectrometer using ESI-TOF (electrospray ionization-time of flight). All UV/Vis spectra were taken on a Cary 3E Spectrophotometer using quartz cuvettes purchased from Starna Cells (P/N: 29-Q-10) and spectrometric or HPLC grade solvents. Photoirradiation was carried out with LEDs purchased from Mouser Electronics (405, 460, 523, 567, 590, 623, 660, and 740 nm) or Roithner-LaserTechnik GmbH (420, 490, 505, 690, and 720 nm). For photostationary state determination, samples were irradiated in borosilicate glass HPLC vials purchased from Thermo Scientific (C4000-1). For part numbers of individual LEDs and detailed description of the irradiation setup, see the accompanying Supplementary Information. HPLC quantitation of photostationary state composition was performed using an Agilent 1260 HPLC with a Chiralpak IA column ((250 x 4.6mm, 5µM particle size).</p><!><p>To a flame-dried 5 mL microwave vial flask equipped with a magnetic stir bar was added N-Bocpyrrole-2-boronic acid (316 mg, 1.5 mmol, 1.5 equiv), Pd(OAc) 2 (4.5mg, 0.02 mmol, 0.02 equiv), XPhos (19.0 mg, 0.04 mmol, 0.04 equiv), K 3 PO 4 (424 g, 2.0 mmol, 2.0 equiv), and aryl bromide (1.0 mmol, 1.0 equiv). The flask was evacuated and backfilled with nitrogen three times, and then the gas line adapter was quickly replaced with a rubber septum and a balloon of nitrogen. To the flask was added degassed (by sonication for 30 minutes with N 2 sparging), anhydrous n-butanol [2 mL (0.5 M in ArBr)]. The heterogeneous reaction mixture was stirred vigorously for 2 hours and then poured into ethyl acetate (~20 mL). This mixture was filtered through a pad of silica and concentrated under reduced pressure by rotary evaporation. This product was used without further purification.</p><p>To the flask containing the crude product of the crude Suzuki coupling product was added an ovendried magnetic stir bar. The flask was evacuated and backfilled with nitrogen three times, and then the gas line adapter was quickly replaced with a rubber septum and a balloon of nitrogen. To the flask was added anhydrous THF (10 mL) and then NaOMe (5 wt. % in MeOH; 342 µL, 1.5 mmol, 1.5 equiv). The reaction mixture was stirred until no more starting material was observed by TLC (30 -60 minutes). The reaction was quenched by the addition of sat. aq. NH 4 Cl (10 mL). The organic layer was separated, and the aqueous layer was extracted with Et 2 O (3 x 10 mL). The combined organic layers were then washed water (1 x 10 mL), brine (1 x 10 mL) and dried over anhydrous Na 2 SO 4. . The combined organic layers were then filtered and concentrated under reduced pressure by rotary evaporation. This product was used without further purification.</p><p>The crude product from the deprotection was dried by azeotropic distillation with benzene under reduced pressure by rotary evaporation three times. This flask was then evacuated and backfilled with nitrogen, and then the gas line adapter was quickly replaced with a rubber septum and a balloon of nitrogen. To this flask was added anhydrous CH 2 Cl 2 (3 mL) and the flask was sonicated to dissolve the solid.</p><p>To a flame-dried 25mL round bottomed flask equipped with a magnetic stir bar was added anhydrous CH 2 Cl 2 (1 mL), POCl 3 (98 µL, 1.05 mmol, 1.05 equiv), and anhydrous DMF (92µL, 1.2 mmol, 1.2 equiv). After stirring for 5 minutes, the solution of 2-arylpyrrole in CH 2 Cl 2 was transferred by syringe to this flask. Upon addition of the arylpyrrole, the solution immediately became brightly colored (color depending on substrate).</p><p>After stirring for 8-16 hours, the reaction was concentrated first under a stream of N 2 and then under reduced pressure. When no solvent remained, the flask was backfilled with N 2 and then the gas line adapter was quickly replaced with a rubber septum and a balloon of nitrogen. To this flask was added THF (2 mL) and 3M NaOH (aq) (2 mL). This biphasic mixture was stirred vigorously for 30-60 minutes. To the flask was added H 2 O (5 mL) and Et 2 O (5 mL). The organic layer was separated, and the aqueous layer was extracted with Et 2 O (3 × 10 mL). The combined organic layers were washed with water (1 × 20 mL) and brine (1 × 20 mL). The combined organic layers were then dried over anhydrous Na 2 SO 4, filtered and concentrated under reduced pressure by rotary evaporation. Purification by flash column chromatography on silica gel afforded the corresponding aldehydes.</p><!><p>To a flame-dried 5 mL microwave vial equipped with a magnetic stir bar was added N-Boc-pyrrole-2-boronic acid (316 mg, 1.5 mmol, 1.5 equiv), Pd(OAc) 2 (4.5mg, 0.02 mmol, 0.02 equiv), XPhos (19.0 mg, 0.04 mmol, 0.04 equiv), and K 3 PO 4 (424 g, 2.0 mmol, 2.0 equiv),. The flask was evacuated and backfilled with nitrogen three times, and then the gas line adapter was quickly replaced with a rubber septum and a balloon of nitrogen. To the flask was added degassed (by sonication for 30 minutes with N 2 sparging), anhydrous n-butanol [2 mL (0.5 M in ArBr)] and aryl bromide (1.0 mmol, 1.0 equiv). The heterogeneous reaction mixture was stirred vigorously for 2 hours at room temperature and then poured into ethyl acetate (~20 mL). This mixture was filtered through a pad of silica and concentrated under reduced pressure by rotary evaporation. This product was used without further purification as described in the general procedure above.</p><!><p>To a 5 mL flame-dried microwave flask was added benzo [b]thiophen-3(2H)-one (0.24 mmol, 0.12 equiv) and 5-aryl-2-formylpyrrole (0.2 mmol, 0.1 equiv). The flask was capped with an aluminum-PTFE crimp cap, sealed, and evacuated and backfilled with nitrogen three times. To the flask was then added anhydrous toluene (2 mL, 0.1 M in aldehyde) and piperidine (10 µL, 0.1 mmol, 0.5 equiv). The flask was transferred to a pre-warmed oil bath set to 111 ˚C and stirred for two hours. After two hours the flask was removed from the oil bath and cooled to room temperature and then to 0 ˚C in a water-ice bath. To the flask was added hexanes (5 mL) and the flask was allowed to sit for an addition 10-30 minutes. The mixture was the filtered, and the precipitate was then triturated with hexanes to until the filtrate ran clear to provide the pure product as a red, blue, or purple solid depending on the substrate.</p><!><p>Benzo [b]thiophen-3(2H)-one, 4,5-bis(4-methoxyphenyl)-pyrrole-2-carboxalehyde, and 4phenyl-pyrrole-2-carboxaldehyde, and 3-phenyl-pyrrole-2-carboxaldehyde were synthesized according to published procedures.</p><!><p>Prepared according to general procedure. Purification by flash column chromatography on silica gel (hexanes/Et 2 O = 100:0 to 80:20) afforded the title compound (158 mg, 71%) as a pink solid. Rf: 0.32 (hexanes:Et 2 O = 1:1) 1 H NMR (600 MHz, CDCl 3 ): δ 9.59 (s, 1H), 9.44 (br s, 1H), 8.20 -8.15 (m, 1H), 7.95 -7.89 (m, 2H), 7.60 -7.49 (m, 4H), 7.13 (dd, J = 3.9, 2.5 Hz, 1H), 6.64 (dd, J = 3.9, 2. 5 To a flame-dried 20 mL microwave vial equipped with a magnetic stir bar was added N-4,5-dibromopyrrole-2-carboxaldehyde (121 mg, 0.48 mmol, 1.0 equiv), phenylboronic acid (292 mg, 2.4 mmol, 5.0 equiv), Pd(PPh 3 ) 4 (56 mg, 0.048 mmol, 0.10 equiv), and Na 2 CO 3 (305 mg, 2.88 mmol, 6.0 equiv). The flask was evacuated and backfilled with nitrogen three times, and sealed with an aluminum crimp cap. To the flask was added water (4.2 mL) and dioxane (4.2 mL, final concentration ~0.6M in pyrrole). The reaction apparatus was then transferred into a pre-heated oil bath and stirred at 80˚C for two hours. After two hours the reaction was cooled to room temperature, poured into H 2 O (20 mL), and extracted with EtOAc (3 × 20 mL). The combined organic layers were washed with brine (50 mL), dried over anhydrous sodium sulfate, filtered, and concentrated under reduced pressure by rotary evaporation to provide a crude brown solid. Purification by flash column chromatography on silica gel (Et 2 O/hexanes = 0/10 to 2/8) afforded SI-8 (107.2 mg, 73%) as a tan solid. Rf: 0.37 (hexanes:Et 2 O = 1:1) To a flame-dried 5 mL microwave vial equipped with a magnetic stir bar was added anhydrous CH 2 Cl 2 (1 mL), POCl 3 (98 µL, 1.05 mmol, 1.05 equiv), and anhydrous DMF (92µL, 1.2 mmol, 1.2 equiv). After stirring for 5 minutes, a solution of 2,4-diphenylpyrrole (219 mg, 1.0 mmol 1.0 equiv) in CH 2 Cl 2 (3 mL) was transferred by syringe to this flask. After stirring for 16 hours, the reaction was concentrated first under a stream of nitrogen and then under reduced pressure. When no solvent remained, the flask was backfilled with nitrogen and then the gas line adapter was quickly replaced with a rubber septum and a balloon of nitrogen. To this flask was added THF (2 mL) and 3M NaOH (aq) (2 ml). This biphasic mixture was stirred vigorously for 30-60 minutes. To the flask was added H 2 O (5 mL) and Et 2 O (5 mL). The organic layer was separated, and the aqueous layer was extracted with Et 2 O (3 × 50 mL). The combined organic layers were washed with water (1 × 100 mL) and brine (1 × 100 mL). The combined organic layers were then dried over anhydrous Na 2 SO 4 , filtered and concentrated under reduced pressure by rotary evaporation. Purification by flash column chromatography on silica gel (hexanes/Et 2 O = 100:0 to 70:30) afforded the title compound (132 mg, 53%) as a pink solid. Rf: 0.39 (hexanes:Et 2 O = 1:1) 1 H NMR (600 MHz, CDCl 3 ): δ 9.65 (s, 1H), 9.49 (br s, 1H), 7.65 (d, J = 8.4 Hz, 2H), 7.55 (d, J = 8.2 Hz, 2H), 7.47 (at, J = 7.6 Hz, 4H), 7.43 -7.35 (m, 2H), 6.74 (dd, J = 2.9, 1. 2 Aldehyde SI-10 was prepared from 2.0 mmol 3-(4-methoxyphenyl)-4-nitro-1phenylbutan-1-one according to O'Shea's procedure. Without purification, this crude diarrylpyrrole was then formylated as per the procedure for compounds SI-1-SI-7. Purification by flash column chromatography on silica gel (hexanes/Et 2 O = 100:0 to 70:30) afforded the title compound (164 mg, 29.5% over three steps) as a pink solid. Rf: 0.25 (hexanes:Et2O = 1:1) 1 H NMR (600 MHz, CDCl 3 ): δ 9.62 (d, J = 1.1 Hz, 1H), 9.39 (s, 1H), 7.63 (d, J = 7.9 Hz, 2H), 7.52 -7.43 (m, 4H), 7.43 -7.34 (m, 1H), 7.04 -6.92 (m, 2H), 6.69 (dd, J = 2.8, 1.1 Hz, 1H), 3.87 (s, 3H). 13 C NMR (151 MHz, CDCl 3 ): δ 179. Aldehyde SI-11 was prepared from 1.0 mmol 1-(4-methoxyphenyl)-4-nitro-3phenylbutan-1-one according to O'Shea's procedure. Without purification, this crude diarrylpyrrole was then formylated as per the procedure for compound SI-1-SI-7. Purification by flash column chromatography on silica gel (hexanes/Et 2 O = 100:0 to 70:30) afforded the title compound (68 mg, 24.5% over three steps) as a pink solid. Rf: 0.25 (hexanes:Et 2 O = 1:1) 1 H NMR (600 MHz, CDCl 3 ): δ 9.61 (s, 1H), 9.43 (br s, 1H), 7.65 -7.57 (m, 2H), 7.55 (dd, J = 6.9, 1. 5 Aldehyde SI-12 was prepared from 2.0 mmol 3-(4-methoxyphenyl)-4-nitro-1phenylbutan-1-one according to O'Shea's procedure.* Without purification, this crude diarrylpyrrole was then formylated as per the procedure for compound SI-1-SI-7. Purification by flash column chromatography on silica gel (hexanes/Et2O = 100:0 to 50:50) afforded the title compound (269.6 mg, 17% over four steps) as a purple solid. *Note: In a variation from O'shea's procedure, the Paal-Knorr cyclization step was conducted at 50˚C for 30 minutes to minimize degradation, and then immediately formylated. Rf: 0.11 (hexanes:Et 2 O = 1:1) 1 H NMR (600 MHz, CDCl 3 ): δ 9.58 (s, 1H), 9.35 (s, 1H), 7.57 (d, J = 8. 7</p><!><p>Prepared according to general procedure. Obtained as a red solid (62.0 mg, 77%). 1 H NMR 1 H NMR (600 MHz, DMSO-d 6 ) δ 12.46 (br s, 1H), 8.57 (s, 2H), 8.47 (s, 1H), 8.17 (d, J = 8.9 Hz, 1H), 8.13 (d, J = 7.3 Hz, 1H), 8.10 -8.07 (m, 1H), 8.01 (s, 1H), 7.95 (d, J = 8.9 Hz, 1H), 7.84 (d, J = 7.6 Hz, 1H), 7.81 (d, J = 7.9 Hz, 1H), 7.71 (t, J = 7.5 Hz, 1H), 7.57 -7.47 (m, 2H), 7.41 (t, J = 7.4 Hz, 1H), 7.20 -7.18 (m, 1H), 7.00 -6.87 (m, 1H). 13 C NMR (126 MHz, DMSO-d 6 @ 120˚C): 186.9, 144.</p><!><p>Prepared according to general procedure (0.25 mmol scale of aldehyde). Obtained as a red/purple solid (77.0 mg, 73 %). 1 H NMR (500 MHz, CD 2 Cl 2 ): δ 8.03 (d, J = 7.9 Hz, 1H), 7.90 (d, J = 7.7 Hz, 2H), 7.54 (ddt, J = 20.5, 14.7, 7.3 Hz, 8H), 7.42 (q, J = 7.1 Hz, 2H), 7.35 (d, J = 3. 4</p><!><p>Prepared according to general procedure. Obtained as a purple solid (67.5 mg, 77%).</p>

ChemRxiv

Thorium–ligand multiple bonds via reductive deprotection of a trityl group

Reaction of [Th(I)(NR 2 ) 3 ] (R ¼ SiMe 3 ) (2) with KECPh 3 (E ¼ O, S) affords the thorium chalcogenates, [Th(ECPh 3 )(NR 2 ) 3 ] (3, E ¼ O; 4, E ¼ S), in moderate yields. Reductive deprotection of the trityl group from 3 and 4 by reaction with KC 8 , in the presence of 18-crown-6, affords the thorium oxo complex, [K(18crown-6)][Th(O)(NR 2 ) 3 ] (6), and the thorium sulphide complex, [K(18-crown-6)][Th(S)(NR 2 ) 3 ] (7),respectively. The natural bond orbital and quantum theory of atoms-in-molecules approaches are employed to explore the metal-ligand bonding in 6 and 7 and their uranium analogues, and in particular the relative roles of the actinide 5f and 6d orbitals.

thorium–ligand_multiple_bonds_via_reductive_deprotection_of_a_trityl_group

Introduction<!>Results and discussion<!>View Article Online<!>Conclusions<!>Experimental<!>[Th(Cl)(NR 2 ) 3 ] (1)<!>X-ray crystallography<!>Computational details

<p>The study of actinide-ligand multiple bonds has intensied in recent years due to the need to understand the extent of both forbital participation and covalency in actinide-ligand bonding. [1][2][3][4][5][6][7][8][9] In this regard, the past ten years have seen considerable progress in the synthesis of oxo, [10][11][12][13] imido, [14][15][16][17][18][19][20][21][22] carbene, [23][24][25][26][27][28][29] and nitrido complexes of uranium. [30][31][32][33][34][35] More recently, several terminal phosphinidene 36,37 and chalcogenido (S, Se, Te) complexes of uranium have also been isolated, [38][39][40][41][42] demonstrating that this chemistry can be extended to the heavier main group elements.</p><p>Despite these advancements, multiply-bonded complexes of the other actinides remain rare. 43 Only one thorium terminal oxo complex is known, namely, [h 5 -1,2,4-t Bu 3 C 5 H 2 ] 2 -Th(O)(dmap) (dmap ¼ 4-dimethylaminopyridine), which was recently reported by Zi and co-workers. 44 In addition, a handful of terminal imido complexes have been isolated, 45 including [Cp* 2 Th(NAr)(THF)] (Ar ¼ 2,6-dimethylphenyl), which was reported by Eisen and co-workers in 1996. 46 A few thorium carbene complexes are also known, but in each example the carbene ligand is incorporated into a chelating ligand, which kinetically stabilizes the Th]C bond. [47][48][49] Also of note, terminal thorium sulphides have been invoked as reaction intermediates, 44 but have not been isolated. This paucity of examples can be rationalized by the higher energy of the thorium 5f orbitals, relative to uranium, which likely weakens metal-ligand p-bonding. 50 However, this hypothesis requires further verication, highlighting the need for new complexes that feature thorium-ligand multiple bonds.</p><p>Recently, we reported that selective removal of the trityl protecting group from the U(IV) alkoxide, [U(OCPh 3 )(NR 2 ) 3 ] (R ¼ SiMe 3 ), allowed for the isolation of the oxo complex, [K(18crown-6)][U(O)(NR 2 ) 3 ]. 41 Signicantly, the uranium centre does not undergo a net oxidation state change during the transformation. Inspired by this result, we endeavoured to synthesize the analogous thorium oxo complex, and its sulphido congener, using this deprotection protocol. Thorium was chosen for this study, in part, to address the scarcity of multiply-bonded complexes of the other actinides, but also because Th 4+ is effectively redox inactive, which makes the traditional synthetic routes to multiple bonds (such as oxidative atom transfer) more challenging. Herein, we describe the synthesis of a thorium sulphide and a thorium oxo, along with an analysis of their electronic structures by density functional theory.</p><!><p>Reaction of ThCl 4 (DME) 2 with 3 equiv. of NaNR 2 (R ¼ SiMe 3 ) in THF affords colourless crystals of [Th(Cl)(NR 2 ) 3 ] (1) in 56% yield, upon crystallization from Et 2 O/hexanes. This material was previously prepared by Bradley 51 and Andersen; 52 however, it was never structurally characterized. Crystals of complex 1 suitable for X-ray crystallographic analysis were grown from a concentrated diethyl ether (Et 2 O) solution stored at À25 C for 24 h. Determination of the solid-state structure revealed the anticipated pseudotetrahedral geometry about the thorium centre (see ESI † for full details). In addition, this material has a melting point of 208-210 C, nearly identical to that reported by Andersen and co-workers. 52 Interestingly, crystallization of the reaction mixture from THF/pentane resulted in isolation of the "ate" complex, [Na(THF) 4.5 ][Th(Cl) 2 (NR 2 ) 3 ], as determined by Xray crystallography (see the ESI †). However, this material can readily be converted into 1 upon extraction into, and recrystallization from, Et 2 O.</p><p>(1) Subsequent reaction of complex 1 with 12 equiv. of Me 3 SiI, in diethyl ether, affords [Th(I)(NR 2 ) 3 ] (2) as a white powder in 95% yield (eqn (1)). A similar procedure was recently used to prepare the related cerium iodide complex, [Ce(I)(NR 2 ) 3 ]. 53 Crystals of 2 suitable for X-ray diffraction analysis were grown from a concentrated diethyl ether solution stored at À25 C for 24 h. Complex 2 crystallizes in the hexagonal setting of the rhombohedral space group R3c, and its solid state molecular structure is shown in Fig. S19. † Complex 2 is isostructural with its chloride analogue 1. Its Th-N distance (2.299(4) Å) is identical to that of 1, while the Th-I bond (3.052(1) Å) is longer than the Th-Cl bond of 1 (2.647(1) Å), consistent with the larger single bond covalent radius of I À (1.33 Å) vs. Cl À (0.99 Å). 54 The 1 H and 13 C NMR spectra of 2 each exhibit a single resonance, at 0.45 ppm and 5.13 pm, respectively, assignable to the methyl groups of the silylamide ligands (Fig. S5 and S6 †).</p><p>We previously reported the synthesis of a U(IV) alkoxide complex, [U(OCPh 3 )(NR 2 ) 3 ], via reaction of KOCPh 3 and [U(I)(NR 2 ) 3 ], 41 and with 2 in hand, we endeavoured to synthesise the analogous thorium alkoxide. Thus, addition of 1 equiv. of KOCPh 3 to a cold (À25 C) suspension of 2 in toluene affords a colourless solution, concomitant with the deposition of ne white powder. A colourless oil is obtained upon work-up, and storage of this oil at À25 C for 24 h affords [Th(OCPh 3 )(NR 2 ) 3 ] (3) as a colourless crystalline solid in 33% yield (eqn (2)). Similarly, reaction of complex 2 with 1 equiv. of KSCPh 3 , in toluene, results in the formation of [Th(SCPh 3 )(NR 2 ) 3 ] (4) in 57% yield, aer crystallization from hexanes (eqn (2)).</p><p>(2)</p><p>We were unable to obtain X-ray quality crystals of 3; however, complex 4 was amenable to an X-ray diffraction analysis. This material crystallizes in the triclinic space group P 1, and features a pseudotetrahedral geometry about the thorium centre (Fig. 1). The Th-S bond length in 4 (2.704(1) Å) is similar to those of other thorium thiolate complexes (ca. 2.74). 55,56 In addition, the Th-S-C angle (136.72 (1) ) is rather small, suggesting that there is minimal 3p p-donation from S to Th. Other thorium thiolates also feature similarly acute Th-S-C angles. 55,56 The 1 H NMR spectrum of 3 exhibits a singlet at 0.39 ppm, in benzene-d 6 , assignable to the methyl groups of the silylamide ligands. In addition, it features resonances at 7.09, 7.18, and 7.39 ppm, in a 3 : 6 : 6 ratio, respectively, corresponding to the p-, m-, and o-aryl protons of the trityl-alkoxide ligand (Fig. S7 †), consistent with the proposed formulation. Not surprisingly, the 1 H NMR spectrum of 4, in benzene-d 6 , is almost identical to that of 3, and also features resonances assignable to three silylamide ligands and one trityl moiety (Fig. S9 †).</p><p>Interestingly, the 1 H NMR spectrum of the trityl-alkoxide reaction mixture exhibits resonances due to a second, minor Th-containing product. This was subsequently identied to be the bis(alkoxide) complex, [Th(OCPh 3 ) 2 (NR 2 ) 2 ] (5), which is likely formed by reaction of 3 with another equivalent of KOCPh 3 . The 1 H NMR spectrum of 5 features a sharp singlet at 0.26 ppm, in benzene-d 6 , which is assignable to the methyl groups of the silylamide ligands (Fig. S11 †). This resonance is slightly upeld from that observed for complex 3, which allows 5 to be distinguished from that complex. Complex 5 was also characterized by X-ray crystallography (see ESI †). Interestingly, there is no evidence for the formation of the analogous uranium complex in the reaction of KOCPh 3 with [U(I)(NR 2 ) 3 ], 41 consistent with the reduced ionicity of the U-N bond vs. the Th-N bond (see also below), which increases the barrier for ligand scrambling in uranium. Complex 1 can also be used as a precursor to 3, but in this case even greater amounts of complex 5 are formed during the reaction.</p><p>Prompted by our aforementioned success at selectively cleaving the C-O bond in [U(OCPh 3 )(NR 2 ) 3 ] to afford a uranium oxo complex, 41 we explored the reductive cleavage of the C-E (E ¼ O, S) bonds in complexes 3 and 4. Gratifyingly, reduction of 3 with 2 equiv. of KC 8 , in the presence of 18-crown-6, in THF, results in formation of a vibrant red solution, indicative of the presence of [CPh 3 ] À . 41,57 Extraction of the reaction mixture into diethyl ether, followed by ltration, permits removal of the [K(18-crown-6)(THF) 2 ][CPh 3 ] by-product, which is insoluble in this solvent. Work-up of the ltrate affords the thorium oxo complex, [K(18-crown-6)][Th(O)(NR 2 ) 3 ], (6) as colourless blocks in 23% yield (eqn (3)). Similarly, reaction of 4 with 2 equiv. of KC 8 , in the presence of 18-crown-6, in THF, results in the formation of the thorium sulphide, [K(18-crown-6)] [Th(S)(NR 2 ) 3 ] (7), which can be isolated as colourless needles in 62% yield aer a similar work-up (eqn (3)). The 1 H NMR spectra of 6 and 7, in benzene-d 6 , both feature two sharp resonances (6 : 0.64 and 3.09 ppm; 7 : 0.74 and 3.17 ppm) in a 54 : 24 ratio, assignable to the methyl groups of the silylamide ligands and the methylene groups of the 18-crown-6 moiety, respectively (Fig. S13 and S15 †), consistent with their proposed formulations. Unfortunately, the Th]E vibrational modes in 6 and 7 could not be denitively identied by either IR or Raman spectroscopies.</p><p>(3) Complex 6 crystallizes in the orthorhombic spacegroup Pbca, as a diethyl ether solvate, 6$0.5Et 2 O, while complex 7 crystallizes in the triclinic spacegroup P 1, with two independent molecules in the asymmetric unit. Their solid state molecular structures are shown in Fig. 2, and selected bond lengths and angles can be found in Table 1. Both complexes feature pseudotetrahedral geometries about their metal centres, along with dative interactions between the chalcogenido ligands and the K + ion of the [K(18-crown-6)] moiety. The Th-O bond length (1.983(7) Å) in 6 is slightly longer than the Th-O distance in the other structurally characterized thorium oxo (Th-O ¼ 1.929(4) Å), 44 but is signicantly shorter than a typical Th-O single bond (ca. 2.20 Å), [58][59][60][61][62][63] suggestive of multiple bond character within the Th-O interaction. Interestingly, the Th-O distance in 6 is 0.09 Å longer than the analogous distance in [K(18-crown-6)][U(O)(NR 2 ) 3 ] (1.890(5) Å), 41 a difference that is greater than the difference in the 4+ ionic radii of these two metals (0.05 Å). 64 The Th-S bond lengths in 7 (2.519(1) and 2.513(1) Å) are signicantly shorter than a typical Th-S single bond (ca. 2.74 Å), 44,55,56,65 and are again suggestive of multiple bond character within the Th-S interaction. In addition, the Th-S distances in 7 are 0.07 Å longer than the analogous distances in [K(18-crown-6)]-[U(S)(NR 2 ) 3 ] (2.4463(6) and 2.4513(6) Å), 41 which is in-line with the anticipated difference based on ionic radii considerations alone. 64 In order to gain further insight into the electronic structure and bonding of 6 and 7, as well as the uranium analogues 6-U and 7-U, we turned to quantum chemistry in the form of density functional theory (DFT). We began by optimising the geometries of the four target molecules using the PBE functional; selected bond lengths and angles are given in Table 1. For complexes 6 and 6-U the agreement between experiment and theory is very good, with differences in bond length of no more than 0.04 Å. DFT predicts both molecules to be almost linear along the M-O-K vector, 179.9 and 176.2 for 6 and 6-U respectively, in reasonable agreement with the experimental angles of 167.5(4) and 170.0(3) , respectively. In contrast, 7 and 7-U have two molecules in the asymmetric unit, with very different M-S-K angles. The PBE optimised structures agree very well with the experimental data for the molecules with the smaller M-S-K angles; the deviation from the experimental angles is only ca. 1.5 . In addition, a constrained geometry optimisation of the Th-S-K angle in 7, from the optimised angle of 150.4 , yields converged geometries up to Th-S-K ¼ 170.4 , at which point the molecule is only 2.6 kJ mol À1 less stable than in the fully optimised structure. Given this shallow bending potential, we wondered if the differences between the two molecules in the asymmetric units of 7 and 7-U might arise from dispersion forces, and hence re-optimised all four targets with these included via the Grimme D3 corrections. The data for these structures are collected in Table 1 and show that, with the exception of a slight shortening of the O-K distance, there is almost no difference between the PBE and PBE + D3 structures for 6 and 6-U. By contrast, the inclusion of dispersion corrections signicantly modies the geometries of 7 and 7-U, most notably the M-S-K angle, which increases by ca. 30 to linear in both cases, and the E-K distances which, in agreement with experiment, shorten by almost 0.1 Å between the bent and linear structures. For the latter, calculation predicts the M-E bond length reduction on going from Th to U to be ca. 0.06 Å in both the oxo and sulphido cases, essentially the same as the difference in ionic radius between Th 4+ and U 4+ , hence underestimating by ca. 0.03 Å the experimentally determined M-O bond length reduction on going from 6 to 6-U. We have analysed the electronic structures of all four targets using the Natural Bond Orbital (NBO) and Quantum Theory of Atoms-in-Molecules (QTAIM) approaches and, in order to allow for better comparison, decided to focus on the linear forms of 7 and 7-U, i.e. the electronic structures have been analysed at the PBE + D3 geometries for all four molecules. Complexes 6 and 7 are, of course, closed shell species and hence there is no net spin density for these systems; for 6-U and 7-U, however, NBO nds net spin densities of 2.092 and 2.085 respectively, as expected for U(IV). In all four cases, NBO nds the M-E interaction to be a triple bond; the s + 2p Th-O natural localised molecular orbitals (NLMOs) in 6 are shown in Fig. 3, and the compositions of the p NLMOs are collected in Table 2 for all four targets. In all cases the orbitals are largely chalcogenbased, a little more so for thorium than uranium. There is clearly more metal involvement in these orbitals in the sulphur systems than the oxygen, and while this is predominantly dbased for thorium there is an almost equal contribution of d and f in 6-U and 7-U.</p><p>NBO nds the M-N interactions to have double bond character. Three dimensional representations of one set of Th-N NLMOs in 6 are shown in Fig. 4, and the averaged compositions of the s and p character orbitals are collected in Table 3 for all four targets. As with the M-E bonding, these NLMOs are all strongly polarized toward the nitrogen. There is slightly more uranium contribution than thorium in analogous NLMOs. For the s orbitals, the metal contributions are signicantly more dbased than f (more so for thorium than uranium), while for the p component there is much more even metal d/f content, with a little more f than d for the uranium NLMOs and vice versa for thorium.</p><p>The deviations of the actinide natural atomic orbital populations (Natural Population Analysis (NPA)) from their formal values are given in Table 4. Typically, deviations from formal</p><p>M-E 1.983 (7) populations are taken as a measure of covalency, and such an approach is valid for the early actinides. Table 4 shows that the 7s and 7p orbitals are little involved in bonding. The 6d orbitals have larger deviations from the formal population than the 5f; these are very similar for the two sulphur compounds (1.49 and 1.50), and reduced for the two oxygen compounds, with slightly more 6d in the uranium system than the thorium (1.17 vs. 1.12). A similar situation is found for the 5f populations; the deviations of the sulphur compounds are very similar for thorium and uranium and larger than for the oxygen compounds, for which the uranium 5f population is a little larger than the thorium 5f. In summary, and in agreement with the analysis of the NLMO compositions, these data suggest greater covalency in the sulphur than the oxygen compounds, greater 6d covalency than 5f and, for the latter orbitals, slightly larger covalency in uranium than thorium. Table 5 presents the calculated atomic partial charges, using the QTAIM and NPA approaches. While the absolute values differ between methods, the trends are the same and suggest strongly polar M-E and M-N bonding. Taking the difference in charge between the metal and the surrounding atoms as a measure of ionicity, the data indicate that the bonding in the thorium compounds is more ionic than the uranium, and that bonding in the oxygen systems is more ionic than the sulphur, in agreement with the compositions of the NLMOs, which are more thorium localized than uranium, and more oxygen localized than sulphur.</p><p>We have pioneered the use of the QTAIM in the study of actinide covalency 2,4 and bond strength, 66,67 and Table 6 collects selected bond critical point (BCP) electron (r) and energy (H) densities and ellipticities (3), and delocalisation indices (d(A, B) -QTAIM measures of bond order). The ellipticity data reinforce the NBO results, indicating cylindrical (or, for 6-U, near cylindrical) triple-bond symmetry for the M-O interactions, and signicantly non-cylindrical double-bond symmetry for M-N. 68 The M-O BCP electron densities for 6 and 6-U are very large for actinide bonds, bordering the 0.2 au covalency threshold, and the M-N BCP r data are typical. 67,69 For both M-O and M-N, the BCP data are larger in an absolute sense in 6-U vs. 6. This is also true of the delocalisation indices, reinforcing the NBO conclusion of greater covalency in 6-U vs. 6. This is also the case for 7 vs. 7-U; the M-S and M-N QTAIM metrics are all larger in an absolute sense in the uranium system.</p><p>The M-E r and H and, to a lesser extent, d(A,B) are signicantly smaller in the sulphur compounds than the oxygen. We have previously cautioned, however, in the context of Th/U-S/Se</p><!><p>bonding, 70 against the interpretation of such reductions in terms of reduced covalency. The QTAIM covalency metrics show very strong dependence on bond length, and we believe that the very signicant (>0.5 Å) difference between M-S and M-O is the dominant factor here.</p><!><p>We have demonstrated the synthesis of oxo and sulphide complexes of thorium via reductive removal of the trityl protecting group. This work further demonstrates the generality of the reduction deprotection methodology, suggesting that this method will be broadly applicable towards the synthesis of multiple bonds in other metal systems, including lanthanides and transition metals, and we are currently exploring this possibility. Quantum chemical analysis (NBO and QTAIM) of the bonding in the thorium systems, and analogous uranium oxo and sulphido molecules, indicates that the M-E interactions are s + 2p triple bonds that are strongly polarised toward the chalcogen, while the M-N bonds (also largely ligand-based) have double bond character. For both the M-E and M-N bonds, there is greater metal-ligand orbital mixing (which, in the early part of the actinide series, we are comfortable describing as covalency) in the sulphur than the oxygen compounds. The Thligand bonds are found to be more ionic than the uranium analogues. Finally, the 6d orbitals play a larger role in the Th-E and Th-N bonds than do the 5f, while the latter are more involved in the uranium-ligand bonding.</p><!><p>General All reactions and subsequent manipulations were performed under anaerobic and anhydrous conditions under an atmosphere of nitrogen. Hexanes, Et 2 O, THF, and toluene were dried using a Vacuum Atmospheres DRI-SOLV Solvent Purication system and stored over 3 Å sieves for 24 h prior to use. Benzened 6 was dried over 3 Å molecular sieves for 24 h prior to use. ThCl 4 (DME) 2 was synthesized according to the previously reported procedure. 71 All other reagents were purchased from commercial suppliers and used as received. NMR spectra were recorded on a Varian UNITY INOVA 400, a Varian UNITY INOVA 500 spectrometer, a Varian UNITY INOVA 600 MHz spectrometer, or an Agilent Technologies 400-MR DD2 400 MHz Spectrometer. 1 H and 13 C{ 1 H} NMR spectra were referenced to external SiMe 4 using the residual protio solvent peaks as internal standards. IR spectra were recorded on a Nicolet 6700 FT-IR spectrometer. Elemental analyses were performed by the Micro-Analytical Facility at the University of California, Berkeley.</p><!><p>To a colourless, cold (À25 C), solution of ThCl 4 (DME) 2 (385.7 mg, 0.70 mmol), in THF (4 mL) was added a cold (À25 C) solution of NaN(SiMe 3 ) 2 (381.6 mg, 2.08 mmol) in THF (4 mL). This mixture was allowed to stir for 18 h, whereupon the solvent was removed in vacuo to afford a colourless solid. This solid was triturated with hexanes (3  4 mL) to yield a colourless powder. The resulting powder was extracted with diethyl ether (10 mL) and ltered through a Celite column supported on glass wool (0.5 cm  3 cm). The cloudy ltrate was again ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to give a clear colourless ltrate. The volume of this ltrate was reduced in vacuo to 4 mL and layered with hexanes (5 mL). Storage of this mixture at À25 C for 24 h resulted in the deposition of colourless crystals, which were isolated by decanting off the supernatant (167 mg, 32%). The supernatant was then dried in vacuo to afford a colourless solid. This solid was then extracted with diethyl ether (5 mL) and ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to afford a colourless ltrate. The volume of this ltrate was reduced to 2 mL in vacuo and layered with hexanes (4 mL). Storage of this mixture at À25 C for 24 h resulted in the deposition of an additional batch of colourless crystals, which were isolated by decanting off the supernatant. Total yield: 294.2 mg, 56%. Crystals suitable for Xray crystallographic analysis were grown from a concentrated Et 2 O solution stored at À25 C for 24 h. Melting point: 208-210 C (lit. value ¼ 210-212 C). [</p><p>To a stirring suspension of [Th(Cl)(NR 2 ) 3 ] (1) (852.3 mg, 1.14 mmol) in hexanes (8 mL) was added TMSI (2 mL, 14.05 mmol). This mixture was allowed to stir for 96 h, whereupon the solvent was removed in vacuo to afford a white solid. The solid was triturated with pentane (2  3 mL) to yield a white powder (908.2 mg, 95%). Crystals suitable for X-ray crystallographic analysis were grown from a concentrated CH 2 Cl 2 solution stored at À25 C for 24 h. Anal. calcd for C 18 H 54 IN To a colourless, stirring suspension of 2 (231.4 mg, 0.28 mmol) in toluene (4 mL) was added a cold (À25 C) solution of KOCPh 3 (84.7 mg, 0.28 mmol) in toluene (4 mL), in two portions over the course of 1 h. This mixture was allowed to stir for another hour, resulting in the deposition of a ne white powder. An aliquot (0.25 mL) of the reaction mixture was taken, the solvent was removed in vacuo, and a 1 H NMR spectrum in benzene-d 6 was recorded. This spectrum indicated the presence of starting material, complex 3, and a small amount complex 5. The amount of remaining starting material was estimated from relative area of its silylamide resonance, whereupon an additional portion of KOCPh 3 (13.4 mg, 0.045 mmol) was added to the reaction mixture. Aer 1 h of stirring, this mixture was ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to afford a colourless ltrate. The solvent was then removed in vacuo to yield a colourless oil. Storage of this oil at À25 C for 24 h resulted in the formation of crystals within the matrix of the oil. The crystalline material was isolated by decanting off the remaining oil and then washed with cold (À25 C) pentane (2 mL). This material consisted mostly of complex 5 and was discarded. The oil and the pentane washings were combined and the solvent was removed in vacuo to yield a colourless oil. Storage of this oil at À25 C for 24 h resulted in the deposition of colourless crystals, which were isolated by decanting off the remaining oil. 88.0 mg, 33%. Anal [Th(SCPh 3 )(NR 2 ) 3 ] (4)</p><p>To a stirring suspension of KSCPh 3 (51.4 mg, 0.16 mmol) in toluene (5 mL) was added 2 (137.4 mg, 0.16 mmol). This solution was allowed to stir for 1 h, whereupon the solvent was removed in vacuo. The resulting white solid was extracted with hexanes (10 mL) and ltered through a Celite column supported on glass wool (0.5 cm  3 cm), to provide a colourless ltrate. The volume of the ltrate was reduced to 3 mL in vacuo. Storage of this solution for 48 h resulted in the deposition of colourless crystals, which were isolated by decanting off the supernatant (92. 3 To a colourless, cold (À25 C), stirring solution of 3 (189.9 mg, 0.20 mmol) in THF (3 mL) was added KC 8 (56.1 mg, 0.42 mmol), which immediately yielded a dark red mixture. Aer 2 min, a cold (À25 C), colourless solution of 18-crown-6 (104.3 mg, 0.39 mmol) in THF (3 mL) was added to this mixture. The solution was allowed to stir for 30 min, whereupon it was ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to provide a vibrant red ltrate. The ltrate was dried in vacuo to provide a red solid that was triturated with diethyl ether (3  3 mL). The resulting red powder was extracted with diethyl ether (5 mL) and ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to afford a large plug of bright red solid and a pale orange-red ltrate. The volume of the ltrate was reduced to 1 mL in vacuo. Storage of this solution at À25 C for 24 h resulted in the deposition of colourless crystals, which were isolated by decanting off the supernatant (47.0 mg, 23% (18-crown-6). IR (KBr pellet, cm À1 ): 599 (m), 665 (m), 677 (m), 724 (w), 755 (m), 770 (m), 832 (s), 867 (s), 966 (s), 986 (s), 1116 (s), 1182 (w), 1243 (s), 1285 (w), 1353 (m), 1455 (w), 1474 (w). Raman (neat solid, cm À1 ): 389 (w), 615 (s), 678 (m).</p><p>[K(18-crown-6)][Th(S)(NR 2 ) 3 ] (7)</p><p>To a colourless, cold (À25 C), stirring solution of 4 (144.7 mg, 0.15 mmol) in THF (3 mL) was added KC 8 (41.2 mg, 0.30 mmol), which immediately yielded a dark red mixture. Aer 2 min, a cold (À25 C), colourless solution of 18-crown-6 (76.5 mg, 0.29 mmol) in THF (3 mL) was added to this mixture. This solution was allowed to stir for 15 min, whereupon it was ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to provide a vibrant red ltrate. The ltrate was dried in vacuo to provide a red solid that was triturated with diethyl ether (8 mL). The resulting red powder was extracted with diethyl ether (8 mL) and ltered through a Celite column supported on glass wool (0.5 cm  3 cm) to afford a large plug of bright red solid and a pale orange-red ltrate. The volume of the ltrate was reduced to 2 mL in vacuo. Storage of this solution at À25 C for 24 h resulted in the deposition of colourless crystals, which were isolated by decanting off the supernatant (48.7 mg, 32%). Subsequent concentration of the mother liquor and storage at À25 C for 24 h resulted in the deposition of additional crystals. (18-crown-6). IR (KBr pellet, cm À1 ): 605 (m), 664 (m), 685 (w), 699 (w), 785 (sh), 771 (m), 842 (s), 882 (sh), 936 (s), 963 (s), 1108 (s), 1182 (m), 1252 (s), 1285 (w), 1352 (m), 1455 (w), 1474 (w). Raman (neat solid, cm À1 ): 385 (w), 578 (s), 630 (s), 682 (s), 843 (m), 883 (m), 1014 (s).</p><!><p>Data for 1, [Na(THF) 4.5 ][Th(Cl) 2 (NR 2 ) 3 ], 2, 4-7 were collected on a Bruker KAPPA APEX II diffractometer equipped with an APEX II CCD detector using a TRIUMPH monochromator with a Mo Ka X-ray source (a ¼ 0.71073 Å). The crystals were mounted on a cryoloop under Paratone-N oil, and all data were collected at 100(2) K using an Oxford nitrogen gas cryostream. Data were collected using u scans with 0.5 frame widths. Frame exposures of 2 s were used for parameter determination were conducted using the SMART program. 72 Integration of the data frames and nal cell parameter renement were performed using SAINT soware. 73 Absorption correction of the data was carried out using the multi-scan method SADABS. 74 Subsequent calculations were carried out using SHELXTL. 75 Structure determination was done using direct or Patterson methods and difference Fourier techniques. All hydrogen atom positions were idealized, and rode on the atom of attachment. Structure solution, renement, graphics, and creation of publication materials were performed using SHELXTL. 75 Further crystallographic details can be found in Tables S1 and S2. † For [Na(THF) 4.5 ][Th(Cl) 2 (NR 2 ) 3 ], one sodium atom and its coordinated THF molecules exhibited positional disorder and were modelled over two positions in a 50 : 50 ratio. The C-C and C-O bond were constrained to 1.5 and 1.4 Å, respectively, using the DFIX command. In addition, the diethyl ether solvate of 6 exhibited positional disorder; one of the carbon atoms of this molecule was modelled over two positions in a 50 : 50 ratio. The anisotropic parameters of the disordered carbon atoms were constrained using the EADP command. Hydrogen atoms were not added to disordered carbon atoms.</p><!><p>Density functional theory calculations were carried out using the PBE functional, 76,77 as implemented in the Gaussian 09 Rev. D.01 quantum chemistry code. 78 Dispersion corrections (D3) due to Grimme et al. 79 were included, as discussed in the main text. (14s 13p 10d 8f)/[10s 9p 5d 4f] segmented valence basis sets with Stuttgart-Bonn variety relativistic pseudopotentials were used for Th and U. 80 For the geometry optimisations, the 6-31G** basis sets were used for all other atoms. The ultrane integration grid was employed in all calculations, as were the SCF convergence criteria. The default RMS force geometry convergence criterion was relaxed to 0.000667 au using IOP 1/7; the maximum force at each converged geometry is given in the ESI. † The electronic structures at the PBE + D3 geometries were recalculated using improved basis sets for the ligands; 6-311G** for O, S, N, K; 6-31G** for C and H. Natural bond orbital calculations were performed using the NBO6 code, interfaced with Gaussian. 81 QTAIM analyses were performed using the AIMAll program package, 82 with wfx les generated in Gaussian used as input.</p>

Royal Society of Chemistry (RSC)

Pattern similarity study of functional sites in protein sequences: lysozymes and cystatins

BackgroundAlthough it is generally agreed that topography is more conserved than sequences, proteins sharing the same fold can have different functions, while there are protein families with low sequence similarity. An alternative method for profile analysis of characteristic conserved positions of the motifs within the 3D structures may be needed for functional annotation of protein sequences. Using the approach of quantitative structure-activity relationships (QSAR), we have proposed a new algorithm for postulating functional mechanisms on the basis of pattern similarity and average of property values of side-chains in segments within sequences. This approach was used to search for functional sites of proteins belonging to the lysozyme and cystatin families.ResultsHydrophobicity and β-turn propensity of reference segments with 3–7 residues were used for the homology similarity search (HSS) for active sites. Hydrogen bonding was used as the side-chain property for searching the binding sites of lysozymes. The profiles of similarity constants and average values of these parameters as functions of their positions in the sequences could identify both active and substrate binding sites of the lysozyme of Streptomyces coelicolor, which has been reported as a new fold enzyme (Cellosyl). The same approach was successfully applied to cystatins, especially for postulating the mechanisms of amyloidosis of human cystatin C as well as human lysozyme.ConclusionPattern similarity and average index values of structure-related properties of side chains in short segments of three residues or longer were, for the first time, successfully applied for predicting functional sites in sequences. This new approach may be applicable to studying functional sites in un-annotated proteins, for which complete 3D structures are not yet available.

pattern_similarity_study_of_functional_sites_in_protein_sequences:_lysozymes_and_cystatins

Background<!>PCS classification<!><!>Segment pattern similarity search for active sites<!><!>Segment pattern similarity search for active sites<!><!>Segment pattern similarity search for active sites<!><!>HSS search for substrate binding sites<!><!>HSS search for substrate binding sites<!>Substrate binding sites reported by site-directed mutagenesis<!>PCS classification<!><!>Active sites<!><!>Substrate binding sites<!>Lysozymes<!><!>Cystatins<!><!>Cystatins<!>Discussion<!><!>Discussion<!>Conclusion<!>Amino acid sequences of proteins<!>Principal components similarity analysis of protein sequences<!>Homology similarity search<!>List of abbreviations<!>Authors' contributions<!>Acknowledgements

<p>In their recent review of protein sequence analysis in silico, Michalovich et al. [1] described the methodology for transferring functional annotation of known proteins to a novel protein. Computer-assisted technology is used to search for and assign the similarity from databases of well-maintained and previously annotated sources. Sequence-based and profile-based searches are conducted using BLAST and PSI-BLAST, respectively. Meanwhile, the Hidden Markov model is more efficient in searching for a distant family. Furthermore, structure-based annotation conducted by using a combination of PSI-BLAST and GenThreader (matching of substitution energy in evolution) may facilitate rapid functional annotation from structure [1]. However, proteins sharing the same fold can have different functions, and structure determination and analysis will not always mean that function can be derived [2]. There are examples of protein families, such as the four-helical cytokine and cytochrome super families, whose sequence similarities are either very low or not detectable [3]. Instead, their topography is more conserved than their sequences. This is rational, since protein functions are classified based on function per se, regardless of whether their sequences or 3D structures are similar or different. An example is the classification of a protein as possessing the function of lysozyme activity, as long as the protein possesses the ability of hydrolyzing peptidoglycans.</p><p>Another direct approach for peptide QSAR has been simultaneously investigated in peptide sequence analysis [4]. A critical difference between those two approaches, namely bioinformatics and QSAR, is the prerequisite of 3D structure information on the basis of evolutionary conservation in the case of former; on the other hand, the 3D information is helpful but not always indispensable in the case of latter, by substituting with simpler steric parameters to account for the functional mechanism [5]. For example, Hellberg et al. [4] used altogether 29 properties of side chains of bioactive peptides. After dimension reduction using principal components analysis (PCA) the resultant three main PC scores, i.e., z1, z2 and z3, representing hydrophobicity, molecular size and electronic parameter, respectively, were used as independent variables in regression analysis on the dependent variable of functionality [4].</p><p>Meanwhile, by using the homology similarity analysis (HSA), we have found the importance of functional segments within 15-residue sequences of lactoferricin derivatives to correlate with the minimum inhibitory concentration (MIC) [6]. Pattern similarity constant (a correlation coefficient) of the pattern of segments within a test derivative, in comparison to the reference pattern of the corresponding segment and the average of property values of the amino acid side-chains in the most potent derivative, was computed and correlated with MIC of the derivatives. In order to obtain the best (lowest) MIC, the pattern similarity should be close to 1.0 and the average property value should be close to that of the reference potent peptide (template). In the case of the above lactoferricin derivatives, higher correlation coefficients were obtained for log MIC predicted by HSA vs. measured log MIC computed as the output variables of regression ANN (artificial neural networks) than by sequence analysis based on the Hellberg approach [4]. More recently, a different approach, namely "additive QSAR" obtained by substituting with other amino acid residues at different positions in the same sequences, was reported to correlate well with peptide functions [7].</p><p>Lejon et al. [8] reported that in PCA analysis of peptide sequences, information of the positions of side chains in the sequence should be included for improving R2X value compared to the results obtained by computing without side chain position data (0.99 vs. 0.60, respectively). Our HSA approach, by segregating segments with and without α-helix propensity, was in good agreement with theirs (R2X of 0.90–0.94 compared to corresponding value of 0.60 but with a much larger number of derivatives). We have further extended this approach to infer the mechanism of emulsifying capacity of peptides with 10–32 residues as a function of hydrophobic periodicity [9]. For the study of emulsification function, a new homology similarity search (HSS) was introduced to plot similarity constants and average property values of segments (3–7 residues) by shifting the segment stepwise from N-terminus towards C-terminus of the sequences; the reference segment used was ELE, i.e., alternate cycle of charged (E), hydrophobic (L) and charged (E) residues. However, emulsification ability is a rather general function of peptides that is not dependent on specific active sites within the sequences; overall, the emulsification ability of peptides was highly correlated with hydrophobic periodicity of their entire sequences.</p><p>There are cases of "peptides" which do not have definitive functional sites but requiring specific segments, or "functions" which do require neither specific sites nor segments. The lactoferricin derivatives described in the above study [4] are an example of the former since all of the mutants were prepared as derivatives of the corresponding wild-type lactoferricin 15-residue sequence, which has distinct helical and cationic segments. In contrast, the peptide emulsions [9] are an example of the latter. Typical examples of proteins with definitive functional sites are enzymes, for which the positions of active sites are critical to elucidate the functional mechanisms. Defective protein folding leading to amyloid fibril formation has been associated with various human diseases, such as Alzheimer's and Creutzfelds-Jacob diseases. In 1993, hereditary non-neuropathic systemic amyloidosis was reported to be caused by naturally occurring variants of human lysozyme that aggregated in the liver [10]. Similarly, cystatin C mutation in an elderly man was reported to be the cause of amyloid angiopathy and intracerebral hemorrhage [11].</p><p>The recent discovery of a new-fold enzyme named Cellosyl [12] led us to select the lysozyme family in this study as an important one to use for validating the HSS approach to search for functional sites [13]. Meanwhile, loss of papain inhibitory activity in recombinant human cystatin C was reported to be due to insolubilization [14]. Assuming that this loss was induced by an amyloidosis, changes of helix-to-strand in the inhibitory sites as well as the binding sites with papain could also be used for a rational example of application of the HSS approach in this study.</p><p>The objective of this paper was to extend application of this new HSS approach to search for functional sites, such as active and substrate binding sites in lysozyme and amyloidosis of cystatin families, to verify the reliability of our new method. The intention was to validate the hypothesis that the evaluation of pattern similarity of short segments with 3–7 residues or even slightly longer in protein sequences is useful in predicting functionality, assuming that they are within allowable topographical units. Accordingly, it is not our intention to replace the 3D approach by the new peptide QSAR proposed in this study; rather, it is anticipated to be supplemental.</p><!><p>Figure 1 shows a scattergram derived from principal components similarity (PCS) analysis of 25 lysozyme sequences using the hydrophobicity index of side chains and hen lysozyme as a reference. A scattergram similar to this figure was also obtained when a charge index was used (instead of the hydrophobicity index) for classification. CH-type lysozymes used herein were from a fungus and Streptomyces globisporus. The v-type lysozymes were T4 and PA2 phage lysozymes, while g-type lysozymes were from goose, black swan, cassowary, ostrich and chicken G. Sixteen lysozymes (chicken C, human, horse, dog, rat, mouse, red deer, rainbow trout, pigeon, turkey, duck, California quail, Japanese quail, common bobwhite, fruit fly Drosophila, and tobacco hornworm) belong to the c-type family. The large deviations in slope (about 2) of CH-type lysozymes as seen in Figure 1 are suggestive of explicit difference in their molecular structures from those of other lysozyme types.</p><!><p>PCS scattergram of lysozyme families (C-, G-, V-, and CH-types) when hydrophobicity was used as property index. Hen lysozyme was used as the reference with [coefficient of determination] = 1.0 and [slope] = 1.0.</p><!><p>The HSS computer program was applied to the sequence alignment patterns shown in Figure 2 using the active sites of hen lysozyme at positions 54–57(F34ESN) and 80–83(T51DYG) as the references. The position numbers in parenthesis are the positions in un-gapped sequences of individual lysozymes, while the immediately preceding numbers outside of parenthesis are the position numbers of the multiple sequence alignment (gapped) in Figure 2. Since the peptidoglycan-lysing activity is associated with glutamic 55(E35) and aspartic 81(D52) side-chains in the hen lysozyme [13], the segments flanking these residues in the sequences were the focus of pattern similarity search using the HSS.</p><!><p>Multiple sequence alignment of five lysozymes belonging to four families.</p><!><p>The search patterns illustrated in Figure 3A (charge) and 3B (turn propensity) are a trial run to validate the HSS approach, applied to human lysozyme vs. hen lysozyme, employing the five residues flanking E35 (K33FESN of hen) as a search unit. The rules herein for selecting active segments are that the greater the similarity approaching to 1.0 and the nearer the average value to that of the reference, the more likely to be active sites in the test sequence. In Figure 3A, in addition to E35 and D53, three residues of E7, S80 and D120 show about the same similarity constants (upper pattern) as well as similar average charge values (shown by arrows on the lower pattern). However, none of the above latter three positions are acceptable as the active site, as N44, I59, C65, Q86, and Q126 in Figure 3B for β-turn search do not have matching peaks in Figure 2A for charge search. Therefore, only E35 and D53 are qualified as the active positions of human lysozyme. The same result was obtained when five residues flanking D52 (S50TDYG) of hen lysozyme were used as an alternative reference segment. The two regions around E35 and D53 determined for human lysozyme are in good agreement with those being reported for the active site in the literature [13]. Despite the fact that the charge is of prime importance in defining active sites of lysozymes, the turn propensity values of the segment rather than its pattern similarity appear to play an important role in the enzyme, as exemplified in a low similarity value of 0.30 for D53 compared to 0.98 for E35, whereas similar average turn values of 1.2 and 1.1, respectively, were computed (Fig. 3B). All these results may imply that the exposure of active sites to react with the substrate binding sites is essential.</p><!><p>HSS search patterns for active sites of human lysozyme. Segment 53–57 of hen lysozyme was used as the reference. A: HSS search pattern based on charge. B: HSS search pattern based on turn propensity.</p><!><p>The same search was conducted for goose and T4 lysozymes as well as the new fold CH-lysozyme [12], with the assumption that it is an un-annotated sequence, to confirm validation of the HSS approach (Table 1). Two positions of 79(E73) and 103(D97) were determined as the active sites of the goose lysozyme sequence. D97 may not be essential for the catalytic activity of the goose lysozyme [15]. In comparison, 11(E11) and 20(D20) were noted for T4 lysozyme, which are in good agreement with those reported in the literature [13]. As shown in Figure 4, in the case of the sequence of Cellosyl (CH-type), 14(D9), 104(D98) and 106(E100) were identified as candidates to be the active positions of catalysis, which are in good agreement with Rau et al. [12]. These results would support the reliability of the HSS approach.</p><!><p>Determination of active sites in sequences of lysozymes in different families</p><p>Position: the first number is the multiple sequence alignment position shown in Figure 2. Number in bracket is that in the sequence of each lysozyme. Charge 1 and 2 and Turn 1 and 2: Sites 54–57 and 80–83 (alignment position numbers in Fig. 2) were used as references. These position numbers correspond to 34–37 and 50–54, respectively in the sequence of hen lysozyme. The first and second digits n each cell of Charge and Turn are similarity constant and average of property value.</p><p>HSS search patterns for active sites in Strep. coelicolor lysozyme. Segment 79–83 (STDYG) of hen lysozyme was used as the reference based on charge.</p><!><p>Compared to the active sites that are explicitly negative in charge at single positions, the substrate binding sites of lysozymes are rather loosely defined, mainly due to the greater complexity of determining the 3D structure of enzyme-substrate complexes than that of enzyme alone. It is generally agreed that the substrates locate inside the cleft formed between the helix lobe and the strand lobe of most lysozyme molecules, except for Cellosyl, the bacterial muramidase from Streptomyces coelicolor, which can be attributed to structural difference in the catalytic crevice [12]. The six-residue segment at alignment positions 84–89 (I55LQINS) of hen lysozyme was employed as the reference segment [16] using the hydrogen bonding scale (Table 2). Based on the high pattern similarity constants and the average hydrogen bonding index values, eight potential sites were identified for hen and human lysozymes. The same rule as that for selecting active site was used herein for selecting of binding sites. Position 77(D48) and 188(W111) shown in "Hen 1" of Table 2 with lower similarity constant and hydrogen bonding value, respectively, may not be the potent substrate binding sites in the hen lysozyme. In the 3D structure [17], those two positions are far away from the catalytic cleft where the substrates snugly fit in. In the human lysozyme, 188(W112) is more likely to be the binding site than 102(A73), with higher pattern similarity and strength of hydrogen bonding of 0.89/0.45 than 0.80/0.32, respectively. Not only strong hydrogen bonding, but also high pattern similarity of a segment may be required to be qualified for substrate binding sites.</p><!><p>Determination of substrate binding sites in amino acid sequences of lysozyme families</p><p>The first/second digits are similarity constants and average hydrogen bond index values of binding site with segments of sox residues beginning with the positions shown. Bold digits show more likely binding sites than non-bold digits.</p><p>Hen 1 and Human 1: from the alignment shown in Figure 2; Hen 2 and Human 2; from the alignment of the lysozyme C family exclusively.</p><!><p>For the goose lysozyme, six potential binding positions were detected (Table 2); I113 and G163appear more likely to be the binding sites than other positions considering the location of the cleft in the molecule. Similarly, nine sites were found to be potential sites of T4 lysozyme, especially three positions, i.e. M6, L66 and S136 (Table 2). In the case of Cellosyl, eight positions were identified as the potential binding sites (Table 2). Probably due to the considerable 3D-structure difference of this lysozyme from those of other lysozyme families [12], the alignment positions 40–45 (T34EGTNY) instead of hen's 84–89 (I55LQINS) were used as a reference segment for obtaining more rational search results. Instead of hydrogen-bonding motivated interactions, less polar van der Waals interaction with the aromatic side chains in CH-lysozyme may be regarded as the second important stereochemical forces in the substrate binding [16].</p><p>In the literature, the most frequently cited substrate-binding sites in c-type lysozymes family have been W62 and D101 of hen lysozyme [13]. Since Figure 2 includes the distant family of CH-type, the segment similarity search was repeated within the c-type lysozymes alone to restrict the search within similar fold. The results are shown as "hen 2" and "human 2" in Table 2. Those results almost perfectly match to the substrate binding mechanism based on X-ray crystallographic analysis, e.g. D101, N103, N104, A107, V109, E35, N46, V110, E52, N59, and W63 [15]. Almost all of these side-chains are very close or adjacent to the segments listed in "Hen 1" and "Hen 2" of Table 2.</p><!><p>Among three mutants obtained by replacing W62 with Y, F or H, the W62H mutant, and especially the double mutant W62H/D101G, reduced substrate binding drastically [15]. This change can be explained by a decrease in the hydrogen bond average value from 0.58 to 0.54 and from 0.46 to 0.29 in V62H and D101G, respectively, when the index values employed in this study were used in computation. The double mutant changed substrate-binding mode while maintaining the overall protein structure almost identical to that of the wild type [18]. An extensive cluster of hydrophobic structure is involved in distinct regions of the sequence, but is all disrupted by a single point mutation of W62G located at the interface of the two major structural domains in the native lysozyme [19]. Similar effects were observed in mutants Y63L and D102E of human lysozyme [20]. The double mutants R41N/R101S and V74R/Q126R of human lysozyme were better catalysts for lysis of Micrococcus lysodeikticus [18]. The average hydrogen bond value of both R41N and R102S was shown to increase in our HSS search, but similar effects could not be observed for V74R/Q126R. An interesting finding is that these two mutations have both resulted in the side chains being identical to those of hen lysozyme. R41 and V74 are near A42 and A73, respectively. Importance of R115 in substrate binding of human lysozyme was reported [21], which is in good agreement of W112 within the same subsite F (Table 2).</p><!><p>The PCS scattergram of the 17 cystatins using human cystatin C (HCC) as a reference and hydrophobicity as side-chain property index is shown in Figure 5; alteration of the index to α-helix and β-strand propensities did not appreciably change the grouping results. The three groups include human cystatins C, D, S, SA, SN and hen cystatin (Group I), human cystatins E, F and M (Group II), and human cystatins A and B (Group III) which are the stefin group cystatins that are smaller in molecular size and have slightly lower papain inhibitory activity than HCC [22].</p><!><p>PCS scattergram of cystatins when hydrophobicity was used as property index. Human cystatin C (HuC) was used as the reference. Human cystatins M, E, S, SA, SN, D, F, A and B are labelled as 1, 2, 7, 8, 9, 10, 15, 16 and 17. Labels 3, 4, 6, and 11–14 are for cystatins from mouse C, rat C, bovine, hen, rainbow trout, chum salmon and carp, respectively.</p><!><p>The HSS patterns using hydrophobicity to search for active sites of the four cystatins (HCC, EWC, HCA and HCB), when L9VGG of HCC has been employed as the reference, are shown in Figure 6. The active sites shown with arrows are at about the same location in all cystatins sequences used in this study. Similar results were obtained when bulkiness was used as side-chain index. In these cases, the similarity peaks are the major clue for identifying active sites. However, when similarity peaks appear in the neighbourhood, the average index values would become more reliable for identifying active sites as shown in Figure 6B; hen cystatin has two probable active positions side by side with the same similarity constants. The active sites, therefore, should be near the N-terminus with Prosite-type patterns of [L,I,M]-x(4)-G- [G,A]; the active sites are L9VGG and L7LGA in human cystatin C and hen cystatin, respectively. The similarity constants and the average hydrophobicity of the active sites are shown in Table 3. Stefin B (HCB) shows much lower similarity constant and average hydrophobicity than those of other cystatins. This result is in good agreement with ki difference reported by Abrahamson [23].</p><!><p>Active and substrate binding sites of cystatins</p><p>* Pattern similarity constant / average hydrophobicity</p><p>** Pattern similarity constant / average turn propensity</p><p>Similar to the corresponding tables for lysozymes (Tables 1 and 2), Sim/Const is 1.0 for reference HCC, and the greater the Av.Property the greater the property strength.</p><p>HSS search patterns for active sites of cystatins against human cystatin C based on hydrophobicity. A: HCC (reference), B: EWC (egg white cystatin), C: HCA and D: HCB.</p><!><p>A HSA study similar to our previous paper [6] was conducted at the active and two binding sites of cystatins, yielding results (Table 3) which are in good agreement with Turk et al. [22]. Substrate-binding site 1 had the pattern Q-x(3)-V- [S,A]-G, while substrate-binding site 2 had the pattern [L,I,V]-P-x(3)-x(3)- [N,G]. Similarity constants of binding loop 2 of egg white cystatin (EWC) and HCA are lower than that of HCC, whereas not only similarity but also average hydrophobicity are lower in HCB. Similarity constants at the active site (against 1.0 for HCC) using hydrophobicity index were >0.8 for cystatins A, D, F and hen, ~0.5 for E and M, and 0.1–0.2 for cystatins B, S, SA and AN. Similarity constants at binding loop 2, when strand propensity was used for PCS computation, were lower for stefins A and B with values of 0.8 and 0.6, respectively, than >0.9 for other cystatins. On the other hand, similarity constants for strand at binding site 1 were not much different among different cystatins, with values >0.9 (not included in Table 3).</p><p>It is interesting to note that stefins A and B do not have the PW pair which is in the binding site 2 of HCC and EWC; instead they have PG and PH pairs, respectively (Table 3). The W → G replacement increased strand propensity, while W → H replacement did so moderately. The values shown in Table 3 were almost inversely proportional to the equilibrium inhibition constant ki except for human cystatin S that was weak in the inhibitory activity, which might have been due to the difference in phosphorylation of serine at N-terminal region [23]. Although stefins A and B are classified differently from other groups on PCS scattergram (Fig. 5), the weak binding at the binding site 2 may not have considerable effects on the ki values.</p><p>Turk et al. [22] have stated that the differences in the binding constants between cystatins and various cysteine proteases arise primarily from differences in the structure of enzyme active site clefts. The inhibition of endopeptidases, i.e. papain and cathepsins S and L, by cystatins is extremely tight and rapid, whereas the inhibition of exopeptidases, i.e. cathepsins B and H, is considerably weaker. The active site cleft of known endopeptidases is free to accommodate inhibitors, while in the case of exopeptidases, the active site cleft contains extra residues in it. In the N-terminal region of cystatins, it was observed that the affinity for target proteases decreased with both size and charge of substituting residues [22]. These observations are in good agreement with the results when bulkiness of side chains was used for the HSS computation for the binding site 1, "SimConst /Av.bulk" values were 1.00/12.3, 0.92/14.2, 0.98/11.4 and 0.91/11.34 for HCC, EWC, HCA and HCB, respectively. As expected, stefins A and B were less bulky. Furthermore, HCC and EWC include longer chains at the N-terminal sides with bulkier residues than those of stefins. These findings are in good agreement with the effect of bulkiness of G4 in the stefin A sequence, implying that the bulkier the residue at position 4, the weaker the papain inhibitory activity [24].</p><!><p>Similarity constants and average propensities of α-helix and β-strand were computed for G54IL and G54ILQIN of hen lysozyme (G55IF and G55IFQIN in the case of human lysozyme) as shown in Table 4. The amyloidogenic mutant I55T showed increased strand propensity from 0.82 to 0.85, without a substantial change in the similarity constants. With regard to the helix structure, the similarity constant decreased from 1.00 to 0.93 while the average value increased from 1.08 to 1.14, thereby implicating a decrease in helix, since the helix index used herein is inversely related to the content of helix structure. These changes are favourable for amyloidosis. The fact that position 56 in human lysozyme is near its active position at D53 may explain its dramatic effect on the enzymatic activity, more effective than other positions in the sequence. The six-residue computation did not show as clear a difference as was found in the three-residue computation. Nine double-site mutations in addition to I55T at other positions selected at random in the sequences of the amyloidogenic mutant I55T by using the RCG program did not restore the activity of wild-type lysozyme (unpublished). These results infer that the amyloid, once formed by detrimental mutation at the active site, cannot be restored by mutation at other locations in the sequence.</p><!><p>HSA computation for I55T lysozyme</p><p>L56 for hen and F57 for human. * Similarity constant.</p><!><p>Heat treatment of HCC induced its dimer formation at an early stage of separation, resulting in a complete loss of its activity [25]. Based on a dramatic decrease in the monomer form as shown by its CD spectrum, polymerization such as amyloidosis could be a cause of the loss of papain inhibitory activity of mutated HCC [14]. Of 35 residues (positions 1–35) of the helix domain of HCC, 17 residues were mutated in the 22 single-site mutants using the RCG program [14 (Table 1)]. When 33 mutants obtained by adding one extra residue each in both side of the original 17 residues after eliminating duplication were used for PCS computation, the resultant PCS demonstrated that helix propensity and bulkiness were playing important roles in thermostability (data not shown). Employment of three residues flanking the mutated residue was important in pattern similarity computation. This conclusion is in good agreement with Hall et al. [26] who did an exhaustive study showing that mutations at positions 8–10 enhanced thermostability of cystatin. With regard to the papain inhibitory activity, the importance of hydrophobicity and bulkiness was demonstrated (the PCS scattergrams, similar to Fig. 7, are not shown here).</p><!><p>Effects of mutating the strand domain of human cystatin C (mutated 21 residues). A: Strand index, B: Helix index. The numbers show multiples of activity increases from wild-type. 1 shows no increase of inhibitory activity. 5* is the reference mutant 12W86V with the highest inhibitory activity.</p><!><p>Of 86 residues in the strand domain (positions 36–121) of HCC, 21 residues (positions 36–120) were mutated in the 23 double-site mutants using the RCG program [14]. Thirty-seven residues were used for the PCS computation of single-site mutations as described above. Hydrophobicity appeared to be playing an important role in thermostability, while strand propensity was important for inhibitory activity (data not shown). Strand and helix propensities in the strand domain were influential to the papain inhibitory activity of HCC (Fig. 7). The figures show 12 data points only by eliminating data from single site mutation in the helix domain, which did not show distinct trends with broader scatter in these figures. The second mutations in addition to the above single mutations were conducted at the strand domain of the enzyme [14]. Coefficient of determination of 1.0 and slope of 1 indicate perfect match with the reference sample (5*) that is mutant G12W/H86V with the lowest strand propensity along with highest helix propensity in the strand domain among 23 double mutants. It is worth noting that the PCS is a classification program comparing pattern similarity without demonstrating quantitative relationships with functions but providing the information of the extent of involvement of side chain properties in the functions of interest.</p><p>For mutant G12W/H86V that gained the greatest activity increase of 4.98 ± 0.09 times (mean ± SD at n = 3) that of recombinant wild-type [14], the strand propensity decreased from 0.78 to 0.69 (H86V) with a slight increase in the helix propensity (corresponding to decrease in the index values). The same was true for mutant D15P/H86I with 2.65 ± 0.30 times activity increase. A similar result was observed in mutant G4L/D40I with 2.11 ± 0.29 times activity increase, due to strand decrease along with almost no change in helix (D40I). However, mutant V10S/R93G with 4.50 ± 0.07 times activity increase behaved differently with increased strand and simultaneous decrease in helix. It is worth noting that the single mutation of V10S alone increased the activity 2.96 ± 0.06 times, therefore, changes in the helix domain may have a more predominant effect on the inhibitory activity than mutations in the strand domain. The activity change due to mutation helix → strand in the strand domain in the sequence may be slight in this case.</p><p>It is well known that a single-point mutation of human lysozyme, namely I56T, has been identified as the origin of hereditary systemic amyloidosis [27]. The amyloidogenic nature of the lysozyme variants arises from a decrease in the stability of the native fold relative to partially folded intermediates. Accordingly, in a low population of soluble, partially folded species, the protein can aggregate in a slow and controlled manner to form amyloid fibrils. Similarly, sporadic amyloid angiopathy and intracerebral hemorrhage was reported in an elderly man due to cystatin C mutation [11]. In the case of human cystatin C, the decrease in strand along with an increase in helix might have prevented amyloidosis, despite the fact that helix change was not always as evident as in the case of lysozyme. Some inconsistency in the amyloidosis as a cause of inhibitory activity of human cystatin C in our mutation optimization [14] may be due to lack of the data of single-site mutation in the strand domain of the cystatin sequence. Unfortunately, the objective of that study [14] was for mutation optimization and not for investigation of the mechanism of amyloidosis. It has been reported that stefin B (HCB) readily formed amyloid [28], which may imply declined importance of the role being played by the binding site 2 in amyloidosis of HCC.</p><!><p>In a review on the quest to deduce protein function from sequences [29], the author stated that the searching of pattern databases would be more sensitive and selective than searching of sequence database. It was predicted that the sequence pattern databases, especially by comparing the pattern similarity, would play an increasingly important role, as the post-genome quest to assign functional information to raw sequence data gains pace [29]. Pattern similarity computation requires at least three residues in segments to represent a nonlinear curve, which is unlikely to be due to the effect of a single point mutation per se.</p><p>With regard to an apparent effect of the single residue mutations of hen lysozyme on substrate binding, the structural analysis by NMR of the position-62 mutant of hen lysozyme [18,30] found major changes in the chemical shift of back bone protons, especially in a loop region (positions 61–78), which contains W62 influencing the local folding. Similarly, Muraki et al. [20] reported that compared to the wild-type human lysozyme, the N-acetylglucosamine residue at subsite B of the L63 mutant markedly moved away from the 63rd residue, with substantial loss of hydrogen-bonding interaction. In Figure 5 of Ref 17, involvement of not only Y63 but also W64 is evident. These results are supportive of the importance of pattern similarity of ≥ 3 residues, which are affected by single-residue mutation.</p><p>The predictability of the active and binding sites solely on the basis of protein sequences [31] may be useful for investigating the underlying mechanisms of unknown functions of human genes after translation to protein sequences. Usually, two or three essential residues are directly involved in the bond making and breaking steps leading to formation of enzyme catalysis; however, the removal of an essential group often does not abolish activity, but can significantly alter the catalytic mechanism [32]. T4 lysozyme was cited by Peracchi [32] as an example of the alteration of catalytic mechanisms; the lytic activity of lysozyme changed to that of a transglucosidase.</p><p>An approach utilizing the property of side chains in a sequence for identifying functional motifs has already been utilized in the computer-assisted selection of antigenic peptide sequences [33]. The authors stated that an antibody produced in response to a simple linear peptide with 7–9 residues in a protein would most likely recognize a linear epitope. Furthermore, this epitope must be solvent-exposed to be accessible to the antibody. In a large scale data mining study, Binkowski et al. [34] described the importance of local sequence and spatial surface patterns in inferring functional relationships of proteins. The general feature of protein structure that would correspond to these criteria could be turns or loop structures, which are generally found on the molecular surface connecting to other elements of secondary structure, and the area of high hydrophobicity, especially for those containing charged residues.</p><p>Successful identification of active sites of new-fold of CH-lysozyme using the HSS approach in this study suggests that this approach could be applied to query proteins translated from unknown RNA segments of the human genes against templates with known functions, when their 3D structure information is still unavailable. It has been shown that the inhibition of the papain family by cystatin is due to a tripartite wedge-shaped structure with a good supplement to the active site clefts of the enzyme [35]. Todd [36] stated that despite highly homologous relationship as seen in Figure 8, lysozyme functions as an O-glycosyl hydrolase, while α-lactalbumin lacks this activity and instead regulates the substrate specificity of galactosyltransferase. The active site of peptidoglycan lysis is disrupted in α-lactalbumin. The ESS computation showed that although a pattern equivalent to hen's D53 exists in the form of TEYG/YDYG, there is no residue equivalent to hen's E35 around corresponding positions as in the form of HTSG/WESG. Two side-chain carboxyl radicals are required for the lysozyme activity within the crevice between the helix and strand domains of the molecule belonging to C-type family [16]. According to Alvarez-Fernandez et al. [35], the three parts of the cystatin polypeptide chain included in the enzyme-binding domain are the N-terminal segment, a central loop-forming segment with motif QXVXG and second C-terminal loop typically containing a PW pair [31,37,38].</p><!><p>An example of enzyme vs. non-enzyme. Adopted from Figure 10.3b [36]. Fig. 8A: 1IWT human α-lactalbumin, Fig. 8B: 1B9O human lysozyme C using Swiss-PdbViewer (spdbv). Blast 2 sequences [1] showed that the identities and the positives between the two proteins were 35% and 55% respectively.</p><!><p>For multiple sequence alignment of an uncharacterized protein or peptide, many Web alignment servers are available for use [1], such as Blast and NPSA, as was done in this study. For classification of uncharacterized sequences, the PCS scatterplots are also useful as shown in Figures 1, 5 and 7. The PCA demonstrated the classifying capacity superior to that of distance-based cluster analysis [39]. The PCS is more flexible than cluster analysis as different pattern similarity patterns can be drawn by rotating the reference segment for searching. It implies that similarity is not always [1 – dissimilarity]. This difference resulted in the possibility of selecting outliers, which is critical in deriving true classes or ranking [40]. Most of the currently available peptide QSAR, such as the method of Hellberg et al. [4], intends to be based on whole sequence data. The new HSS approach reported in this study could be just the beginning of more detailed, reliable peptide QSAR to be developed in the future. Analysis of a variety of bioactive proteins contributing to human health is a potential future application of the HSS software package as well as multifunctional PCS. Considering the multifunctional nature of human diseases, the functionality of food proteins also can be manipulated based on combinations of bioactive segments in different or even single natural protein sequences. Therefore, for an uncharacterized protein or peptide, a new plan is proposed: (1) A reference sequence is chosen from multiple sequence alignment (MSA) as discussed above; PCS scattergrams would assist this selection in addition to BLAST search. (2) Based on segments with high similarity in MSA, segments to be used for search are selected within the reference sequence. Then, (3) HSS search is conducted to identify functional segments in the uncharacterized sequence. (4) From the above PCS computation, important PC scores are screened (PCA is a subroutine subprogram of PCS). (5) Regression neural networks are conducted using selected PC scores as input variables as exemplified in our lactoferricin derivative study [6]. (6) RCG would be useful for confirming the HSS data and also to find the best segment or sequence as exemplified in our HCC mutation [14].</p><p>One of the original purposes of our new approach in unsupervised data mining was to verify the hypothesis that there might be adaptability of different human cystatins to better inhibit different human cathepsins [41]. This hypothesis has not been fully pursued in the past, probably because of costly separation of pure cystatins and cathepsins. An advantage of our approach is to derive potential hypothesis for enzyme/substrate interactions exclusively from their sequence data. Although the verification of those hypotheses may need to await future 3D-structure study, it is important that most of the useful QSAR data could become available, which would promote the functional mechanism study based on 3D structure. However, we admit that more examples of application should be performed in the future to more thoroughly verify and establish this method for predicting functions based on sequences. This work is underway in our laboratory.</p><!><p>Although the importance of pattern similarities of motifs with 20–30 residues as a whole has been reported for peptide QSAR in the past, the importance of a search for segments with three or more residues as functional sites of protein sequences has not been investigated. Lysozymes and cystatins were used as examples of proteins to demonstrate the capacity of segment pattern similarity analysis to predict functions, such as active and binding sites, amyloidosis and thermostability as a tool for quantitative functional sequence analysis.</p><!><p>Multiple sequence alignments of lysozymes were conducted using the Network Protein Sequence Analysis of Pôle Bio-Informatique Lyonnais [42] based on Clustal W. Similarly, multiple sequence alignments were obtained for human cystatins A (HCA), B (HCB) and C (HCC) and hen egg white cystatin (EWC) as well as for papain as host proteases of cysteine protease inhibitors, i.e. cystatins. For PCS analysis, a total of 17 cystatins were used: human A, B, C, D, E, F, M, S, SA, SN, hen (EWC), bovine, ratC, mouseC, Chum salmon, Rainbow trout and carp.</p><!><p>The method described in the previous papers [9,39] was followed. Principal components analysis (PCA) was modified to principal components similarity (PCS) by incorporating linear regression of PC scores to be able to account for more than three PC scores on a 2D scatter plot. The PCS was then modified to apply to peptide sequences.</p><!><p>Homology similarity search (HSS) was conducted as reported previously [9]. The similarity constant used in this study is eventually a correlation coefficient [43]. A preliminary study was carried out by changing the size of segment (normally 3–7) flanking the potential functional position to determine the most appropriate size of segment in differentiating the functional site from other segments within the sequence of lysozymes and cystains. The property indices used for amino acid side chains were hydrophobicity, charge, propensities of α-helix, β-strand and β-turn, hydrogen bonding, and bulkiness as reported previously [14,44]. Segments with pattern similarity close to 1.0 and average values similar to that of the reference segment were sought within each gapped sequence.</p><p>All software used in this study along with the instructions on how to use the computer programs are available in the form of ftp files on the Web [45] to download to PC computers.</p><!><p>EWC Egg white cystatin or hen cystatin.</p><p>HCC Human cystatin C.</p><p>HCA Human cystatin A or stefin A.</p><p>HCB Human cystatin B or stefin B.</p><p>HSA Homology similarity analysis: the PCS software was modified to compute pattern similarity constants and average side-chain property index values of segments in sequences [6].</p><p>HSS Homology similarity search: A step-wise search program initiated from N-terminus of query sequences by shifting the search unit (reference segment) towards C-terminus based on similar segments in terms of pattern similarity constant and average property values compared to those of template sequences [9].</p><p>MIC Minimum inhibitory concentration.</p><p>PCA Principal components analysis.</p><p>PCS Principal components similarity: PCA modified for multi-functional variables using linear regression of deviation of PC scores on the reference PC scores. Scatter plot is drawn as slope vs. coefficient of determination (r2) [44].</p><p>RCG Random-centroid optimization of site directed mutagenesis.</p><p>QSAR Quantitative structure-activity relationships.</p><!><p>EL participated in laboratory investigation to verify the hypothesis set in this study, while JD was taking care of the computer programming. SN was responsible mainly for the creation and application of software used in this study. All authors read and approved the final manuscript.</p><!><p>This work was financially supported by a Multidisciplinary Network Grant entitled "Structure-function of food biopolymers" (Dr. Rickey Y. Yada of University of Guelph as the principal investigator) from the Natural Sciences and Engineering Research Council of Canada. The authors acknowledge the collaboration of all co-authors listed in our past publications as shown in the following references. Especially, the drawing of 3D structures to compare lysozyme and α-lactalbumin by Dr. Yasumi Horimoto is highly appreciated.</p>

PubMed Open Access

FSP27 and PLIN1 interaction promotes the formation of large lipid droplets in human adipocytes

Human adipocytes express high levels of two distinct lipid droplet proteins, Fat Specific Protein 27 (FSP27; also called CIDEC), a member of the CIDE family, and perilipin1 (PLIN1), a member of the PAT family. Both proteins play a role in fat metabolism in adipocytes, but how they interact is not known. Our present study demonstrates that FSP27 and PLIN1 co-localize and interact in cultured human primary adipocytes. We also found that the C-terminal domain of FSP27, aa 120\xe2\x80\x93220, interacts with PLIN1. Individual expression of exogenous FSP27 or PLIN1 increased triglyceride content and decreased glycerol release (a measure of lipolysis), but co-expression of both proteins did not further increase triglyceride content or decrease lipolysis in human adipocytes. However, the combination of PLIN1 and FSP27 increased the average size of lipid droplets or caused the formation of unilocular adipocytes. Our data suggest that FSP27 interacts with PLIN1 to regulate lipid droplet size in human adipocytes in a concerted manner.

fsp27_and_plin1_interaction_promotes_the_formation_of_large_lipid_droplets_in_human_adipocytes

1. Introduction<!>2.1. Materials<!>2.2. Cell culture<!>2.3. Immunostaining<!>2.4. Lentivirus production and transduction<!>2.5. Adenovirus transduction<!>2.6. Immunoprecipitation<!>2.7. Lipid droplet staining<!>2.8. Microscopy<!>2.9. Lipolysis and Triglyceride Determination<!>3.1. FSP27 co-localizes with PLIN1 in human adipocytes<!>3.2. FSP27 interacts with PLIN1<!>3.3. Effect of exogenous FSP27 and PLIN1 co-expression on triglyceride accumulation and lipolysis in human adipocytes<!>3.4. Effect of FSP27 and PLIN1 co-overexpression on lipid droplet size in adipocytes<!>4. Discussion

<p>Cellular lipid droplets (LDs), now considered to be dynamic intracellular organelles, are composed of a core of neutral lipids surrounded by a phospholipid monolayer and associated proteins [1; 2; 3; 4; 5]. Proteins associated with the surface of LDs contribute to the biogenesis, maturation and stability of these organelles [1; 6]. Of the LD-associated proteins, the best-characterized are members of the PAT family, also called the perilipin (Plin) family of proteins [7; 8; 9; 10; 11]. They act as a scaffold at the LD surface and are suggested to have a structural and/or regulatory role in LD formation and function [8; 10; 12].</p><p>PLIN1 (also called Perilipin1) is highly expressed in adipocytes and plays a crucial role in regulating basal and stimulated lipolysis [8; 13]. Under basal conditions, PLIN1 prevents excess lipolysis by limiting access of hormone sensitive lipase, ATGL and its co-activator CGI-58 to LDs [14; 15; 16; 17; 18]. Upon β-adrenergic stimulation, protein kinase A (PKA) phosphorylates PLIN1 and causes the release of CGI-58 so it can bind and stimulate ATGL and also allows HSL to translocate to the LD surface [18; 19]. PLIN1 knockout increases basal lipolysis and decreases LD size in adipocytes and causes resistance to diet induced obesity in mice [20; 21]. In humans, lower PLIN1 expression is associated with higher rates of lipolysis [21; 22], and mutation in PLIN1 [23; 24], or its expression in obese human adipose tissue [25], correlates positively with insulin sensitivity.</p><p>FSP27 (also called CIDEC in humans) is also abundantly expressed on the LD surface [26; 27; 28] and has been shown to be crucial for the fusion of smaller LDs into larger ones [29; 30] and to promote triglyceride (TG) accumulation [26; 27; 28; 31; 32]. A mutation in CIDEC results in multilocular adipocytes associated with partial lipodystrophy and insulin resistance in a human subject [33]. Also, CIDEC expression was higher in visceral fat from insulin sensitive compared to insulin resistant obese humans [25]. These studies suggest that FSP27 plays an important role in regulating LD morphology and fat metabolism in adipocytes.</p><p>In 3T3-L1 adipocytes, exogenously expressed FSP27 co-localizes with endogenous PLIN1 at the LD surface [27]. However, the interaction of these proteins and its consequences for LD morphology and TG accumulation have not yet been reported. In the present study we analyzed the distribution of endogenous FSP27 and PLIN1 in cultured human primary adipocytes and tested the possibility that PLIN1 and FSP27 interact with each other. Furthermore, we analyzed the role of their interaction in regulating the LD morphology and TG accumulation in human adipocytes.</p><!><p>All chemicals were purchased from Sigma (St Louis, MO), except Rosiglitazone (Merck, Rahway, NJ), recombinant human insulin (Lilly, Indianapolis, IN), HCS LipidTOX-Deep Red (Invitrogen, CA). Fetal bovine serum and culture media were obtained from Invitrogen (Carlsbad, CA).</p><!><p>Human primary preadipocytes, procured from the Boston Nutrition Obesity Research Center adipocyte core, were cultured and differentiated as previously described [34].</p><!><p>For determination of PLIN1 and FSP27 localization, cells were cultured on coverslips. The immunostaining was performed using guinea pig anti-perilipin polyclonal antibody (1:1000 dilution; Research Diagnostics Inc., Flanders, NJ) and FSP27 monoclonal antibodies (1:1000 dilution) as described [27].</p><!><p>293T cells were seeded in 10 cm plates. Recombinant lentiviruses were produced by a five-plasmid transfection procedure as described [35]. The packaged recombinant lentiviruses were harvested from the supernatant of cell cultures 48 h after transfection and filtered through 0.45-μm filters. 500 μl supernatant and 10 μg/ml Polybrene was added to each well of a 12 well plate containing differentiated human adipocytes; after overnight incubation, the medium was changed to a regular maintenance medium. Protein expression was observed after 4 days of transduction.</p><!><p>PLIN1-Flag tagged and FSP27-HA tagged adenoviruses were generated at the Adenoviral Vector Core Facility at Tufts Medical Center. Virus was added at m.o.i of 100 to the human adipocytes. Cells were analyzed for protein expression after 24 or 48 h of infection.</p><!><p>Fully differentiated human adipocytes in 10 cm plates were transduced with recombinant adenovirus or lentivirus. Immunoprecipitations were carried out using antibodies as we described previously [36].</p><!><p>Cells plated on glass cover slips were washed twice with PBS, fixed in 4% formaldehyde for 20 minutes and quenched with 0.1 M glycine. Cells were then incubated with 0.5 μg/ml of Nile Red or HCS LipidTOX-Deep Red stain for 30 minutes and then washed with PBS.</p><!><p>Microscopy was performed using a Zeiss LSM 710-Live Duo scan (Carl Zeiss, Oberkochen, Germany) with a 100X oil immersion objective. Images were processed using Metamorph imaging software, version 6.1 (Universal Imaging, Downingtown, PA).</p><!><p>The cultured adipocytes were washed twice with PBS and incubated in Krebs-Ringer bicarbonate HEPES buffer supplemented with 4% bovine serum albumin. The buffer was collected after 2.5 hr of incubation for assaying glycerol as a measure of lipolysis. For triglyceride measurement the cells were lysed with cell lysis buffer (CellSignal). Glycerol and triglyceride were quantified using the Triglyceride Determination Kit (Sigma) according to the manufacturer's instructions.</p><!><p>Our previous study showed that exogenously expressed GFP-FSP27 co-localizes with endogenous PLIN1 in 3T3-L1 adipocytes [27]. Whether endogenous FSP27 and PLIN1 co-localize is not yet known. Therefore, in the present study the distribution of endogenous proteins was studied by immunofluorescence using monoclonal anti-FSP27 and polyclonal anti-perilipin antibodies. Fig. 1A shows localization of endogenous FSP27 and PLIN1 on the surface of a single LD in a cultured human adipocyte. Although FSP27 and PLIN1 did not completely overlap, the distribution pattern suggested that the two proteins might be in the same complex at the surface of the LD. Interestingly, both FSP27 and PLIN1 were also distributed apart from LDs (Fig. 1B). It could be that besides LDs these proteins are present in the endoplasmic reticulum or on minute LDs. In fact, recent studies have shown that FSP27 [37] and PLIN1 (Skinner et al. Adipocyte Journal (in press)) also localize to the endoplasmic reticulum in adipocytes.</p><!><p>Based upon the distribution pattern of endogenous FSP27 and PLIN1, we hypothesized that these proteins might interact with each other. To study their interaction, PLIN1-Flag and FSP27-HA constructs were used to produce lenti-viral preparations and infect mature human adipocytes. Anti-Flag and anti-HA antibodies were used to pull down the proteins. As shown in Fig. 1(C–D), endogenous PLIN1 co-immunoprecipitated with FSP27-HA (Fig. 1C) and PLIN1-Flag co-immunoprecipitated endogenous FSP27 (Fig. 1D) in human adipocytes. We therefore could pull down PLIN1 with FSP27 and vice versa. In order to confirm that endogenous PLIN1 and endogenous FSP27 interact with each other, we immunoprecipitated PLIN1 using PLIN1 antibodies and immunoblotted for FSP27. As expected, endogenous FSP27 co-immunoprecipitated with endogenous PLIN1 in human adipocytes (Fig. 1E).</p><p>To identify the domain of FSP27 interacting with PLIN1, we first tested if either the N- or C-terminus of FSP27 could pull down PLIN1. HA tagged aa 1–120 (N-terminus) and aa 120–239 (C-terminus) were co-expressed with PLIN1 in COS7 cells, which do not have endogenous expression of FSP27 or PLIN1. HA antibodies were used for immunoprecipitation. Only the C-terminal domain co-immunoprecipitated PLIN1 (data not shown), suggesting that C-terminus of FSP27 is responsible for its interaction with PLIN1. In a recent study we showed that amino acids 173–220 of FSP27 target its localization to LDs and play a role in LD clustering, whereas a fusogenic domain of FSP27 (aa 120–210) is sufficient for both clustering and LD fusion [29]. Therefore, we tested the domain aa 120–220, which spans both functional domains of FSP27 and belongs to the C-terminus region, for its interaction with PLIN1. HA-FSP27(120–220) was expressed in human adipocytes using a lentivirus. HA antibodies were used to immunoprecipitate FSP27. As shown in Fig. 1F, endogenous PLIN1 co-immunoprecipitated with FSP27(120–220), showing that at least aa 120–220 of FSP27 are involved in its interaction with PLIN1.</p><!><p>Overexpression of FSP27 or PLIN1 in adipocytes enhances TG storage [26; 27; 38], whereas FSP27 or PLIN1 depletion increases basal lipolysis in adipocytes [27; 38; 39; 40]. Therefore, in order to test if FSP27 and PLIN1 have additive or synergistic effect on TG accumulation or lipolysis in human adipocytes, we first examined expression levels of FSP27 and PLIN1 after adenoviral transfection of cultured human adipocytes. As shown in Fig. 2A, there was a 3- to 4-fold increase in the expression of both proteins. We then measured glycerol release into the medium, as a measure of lipolysis, and total TG in the cells. As shown in Fig. 2B, 48 hr after adenoviral-mediated overexpression of FSP27 or PLIN1 in human adipocytes, the total TG amount increased by about 40% and 70 %, respectively, but there was no significant further increase in total TG after 48 hrs of FSP27 and PLIN1 co-overexpression. Similar results were obtained after 72 hr of overexpressing FSP27 and/or PLIN1, that is, no difference in lipolysis or TG after co-overexpressing exogenous FSP27 and PLIN1 compared to the individually overexpressed proteins (data not shown). Consistent with this observation, FSP27 and PLIN1 individually decreased the accumulation of glycerol in the medium by about 30% and 60%, respectively (Fig. 2C). However, there was no additional effect of FSP27 and PLIN1 co-overexpression on glycerol release.</p><!><p>FSP27 knockdown causes fragmentation of LDs in adipocytes [27; 40]. Also, we and others recently demonstrated the role of FSP27 in regulating LD morphology [29; 30]. Therefore, we hypothesized that FSP27-PLIN1 interaction might facilitate the increase in LD size in human adipocytes. To test our hypothesis, we infected mature human adipocytes with FSP27 and/or PLIN1 adenovirus and studied the LD morphology. At 48–72 h after infection almost 25% of the FSP27 and PLIN1 co-expressing adipocytes showed unilocular droplets (Fig. 3A). Other cells showed either enlarged multiple droplets with tiny droplets surrounding them, or a much enlarged single droplet with almost 3–4 times the average radius of other droplets. A similar increase in LD size was observed when the PLIN1 interacting domain of FSP27, aa 120–220, was co-expressed with PLIN1 (data not shown). Quantitatively, the range of LD size was increased (Fig. 3B) in agreement with the average decrease in number of LDs (Fig. 3C) in adipocytes transduced with FSP27, PLIN1 or FSP27+PLIN1, with a larger effect in FSP27+PLIN1. These results suggest that both FSP27 and PLIN1 regulate the morphology of LDs in a concerted manner.</p><!><p>We here highlight the role of FSP27-PLIN1 interaction in regulating LD morphology in human adipocytes. We established that endogenous FSP27 and PLIN1 co-localize at the surface of LD in human adipocytes. Co-IP studies showed that these two proteins interact either directly or indirectly. Furthermore, we identified that the C-terminus domain, aa 120–220, of FSP27 interacts with PLIN1. The ability of FSP27 to increase LD size is further enhanced by PLIN1. After 48–72 h of co-expressing FSP27 and PLIN1 in cultured human adipocytes, unilocular LDs were formed in at least 25% of the cells. This morphological change was not associated with further accumulation of TG or a further decline in lipolysis when compared to the individually expressed proteins.</p><p>Our recent study identified the LD fusogenic potential of FSP27 [29]. Although direct evidence is lacking, it is likely that PLIN1 acts as a scaffold for FSP27 at the LD surface where FSP27 facilitates the fusion of LDs. A similar study from another group showed that exogenously expressed FSP27 concentrates at the contact site of droplets and promotes LD growth by lipid transfer between the droplets [30], whereas in our studies we did not observe a distinct distribution of endogenous FSP27 or PLIN1 at the contact site of droplets in human adipocytes (Fig. 1B). Probably a more complex process of membrane dynamics than simply a lipid transfer between droplets is involved in their fusion. Proteins like SNARE's, which have been shown to mediate fusion between cytosolic LDs, could be involved in this integrated process [41]. Further studies are required to establish a mechanism of LD fusion in adipocytes. Our present study suggests a concerted action of FSP27 and PLIN1 in promoting the enlargement of LDs. The expression of exogenous FSP27 in COS7 cells, which do not express endogenous FSP27 or PLIN1, increases LD size [29]. These enlarged droplets in COS7 cells are much smaller than the droplets in adipocytes, suggesting that the presence of both PLIN1 and FSP27 is required for the formation of enlarged LDs in adipocytes. Our observations are further supported by in vivo studies showing that FSP27 knockout mice have multilocular white adipocytes [31; 32; 42], and a mutation in human FSP27 (CIDEC) also mimics the multilocular phenotype in white adipose tissue [33].</p><p>It is commonly believed that the decrease in relative surface area on increasing LD size decreases the access of lipases and thus decreases lipolysis. While both PLIN1 and FSP27 overexpression increased triglyceride accumulation, PLIN1 overexpression increased triglyceride accumulation to a greater extent than FSP27. However, co-expression of both proteins had no additional effect on triglyceride content and lipolysis as compared to PLIN1 despite causing formation of larger and in many cases unilocular LDs. This strongly suggests that inhibition of lipolysis is a direct function of these LD surface proteins themselves and not an indirect result of the change in LD morphology, though clearly these two proteins also have important and synergistic roles in controlling LD morphology in adipocytes.</p>

PubMed Author Manuscript

Infrared Irradiation‐Assisted Solvent‐Free Pd‐Catalyzed (Hetero)aryl‐aryl Coupling via C−H Bond Activation

AbstractThe increasing attention towards environmentally friendly synthetic protocols has boosted studies directed to the development of green and sustainable methods for direct C−H bond arylation of (hetero)arenes. In this context, here the infrared (IR) irradiation‐assisted solvent‐free Pd‐catalyzed direct C−H bond arylation of (hetero)arenes was achieved. Several heteroaryl‐aryl coupling reactions were described, also involving heterocycles commonly used as building blocks for the synthesis of organic semiconductors. The reaction tolerated many functional groups on the aromatic nuclei. The IR‐irradiation as the energy source compared favorably with thermal heating and, in combination with solvent‐free conditions, provided an important contribution to the development of protocols fitting with the principles of green chemistry.

infrared_irradiation‐assisted_solvent‐free_pd‐catalyzed_(hetero)aryl‐aryl_coupling_via_c−h_bond_acti

<!>Introduction<!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!><!>Results and Discussion<!>Conclusion<!>General remarks<!>General procedure for the synthesis of compounds 2 a–f under IR irradiation<!><!>General procedure for the synthesis of compounds 2 a–f under IR irradiation<!>General procedure for the synthesis of compounds 4 a–f under IR irradiation<!>General procedure for the synthesis of compounds 6 a–f under IR irradiation<!>General procedure for the synthesis of compounds 8 a–g under IR irradiation<!>Conflict of interest<!>

<p>G. Albano, G. Decandia, M. A. M. Capozzi, N. Zappimbulso, A. Punzi, G. M. Farinola, ChemSusChem 2021, 14, 3391.</p><!><p>Green chemistry is defined as the "design of chemical products and processes to reduce or eliminate the use and generation of hazardous substances" and is based on the well‐known twelve principles, introduced in 1998 by Anastas and Warner, as operative rules to improve chemical processes sustainability.[1] Over the past 20 years, the green chemistry approach enabled to redesign the organic synthesis in ways that are benign for humans and sustainable in terms of economic, social, and environmental performance. However, many challenges still lie ahead, especially in the field of carbon‐carbon bond formation.</p><p>Palladium‐catalyzed direct C−H bond arylation of (hetero)arenes[2] fits well with most of the twelve principles of green chemistry, including atom economy leading to reduced wastes (principle 2), less hazardous chemical syntheses avoiding the use or generation of substances toxic to humans and/or the environment (principle 3), reduced generation of derivatives with consequent reduction of synthetic steps and minimization of additional waste (principle 8), and use of catalytic reagents (principle 9). In fact, the direct C−H bond activation eliminates the need of the preliminary preparation of air‐ and moisture‐sensitive, expensive, and toxic organometallic reagents required in traditional transition metal‐promoted cross‐coupling reactions. In a typical direct arylation process, an aryl halide reacts with the C−H bond of a (hetero)aromatic compound, in the presence of a palladium catalyst and a base to assist the C−H bond activation step, affording the corresponding coupling product.</p><p>Yet, there are aspects of direct C−H arylation processes that are scarcely compatible with the green chemistry criteria. One of the major drawbacks of most direct C−H arylation protocols is the use of toxic solvents (e. g., N,N‐dimethylformamide, N‐methyl‐2‐pyrrolidone, and N,N‐dimethylacetamide). Significant research efforts have been made in the last decades to set up more sustainable procedures, using environmentally benign solvents such as dialkyl carbonates, poly(ethylene glycol)s, water, γ‐valerolactone, ionic liquids, and deep eutectic solvents.[2a, 2b] According to principle 5 of green chemistry (safer solvents and auxiliaries) the development of fully solvent‐free conditions would provide even more sustainable protocols for direct arylation enabling to reduce wastes (solvent constitutes most of the mass wasted in organic synthesis), avoiding hazard and toxicity associated with some solvents and saving energy by short reaction times and simple workups. Despite these advantages, only a few examples of solvent‐free direct arylation reactions have been reported thus far.[2a, 2b, 3] In this context and in the frame of our studies on synthetic methods for heterocyclic‐based conjugated structures,[4] we previously developed direct arylation protocols for the preparation of fully substituted 1,2,3‐triazoles[4a] and extended heteroaromatic conjugated molecules,[4b] performed in solvent‐free, non‐anhydrous conditions and without exclusion of air.</p><p>Until now, one of the least investigated principles of green chemistry is represented by the principle 6 (design for energy efficiency): energy requirements should be recognized for their environmental impact and should be minimized. This is a very critical point in direct C−H bond arylation reactions since high temperatures are typically required for activation of the (hetero)aryl C−H bonds. The use of non‐conventional energy sources based on microwave irradiation,[5] ultrasound sonication,[6] and mechanical milling[7] has recently attracted attention as a valid alternative to thermal heating, leading to minimized reaction time, higher product yields, and reduced undesired by‐products.[8] However, these protocols often require access to specific and expensive instruments. As an attractive alternative, infrared (IR) irradiation has been recently demonstrated to be a highly efficient form of heating emitted from inexpensive lamps (i. e., a tungsten filament sealed in a quartz envelope with a halogen gas), and it represents a promising tool for fast, cheap, and green organic synthesis by respecting the principle 6 of green chemistry. IR radiation, able to excite the molecular vibrational levels, has been used as a convenient thermal activation method for various chemical processes, such as selective extraction of natural products and condensation reactions.[9] We recently reported the solvent‐free synthesis of squaraine and croconaine dyes by condensation reactions of oxocarbonic acids with indolenine‐based derivatives under IR‐light activation.[9c] However, the potential of IR‐assisted reactions is still almost unexplored, especially for palladium‐catalyzed coupling chemistry. Only a few examples of palladium‐catalyzed Heck reactions[9a] and Suzuki‐Miyaura cross couplings[9b] promoted by IR irradiation have been reported so far.</p><p>In this work, we report the first application of IR irradiation to palladium‐catalyzed direct C−H bond arylation reactions of (hetero)arenes, which are performed under solvent‐free and non‐anhydrous conditions. Our experiments show that this protocol reduces energy consumption with respect to the conventional thermal activation of reagents. In particular, the effectiveness of the IR irradiation as energy source in the solvent‐free C−H activation reaction of several heterocyclic structures leading to the synthesis of conjugated frameworks, is demonstrated. Combining the typical features of direct C−H arylation reactions with the use of IR irradiation under solvent‐free conditions enabled the development of a highly sustainable synthetic protocol, providing a clear progress in the context of green chemistry.</p><!><p>We started our study from direct arylation reaction of benzo[b]thiophene 1 with several aryl iodides. Arylated benzo[b]thiophenes are used as scaffolds in biologically active compounds and molecular semiconductors, and therefore several protocols, mostly based on the use of a Pd catalyst, have been developed for direct arylation of 1. Although C2‐regioselectivity is commonly observed,[10] C3‐arylation has been also reported under heterogeneous Pd catalysis.[11] The protocols described typically require high‐boiling solvents such as N,N‐dimethylacetamide or N,N‐dimethylformamide, which are toxic, and only recently examples of room‐temperature arylation of 1 in hexafluoro‐2‐propanol[10a] or water[10d] have been reported. Furthermore, long reaction time is needed with a few exceptions[12] including a microwave‐assisted procedure.[12c] We studied the IR‐promoted arylation reaction of 1 with iodobenzene in the absence of solvent and in various experimental conditions (Table 1). Homogeneous catalysts, such as Pd2(dba)3 in the presence of P(o‐MeOPh)3, Cs2CO3, and pivalic acid (PivOH)[4b] and Pd(OPiv)2 in the presence of P(o‐MeOPh)3 and Ag2CO3,[4b] in non‐anhydrous conditions and without exclusion of air, were initially tested leading to the coupling product 2  a in low (25 %, entry 1) to moderate yield (61 %, entry 2), respectively. In the latter conditions higher C2‐regioselectivity was observed (89 : 11 vs. 81 : 19). Supported Pd0 catalysts were then investigated. 2  a was obtained in 25 % yield (C2/C3 ratio 90 : 10, entry 3) in the presence of Pd/C and tetra‐n‐butylammonium acetate (Bu4NOAc) as the base,[4a] while reaction yield increased to 59 % (C2/C3 ratio 99 : 1, entry 4) when Pd/C was used in the presence of P(o‐MeOPh)3 and Ag2CO3. Pd/AlO(OH) nanoparticles without any additive are unable to catalyze the direct arylation of 1 (entry 5). When Pd/AlO(OH) nanoparticles at loadings as low as 0.15 mol% were used in the presence of Bu4NOAc or P(o‐MeOPh)3 and Ag2CO3, C2‐regioselective arylation occurred affording 2  a in 25 % yield (C2/C3 ratio 89 : 11, entry 6) and 65 % yield (C2/C3 ratio 98 : 2, entry 7), respectively. As it can be seen from results in entries 8 and 9, both phosphine and silver salt are needed for reaction to be proceed. The substitution of P(o‐MeOPh)3 with the less expansive PPh3 (entry 10) led to comparable yields (62 vs. 65 %) and a slightly higher C2‐regioselectivity (99.5 vs. 98). Similarly, it was possible to reduce PPh3 loading from 10 to 3 % without reduction of the yield (entry 11). Change of stoichiometry of the two coupling partners as well as of the catalyst loading was explored to improve the reaction conversion. We found that increasing the molar ratio 1/PhI from 1 : 1 to 1 : 1.5 (entry 12) or reducing to 1.5 : 1 (entry 13) does not significantly improve the reaction yield (59 and 63 %, respectively) and C2/C3 regioselectivity, while increasing catalyst loading to 0.3 mol% negatively affects the reaction outcome lowering the reaction yield to 49 % (entry 14). Remarkably, reduction of the reaction time from 1 h (entry 11) to 15 min (entry 15) gave quite similar conversion (80 vs. 83 %), C2/C3 regioselectivity (>99 % in both cases) and yield (60 vs. 58 %), enabling significant reduction of the energy consumption.</p><!><p>Optimization of the synthesis of 2  a.</p><p></p><p>Entry</p><p>1/PhI</p><p>Catalyst [mol %]</p><p>Phosphine [mol %]</p><p>Base (1 equiv.)</p><p>t</p><p>Conv.[a] [%]</p><p>2a/2aa[a]</p><p>Yield of 2a[b] [%]</p><p>1</p><p>1 : 1</p><p>Pd2(dba)3 (2)</p><p>P(o‐MeOPh)3 (4)</p><p>Cs2CO3</p><p>1 h</p><p>49</p><p>81 : 19</p><p>25[c]</p><p>2</p><p>1 : 1</p><p>Pd(OPiv)2 (5)</p><p>P(o‐MeOPh)3 (10)</p><p>Ag2CO3</p><p>1 h</p><p>86</p><p>89 : 11</p><p>61</p><p>3</p><p>1 : 1</p><p>Pd/C (5)</p><p>–</p><p>nBu4NOAc</p><p>1 h</p><p>54</p><p>90 : 10</p><p>24</p><p>4</p><p>1 : 1</p><p>Pd/C (5)</p><p>P(o‐MeOPh)3 (10)</p><p>Ag2CO3</p><p>2 h</p><p>88</p><p>99 : 1</p><p>59</p><p>5</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>–</p><p>–</p><p>1 h</p><p>0</p><p>–</p><p>–</p><p>6</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>–</p><p>nBu4NOAc</p><p>1 h</p><p>50</p><p>89 : 11</p><p>25</p><p>7</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>P(o‐MeOPh)3 (10)</p><p>Ag2CO3</p><p>1 h</p><p>85</p><p>98 : 2</p><p>65</p><p>8</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>P(o‐MeOPh)3 (10)</p><p>–</p><p>1 h</p><p>0</p><p>–</p><p>–</p><p>9</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>–</p><p>Ag2CO3</p><p>1 h</p><p>17</p><p>71 : 29</p><p>10</p><p>10</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (10)</p><p>Ag2CO3</p><p>1 h</p><p>82</p><p>99.5:0.5</p><p>62[d]</p><p>11</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>1 h</p><p>80</p><p>99.5:0.5</p><p>60</p><p>12</p><p>1 : 1.5</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>1 h</p><p>78</p><p>99.5:0.5</p><p>59</p><p>13</p><p>1.5 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>2 h</p><p>–</p><p>99.5:0.5</p><p>63</p><p>14</p><p>1 : 1</p><p>Pd/AlO(OH) (0.3)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>1 h</p><p>73</p><p>99 : 1</p><p>49</p><p>15</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>15 min</p><p>83</p><p>99.5:0.5</p><p>58[e]</p><p>[a] Conversion and C2/C3 regioselectivity by GC–MS analysis of crude reaction mixtures. [b] Unless specified, C−H arylations were carried out on 1 mmol scale. Yields on isolated product. [c] Pivalic acid (30 mol%) was used as additive. [d] After replacing Ag2CO3 with Cs2CO3, 2  a was isolated in 14 % yield (reaction conversion: 28 %; C2/C3 ratio: 78 : 22). [e] This reaction was repeated on 3 mmol scale (1st run: 58 % yield, 2nd run: 32 % yield).</p><!><p>To investigate the scope of the reaction, 1 was reacted with various aryl iodides under the experimental conditions defined in entry 15 of Table 1. The results of the screening are shown in Scheme 1. The benzo[b]thiophene‐aryl coupling reactions occurred in moderate to good yields using aryl iodides functionalized with both electron‐donating functionalities, such as methyl and methoxy groups (2  c: 70 % and 2  d: 52 %, respectively) and electron‐withdrawing groups (2  b: 51 %, 2  e: 68 %, 2  f: 43 %). In the same experimental conditions, a conversion of 20 % was detected replacing iodobenzene with bromobenzene.</p><!><p>Direct arylation of benzo[b]thiophene 1 with iodoarenes. The C−H arylation was performed on 1 mmol scale: 1 (1 equiv.), aryl iodide (1 equiv.), Pd/AlO(OH) nanoparticles (0.15 mol%), PPh3 (3 mol%), Ag2CO3 (1 equiv.) in solvent‐free and non‐anhydrous conditions and in the presence of air, under IR radiation for 15 min. [a] Conversion by GC‐MS analysis. α‐Selectivity >99 % by GC‐MS analysis. [b] Isolated yield. [c] Conversion of 20 % was detected replacing iodobenzene with bromobenzene.</p><!><p>We also explored 5‐octylthieno[3,4‐c]pyrrole‐4,6‐dione (TPD) (3) as the starting reagent. This core is widely used as an electron‐deficient unit in the synthesis of low‐bandgap donor–acceptor molecules and polymers for organic solar cells, which can be synthesized by direct (hetero)arylation polymerization.[13] Preliminary investigation was carried out using 3 with iodobenzene under different experimental conditions (Table 2).</p><!><p>Optimization of the synthesis of 4  a.</p><p></p><p>Entry</p><p>3/PhI</p><p>Catalyst [mol %]</p><p>Phosphine [mol %]</p><p>Base (1 equiv.)</p><p>t</p><p>Conv.[a] [%]</p><p>Yield of 4a[a] [%]</p><p>1</p><p>1 : 2.4</p><p>Pd/AlO(OH) (0.3)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>2 h</p><p>96[b]</p><p>59</p><p>2</p><p>1 : 3</p><p>Pd/AlO(OH) (0.3)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>2 h</p><p>91[b]</p><p>65</p><p>3[c]</p><p>1 : 3</p><p>Pd2(dba)3 (2)</p><p>P(o‐MeOPh)3 (4)</p><p>Cs2CO3</p><p>2 h</p><p>96[b]</p><p>52</p><p>4</p><p>1 : 3</p><p>Pd(OPiv)2 (5)</p><p>P(o‐MeOPh)3 (10)</p><p>Ag2CO3</p><p>1 h</p><p>100[d]</p><p>78</p><p>5</p><p>1 : 3</p><p>Pd(OPiv)2 (5)</p><p>PPh3 (10)</p><p>Ag2CO3</p><p>1 h</p><p>100[d]</p><p>79</p><p>6</p><p>1 : 3</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>1 h</p><p>100[d]</p><p>77</p><p>7</p><p>1 : 3</p><p>Pd(OPiv)2 (1)</p><p>PPh3 (2)</p><p>Ag2CO3</p><p>1 h</p><p>99[b]</p><p>70</p><p>8</p><p>1 : 3</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>30 min</p><p>100[d]</p><p>72</p><p>[a] Reactions carried out on 0.5 mmol scale. Yields on isolated product. [b] Conversion by GC–MS analysis. [c] Pivalic acid (30 mol%) was used as additive. [d] Complete conversion by thin‐layer chromatography (TLC) and GC‐MS analysis.</p><!><p>When 3 was reacted with iodobenzene (3/PhI 1 : 2.4 molar ratio) using Pd/AlO(OH) nanoparticles as the catalyst in the presence of PPh3 and Ag2CO3, 4  a was obtained in moderate yield (59 %, entry 1) and a significant amount of mono‐coupling product was obtained. No significant increase of the yield was observed by increasing 3/PhI molar ratio to 1 : 3 (65 %, entry 2). The yield was also moderate using Pd2(dba)3 in the presence of P(o‐MeOPh)3, Cs2CO3, and PivOH (52 %, entry 3), whereas Pd(OPiv)2 in the presence of P(o‐MeOPh)3 and Ag2CO3 afforded 4  a in 78 % (entry 4). Having selected Pd(OPiv)2 as the best catalyst, we examined the role of phosphine ligands, finding again that the replacement of P(o‐MeOPh)3 with the less expansive PPh3 led to a quite similar reaction outcome (79 % yield, entry 5). Lowering the Pd(OPiv)2 loading to 2 mol% (entry 6) resulted in a negligible decrease of the reaction yield (76 vs. 79 %). Further decreasing the amount of the catalyst to 1 mol% (entry 7) or shortening the reaction time to 30 min (entry 8) produced a more significant decrease of the yield to 70 % (entry 7) and 72 % (entry 8), respectively.</p><p>With the optimized conditions in hand (Table 2, entry 6), we investigated the scope of the reaction (Scheme 2). TPD 3 was coupled with a series of aryl iodides affording the bis‐arylated compounds 4  a–f in in good to excellent yields after only 1 h of IR irradiation. Both electron‐donating functionalities, such as methyl in the ortho‐position and methoxy groups (4  e: 71 % and 4  f: 70 %, respectively) and electron‐withdrawing groups (4  b: 77 %, 4  c: 73 %, 4  d: 54 %) can be tolerated. In the same experimental conditions, 4  a was obtained in 16 % yield (69 % conversion) using bromobenzene instead of iodobenzene.</p><!><p>Direct arylation of 5‐octylthieno[3,4‐c]pyrrole‐4,6‐dione 3 with iodoarenes. The C−H arylation was performed on 0.5 mmol scale: 3 (1 equiv.), aryl iodide (3 equiv.), Pd(OPiv)2 (2 mol %), PPh3 (4 mol %), Ag2CO3 (1 equiv.) in solvent‐free and non‐anhydrous conditions and in the presence of air, under IR radiation for 1 h. Complete conversion by TLC and GC–MS analysis. Isolated yields. [a] 4  a was obtained in 16 % yield by use of bromobenzene instead of iodobenzene.</p><!><p>1‐Hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazole 5 was then selected as a model nitrogen aromatic heterocycle because of the relevance of triazolyl[14] motif in many compounds of interest in biology and materials science. Although the Pd‐catalyzed direct arylation of 1,4‐disubstituted 1,2,3‐triazoles is the most general approach for the synthesis of fully substituted 1,2,3‐triazoles, only a few examples of sustainable direct arylation protocols based on the use of environmentally benign reaction solvents (e. g., polyethylene glycol, γ‐valerolactone) instead of the traditional high‐boiling toxic solvents (e. g., N,N‐dimethylformamide, N‐methyl‐2‐pyrrolidone, toluene) have been reported in the literature.[15] Recently, we developed the first Pd‐catalyzed direct arylation protocol of 1,4‐disubstituted 1,2,3‐triazoles performed in solvent‐free conditions affording fully substituted 1,2,3‐triazoles in 44–81 % yields after 24 h of conventional thermal heating.[4b]</p><p>A preliminary screening of the experimental conditions shows that the solvent‐free direct arylation of 1,4‐disubstituted 1,2,3‐triazoles can be carried out in shorter reaction time by IR irradiation (Table 3). When 5 was reacted with iodobenzene (5/PhI 1 : 1.5 molar ratio) using Pd/AlO(OH) nanoparticles as the catalyst in the presence of PPh3 and Ag2CO3, 6  a was obtained in low yield (38 %, entry 1). The use of Pd(OPiv)2 as the catalyst in the presence of PPh3 and Ag2CO3 afforded 6  a in 69 % yield after 30 min (entry 2) and in 76 % yield after 1 h (entry 3). Increasing the 5/PhI molar ratio to 1 : 2 and the PPh3 loading to 6 mol% resulted in a small decrease of the reaction yields (entries 4 and 5). On the contrary, increasing the reaction time to 2 h afforded a higher yield (83 %, entry 6).</p><!><p>Optimization of the synthesis of 6  a.</p><p></p><p>Entry</p><p>5/PhI</p><p>Catalyst [mol %]</p><p>Phosphine [mol %]</p><p>Base (1 equiv.)</p><p>t</p><p>Conv.[a] [%]</p><p>Yield[b] [%]</p><p>1</p><p>1 : 1.5</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>2 h</p><p>60</p><p>38</p><p>2</p><p>1 : 1.5</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>30 min</p><p>86</p><p>69</p><p>3</p><p>1 : 1.5</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>1 h</p><p>95</p><p>76</p><p>4</p><p>1 : 2</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>1 h</p><p>100</p><p>71</p><p>5</p><p>1 : 1.5</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (6)</p><p>Ag2CO3</p><p>1 h</p><p>97</p><p>71</p><p>6</p><p>1 : 1.5</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>2 h</p><p>97</p><p>83</p><p>[a] Conversion by recovery of unreacted triazole 1. [b] Reactions carried out on 0.5 mmol scale. Yields on isolated product.</p><!><p>In the latter conditions, the scope of the reaction was investigated using 5 with aryl iodides bearing various substituents (Scheme 3). All the coupling reactions occurred in good yields using aryl iodides substituted with both electron‐donating functionalities, such as methyl groups (6  b: 77 %, 6  c: 74 %, 6  d: 74 %) and electron‐withdrawing groups (6  e: 69 %, 6  f: 69 %). In the same experimental conditions, the conversion dropped down to 40 % when iodobenzene was replaced with bromobenzene.</p><!><p>Direct arylation of 1‐hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazole 5 with iodoarenes. The C−H arylation was performed on 0.5 mmol scale: 5 (1 equiv.), aryl iodide (1.5 equiv.), Pd(OPiv)2 (2 mol %), PPh3 (4 mol %), Ag2CO3 (1 equiv.) in solvent‐free and non‐anhydrous conditions and in the presence of air, under IR radiation for 2 h. [a] Conversion by recovery of unreacted triazole 5. [b] Isolated yields. Reactions carried out on 0.5 mmol scale. [c] A conversion of 40 % was detected replacing iodobenzene with bromobenzene. [d] In the same experimental conditions, after 1 h: 78 % conversion, 60 % yield.</p><!><p>Finally, we extended the investigation to the C−H arylation to fluorinated arenes, useful building blocks for the synthesis of a variety of materials for organic optoelectronics.[16] In this context, we investigated the pentafluorobenzene 7 as the starting material. Several protocols based on the use of both homogeneous[17] and heterogeneous Pd catalyst[18] for direct arylation of 7 have been already reported in the literature. These reactions are typically carried out in high boiling solvents such as N,N‐dimethylacetamide but an example of low‐temperature arylation of 7 in THF was also reported.[17b] To the best of our knowledge, the direct arylation reaction of 7 in solvent‐free conditions has not been reported so far. A preliminary screening of experimental conditions shows that the IR irradiation allows the direct arylation of 7 in solvent free conditions in very short reaction times and in the presence of a low catalytic loading (Table 4).</p><!><p>Optimization of the synthesis of 8  a.</p><p></p><p>Entry</p><p>7/PhI</p><p>Catalyst [mol %]</p><p>Phosphine [mol %]</p><p>Base (1 equiv.)</p><p>t</p><p>Yield[a] [%]</p><p>1</p><p>1 : 1</p><p>Pd(OPiv)2 (2)</p><p>PPh3 (4)</p><p>Ag2CO3</p><p>1 h</p><p>27</p><p>2</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>1 h</p><p>85</p><p>3</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>30 min</p><p>87</p><p>4</p><p>1 : 1</p><p>Pd/AlO(OH) (0.15)</p><p>PPh3 (3)</p><p>Ag2CO3</p><p>15 min</p><p>87</p><p>[a] Reactions carried out on 1 mmol scale. Yields on isolated product. Complete conversion by TLC and GC‐MS analysis.</p><!><p>While the expected product 8  a was isolated in low yield using Pd(OPiv)2 as the catalyst (27 %, entry 1), the use of Pd/AlO(OH) nanoparticles in only 0.15 mol% loading afforded 8  a in high yields (≥85 %, entries 2–4). Notably, reducing the reaction time from 1 h (entry 2) to 30 min (entry 3) and then to 15 min (entry 4) led to 8  a in the same yield, indicating that the reaction is very fast under these conditions. With the optimized conditions in hand (Table 4, entry 4), the scope of the reaction was investigated also in this case (Scheme 4). We found that coupling products can be obtained in good yields using aryl iodides bearing both electron‐donating functionalities, such as methyl (8  d: 78 %, 8  f: 86 %) and methoxy (8  c: 54 %) groups, and electron‐withdrawing groups (8  b: 76 %, 8  e: 77 %, 8  g: 84 %, 8  h: 68 %). As for the other substrates, a conversion lower than 20 % was detected replacing iodobenzene with bromobenzene.</p><!><p>Direct arylation of pentafluorobenzene 7 with iodoarenes. The C−H arylation was performed on 1 mmol scale: 7 (1 equiv.), aryl iodide (1 equiv.), Pd/AlO(OH) (0.15 mol %), PPh3 (3 mol %), Ag2CO3 (1 equiv.) in solvent‐free and non‐anhydrous conditions and in the presence of air, under IR radiation for 15 min. Complete conversion by TLC and GC‐MS analysis. Isolated yields. [a] A conversion lower than 20 % was detected replacing iodobenzene with bromobenzene. [b] Reaction carried out on 0.5 mmol scale. [c] Reaction carried out in the presence of a mixture of cyclopentyl methyl ether (CPME, 0.1 mL) and dimethyl sulfoxide (DMSO, 0.1 mL).</p><!><p>A comparative study of solvent‐free direct arylation protocols energy consumption under IR irradiation and under thermal heating was carried out by measuring the energy supplied to obtain one mmol of reaction product under the two different experimental conditions. For these experiments, direct arylation reactions of 1, 3, 5, and 7 with iodobenzene were selected as model reactions. Each heterogeneous reaction mixture was charged in a Carius tube, then heated under IR lamp (the distance between the bottom of Carius tube and the lamp bulb was set to 7 cm) or in a pre‐warmed (160 °C) sand bath, under magnetic stirring. Keeping all the other experimental parameters the same, including reaction times, the measurements showed that the reactions performed under IR irradiation require significantly less energy compared to those performed under conventional thermal heating activation (Table 5, Figure 1). The IR‐irradiation assisted reactions afforded compounds 2  a and 4  a in yields comparable to those obtained from reactions using conventional thermal heating (2  a: 58 vs. 55 %; 4  a: 77 vs. 82 %) with energy consumption 17 and 6 times lower, respectively. Similarly, compounds 6  a and 8  a were isolated in higher yields (6  a: 83 vs. 74 %, 8  a: 87 vs. 72 %) with energy consumption 6 and 20 times lower, respectively. These results clearly show that IR irradiation represents an efficient and inexpensive activation method for the palladium‐catalyzed direct C−H bond arylation of (hetero)arenes in solvent‐free conditions in compliance with the principle 6 of green chemistry (design for energy efficiency).</p><!><p>Energy consumption for the synthesis of compounds 2  a, 4  a, 6  a, and 8  a under IR irradiation and conventional thermal heating.[a,b]</p><p>Compound</p><p>IR irradiation[c]</p><p>Thermal heating[d]</p><p>Yield [%]</p><p>Energy [kWh mmol−1]</p><p>Yield [%]</p><p>Energy [kWh mmol−1]</p><p>2a</p><p>58</p><p>0.11</p><p>55</p><p>1.88</p><p>4a</p><p>77</p><p>0.65</p><p>82</p><p>4.02</p><p>6a</p><p>83</p><p>1.20</p><p>74</p><p>6.69</p><p>8a</p><p>87</p><p>0.07</p><p>72</p><p>1.43</p><p>[a] The stirred heterogeneous reaction mixture charged in a Carius tube was heated by a white IR lamp (the distance between the bottom of Carius tube and the bulb lamp was set to 7 cm) or in a pre‐warmed (160 °C) sand bath. [b] Energy consumption calculated as the energy absorption of the instrumental set up for isolated mmol of compound. [c] Energy: 0.25 kW×reaction time (h)×1/isolated mmol. [d] Energy: 0.825 kW×[pre‐heating (1 h)+reaction time (h)]×1/isolated mmol.</p><p>Energy consumption for the synthesis of compounds 2  a, 4  a, 6  a, and 8  a under IR irradiation and conventional thermal heating.</p><!><p>Finally, to further address the sustainability of our IR‐assisted conditions as a general solvent‐free protocol, we tested the combination of the solvent free arylation reaction with a product isolation protocol different from column chromatography, which requires the use of a considerable amount of solvent. As an example, the synthesis of 2  a was scaled‐up (reaction was carried out on 3 mmol scale) and the crude reaction mixture, after a short percolation on silica gel to eliminate catalyst and salts, was purified by crystallization from hexane. This result highlights the possibility of reducing the solvent used also in the product isolation (≈100 mL was used for both percolation and crystallization, while more than 1 L was necessary for purification on column chromatography).</p><!><p>We have reported the first IR irradiation‐assisted, solvent‐free Pd‐catalyzed (hetero)aryl‐aryl coupling via C−H bond activation, in compliance with several principles of green chemistry. In particular, the combination of the advantages of direct C−H arylation reaction mainly related to the principles 2, 3, 8 and 9 with the use of IR irradiation (principle 6) under solvent‐free conditions (principle 5) enabled the development of a highly sustainable and environmentally friendly synthetic procedure. The protocol was tested for several (hetero)aryl‐aryl couplings, leading to diverse structural motifs. The effectiveness of the IR irradiation as a convenient energy source versus the conventional thermal heating is demonstrated. We are convinced that the application of IR irradiation to organic reactions can provide significant advantages in the context of green chemistry, which include reduced energy consumption, shortened reaction times, and even access to new mechanistic pathways, in addition to its compatibility with solvent‐free conditions as reported here. Therefore, IR irradiation may soon become a precious tool for fast, cheap, and sustainable synthesis: a powerful enabling technology which can help to usher in a greener era of organic synthesis.</p><!><p>Reagents and solvents were purchased at the highest commercial purity and used without further purification. Benzo[b]thiophene 1 and pentafluorobenzene 7 were purchased from Sigma Aldrich. 5‐Octylthieno[3,4‐c]pyrrole‐4,6‐dione 3 was purchased from TCI Europe and SunaTech Inc. 1‐Hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazole 5 was prepared according to a literature procedure.[4a] Preparative column chromatography was performed using Macherey‐Nagel silica gel (60, particle size 0.063–0.2 mm). Macherey‐Nagel aluminum sheets with silica gel 60 F254 were used for TLC. All new compounds were characterized by 1H NMR, 13C NMR, and LC−MS analyses. 1H NMR and 13C NMR spectra were acquired on an Agilent 500 spectrometer at 500 and at 126 MHz, respectively, using the CDCl3 residual proton peak at δ=7.26 ppm as internal standard for 1H spectra and the signals of CDCl3 at δ=77.16 ppm as internal standard for 13C spectra. GC−MS analyses were performed on a Thermo Polaris Q spectrometer equipped with a Macherey‐Nagel Optima‐1 capillary column (30 m×0.25 mm id), ionization mode EI (70 eV). Attenuated total reflectance Fourier‐transform infrared (ATR‐FTIR) spectra were acquired with a Perkin Elmer Spectrum Two Spectrophotometer equipped with A 2×2 mm Diamond crystal. Spectra were recorded in the range 4000–400 cm−1 with a 4 cm−1 resolution, using 0.25 cm−1 acquisition interval and acquiring 16 scans for each sample. High‐resolution mass spectra were acquired with a Shimadzu high‐performance liquid chromatography ion trap time‐of flight (LC‐ESI‐IT‐TOF) mass spectrometer via direct infusion of the samples. Melting points were determined on a Stuart Scientific Melting point apparatus SMP3. Reactions under IR‐irradiation were carried out using a Philips Infrared Industrial Heat Incandescent lamp Br125 IR 250 W 230–250 VCL 1CT (it has a broad spectrum, but most of the radiation covers the NIR with an emission peak at 1200 nm). Under IR irradiation, reaction temperatures rapidly increased up to 160 °C as detected by an IR or a digital thermometer.</p><!><p>A Carius tube (ø=1.6 cm) with a screw cap and equipped with a magnetic stirrer was charged with benzo[b]thiophene 1 (1.0 mmol), aryl iodide (1.0 mmol), Pd/AlO(OH) nanoparticles (0.15 mol%), PPh3 (3 mol%), Ag2CO3 (1.0 mmol). The resulting heterogeneous reaction mixture was heated under an IR lamp (the distance between the bottom of Carius tube and the bulb was set to 7 cm, Figure 2). After 15 min, the mixture was cooled to room temperature and the crude product was purified by column chromatography on silica gel.</p><!><p>Experimental set‐up</p><!><p>2‐Phenylbenzo[b]thiophene (2  a):[10a] Compound 2  a was synthesized from 1 (135 mg, 1.0 mmol) and iodobenzene (204 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=99 : 1) afforded 122 mg of compound 2  a as a white solid (58 % yield). Analytical data are in agreement with those previously reported in the literature.[10a] R f (n‐hexane/ethyl acetate=99 : 1)=0.52; 1H NMR (500 MHz, CDCl3): δ=7.84 (d, J=8.2 Hz, 1H), 7.78 (d, J=7.4 Hz, 1H), 7.74–7.71 (m, 2H), 7.56 (s, 1H), 7.44 (t, J=7.6 Hz, 2H), 7.38–7.30 ppm (m, 3H); 13C NMR (126 MHz, CDCl3): δ=144.4, 140.8, 139.6, 134.4, 129.1, 128.4, 126.6, 124.6, 124.4, 123.7, 122.4, 119.6 ppm; MS (70 eV): m/z (%): 210 (100) [M]+., 209 (13) [M‐H]+.</p><p>2‐(4‐Nitrophenyl)benzo[b]thiophene (2  b):[10a] Compound 2  b was synthesized from 1 (135 mg, 1.0 mmol) and 1‐iodo‐4‐nitrobenzene (249 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=99:1→9:1) afforded 131 mg of compound 2  b as a pale‐yellow solid (51 % yield). Analytical data are in agreement with those previously reported in the literature.[10a] R f (n‐hexane/ethyl acetate=99 : 1)=0.33; 1H NMR (500 MHz, CDCl3): δ=8.28 (d, J=9.0 Hz, 2H), 7.88–7.82 (m, 4H), 7.71 (s, 1H), 7.43–7.37 ppm (m, 2H); 13C NMR (126 MHz, CDCl3): δ=147.3, 141.3, 140.7, 140.4, 140.4, 126.9, 125.7, 125.2, 124.5, 124.4, 122.6, 122.6 ppm; MS (70 eV): m/z (%): 255 (100) [M]+., 209 (25) [M‐NO2]+.</p><p>2‐(p‐Tolyl)benzo[b]thiophene (2  c):[10a] Compound 2  c was synthesized from 1 (135 mg, 1.0 mmol) and 1‐iodo‐4‐methylbenzene (218 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 157 mg of compound 2  c as a white solid (70 % yield). Analytical data are in agreement with those previously reported in the literature.[10a] R f (n‐hexane)=0.50; 1H NMR (500 MHz, CDCl3): δ=7.82 (d, J=8.2 Hz, 1H), 7.76 (d, J=7.6 Hz, 1H), 7.62 (d, J=8.0 Hz, 2H), 7.51 (s, 1H), 7.35 (td, J=7.6, 1.2 Hz, 1H), 7.32–7.28 (m, 1H), 7.24 (d, J=8.0 Hz, 2H), 2.40 ppm (s, 3H); 13C NMR (126 MHz, CDCl3): δ=144.5, 140.9, 139.5, 138.4, 131.6, 129.8, 126.5, 124.6, 124.3, 123.5, 122.4, 119.0, 21.4 ppm; MS (70 eV): m/z (%): 224 (100) [M]+., 223 (45) [M‐H]+.</p><p>2‐(4‐Methoxyphenyl)benzo[b]thiophene (2  d):[10a] Compound 2  d was synthesized from 1 (135 mg, 1.0 mmol) and 1‐iodo‐4‐methoxybenzene (234 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/CH2Cl2=4 : 1) afforded 125 mg of compound 2  d as a white solid (52 % yield). Analytical data are in agreement with those previously reported in the literature.[10a] R f (n‐hexane/CH2Cl2=4 : 1)=0.49; 1H NMR (500 MHz, CDCl3): δ=7.81 (d, J=8.2 Hz, 1H), 7.74 (d, J=7.7 Hz, 1H), 7.65 (d like, J=8.8 Hz, 2H), 7.43 (s, 1H), 7.34 (td, J=7.7, 1.2 Hz, 1H), 7.31–7.26 (m, 1H), 6.96 (d like, J=8.8 Hz, 2H), 3.86 ppm (s, 3H); 13C NMR (126 MHz, CDCl3): δ=159.9, 144.3, 141.0, 139.3,127.9, 127.2, 124.6, 124.1, 123.4, 122.3, 118.4, 114.5, 55.5 ppm; MS (70 eV): m/z (%): 240 (100) [M]+., 225 (93) [M−CH3]+.</p><p>2‐(4‐Fluorophenyl)benzo[b]thiophene (2  e):[10a] Compound 2  e was synthesized from 1 (135 mg, 1.0 mmol) and 1‐fluoro‐4‐iodobenzene (222 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 155 mg of compound 2  e as a white solid (68 % yield). Analytical data are in agreement with those previously reported in the literature.[10a] R f (n‐hexane)=0.42; 1H NMR (500 MHz, CDCl3): δ=7.83 (d, J=7.8 Hz, 1H), 7.77 (d, J=7.6 Hz, 1H), 7.71–7.65 (m 2H), 7.47 (s, 1H), 7.36 (td, J=7.6, 1.2 Hz, 1H), 7.32 (td, J=7.8, 1.3 Hz, 1H), 7.13 ppm (t like, J=8.6 Hz, 2H); 13C NMR (126 MHz, CDCl3): δ=163.9 (d, J=248.4 Hz), 143.2, 140.8, 139.6, 130.7 (d, J=3.5 Hz), 128.3 (d, J=8.1 Hz), 124.8, 124.5, 123.7, 122.4, 119.6 (d, J=1.3 Hz), 116.1 ppm (d, J=21.9 Hz); MS (70 eV): m/z (%): 228 (100) [M]+., 227 (9) [M‐H]+.</p><p>1‐(4‐(Benzo[b]thiophen‐2‐yl)phenyl)ethanone (2  f):[10a] Compound 2  f was synthesized from 1 (135 mg, 1.0 mmol) and 1‐(4‐iodophenyl)ethanone (246 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=9 : 1) afforded 108 mg of compound 2  f as a white solid (43 % yield). Analytical data are in agreement with those previously reported in the literature.[10a] R f (n‐hexane/ethyl acetate=9 : 1)=0.29; 1H NMR (500 MHz, CDCl3): δ=8.02 (d like, J=8.5 Hz, 2H), 7.87–7.84 (m, 1H), 7.83–7.79 (m, 3H), 7.68 (s, 1H), 7.40–7.33 (m, 2H), 2.64 ppm (s, 3H); 13C NMR (126 MHz, CDCl3) δ :197.4, 142.8, 140.6, 140.0, 138.8, 136.5, 129.2, 126.5, 125.2, 124.9, 124.1, 122.5, 121.3, 26.8 ppm; MS (70 eV): m/z (%): 252 (65) [M]+., 237 (100) [M−CH3]+. 209 (33) [M−C(O)CH3]+.</p><!><p>A Carius tube (ø=1.6 cm) with a screw cap and equipped with a magnetic stirrer was charged with 5‐octylthieno[3,4‐c]pyrrole‐4,6‐dione 3 (0.5 mmol), aryl iodide (1.5 mmol), Pd(OPiv)2 (2 mol%), PPh3 (4 mol%), Ag2CO3 (0.5 mmol). The resulting heterogeneous reaction mixture was heated under an IR lamp (the distance between the bottom of Carius tube and the bulb was set to 7 cm, Figure 2). After 1 h, the mixture was cooled to room temperature and the crude product was purified by column chromatography on silica gel.</p><p>5‐Octyl‐1,3‐diphenyl‐4H‐thieno[3,4‐c]pyrrole‐4,6(5H)‐dione (4  a):[4b, 4c] Compound 4  a was synthesized from 3 (133 mg, 0.5 mmol) and iodobenzene (306 mg, 1.5 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=9 : 1) afforded 160 mg of compound 4  a as a pale‐yellow solid (77 % yield). Analytical data are in agreement with those previously reported in the literature.[4c] R f (n‐hexane/ethyl acetate=9 : 1)=0.68; 1H NMR (500 MHz, CDCl3): δ=8.13 (d like, J=7.0 Hz, 4H), 7.51–7.40 (m, 6H), 3.67 (t, J=7.5 Hz, 2H), 1.71–1.64 (m 2H), 1.39–1.22 (m, 10H), 0.86 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=162.9, 144.9, 130.6, 130.5, 130.1, 129.0, 128.0, 38.7, 31.9, 29.3, 29.3, 28.6, 27.1, 22.7, 14.2 ppm; MS (70 eV): m/z (%): 417 (91) [M]+., 318 (93) [M−C 7H15]+, 304 (13) [M−C 8H17]+.</p><p>1,3‐Bis(4‐nitrophenyl)‐5‐octyl‐4H‐thieno[3,4‐c]pyrrole‐4,6(5H)‐dione (4  b):[4b, 4c] Compound 4  b was synthesized from 3 (133 mg, 0.50 mmol) and 1‐iodo‐4‐nitrobenzene (374 mg, 1.50 mmol), in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8:2→7:3) afforded compound 4  g (184 mg, 77 % yield) as a yellow solid. Analytical data are in agreement with those previously reported in the literature.[4c] R f (n‐hexane/ethyl acetate=8 : 2)=0.67; 1H NMR (500 MHz, CDCl3): δ=8.35 (s, 8H), 3.71 (t, J=7.2 Hz, 2H), 1.74–1.66 (m, 2H), 1.40–1.22 (m, 10H), 0.87 ppm (t, J=6.9 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=162.4, 148.5, 143.0, 135.9, 133.4, 129.2, 124.5, 39.2, 31.9, 29.3, 29.3, 28.5, 27.1, 22.8, 14.2 ppm.</p><p>Dimethyl 4,4′‐(5‐Octyl‐4,6‐dioxo‐5,6‐dihydro‐4H‐thieno[3,4‐c]‐pyrrole‐1,3‐diyl)dibenzoate (4  c):[4b, 4c] Compound 4  c was synthesized from 3 (133 mg, 0.50 mmol) and methyl 4‐iodobenzoate (393 mg,1.50 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8.5 : 1.5) afforded compound 4  c (194 mg, 73 % yield) as a yellow solid. Analytical data are in agreement with those previously reported in the literature.[4c] R f (n‐hexane/ethyl acetate=8.5 : 1.5)=0.36; 1H NMR (500 MHz, CDCl3): δ=8.24‐8.21 (m, 4H), 8.15–8.12 (m, 4H), 3.96 (s, 6H), 3.69 (t, J=7.5 Hz, 2H), 1.72–1.65 (m, 2H), 1.39–1.22 (m, 10H), 0.87 ppm (t, J=6.9 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=166.3, 162.6, 144.0, 134.3, 132.1, 131.4, 130.3, 128.1, 52.5, 38.9, 31.9, 29.3, 29.3, 28.5, 27.1, 22.7, 14.2 ppm.</p><p>1,3‐Bis(4‐acetylphenyl)‐5‐octyl‐4H‐thieno[3,4‐c]pyrrole‐4,6(5H)‐dione (4  d):[4b, 4c] Compound 4  d was synthesized from 3 (133 mg, 0.5 mmol) and 1‐(4‐iodophenyl)ethanone (369 mg, 1.5 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8 : 2) afforded compound 4  d (136 mg, 54 % yield) as a yellow solid. Analytical data are in agreement with those previously reported in the literature.[4c] R f (n‐hexane/ethyl acetate=8 : 2)=0.43; 1H NMR (500 MHz, CDCl3): δ=8.27–8.23 (m, 4H), 8.08–8.05 (m, 4H), 3.69 (t, J=7.5 Hz, 2H), 2.65 (s, 6H), 1.72–1.64 (m, 2H), 1.39–1.22 (m, 10H), 0.87 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=197.1, 162.6, 144.0, 137.9, 134.4, 132.2, 129.0, 128.3, 38.9, 31.9, 29.3, 29.3, 28.5, 27.1, 26.8, 22.7, 14.2 ppm.</p><p>5‐Octyl‐1,3‐di‐o–tolyl‐4H‐thieno[3,4‐c]pyrrole‐4,6(5H)‐dione (4  e):[4b, 4c] Compound 4  e was synthesized from 3 (133 mg, 0.50 mmol) and 2‐iodotoluene (327 mg, 1.50 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=9 : 1) afforded 159 mg of compound 4  e (71 % yield) as a pale‐yellow viscous liquid. Analytical data are in agreement with those previously reported in the literature.[4c] R f (n‐hexane/ethyl acetate=9 : 1)=0.61; 1H NMR (500 MHz, CDCl3): δ=7.51 (d, J=7.4 Hz, 2H), 7.39–7.32 (m, 4H), 7.30–7.26 (m, 2H), 3.57 (t, J=7.2 Hz, 2H), 2.48 (s, 6H), 1.66–1.58 (m, 2H), 1.32–1.19 (m, 10H), 0.85 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3) δ : 162.8, 144.5, 137.3, 131.6, 131.0, 130.9, 129.9, 129.5, 126.0, 38.4, 31.9, 29.2, 28.5, 27.0, 22.7, 20.6, 14.2 ppm (one coincident signal not observed); MS (70 eV): m/z (%): 445 (100) [M]+., 430 (27) [M−CH3]+, 346 (98) [M−C 7H15]+, 332 (75) [M−C8H17]+.</p><p>1,3‐Bis(4‐methoxyphenyl)‐5‐octyl‐4H‐thieno[3,4‐c]pyrrole‐4,6(5H)‐dione (4  f):[4b, 4c] Compound 4  f was synthesized from 3 (133 mg,0.5 mmol) and 1‐iodo‐4‐methoxybenzene (351 mg, 1.5 mmol) in accordance with the general procedure. Purification by column chromatography (CH2Cl2/n‐hexane=6 : 4) afforded compound 4  f (167 mg, 70 % yield) as a pale yellow solid. Analytical data are in agreement with those previously reported in the literature.[4c] R f (CH2Cl2/n‐hexane=6 : 4)=0.52; 1H NMR (500 MHz, CDCl3): δ=8.12–8.08 (m, 4H), 7.00–6.96 (m, 4H), 3.87 (s, 6H), 3.65 (t, J=7.5 Hz, 2H), 1.70–1.63 (m, 2H), 1.37–1.21 (m, 10H), 0.86 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=163.3, 161.1, 144.3, 129.8, 129.0, 123.7, 114.3, 55.5, 38.7, 31.9, 29.4, 29.3, 28.6, 27.1, 22.8, 14.2 ppm.</p><!><p>A Carius tube (ø=1.6 cm) with a screw cap and equipped with a magnetic stirrer was charged with 1‐hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazole 5 (0.5 mmol), aryl iodide (0.75 mmol), Pd(OPiv)2 (2 mol%), PPh3 (4 mol%), Ag2CO3 (0.5 mmol). The resulting heterogeneous reaction mixture was heated under an IR lamp (the distance between the bottom of Carius tube and the bulb was set to 7 cm, Figure 2). After 2 h, the mixture was cooled to room temperature and the crude product was purified by column chromatography on silica gel.</p><p>1‐Hexadecyl‐4,5‐diphenyl‐1H‐1,2,3‐triazole (6  a):[4a] Compound 6  a was synthesized from 5 (185 mg, 0.5 mmol) and iodobenzene (153 mg, 0.75 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8.5 : 1.5) afforded compound 6  a (184 mg, 83 % yield) as a white solid. Analytical data are in agreement with those previously reported in the literature.[4a] R f (n‐hexane/ethyl acetate=8.5 : 1.5)=0.59; 1H NMR (500 MHz, CDCl3): δ=7.54 (dd like, J=8.2, 1.7 Hz, 2H), 7.53–7.50 (m, 3H), 7.35–7.31 (m, 2H), 7.28–7.21 (m, 3H), 4.19 (t, J=7.2 Hz, 2H), 1.81–1.74 (m, 2H), 1.31–1.17 (m, 26H), 0.88 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=144.2, 133.8, 131.1, 130.1, 129.8, 129.5,128.5, 128.4,127.7, 126.9, 48.4, 32.1, 30.2, 29.8, 29.8, 29.8, 29.8, 29.8, 29.7, 29.6, 29.5, 29.4, 29.0, 26.5, 22.8, 14.3 ppm; MS (70 eV): m/z (%): 445 (4) [M]+., 417 (2) [M‐N2]+., 193 (100) [M−C 16H32N2]+., 192 (26) [M−C 16H33N2]+.</p><p>1‐Hexadecyl‐4‐phenyl‐5‐(p–tolyl)‐1H‐1,2,3‐triazole (6  b):[4a] Compound 6  b was synthesized from 5 (185 mg, 0.5 mmol) and 1‐iodo‐4‐methylbenzene (164 mg, 0.75 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8.5 : 1.5) afforded compound 6  b (177 mg, 77 % yield) as a white solid. Analytical data are in agreement with those previously reported in the literature.[4a] R f (n‐hexane/ethyl acetate=8.5 : 1.5)=0.42; 1H NMR (500 MHz, CDCl3): δ=7.57–7.54 (m, 2H), 7.31 (d, J=8.0 Hz, 2H), 7.28–7.22 (m, 3H), 7.20 (d, J=8.0 Hz, 2H), 4.18 (t, J=7.5 Hz, 2H), 2.45 (s, 3H), 1.81–1.74 (m, 2H), 1.31–1.17 (m, 26H), 0.88 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=144.0, 139.9, 133.9, 131.1, 130.2, 129.9, 128.5, 127.7, 126.9, 125.1, 48.4, 32.1, 30.2, 29.8, 29.8, 29.8, 29.8, 29.7, 29.6, 29.5, 29.5, 29.0, 26.5, 22.8, 21.6, 14.3 ppm (one coincident signal not observed); MS (70 eV): m/z (%): 459 (4) [M]+., 431 (4) [M‐N2]+., 207 (100) [M−C 16H32N2]+., 206 (16) [M−C16H33N2]+.</p><p>1‐Hexadecyl‐4‐phenyl‐5‐(m–tolyl)‐1H‐1,2,3‐triazole (6  c):[4a] Compound 6  c was synthesized from 5 (185 mg, 0.5 mmol) and 1‐iodo‐3‐methylbenzene (164 mg, 0.75 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8.5 : 1.5) afforded compound 6  c (170 mg, 74 % yield) as a white solid. Analytical data are in agreement with those previously reported in the literature.[4a] R f (n‐hexane/ethyl acetate=8.5 : 1.5)=0.42; 1H NMR (500 MHz, CDCl3): δ=7.57–7.54 (m, 2H), 7.39 (t, J=7.9 Hz, 1H), 7.32 (br d, J=7.9 Hz, 1H), 7.29–7.21 (m, 3H), 7.13–7.10 (m, 2H), 4.18 (t, J=7.3 Hz, 2H), 2.40 (s, 3H), 1.81–1.74 (m, 2H), 1.31–1.17 (m, 26H), 0.88 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=144.0, 139.3, 134.0, 131.1, 130.6, 130.5, 129.3, 128.5, 128.2, 127.7, 127.2, 126.8, 48.4, 32.1, 30.2, 29.8, 29.8, 29.8, 29.8, 29.8, 29.7, 29.6, 29.5, 29.4, 29.0, 26.5, 22.8, 21.5, 14.2 ppm; MS (70 eV): m/z (%): 459 (5) [M]+., 431 (4) [M‐N2]+., 207 (100) [M−C 16H32N2]+., 206 (20) [M−C16H33N2]+.</p><p>5‐(3,5‐Dimethylphenyl)‐1‐hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazole (6  d):[4a] Compound 6  d was synthesized from 5 (185 mg, 0.5 mmol) and 1‐iodo‐3,5‐dimethylbenzene (174 mg, 0.75 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8.5 : 1.5) afforded compound 6  d (175 mg, 74 % yield) as a white solid. Analytical data are in agreement with those previously reported in the literature.[4a] R f (n‐hexane/ethyl acetate=8.5 : 1.5)=0.47; 1H NMR (500 MHz, CDCl3): δ=7.59–7.56 (m, 2H), 7.29–7.21 (m, 3H), 7.13 (br s, 1H), 6.92 (br s, 2H), 4.16 (t, J=7.5 Hz, 2H), 2.36 (s, 6H), 1.82–1.75 (m, 2H), 1.31–1.17 (m, 26H), 0.88 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=143.9, 139.1, 134.1, 131.4, 131.3, 128.5, 128.1, 127.7, 127.6, 126.7, 48.3, 32.1, 30.2, 29.8, 29.8, 29.8, 29.7, 29.6, 29.5, 29.4, 29.0, 26.5, 22.8, 21.4, 14.3 ppm (two coincident signals not observed); MS (70 eV): m/z (%): 473 (5) [M]+., 445 (6) [M‐N2]+., 221 (100) [M−C16H32N2]+., 220 (15) [M−C16H33N2]+.</p><p>5‐(4‐Fluorophenyl)‐1‐hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazole (6  e): Compound 6  e was synthesized from 5 (185 mg, 0.5 mmol) and 1‐fluoro‐4‐iodobenzene (167 mg, 0.75 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8 : 2) afforded compound 6  e (161 mg, 69 % yield) as a white solid, m.p. 65.0–66.0 °C (after crystallization from n‐hexane). R f (n‐hexane/ethyl acetate=8 : 2)=0.69; 1H NMR (500 MHz, CDCl3): δ=7.52 (dd like, J=8.1, 1.6 Hz, 2H), 7.34–7.20 (m, 7H), 4.18 (t, J=7.2 Hz, 2H), 1.81–1.74 (m, 2H), 1.31–1.18 (m, 26H), 0.87 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=163.5 (d, J=250.7 Hz), 144.4, 132.7, 132.1 (d, J=8.4 Hz), 130.9, 128.6, 127.9, 126.9, 124.3 (d, J=3.6 Hz), 116.8 (d, J=21.8 Hz), 48.4, 32.1, 30.2, 29.8, 29.8, 29.8, 29.8, 29.8, 29.7, 29.6, 29.5, 29.4, 29.0, 26.5, 22.8, 14.3 ppm; IR (neat): ṽ=2916 (vs), 2847 (vs), 1515 (m), 1486 (M), 1471 (m), 1227 cm−1 (m); MS (70 eV): m/z (%): 463 (4) [M]+., 435 (2) [M‐N2]+., 211 (100) [M−C16H32N2]+., 210 (16) [M−C16H33N2]+; HRMS (LC–IT‐TOF, elution with 0.1 % (v/v) formic acid in methanol) m/z: [M+H]+ Calcd for C30H43FN3 464.3436; Found 464.3445, mass error=1.94 ppm, C (30 : 11).</p><p>1‐(4‐(1‐Hexadecyl‐4‐phenyl‐1H‐1,2,3‐triazol‐5‐yl)phenyl)ethenone (6  f): Compound 6  f was synthesized from 5 (185 mg, 0.5 mmol) and 1‐(4‐iodophenyl)ethanone (185 mg, 0.75 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=8.5 : 1.5→8:2) afforded compound 6  f (169 mg, 69 % yield) as a white solid, m.p. 57.9–58.3 °C (after crystallization from n‐hexane). R f (n‐hexane/ethyl acetate=8.5 : 1.5)=0.22; 1H NMR (500 MHz, CDCl3): δ=8.09 (d like, J=8.4 Hz, 2H), 7.51–7.48 (m, 2H), 7.44 (d like, J=8.4 Hz, 2H), 7.30–7.24 (m, 3H), 4.22 (t, J=7.3 Hz, 2H), 2.68 (s, 3H), 1.81–1.74 (m, 2H), 1.31–1.17 (m, 26H), 0.87 ppm (t, J=7.0 Hz, 3H); 13C NMR (126 MHz, CDCl3): δ=197.4, 144.7, 137.9, 133.1, 132.7, 130.6, 130.4, 129.3, 128.7, 128.1, 127.1, 48.7, 32.0, 30.2, 29.8, 29.8, 29.8, 29.8, 29.8, 29.7, 29.6, 29.5, 29.4, 29.0, 26.9, 26.5, 22.8, 14.3 ppm; IR (neat): ṽ=2916 (vs), 2851 (vs), 1684 (s), 1605 (m), 1469 (m), 1355 (m), 1264 (m), 1256 cm−1 (m); MS (70 eV): m/z (%): 487 (7) [M]+., 459 (5) [M‐N2]+., 235 (100) [M−C 16H32N2]+., 234 (39) [M−C 16H33N2]+; HRMS (LC–IT‐TOF, elution with 0.1 % (v/v) formic acid in methanol) m/z: [M+H]+ Calcd for C32H46N3O 488.3635; Found 488.3627, mass error=1.64 ppm, C (32 : 12).</p><!><p>A Carius tube (ø=1.6 cm) with a screw cap and equipped with a magnetic stirrer was charged with pentafluorobenzene 7 (0.5 or 1.0 mmol), aryl iodide (0.5 or 1.0 mmol), Pd/AlO(OH) nanoparticles (0.15 mol%), PPh3 (3 mol%), Ag2CO3 (1.0 mmol). The resulting heterogeneous reaction mixture was heated under an IR lamp (the distance between the bottom of Carius tube and the bulb was set to 7 cm, Figure 2). After 15 min, the mixture was cooled to room temperature and the crude product was purified by column chromatography on silica gel.</p><p>2,3,4,5,6‐Pentafluoro‐1,1′‐biphenyl (8  a):[17b, 19] Compound 8  a was synthesized from 7 (168 mg, 1.0 mmol) and iodobenzene (204 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 212 mg of compound 8  a as a white solid (87 % yield). Analytical data agree with those previously reported in the literature.[17b, 19] R f (n‐hexane)=0.59; 1H NMR (500 MHz, CDCl3): δ=7.52–7.45 (m, 3H), 7.44–7.40 ppm (m, 2H); 13C NMR (126 MHz, CDCl3): δ=144.3 (m, incl. app. d, J=247.7 Hz), 140.6 (m, incl. app. d, J=253.7 Hz), 138.0 (m, incl. app. d, J=252.9 Hz), 130.3, 129.4, 128.9, 126.6, 116.1 ppm (td, J=17.3, 3.9 Hz); MS (70 eV): m/z (%): 244 (100) [M]+., 243 (8) [M‐H]+, 225 (18) [M‐F]+.</p><p>2,3,4,4′,5,6‐Hexafluoro‐1,1′‐biphenyl (8  b):[17b, 20] Compound 8  b was synthesized from 7 (168 mg, 1.0 mmol) and 1‐fluoro‐4‐iodobenzene (222 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 199 mg of compound 8  b as a white solid (76 % yield). Analytical data are in agreement with those previously reported in the literature.[17b, 20] R f (n‐hexane)=0.62; 1H NMR (500 MHz, CDCl3): δ=7.43–7.39 (m, 2H), 7.19 ppm (t like, J=8.7 Hz, 2H); 13C NMR (126 MHz, CDCl3): δ=163.4 (d, J=249.9 Hz), 144.3 (m, incl. app. d, J=247.5 Hz), 140.6 (m, incl. app. d, J=254.2 Hz), 138.1, (m, incl. app. d, J=253.2 Hz), 132.2 (d, J=8.5 Hz), 122.4, 116.1 (d, J=22.0 Hz), 115.0 ppm (td, J=17.0, 3.8 Hz); MS (70 eV): m/z (%): 262 (100) [M]+., 243 (19) [M‐F]+, 242 (22) [M‐HF]+..</p><p>2,3,4,5,6‐Pentafluoro‐2′‐methoxy‐1,1′‐biphenyl (8  c):[17f, 21] Compound 8  c was synthesized from 7 (168 mg, 1.0 mmol) and 1‐iodo‐2‐methoxybenzene (234 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 149 mg of compound 8  c as a white solid (54 % yield). Analytical data are in agreement with those previously reported in the literature.[17f, 21] R f (n‐hexane)=0.35; 1H NMR (500 MHz, CDCl3): δ=7.47 (ddd, J=8.3, 7.5, 1.7 Hz, 1H), 7.23 (d br, J=7.5 Hz, 1H), 7.06 (td, J=7.5, 1.0 Hz, 1H), 7.03 (d, J=8.3 Hz, 1H), 3.81 ppm (s, 3H); 13C NMR (126 MHz, CDCl3): δ=157.3, 144.6 (m, incl. app. d, J=247.1 Hz), 140.7 (m, incl. app. d, J=252.7 Hz), 137.7 (d, J=252.0 Hz), 131.9, 131.3, 120.8, 115.4, 113.0 (td, J=19.2, 3.9 Hz), 111.4, 55.8 ppm; MS (70 eV): m/z (%): 274 (100) [M]+., 259 (25) [M−CH3]+.</p><p>2,3,4,5,6‐Pentafluoro‐3′‐methyl‐1,1′‐biphenyl (8  d):[20, 22] Compound 8  d was synthesized from 7 (168 mg, 1.0 mmol) and 3‐iodotoluene (218 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 200 mg of compound 8  d as a white solid (78 % yield). Analytical data are in agreement with those previously reported in the literature.[20, 22] R f (n‐hexane)=0.61; 1H NMR (500 MHz, CDCl3): δ=7.38 (t, J=7.6 Hz, 1H), 7.28 (d, J=7.6 Hz, 1H), 7.24–7.19 (m, 2H), 2.42 ppm (s, 3H); 13C NMR (126 MHz, CDCl3): δ=144.3 (m, incl. app. d, J=247.4 Hz), 140.5 (m, incl. app. d, J=253.5 Hz), 138.7, 138.0 (m, incl. app. d, J=250.6 Hz), 130.9, 130.2, 128.7, 127.3, 126.4, 116.3 (td, J=17.2, 3.9 Hz), 21.5 ppm; MS (70 eV): m/z (%): 258 (100) [M]+., 257 (25) [M‐H]+, 239 (15) [M‐F]+.</p><p>2,3,4,5,6‐Pentafluoro‐4′‐(trifluoromethyl)‐1,1′‐biphenyl (8  e):[23] Compound 8  e was synthesized from 7 (168 mg, 1.0 mmol) and 1‐iodo‐4‐(trifluoromethyl)benzene (272 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 241 mg of compound 8  e as a white solid (77 % yield). R f (n‐hexane)=0.52; 1H NMR (500 MHz, CDCl3): δ=7.76 (d, J=8.1 Hz, 2H), 7.56 ppm (d, J=8.1 Hz, 2H); 13C NMR (126 MHz, CDCl3): δ=144.3 (m, incl. app. d, J=249.1 Hz), 141.2 (m, incl. app. d, J=255.4 Hz), 138.1 (m, incl. app. d, J=253.4 Hz), 131.7 (q, J=32.8 Hz), 130.8, 130.3, 125.9 (q, J=3.7 Hz), 123.9 (q, J=272.3 Hz), 114.7 ppm (td, J=17.0, 4.0 Hz); MS (70 eV): m/z (%): 312 (100) [M]+., 293 (27) [M‐F]+, 243 (19) [M−CF3]+.</p><p>2,3,4,5,6‐pentafluoro‐3′,5′‐dimethyl‐1,1′‐biphenyl (8  f):[20, 22] Compound 8  f was synthesized from 7 (84 mg, 0.5 mmol) and 1‐iodo‐3,5‐dimethylbenzene (116 mg, 0.5 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane) afforded 117 mg of compound 8  f as a white solid (86 % yield). Analytical data agree with those previously reported in the literature.[20, 22] R f (n‐hexane)=0.66; 1H NMR (500 MHz, CDCl3): δ=7.10 (s br, 1H), 7.02 (s br, 2H), 2.38 ppm (s, 6H); 13C NMR (126 MHz, CDCl3): δ=144.3 (m, incl. app. d, J=247.0 Hz), 140.4 (m, incl. app. d, J=253.3 Hz), 138.5, 137.9 (m, incl. app. d, J=252.7 Hz), 131.1, 128.0, 126.3, 116.4 (td, J=18.1, 4.2 Hz), 21.4 ppm; MS (70 eV): m/z (%): 272 (100) [M]+., 271 (10) [M‐H]+, 257 (75) [M−CH3]+.</p><p>Methyl 2′,3′,4′,5′,6′‐pentafluoro‐[1,1′‐biphenyl]‐4‐carboxylate (8  g):[24] Compound 8  g was synthesized from 7 (168 mg, 1.0 mmol) and methyl 4‐iodobenzoate (262 mg, 1.0 mmol) in accordance with the general procedure. Purification by column chromatography (n‐hexane/ethyl acetate=9.5:0.5) afforded 253 mg of compound 8  g as a white solid (84 % yield). Analytical data are in agreement with those previously reported in the literature.[24] R f (n‐hexane/ethyl acetate=9.5:0.5)=0.24; 1H NMR (500 MHz, CDCl3): δ=8.16 (d, J=8.5 Hz, 2H), 7.51 (d, J=8.5 Hz, 2H), 3.96 ppm (s, 3H); 13C NMR (126 MHz, CDCl3): δ=166.5, 144.2 (m, incl. app. d, J=248.8 Hz), 141.0 (m, incl. app. d, J=255.0 Hz), 138.1 (m, incl. app. d, J=253.4 Hz), 131.1, 130.4, 130.0, 115.1 (td, J=17.0, 3.9 Hz), 52.4 ppm; MS (70 eV): m/z (%): 302 (43) [M]+., 271 (100) [M‐OCH3]+, 243 (23) [M−CO2CH3]+.</p><p>1‐(2′,3′,4′,5′,6′‐pentafluoro‐[1,1′‐biphenyl]‐4‐yl)ethanone (8  h):[18, 24] A Carius tube (ø=1.6 cm) with a screw cap and equipped with a magnetic stirrer was charged with 7 (168 mg, 1.0 mmol), 1‐(4‐iodophenyl)ethanone (246 mg, 1.0 mmol), Pd/AlO(OH) nanoparticles (32 mg), PPh3 (8 mg), Ag2CO3 (276 mg, 1.0 mmol). The resulting heterogeneous reaction mixture was heated under an IR lamp (the distance between the bottom of Carius tube and the bulb was set to 7 cm, Figure 1). After 15 min, the mixture was cooled to room temperature, then quenched with a saturated aqueous solution of NH4Cl (20 mL) and extracted with dichloromethane (3×30 mL). The combined organic extracts were washed with an aqueous solution of NaCl (3×20 mL), dried with Na2SO4, and concentrated under vacuum. The crude product was purified by column chromatography (n‐hexane/ethyl acetate=90 : 5) afforded 195 mg of compound 8  g as a yellow solid (68 % yield). Analytical data are in agreement with those previously reported in the literature.[18, 24] R f (n‐hexane/ethyl acetate=90 : 5)=0.21; 1H NMR (500 MHz, CDCl3): δ=8.08 (d, J=8.5 Hz, 2H), 7.54 (d, J=8.5 Hz, 2H), 2.66 ppm (s, 3H); 13C NMR (126 MHz, CDCl3): δ=197.2, 144.1 (m, incl. app. d, J=248.9 Hz), 140.8 (m, incl. app. d, J=255.2 Hz), 137.9 (m, incl. app. d, J=253.6 Hz), 137.5, 131.0, 130.5, 128.5, 114.8 (td, J=17.0, 4.1 Hz), 26.6 ppm; MS (70 eV): m/z (%): 286 (9) [M]+., 271 (100) [M−CH3]+, 243 (35) [M−C(O)CH3]+.</p><!><p>The authors declare no conflict of interest.</p><!><p>As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.</p><p>Supporting Information</p><p>Click here for additional data file.</p>

PubMed Open Access

Angiogenin regulates PKD activation and COX-2 expression induced by TNF-\xce\xb1 and bradykinin in the colonic myofibroblast

Introduction: The myofibroblast is a gastrointestinal stromal cell that is a target of tumor necrosis factor-alpha (TNF-\xce\xb1), a pro-inflammatory cytokine strongly implicated in colitis-associated cancer. Crosstalk between TNF-\xce\xb1 and other pro-inflammatory mediators amplify inflammatory signaling but the mechanism is unknown. Angiogenin (ANG) is a 14-kDa angiogenesis protein that is regulated in patients with inflammatory bowel disease. However, the role of ANG on inflammatory mediator crosstalk in the myofibroblast is unknown. Methods: The human colonic myofibroblast cell line 18Co, as well as primary mouse and human colonic myofibroblasts, were exposed to TNF-\xce\xb1 (10 ng/ml) and bradykinin (BK, 100 nM). ANG was quantified by ELISA. The expression of cyclo-oxygenase-2 (COX-2) and phosphorylation of PKD was assessed by Western Blot. Results: Primary mouse and human colonic myofibroblasts exposed to TNF-\xce\xb1/BK led to enhanced PKD phosphorylation and synergistic COX-2 expression. 18Co cells secrete high levels of ANG (24h, 265 \xc2\xb1 5 pg/ml). The monoclonal antibody 26-2F, which neutralizes ANG, inhibited TNF-\xce\xb1/BK-mediated PKD phosphorylation and synergistic COX-2 expression in primary human myofibroblasts. Likewise, in primary mouse myofibroblasts that do not express ANG (ANG-KO), TNF-\xce\xb1/BK failed to enhance PKD phosphorylation and COX-2 expression. Conclusions: TNF-\xce\xb1/BK enhance PKD phosphorylation and COX-2 expression in primary mouse and human colonic myofibroblasts. Angiogenin is produced by the myofibroblast, and inhibition of ANG signaling, either by its absence (ANG-KO) or by pharmacologic inhibition, blocks enhanced PKD phosphorylation and synergistic COX-2 expression induced by TNF-\xce\xb1/BK. ANG mediates crosstalk signaling between TNF-\xce\xb1/BK in the regulation of stroma-derived COX-2 and may be a novel therapeutic target for the management of colitis-associated cancer.

angiogenin_regulates_pkd_activation_and_cox-2_expression_induced_by_tnf-\xce\xb1_and_bradykinin_in_t

Introduction<!>Materials and methods<!>Cell culture<!>Isolation of primary mouse myofibroblasts<!>Isolation of primary human myofibroblasts<!>SDS-PAGE and immunoblotting<!>ELISA<!>Materials and reagents<!>TNF-\xce\xb1 enhances bradykinin-mediated PKD phosphorylation and leads to synergistic COX-2 expression in primary mouse and human colonic myofibroblasts.<!>The Myofibroblast is a Source of Angiogenin.<!>Angiogenin Regulates PKD activation and COX-2 Expression induced by TNF-\xce\xb1 and Bradykinin in the Colonic Myofibroblast.<!>Discussion

<p>Chronic inflammatory bowel disease (IBD) predisposes to colorectal cancer, occurring in up to 18% of patients [1]. Colitis-associated cancer is characterized by rapid progression and high mortality compared to sporadic forms [2,3], and the risk increases with the extent, duration, and severity of colitis. While the association between chronic inflammation and cancer is well established [3,4], the precise mechanism(s) leading to neoplasia, and the contribution of specific cell populations on this process, remain unclear.</p><p>The myofibroblast is a gastrointestinal stroma cell that regulates epithelial proliferation [5,6], mucosal repair [5], and fibrosis [7,8] through paracrine signaling, and has been implicated in colitis-associated cancer [9–12]. The myofibroblast is the predominant nonmalignant stromal cell of the tumor microenvironment [13,14] and a major reservoir of stroma-derived cyclo-oxygenase-2 (COX-2) [15,16]. COX-2, encoded by the PTGS2 gene, is an early response enzyme that is inducibly expressed by inflammatory mediators [17,18], leading to the production of prostaglandins that not only participate in the GI response to colitis [5] but also predispose to cancer [12,15,17,19].</p><p>The myofibroblast is a target of inflammatory mediators like TNF-α [9,18,20], a potent pro-inflammatory cytokine that plays a key role in both IBD as well as colitis-associated cancer [9–11,21]. In the myofibroblast cell line 18Co, we have previously shown that TNF-α enhances the physiologic responses of the myofibroblast to G protein-coupled receptor (GPCR) agonist signaling, leading to a synergistic upregulation of PTGS2 (COX-2) mRNA, COX-2 protein, PTGES (mPGES-1) mRNA, and PGE2 [18,20]. This involved the enhanced activation of protein kinase D (PKD), a ubiquitous serine-threonine kinase known to participate in biological responses to inflammation. While TNF-α did not independently activate PKD [18], TNF-α augmented GPCR agonist-mediated PKD signaling [18,20]. Furthermore, inhibition of PKD with pharmacologic PKD inhibitors, as well as with PRKD1 (PKD) siRNA, completely blocked the synergistic expression of PTGS2 (COX-2) mRNA and COX-2 protein expression [18,20], illustrating the important role that PKD plays in this process.</p><p>The goal of our present study was to further elucidate the signaling interactions between TNF-α and GPCR's within the myofibroblast, and to confirm that our findings were not specific to a myofibroblast cell line. Here we report for the first time that angiogenin, an angiogenesis protein with growth and survival properties, is a required element of this pro-inflammatory mediator crosstalk and may be an important link connecting the processes of inflammation and carcinogenesis.</p><!><p>Animal experiments were approved by the Institutional Animal Care and Use Committee of Tufts Medical Center. The animal facility is accredited by the AALAC.</p><!><p>18Co cells (CRL-1459) were purchased from American Type Culture Collection (Rockville, MD). 18Co cells mimic colonic myofibroblasts structurally and functionally [22]. 18Co cells, along with primary mouse and human myofibroblasts, were maintained at 37 °C in DMEM supplemented with 10%FBS in a humidified atmosphere containing 10%CO2–90% air. Cells were plated in 35-mm dishes and grown in DMEM containing 10%FBS for 5–7days until confluent and used from passages 8–14.</p><!><p>Primary mouse myofibroblasts were isolated from C57BL/6 mice (Jackson Laboratory, Bar Harbor, ME) as previously described [23]. Briefly, the colon of male/female 8–10-week-old C57BL/6 mice was washed with ice cold sterile PBS and incubated in HBSS containing 5 mM EDTA in a shaking air bath, de-epithelializing the tissue. The tissue was incubated in RPMI-5 [RPMI with 5%FCS, 10 mM HEPES, 2 mM L-glutamine, 1 mM sodium pyruvate, 100U/ml Pen-Strep] containing 10U dispase (GIBCO-Invitrogen, Carlsbad, CA) and 2000U of collagenase D (Roche Diagnostics, Indianapolis, IN) in a shaking 37 °C air bath for 60min. The tissue was pelleted and resuspended with ACK lysis buffer (150 mM NH4Cl, 10 mM KHCO3, 0.1 mM Na2EDTA, pH = 7.2–7.4), filter sterilized (0.2-mm filter), then re-pelleted and re-suspended in RPMI-5, and passed through a 70 μM mesh strainer. After a 3h incubation, non-adherent cells were washed away leaving adherent cells consisting of epithelial cells, macrophages and myofibroblasts. After several days, only cells with a myofibroblast-like phenotype remain viable. We have previously confirmed that the isolated cells stain positive for α-SMA and vimentin and are negative for desmin [23]. Primary myofibroblasts were grown in cell culture and used 1–2 weeks after initial isolation.</p><!><p>A protocol to obtain human tissue from surgical patients was approved by our institutional review board. Human colon tissue immediately taken from surgically resected colon was washed with ice cold sterile PBS and shaken five times for 15min in HBSS containing 5 mM EDTA, which de-epithelialized the tissue. The tissue was incubated in 20 ml of RPMI-5 [RPMI with 5%FCS, 10 mM HEPES, 2 mM L-glutamine, 1 mM sodium pyruvate, 100U/ml Pen-Strep] containing 10.5 mg of Dispase (GIBCO-Invitrogen, Carlsbad, CA) and 7.2 mg of collagenase D (Roche Diagnostics, Indianapolis, IN) for 2h in a shaking 37 °C incubator. The digested tissue was treated with ACK lysis buffer for 5min, then passed through a 70-μM cell strainer into 100-mm dishes in RPMI-5. After a 3h incubation, the nonadherent cells were washed away, leaving adherent cells consisting mainly of macrophages and myofibroblasts. After several days the macrophages died, leaving cells with a myofibroblast phenotype (α-SMA and vimentin positive). Primary colonic myofibroblast cultures were used for experiments up to passage 4.</p><!><p>Cell lysis was performed using Triton buffer (50 mM Tris, pH 7.5, 1 mM EDTA, 1 mM EGTA, 1 mM Na3VO4, 5 mM sodium pyrophosphate, 10 mM sodium glycerophosphate, 1% Triton X-100, 50 mM NaF plus 1% Calbiochem Protease Inhibitor Cocktail) and lysates were assayed for protein using the Bradford protein assay, then diluted with 5x Laemmli loading buffer for SDS-PAGE. Equal amounts of protein were loaded in 4–20% Tris/glycine gels and electrophoresed for 120 min at 130 V. The gel was blotted onto a PVDF membrane by electrophoretic transfer at 25 V overnight. The membrane was washed, blocked with 5% milk, and probed with primary antibodies. Secondary antibodies conjugated to horse-radish peroxidase (Pierce, Rockford, IL) and a chemiluminescent substrate (SuperSignal, Pierce, Rockford, IL) were used to visualize immunoreactive bands.</p><!><p>Angiogenin was quantified from the supernatant of serum-starved, confluent 18Co cells. The collected supernatant was centrifuged at 5,000g for 5min to remove cell debris. Absorbance readings were set between 405 and 420 nm on a spectrophotometer.</p><!><p>HBSS, EDTA, Dispase and RPMI-1640 were purchased from Thermo Fisher Scientific (Waltham MA). DMEM, FBS, penicillin G potassium, streptomycin, fungizone, and glutamine were purchased from Invitrogen (Carlsbad, CA). TNF-α was purchased from R&D Systems (Minneapolis, MN). Bradykinin and α-SMA antibody were purchased from Sigma-Aldrich (St. Louis, MO). COX-2 antibody was purchased from Cell Signaling Technology (Beverly, MA). C527 was provided by the Hu laboratory. The phospho-PKD polyclonal antibodies pSer916 was purchased from (Millipore, Bill-erica, MA). Antibody to GAPDH was purchased from Santa Cruz (Dallas, TX).</p><!><p>While the pro-inflammatory cytokine TNF-α does not independently activate PKD [18], we have previously demonstrated in the myofibroblast cell line 18Co that TNF-α augments GPCR-mediated PKD signaling [18,20], leading to a synergistic upregulation of COX-2 protein expression. To demonstrate that this finding was not cell line-specific, experiments were verified using primary myofibroblasts isolated from both mouse (Fig. 1) and human (Fig. 2) colon tissue using a well-established technique [24]. In Fig. 1, primary mouse myofibroblasts were exposed to bradykinin (100 nM) and TNF-α (10 ng/ml), either alone or in combination, for 4h. Phosphorylation of PKD at Ser916 and COX-2 protein expression were analyzed by Western blot. Consistent with previously reported data [18,20], TNF-α did not independently lead to phosphorylation of PKD but did result in a modest increase in COX-2 protein expression. Exposure to bradykinin alone led to phosphorylation of PKD that was evident at 1h, with a steady decline over 4h, followed by a modest increase in COX-2 expression at 2h and 4h. Confirming our prior data, simultaneous exposure of primary mouse myofibroblasts to both TNF-α and bradykinin led to enhanced PKD phosphorylation that was statistically significant at 1h and 2h (Fig. 1B), with a corresponding increase in COX-2 protein expression at 1h, 2h, and 4h (Fig. 1C).</p><p>Experiments were also performed using primary myofibroblasts that were isolated from surgically resected human colon tissue. TNF-α (10 ng/ml) alone did not activate PKD in primary human myofibroblasts (data not shown), while bradykinin (100 nM) led to phosphorylation of PKD that was evident at 0.5h, with a steady decline over 4h (Fig. 2A). Consistent with the responses seen in the myofibroblast cell line 18Co and in primary mouse myofibroblasts, TNF-α augmented bradykinin-mediated PKD phosphorylation, with statistically significant differences seen at 1h, 2h, and 4h compared to primary myofibroblasts exposed to bradykinin alone (Fig. 2A). The effect of TNF-α and bradykinin, alone and in combination, on COX-2 expression in primary human myofibroblasts was analyzed for up to 24h (Fig. 2B). Exposure to TNF-α alone led to a modest increase in COX-2 protein over 24h. Exposure of primary human myofibroblasts to bradykinin led to a more pronounced increase in COX-2 protein expression, with the highest levels occurring at 2 and 4h followed by a decrease in protein expression at 8h and 24h. However, exposure to both TNF-α and bradykinin led to a synergistic increase in COX-2 protein expression (Fig. 2C) that was evident at 2h and most pronounced at 4h and 8h. The synergistic increase in COX-2 expression was sustained at 24h, with a 2-old increase in protein expression at each time point compared to the additive response (Fig. 2C). At 24h, the corresponding synergistic increase in PGE2 production was even more pronounced (Fig. 2D), quantified by ELISA.</p><!><p>Angiogenin is a 14-kDa protein that is a member of the pancreatic ribonuclease superfamily initially isolated from the media of the human colon cancer cell line HT-29 as the first tumor-derived angiogenesis protein [25]. Human patients with active IBD have elevated serum levels of angiogenin [26,27], suggesting that angiogenin may play a role in the pathophysiology or counter-regulatory response to colitis. In an effort to identify cell populations that generate angiogenin, we found that the myofibroblast cell line 18Co is a robust source (Fig. 3A). Confluent 18Co cells were placed in serum-free media and angiogenin concentration was analyzed by ELISA. 18Co cells secrete high levels of angiogenin (265 ± 5 pg/ml) in serum-free media after 24h, a finding consistent with recently reported data that angiogenin is secreted by human colon cancer-associated myofibroblasts [28].</p><!><p>Having demonstrated that the myofibroblast produces angiogenin, this raises the possibility that myofibroblast function may be regulated through angiogenin signaling. To explore whether angiogenin is involved in TNF-α/GPCR-induced, PKD-mediated COX-2 expression, we utilized 26-2F, a murine monoclonal antibody which is an IgG1kappa with an IC binding affinity of 1.6 nM that neutralizes human ANG [29]. While pre-treatment of 18Co cells with 26-2F did not regulate PKD activation or COX-2 expression induced by either TNF-α or bradykinin alone (Figs. 3B), 26-2F inhibited the enhanced PKD phosphorylation (Fig. 3C) as well as the synergistic upregulation of COX-2 (Fig. 3D) induced by their combination. These findings were verified using myofibroblasts isolated from angiogenin knockout (ANG-KO) C57BL/6 mice, a whole-body homozygous knockout strain. ANG-KO C57BL/6 mice are phenotypically normal and do not express angiogenin anywhere, including the gastrointestinal tract. Myofibroblasts isolated from the colon of ANG-KO C57BL/6 mice were grown in cell culture. PKD activation and COX-2 expression was analyzed following exposure to TNF-α (10 ng/ml) and bradykinin (100 nM). Consistent with the findings in 18Co cells following 26-2F treatment, ANG-KO myofibroblasts failed to demonstrate enhanced PKD activation or synergistic COX-2 expression at both 1h and 4h (Fig. 4).</p><!><p>Dynamic GI epithelial-stromal cell interactions regulate the development of inflammation-associated cancer. Understanding the stromal contribution to carcinogenesis may provide new therapeutic avenues that do not currently exist, since traditional treatments focus on the primary tumor. The myofibroblast has been gaining considerable attention as a potential therapeutic target because of its role as a major source of COX-2 in the gastrointestinal tract. In the present study, we show that angiogenin, a multifunctional ribonuclease that is dynamically regulated in colitis and colorectal cancer, is a required element of the activity of pro-inflammatory mediators to enhance GPCR-induced COX-2 expression signaling within the myofibroblast.</p><p>Considerable evidence supports a role of COX-2 in the pathophysiology of colorectal cancer [19]. COX-2 is induced in the stroma of patients with IBD [15,16,30], and has been implicated in all stages of colorectal cancer development, from adenoma formation [31] to tumor progression [32,33]. Selective and non-selective COX-2 inhibitors have demonstrated clinical benefit as a therapeutic agent in the prevention and treatment of colorectal cancer in both general [34,35] and high-risk populations [36]. In this context, COX-2 is an attractive molecular target of anti-cancer therapy. However, GI and cardiovascular side effects have limited their use [37,38], and COX-2 inhibitors are generally contraindicated in patients with IBD for this reason [4,39,40]. As an alternative to systemic COX-2 inhibition, regional inhibition of COX-2 and its by-products by targeting the stroma may be more effective and less toxic. Local prostaglandin release by GI stromal cells have important regulatory functions that rely as much on close cellular proximity as concentration [5,41]. Moreover, several studies provide experimental evidence that stroma-directed therapies are feasible [42,43]. Within this context, important questions remain regarding the relative contribution of myofibroblast-derived COX-2 on the development of colitis-associated cancer, and whether its selective inhibition can be developed as an anti-cancer strategy that avoids systemic toxicity.</p><p>In conclusion, angiogenin regulates crosstalk signaling between TNF-α and GPCR's to enhance COX-2 expression via PKD in the myofibroblast. This is supported by experiments utilizing neutralizing monoclonal antibodies of angiogenin, as well as ANG-KO myofibroblasts. Taken together, these findings suggest that myofibroblast-derived angiogenin may play an important role as a paracrine mediator of cell-cell crosstalk in the setting of colitis-associated cancer. These findings may serve as a foundation for new therapeutic approaches that target angiogenin signaling within stroma.</p>

PubMed Author Manuscript

Efficient photoredox conversion of alcohol to aldehyde and H₂ by heterointerface engineering of bimetal–semiconductor hybrids

Controllable and precise design of bimetal-or multimetal-semiconductor nanostructures with efficient light absorption, charge separation and utilization is strongly desired for photoredox catalysis applications in solar energy conversion. Taking advantage of Au nanorods, Pt nanoparticles, and CdS as the plasmonic metal, nonplasmonic co-catalyst and semiconductor respectively, we report a steerable approach to engineer the heterointerface of bimetal-semiconductor hybrids. We show that the ingredient composition and spatial distribution between the bimetal and semiconductor significantly influence the redox catalytic activity. CdS deposited anisotropic Pt-tipped Au nanorods, which feature improved light absorption, structure-enhanced electric field distribution and spatially regulated multichannel charge transfer, show distinctly higher photoactivity than blank CdS and other metal-CdS hybrids for simultaneous H 2 and value-added aldehyde production from one redox cycle.

efficient_photoredox_conversion_of_alcohol_to_aldehyde_and_h₂_by_heterointerface_engineer

Introduction<!>Results and discussion<!>Conclusions<!>Synthesis of Au NRs<!>Preparation of Au-Pt<!>Preparation of Au-Pt@CdS<!>Material characterization<!>FDTD simulations<!>Photoactivity<!>Conflicts of interest

<p>Harvesting solar energy to drive articial photosynthesis for the production of value-added chemicals and renewable energy is a promising strategy to solve the growing worldwide energy crisis. [1][2][3][4][5] However, the solar-to-chemical conversion efficiency of semiconductors is oen limited by their nite light absorption and/or slow charge separation rates and reaction kinetics. [6][7][8][9][10] Integrating different functional materials into a single hybrid structure with precise design holds great promise for constructing efficient composite photocatalysts owing to the synergistic properties induced by the interactions between these components in an integrative ensemble. 5,[11][12][13][14][15][16] Bimetallic nanostructures, coupling a surface plasmon resonance (SPR, Scheme S1 †) functionality with an efficient cocatalytic effect, could be an ideal candidate to simultaneously modulate the photoabsorption and steer the multichannel charge separation/transfer and reaction kinetics of semiconductors. [17][18][19][20][21] The design of effective bimetal-semiconductor composite photocatalysts requires the rational understanding of the structural design principle, because the randomly hybridizing counterparts would oen shield the SPR intensity and local electric eld of the plasmonic metal or weaken the net photoabsorption of the semiconductor. [22][23][24][25] In addition, recent research has predominantly focused on charge separation and transfer mainly occurring at the plasmonic metal domains (i.e., SPR-induced sensitization effect), [25][26][27] and the quantum efficiency over such systems is still relatively low in contrast to those by semiconductor photoexcitation. To obtain high photocatalytic activity, the structural design of special composite catalysts to synergistically utilize the SPR enhancement mechanism and band-gap photoexcitation of semiconductors is desirable. 28,29 However, thus far, it is still unclear how the composition and structural arrangement of plasmonic-nonplasmonic bimetal hybrids comprehensively affect their interactions with the semiconductor and the subsequent band alignment, charge transfer dynamics, local electric eld distribution and redox catalysis performance.</p><p>Herein, we report a controllable way to design bimetalsemiconductor hybrids with different heterointerfaces for progressively improved redox catalysis conversion of alcohol to H 2 and aldehyde under visible-near-infrared (Vis-NIR) light irradiation. Au nanorods (NRs) and Pt nanoparticles (NPs) are promising metallic nanocrystal platforms for fabricating metalsemiconductor hybrids due to their tunable longitudinal-SPR absorption in the near-infrared (NIR) region and high efficiency for catalytic proton reduction reaction, respectively. 13,[30][31][32][33][34] In this regard, we chose Au NRs and Pt NPs to form the plasmonic bimetal component. CdS, a well-known visible (Vis) light responsive photocatalyst with a direct band-gap of around 2.4 eV, 8,[35][36][37][38] is chosen as the semiconductor component. Integrating the co-catalytic factor with semiconductor photoexcitation and SPR resonance modes in different optical response regions by the rational assembly of nonplasmonic Pt NPs and semiconductor CdS on the surface of Au NRs can provide the spatial transfer multichannel for electrons and boost the local electric eld, promoting the generation and migration of electron-hole charge carriers. As a result, the CdS deposited anisotropic Pt-tipped Au NRs (Au-Pt@CdS), which features the multiple metal-semiconductor and metal-metal heterojunctions, exhibits distinctly higher photoactivity than blank CdS and other metal-CdS hybrid counterparts for photocatalytic conversion of alcohol to aldehyde and H 2 by simultaneous utilization of photogenerated holes and electrons in one redox cycle. Resorting to electric eld simulations, transient absorption spectroscopy and multiple control experiments, it is demonstrated that the redox photoactivity is highly dependent on the ingredient composition and spatial distribution of the metal components because they play a signicant role in affecting multiple electron transfer pathways and local electric eld enhancement.</p><!><p>The fabrication process is based on progressively seed-mediated growth, as illustrated in Scheme 1. The stronger interaction between the cetyltrimethylammonium bromide (CTAB) surfacecapping molecules and the side facets of Au NRs results in the higher packed density of CTAB at the sides than that at the ends of Au NRs. 24,25 By taking advantage of this anisotropic surface structure, Pt NPs were rstly selectively deposited on the tips of Au NR seeds for the preparation of anisotropic Pt-tipped Au NRs (Au-Pt). The spatial distribution of Pt on the Au NR surface depends on the surface-capping molecules. Pt-covered Au NRs (Au@Pt) can be synthesized by decreasing the concentration of CTAB molecules. The Au-based NRs were subsequently used as seeds for the assembly of semiconductor CdS via a facile and controllable reuxing process. It should be noticed that our synthesis reaction is performed at a low temperature (85 C) and in the absence of metal ion sources (e.g., Ag + or Cu 2+ ) as a "bridge" between Au NRs and CdS to achieve the heterogrowth, 39,40 which can prevent the Au NRs from undesired reshaping in the wet-chemistry growth process.</p><p>The samples obtained in each growth stage were characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analysis. The average diameter and length of the original Au NRs are 29.0 and 92.5 nm, respectively (Fig. 1a and S1 †). Aer the growth of Pt on the tips of Au NRs, the smooth ends of Au NRs become gibbous, while the surface at the side of Au NRs remains almost unchanged (Fig. 1b and S2 †). The average diameter at the middle of Au-Pt NRs is 29.1 nm, and the average length is increased to 114.0 nm. These results suggest that Pt tends to anisotropically deposit at the two ends of Au NRs. Fig. 1c and S3 † show the morphology of Au@Pt with an average diameter of 33.2 nm and length of 107.9 nm, which are enclosed by the Pt shell.</p><p>The morphology information of CdS deposited Au NRs (Au@CdS), CdS deposited Pt-tipped Au NRs (Au-Pt@CdS) and CdS deposited Pt-covered Au NRs (Au@Pt@CdS) is disclosed in Fig. 1d-f and S4. † No noticeable structural deformation of Aubased seeds can be discerned aer depositing CdS nanoshells, which should benet from the mild reaction process at a low temperature. For Au@CdS, we can clearly see from Fig. 1d and S4a-c † that the Au NR core with hemispherical ends are coated with a loose and porous CdS semiconductor layer in thicknesses of 15-20 nm. TEM images of Au-Pt@CdS (Fig. 1e) and Au@Pt@CdS (Fig. 1f) indicate their similar overall shape to Au@CdS. However, the bimetal cores in Au-Pt@CdS and Au@Pt@CdS respectively show convex (Fig. S4d-f †) and bar-like (Fig. S4g-i †) shapes. Elemental mapping analysis of Au-Pt@CdS (Fig. 1g) discloses that the Pt is located at the ends of Au NRs, further conrming the tip-coated morphology of the Au-Pt core in Au-Pt@CdS. Elemental mapping study of Au@Pt@CdS indicates that the layers of Pt and CdS shells are both isotropically deposited on the entire surface of Au NRs Scheme 1 Schematic flowchart illustrating the controllable preparation of CdS deposited Pt-tipped Au NRs (Au-Pt@CdS), CdS deposited Au NRs (Au@CdS) and CdS deposited Pt-covered Au NRs (Au@Pt@CdS).</p><p>Fig. 1 SEM images of (a) Au NRs, (b) Au-Pt, and (c) Au@Pt, scale bar, 200 nm. The insets of (a-c) show TEM images of the corresponding samples, scale bar, 20 nm. TEM images of (d) Au@CdS, (e) Au-Pt@CdS and (f) Au@Pt@CdS, scale bar, 200 nm. Elemental mapping results of (g) Au-Pt@CdS and (h) Au@Pt@CdS.</p><p>(Fig. 1h). The morphology of blank CdS was also analyzed (Fig. S5 †), suggesting that blank CdS is composed of tiny NPs.</p><p>X-ray diffraction (XRD) patterns of blank CdS and metal-CdS hybrids are shown in Fig. 2a, in which the diffraction peaks of hexagonal phase CdS (JCPDS, no. 41-1049) and cubic phase Au (JCPDS, no. 65-8601) can be well identied. The characteristic diffraction peaks of Pt are hardly observed due to their relatively low content in the composites. 41 Raman spectra, as displayed in Fig. 2b, show that blank CdS exhibits Raman signals at 299 cm À1 , 597 cm À1 and 890 cm À1 , which are identied as characteristic peaks of the longitudinal optical (LO) phonons of the CdS phase. 42 In comparison with CdS, all of these peaks are signicantly intensied for metal-CdS hybrids, suggesting an enhanced light-matter interaction due to the strong electric eld enhancement near the surface of plasmonic Au-based NRs. 42 The evolution of optical absorption spectra along with the structural variation of the samples is displayed in Fig. 2c. The raw Au NRs have two SPR absorption bands centered at 510 and 800 nm, which are respectively assigned to transverse-SPR (T-SPR) and longitudinal-SPR (L-SPR) photoabsorption (inset of Fig. 2c). Aer Pt is deposited on Au NRs, the L-SPR band red-shis to 833 and 865 nm for Au@Pt and Au-Pt, respectively. In addition, the T-SPR band of Au@Pt slightly red-shis to 527 nm, while almost no change occurs for that of Au-Pt, which is probably due to the selective deposition of Pt onto the tips of Au NRs for the Au-Pt sample. 24 Both T-SPR and L-SPR bands are further red-shied aer the semiconductor CdS is grown on Au@Pt and Au-Pt, resulting from the increase of the surrounding dielectric constant. 31,43 The blank CdS and metal-CdS hybrids disclose a similar optical absorption threshold located at 520 nm, which corresponds to the optical band-gap of about 2.4 eV in the pristine CdS semiconductor. However, the absorption of metal-CdS hybrids is higher than that of blank CdS throughout the whole Vis to NIR region due to the contribution from the SPR absorption of Au-based NRs. 36,43 We tested the samples as dual-function photocatalysts for the conversion of benzyl alcohol (BA) to H 2 and benzaldehyde (BAD) under Vis-NIR light (l > 420 nm, Fig. S6 †) irradiation. We initially studied the effects of the proportion of different components on the photoactivity and determined the sample with optimal photoactivity, as shown in Fig. S7a-c. † The direct photoactivity comparison with the H 2 and BAD production rates over the samples with the optimal proportion of components is shown in Fig. 2d. Notably, the molar ratio of the reduction product (H 2 ) and oxidation product (BAD) is calculated to be ca. 1.0, suggesting a stoichiometric dehydrogenation reaction. The ne control of the heterointerface of metal-semiconductor composites can result in progressively optimal photoactivity. Blank Au-Pt and CdS show very low activity for H 2 and BAD production due to the fast recombination of electron-hole pairs. 11,12,20,31 For binary Au@CdS, the H 2 evolution rate is enhanced to 53.2 mmol h À1 . Aer coupling the co-catalyst Pt with Au@CdS, the H 2 evolution rates over ternary Au@Pt@CdS and Au-Pt@CdS reach 96.6 mmol h À1 and 153.0 mmol h À1 , respectively, which are about 13.4 and 21.2 times as high as that over blank CdS (7.2 mmol h À1 ). Notably, the anisotropic Au-Pt@CdS exhibits higher H 2 and BAD production rates than Au@CdS and Au@Pt@CdS, implying that the photoactivity enhancement of bimetal-semiconductor composites is not only dependent on the ingredient composition, but also affected by the spatial distribution of metal components. For comparison, we also investigated the photoactivity of CdS supported Au-Pt NRs (Au-Pt/CdS, Fig. S7d †) and the result shows that the photoactivity of such supported Au-Pt/CdS is much lower than that of Au-Pt@CdS, which manifests that the core-shell conguration can strengthen the interfacial contact between the metal and semiconductor CdS, thereby facilitating the charge carrier separation and transfer across the interfacial domain and consequently boosting the photoactivity.</p><p>The photoactivity enhancement and general applicability of Au-Pt@CdS were further investigated by conversion of other aromatic alcohols (R-PhCH 2 OH, R ¼ OCH 3 , CH 3 , Cl and OH) with different substituent groups. By taking unsubstituted BA (Fig. 2d) as the reference, the results (Fig. S8a-d †) indicate that the H 2 and aldehyde production rates are enhanced by electrondonating substituents (R ¼ OCH 3 and CH 3 ) and retarded by electron-withdrawing groups (R ¼ Cl and OH) for all photocatalysts. Au-Pt@CdS displays higher photoactivity than blank CdS and other metal-CdS hybrids for conversion of these alcohols. In addition, the photocatalytic performance of Au-Pt@CdS is either comparable or superior to other similar coupled reaction systems for simultaneous production of H 2 and value-added chemicals (Table S1 †).</p><p>Fig. 3a shows the long-term photocatalytic performance of Au-Pt@CdS toward the conversion of BA under Vis-NIR light irradiation. Aer 5 h of irradiation, the conversion of BA is about 80.1% and the selectivity for BAD reaches 94.0%. The H 2 and BAD production rates display no obvious decrease during four successive runs within 20 h. In addition, the morphology, composition and crystalline structure of Au-Pt@CdS aer recycling photocatalytic reactions are similar to those of the fresh sample (Fig. S9 †). These results indicate the good stability of Au-Pt@CdS under our photocatalytic reaction conditions. To understand the roles respectively played by the semiconductor and metal components of Au-Pt@CdS in the photoactivity enhancement, we performed the wavelength-dependent experiment. As shown in Fig. 3b, the action spectrum of apparent quantum yield efficiency (AQY) is in agreement with the bandgap absorption of the CdS component. This result reveals that the photocatalytic conversion of BA to produce BAD and H 2 proceeds through light absorption by the semiconductor CdS component instead of SPR excitation of Au-Pt bimetal. 24,44 Therefore, it is crucial to explore what is the specic role of plasmonic Au and nonplasmonic Pt in improving the photoactivity of semiconductor CdS, and what kind of contribution of the SPR excitation is associated with bimetallic Au-Pt in inuencing the separation of charge carriers photogenerated from CdS in Au-Pt@CdS.</p><p>Since electric eld distribution and intensity are related to the SPR enhancement, 25,45,46 we simulated the electric eld (|E|/ |E 0 |) distribution around different metal-CdS hybrids, aiming to ascertain the region of electric eld enhancement upon SPR excitation and its possible contribution to the photoactivity enhancement. As shown in Fig. 3c, differing from strong electric eld distribution at both ends of binary Au@CdS, the ternary Au@Pt@CdS sample exhibits weak electric eld enhancement. When the continuous Pt shell encapping the entire surface of Au NRs in Au@Pt@CdS is replaced by discrete Pt selectively tipped onto the two ends of Au NRs in Au-Pt@CdS, the electric eld enhancement around the surface of Au-Pt@CdS is greatly boosted. The weakest electric eld enhancement of Au@Pt@CdS could be ascribed to the plasmon-induced electron transfer from Au to Pt and the serious plasmon damping effect of the continuous Pt shell. [23][24][25]36 According to the simulation result, the maximum values of electric eld enhancement at the outside surface of CdS for Au@CdS, Au-Pt@CdS and Au@Pt@CdS are about 15, 13 and 5, respectively. The enhanced electric eld can improve the light harvesting ability of the catalyst, and increase the generation and separation rate of electron-hole pairs near the surface of the semiconductor material. [45][46][47] However, the trend in electric eld enhancement (i.e., Au@CdS > Au-Pt@CdS [ Au@Pt@CdS) is inconsistent with that of photoactivity (i.e., Au-Pt@CdS > Au@Pt@CdS > Au@CdS). This indicates that in addition to the effect of electric eld enhancement factor on the photoactivity of metal-semiconductor hybrids, other factors should be simultaneously considered to account for the difference in photoactivity enhancement.</p><p>We then investigated charge transfer dynamics in CdS and metal-CdS hybrids by using ultrafast transient absorption (TA) spectroscopy. Upon 370 nm excitation, a negative absorption peak at about 500 nm corresponding to the ground state bleach (GSB) signal of the CdS component is formed due to the band-lling by photoinduced electrons and holes (Fig. 3d and S10 †). The recovery kinetics of this GSB reects the charge dissipating processes by recombination and/or transfer (Fig. 3e). In blank CdS, the recovery kinetics originates from the recombination of charge carriers and the possible charge trapping by the defects. 15,48 In the presence of metal nanostructures, the kinetics become signicantly faster. We attribute this observation to the photoinduced electron transfer from CdS to the metal ingredient, as reported in similar semiconductor-metal composites. 11,29,49 In order to quantitatively determine the electron transfer rate, the recovery kinetics were tted by a biexponential function and the electron transfer rates were estimated by comparing the charge transfer rate constants (k ct , see eqn (S1)-(S3) and Table S2 †). 50 In comparison with blank CdS, the charge transfer rate over binary Au@CdS is increased, which indicates an electron transfer channel from CdS to Au because the work function of Au (5.10 eV) is larger than that of CdS (4.20 eV). 51,52 Aer the Pt NPs (with a work function of 5.40 eV) are deposited on Au NRs, the k ct values of both Au@Pt@CdS and Au-Pt@CdS are further enhanced. The highest k ct value for Au-Pt@CdS signies that the Au-Pt bimetal nanostructure is more effective than Au@Pt in facilitating the photoexcited charge transfer in the photocatalytic system, due to the additional interfacial electron transfer channels from CdS to Au and to Pt guaranteed by the direct contact and matched band alignment among the three components (Fig. S11 †). 51,52 Fig. 3 To study the effect of SPR excitation on photoactivity enhancement, we performed a wavelength-control experiment over Au-Pt@CdS under selective photoexcitation of the plasmonic Au-Pt component (Fig. S12a †). 31,53 It is seen from Fig. S12b † that the Au-Pt@CdS hybrids show only trace photoactivity under SPR excitation alone, indicating that the effect of hot electron injection from Au-Pt to CdS on the photoactivity is negligible. When we used the photon energy at 570 nm to excite the T-SPR of Au-Pt@CdS in the TA measurement, the sample shows no signal corresponding to excitation and relaxation kinetics (Fig. S12c †), which further conrms the absence of the hot electron transfer process. Thus, the SPR enhancement mechanisms should be interpreted in terms of the electric eld effect. 45 In addition, wavelength-control experiments under selective photoexcitation of CdS or simultaneous photoexcitation of CdS and Au-Pt (Fig. S13a †) disclose that the Au-Pt@CdS exhibits enhanced photoactivity as compared to bare CdS under both irradiation conditions, and the photoactivity enhancement is more prominent under simultaneous photoexcitation of CdS and Au-Pt components (Fig. S13b †). We also prepared nonplasmonic Pt-loaded CdS (Pt-CdS) through the well-reported photodeposition method. 44,54 The photocatalytic activity of nonplasmonic Pt-CdS is much lower than that of plasmonic Au-Pt@CdS under Vis-NIR light irradiation (Fig. S13c †).</p><p>The above joint results signify that the promoted photoactivity of Au-Pt@CdS is induced by the synergistic coupling of the band-gap photoexcitation of semiconductor CdS with the electric eld enhancement and the electron sink effect of Au-Pt bimetal, as depicted in Fig. 4a. 55,56 Specically, when the Au-Pt@CdS ternary heterostructure is illuminated by Vis-NIR light (l > 420 nm), the CdS component can harvest short-wavelength visible light (420 nm < l < 520 nm), yielding electron-hole charge carriers (e À -h + ). Meanwhile, the SPR excitation of plasmonic Au-Pt bimetal by longer-wavelength light irradiation provides extra electric eld enhancement to improve the photoabsorption, and promote the generation and separation of electron-hole pairs in CdS. 45,46,57 Subsequently, the photogenerated electrons traverse from the conduction band (CB) of CdS to the anisotropic Au-Pt bimetal component. The protons (H + ) diffuse through the loose and porous CdS thin layer and react with electrons to generate H 2 . 35,58,59 The holes retained in the valence band (VB) of CdS can selectively oxidize alcohols to aldehydes, which is the overall activity-limiting step in the redox cycle. 44,60 The photogenerated electrons and holes are spatially separated, signicantly reducing the recombination probability, which leads to greatly improved photoactivity of Au-Pt@CdS.</p><p>The investigation of the photoelectrochemical (PEC) process can further reveal the picture of electron transfer and the underlying photoactivity enhancement mechanism. As shown in Fig. 4b, transient photocurrent responses of different samples under chopped Vis-NIR light illumination indicate that the construction of bimetal-semiconductor hybrids is conducive to enhancing the photocurrent of semiconductor CdS, which follows the same order as the photoactivity: Au-Pt@CdS > Au@Pt@CdS > Au@CdS > CdS. This result indicates a more effective separation of electron-hole pairs over Au-Pt@CdS than other electrode samples. 9,35,61,62 Au-Pt@CdS and Au@Pt@CdS consist of the same hetero-components, but the anisotropic Au-Pt@CdS exhibits higher photocurrent and photoactivity than isotropic Au@Pt@CdS under Vis-NIR light illumination. This suggests that the inappropriate arrangement of the plasmonic-nonplasmonic bimetal heterostructure in Au@Pt@CdS leads to the suppression of electric eld enhancement and electron sink effect, as respectively proved by the results of electric eld simulation (Fig. 3c) and TA characterization (Fig. 3e). 24,25 Electrochemical impedance spectroscopy (EIS, Fig. 4c) and Mott-Schottky (Fig. 4d) analysis were conducted under Vis-NIR light illumination. The arc at the middle frequencies of the Nyquist plot in Fig. 4c is characteristic of charge transportation resistance. 63 Apparently, the diameter of the arc for the Au-Pt@CdS electrode is much smaller than that of CdS, Au@CdS and Au@Pt@CdS, indicating that the resistance of interfacial charge transportation is signicantly decreased over the Au-Pt@CdS electrode. The Mott-Schottky analysis can be used to provide fundamental insights into the charge carrier density (N D ), which is obtained from the following equation: 63,64 Fig. 4</p><p>where C is the capacitance, e is the elementary electronic charge, 3 0 is the permittivity in vacuum, and 3 is the dielectric constant, specically 8.99 for CdS. [63][64][65] From the slope in the plot of 1/C 2 vs. V in Fig. 4d, N D can be determined by the above equation. A summary of N D values is given in Table S3. † The plot of the Au-Pt@CdS electrode shows the smallest slope value among the samples, indicating a much higher N D than that of CdS, Au@CdS and Au@Pt@CdS. The higher N D signies lower resistance, faster charge transfer rate and consequently enhanced PEC and photocatalytic performance. In addition, all plots show positive slopes, indicating the n-type semiconductor characteristic of CdS. 63,66 The formed multiple Schottky barrier between the n-type CdS semiconductor and Au-Pt bimetal would prevent the electrons the metal driing back to the semiconductor. 67 Based on the above results, it can be concluded that Au-Pt can effectively facilitate the generation and transfer of charge carriers from CdS, due to the boosted local electric eld and the enriched spatial charge transfer channels. Fig. 4e displays the linear sweep voltammetry (LSV) curves of Au-Pt@CdS, Au@Pt@CdS, Au@CdS and CdS electrodes without light irradiation, from which it is seen that the addition of nonplasmonic Pt into Au@CdS can obviously enhance the cathodic current density and decrease the overpotential of H 2 production, thus further promoting catalytic efficiency. 31,48</p><!><p>In summary, we have accomplished a controllable design of bimetal-semiconductor hybrids for optimizing the redox photocatalysis performance of alcohol conversion to H 2 and valueadded aldehyde for the rst time. semiconductor hybrids, as well as the underlying SPR-coupled multichannel electron transfer mechanism illustrated here, could be instructive for further rational design of plasmonic bimetal-or multimetal-semiconductor hybrids toward efficient redox catalysis.</p><!><p>The Au NRs were prepared using a seed-mediated growth method. 68 The seed solution for Au NR growth was prepared as follows: 5 mL of 0.5 mM HAuCl 4 was mixed with 5 mL of 0.2 M CTAB solution in a 20 mL scintillation vial. 0.6 mL of fresh 0.01 M NaBH 4 was diluted to 1 mL with water and was then injected into the above solution under vigorous stirring (1200 rpm). The solution color changed from yellow to brownish yellow and the stirring was stopped aer 2 min. The seed solution was aged at room temperature for 2 h before use. Subsequently, 1.4 g of CTAB and 0.25 g of NaOL were dissolved in 50 mL of warm water ($50 C) in a 100 mL Erlenmeyer ask. The solution was allowed to cool down to 30 C and 3.6 mL of 4 mM AgNO 3 solution was added. The mixture was kept undisturbed at 30 C for 15 min aer which 50 mL of 1 mM HAuCl 4 solution was added. The solution became colorless aer 90 min of stirring (700 rpm) and 0.3 mL of HCl (37 wt% in water, 12.1 M) was then introduced. Aer another 15 min of slow stirring at 400 rpm, 0.25 mL of 0.064 M AA was added and the solution was vigorously stirred for 30 s. Finally, 0.4 mL of seed solution was injected into the growth solution. The resultant mixture was stirred for 30 s and le undisturbed at 30 C for 12 h for NR growth.</p><!><p>Au-Pt was prepared by using Au NRs as the template. 24 Briey, 10 mL of the prepared Au NRs was separated from excess CTAB by centrifugation twice (at 10 000 rpm) and redispersed in 0. added into 10 mL of as-made Au NR suspension. 100 mL of 0.01 M H 2 PtCl 6 $6H 2 O and subsequently 0.08 mL of 0.01 M HCl were added to the reaction mixture. The mixture was le undisturbed for 24 h at 30 C. Pt-covered Au NRs (Au@Pt) were prepared by using Au NRs in 0.03 M CTAB solution as the template following the same procedure.</p><!><p>For the synthesis of Au-Pt@CdS, 10 mL of the as-prepared Au-Pt seeds and 10 mL of aqueous Gly solution (0.2 M) were mixed in a 50 mL vial, and subsequently 300 mL aqueous NaOH solution (2 M) was added to the reaction mixture. The mixture was kept at 30 C for 30 min without stirring. Next, 200 mL of Cd(Ac) 2 (0.1 M) and TAA (0.1 M) solution were injected into the above solution drop by drop. The reaction was allowed to proceed at 85 C under vigorous stirring for 2 h. The suspensions were centrifuged at 12 000 rpm for 10 min and washed with ethanol three times, and then the precipitates were vacuum dried at 40 C. Au@CdS, Au@Pt@CdS and blank CdS were also synthesized by the above method, except that the corresponding seeds or blank CTAB (0.1 M) aqueous solution was used instead of Au-Pt, respectively, in the synthesis process. The Au-Pt/CdS sample was prepared by mixing the blank CdS with an appropriate amount of Au-Pt in solution with vigorous stirring for 24 h followed by the wash and dry process similar to Au-Pt@CdS.</p><!><p>The crystal phase properties of the samples were analysed with a Bruker D8 Advance X-ray diffractometer (XRD) using Ni-ltered Cu Ka radiation at 40 kV and 40 mA in the 2q range from 20 to 80 with a scan rate of 0.02 per second. The optical properties of the samples were characterized using a Cary-5000 ultraviolet-visible-near infrared diffuse reectance spectrophotometer (DRS, Varian Co.). The morphology and elemental distribution of the samples were analysed by eld-emission scanning electron microscopy (FESEM) on a FEI Nova NANO-SEM 230 spectrophotometer and transmission electron microscopy (TEM), high-resolution TEM (HRTEM) and elemental mapping analysis using a JEOL 2100F instrument at an accelerating voltage of 200 kV. Raman spectroscopy was performed on a Renishaw inVia Raman System 1000 with a 532 nm Nd:YAG excitation source at room temperature. X-ray photoelectron spectroscopy (XPS) measurements were performed using a Thermo Scientic ESCA Lab250 spectrometer that consists of monochromatic Al Ka as the X-ray source, a hemispherical analyser, and a sample stage with multiaxial adjustability to obtain the composition on the surface of the samples. All of the binding energies were calibrated using the C 1s peak of the surface adventitious carbon at 284.6 eV. The elemental concentration analysis was performed using an inductively coupled plasma emission spectroscopy instrument (ICP, PerkinElmer Optima 8000). The carrier dynamics were measured by using femtosecond transient absorption spectroscopy (Time-Tech Spectra, femtoTA-100). Part of the 800 nm output pulse from the amplier was used to pump a TOPAS Optical Parametric Amplier (OPA) which generates the 370 nm pump beam. The pump pulses were chopped by a synchronized chopper at 500 Hz and the absorbance change was calculated with two adjacent probe pulses (pump-blocked and pumpunblocked), and the pump power was approximately 1 mW. The samples were dispersed in water for all pump-probe characterizations performed under ambient conditions. The photoelectrochemical analysis was carried out in a conventional three-electrode cell using a Pt plate and an Ag/AgCl electrode as the counter electrode and reference electrode, respectively. The electrolyte was 0.2 M Na 2 SO 4 aqueous solution containing 0.1 mM BA. The working electrode was prepared on indium-tin oxide (ITO) glass that was cleaned by sonication in ethanol for 30 min and dried at 353 K. The boundary of ITO glass was protected using Scotch tape. 5 mg of the sample was dispersed in 0.5 mL of N,N-dimethylformamide (DMF, supplied by Sinopharm Chemical Reagent Co., Ltd) by sonication to get a slurry. The slurry (20 mL) was spread onto pre-treated ITO glass. Aer air drying, the working electrode was further dried at 393 K for 2 h to improve adhesion. Then, the Scotch tape was unstuck, and the uncoated part of the electrode was isolated with epoxy resin. The exposed area of the working electrode was 0.25 cm 2 . The light irradiation source was a 300 W Xe arc lamp system equipped with a lter to cut off light of wavelength l < 420 nm. The cathodic polarization curves were obtained using the linear sweep voltammetry (LSV) technique with a scan rate of 2 mV s À1 . The electrochemical impedance spectroscopy (EIS) experiments were conducted on an AUTOLAB M204 workstation.</p><!><p>The electric eld simulations were carried out by using a nitedifference time-domain (FDTD) soware package (Lumerical Solutions, Inc.). The refractive indices of CdS, BTF, Au and Pt were taken from previous reported data. 19,23,69 A total-eld/ scattered eld (TFSF) source was used as an incident eld into the simulation region, which coincided with the wavelength of our experimental irradiation source. Perfectly matched layer (PML) boundary conditions were used in our simulations. The Au NRs are cylinders with round ends and the size was taken to match their average values. The radius of the cylinder is 14.5 nm and radii of the ends are 8 nm. The total length of the Au NRs is 92.5 nm. The shell thickness of CdS is 20 nm. For the model of Au-Pt@CdS, elliptical Pt spheres with diameters of 14 nm were located at both ends of the Au NRs with a total length of 98 nm. For Au@Pt@CdS, the Pt shell is a cylinder with a radius of 2.1 nm and the total length of the Au NRs is 107.9 nm.</p><!><p>The experiments were performed referring to the previously reported literature with some modications. 44,70 In a typical photocatalytic reaction, 2 mL catalyst suspension (1 mg mL À1 in BTF) containing 0.5 M alcohol was placed in a quartz reactor (25 mL) equipped with a magnetic stir bar. The reaction suspension was sonicated for 2 min at room temperature and purged with Ar gas for 30 min. The reactor was then tightly sealed and then stirred for 30 minutes in the dark to achieve an adsorptiondesorption equilibrium. A 300 W Xe arc lamp (PLS-SXE 300, Beijing Perfect light Co., Ltd) with a lter to cut off light of wavelength l < 420 nm was used as the irradiation source. The light intensity was xed at 800 mW cm À2 . The photon ux of incident light was measured using an Optical Power/Energy Meter (Newport 842-PE). The irradiation area is 3.8 cm 2 . During photocatalysis, the suspension was continuously stirred to ensure uniform irradiation. The evolved gases were analysed using a gas chromatograph (Shimadzu GC-2014C, MS-5 A column, Ar carrier) equipped with a thermal conductivity detector (TCD). Products in solution were quantied using an Agilent Gas Chromatograph (GC-7820) with a ame-ionization detector (FID) and identied by gas chromatography-mass spectrometry (GC-MS, Agilent Technologies, GC6890N, MS 5973). The recycling test for photocatalytic conversion of BA over Au-Pt@CdS was performed as follows. Aer 5 h reaction under Vis-NIR light irradiation, the suspension was centrifuged and mixed with 2 mL BTF containing 0.5 M BA for continuous test. The conversion of BA and selectivity for BAD were calculated with the following equations: 71</p><p>here C 0 is the initial concentration of BA; C BA and C BAD are the concentrations of the residual BA and the corresponding BAD at a certain time aer the catalytic reaction, respectively. The apparent quantum efficiency (AQE) was calculated from the ratio of twice the number of H 2 molecules to the number of incident photons by using the following expression: 22,31 AQE ¼ 2  number of H 2 molecules number of incident photons  100%</p><p>where M is the molar amount of H 2 molecules, N A is the Avogadro constant, h is the Planck constant, c is the speed of light, S is the irradiation area, P is the intensity of the irradiation, t is the photoreaction time and l is the wavelength of the monochromatic light. The power density of different monochromatic lights was xed at 30.0 mW cm À2 .</p><!><p>There are no conicts to declare.</p>

Royal Society of Chemistry (RSC)

Examining sterically demanding lysine analogs for histone lysine methyltransferase catalysis

Methylation of lysine residues in histone proteins is catalyzed by S-adenosylmethionine (SAM)dependent histone lysine methyltransferases (KMts), a genuinely important class of epigenetic enzymes of biomedical interest. Here we report synthetic, mass spectrometric, nMR spectroscopic and quantum mechanical/molecular mechanical (QM/MM) molecular dynamics studies on KMtcatalyzed methylation of histone peptides that contain lysine and its sterically demanding analogs. our synergistic experimental and computational work demonstrates that human KMts have a capacity to catalyze methylation of slightly bulkier lysine analogs, but lack the activity for analogs that possess larger aromatic side chains. overall, this study provides an important chemical insight into molecular requirements that contribute to efficient KMT catalysis and expands the substrate scope of KMTcatalyzed methylation reactions.Posttranslational modifications on histone proteins regulate the structure and function of human chromatin 1-3 . Well-established examples include lysine acetylation, which is linked with the transcriptionally active region of human genome, and lysine methylation, which is associated with gene activation and suppression, depending on the histone sequence and methylation state 4,5 . Histone lysine methylation is catalyzed by S-adenosylmethionine (SAM)-dependent histone lysine methyltransferases (KMTs), and can lead to a formation of monomethyllysine (Kme), dimethyllysine (Kme2) and trimethyllysine (Kme3) 6,7 . It is generally believed that the methylation state depends on the constitution of the KMT active site (Fig. 1a) 8 . With the exception of DOT1L, all members of KMT family possess the SET (Su(var)3-9, Enhancer-of-zeste and Trithorax) domain [9][10][11] . Structural analyses of KMTs complexed with histone peptide/methylated peptide and S-adenosylhomocysteine product (SAH) revealed that the lysine side chain occupies a narrow, hydrophobic channel, typically comprised of side chains of several tyrosine and phenylalanine residues (Fig. 1b) 8 . The positioning of the lysine's N ε amino group towards the electrophilic methyl group of the SAM cosubstrate results in an efficient methyl transfer via S N 2 reaction 12,13 .Recent examinations of lysine analogs as substrates for human histone lysine methyltransferases revealed that KMTs possess a high degree of specificity for lysine residues. Enzymatic assays employing MALDI-TOF MS verified that human KMTs preferentially catalyze methylation of lysine residues with L-stereochemistry over D-stereochemistry 14 . Combined experimental and computational studies on histone peptides that bear lysine analogs of different chain length revealed that lysine exhibits an optimal chain length for KMT-catalyzed methylation 15 , and that the enzymatic methylation is limited to N-nucleophiles 16 . Members of KMTs were also found to catalyze methylation of the cysteine-derived γ-thialysine on intact histones and histone peptides 17,18 . Substrate capturing studies using the genetically encoding photo-lysine showed that slightly bulkier γ-diaza-lysine undergoes efficient SETD7-catalyzed methylation in cells 19 . In addition to the essential role of the lysine's side chain,

examining_sterically_demanding_lysine_analogs_for_histone_lysine_methyltransferase_catalysis

<!>Results and Discussion<!>conclusion

<p>its main chain also plays an important role in productive KMT catalysis 20 . Despite these recent findings that shed light on basic understanding of KMT catalysis, a broader scope of lysine analogs as substrates for KMTs has not been explored yet. Here we report enzymatic evaluations of sterically demanding lysine analogs as substrates for human KMTs employing MALDI-TOF MS assays, NMR spectroscopic analyses, and quantum mechanical/ molecular mechanical (QM/MM) molecular dynamics and free energy studies.</p><p>The lysine's side chain is comprised of four hydrophobic methylene groups and the terminal nucleophilic N ε amino group. The zig-zag orientation of the flexible C-C bonds might enable a proper orientation of the lysine's side chain in a narrow hydrophobic pocket of KMTs, leading to efficient KMT catalysis. It remains to be established whether this narrow lysine-binding pocket can accommodate larger moieties that resemble lysine. The objective of this work is to explore whether KMTs do have a capacity to catalyze methylation of bulkier lysine analogs present on histone peptides. We selected six sterically demanding lysine analogs: (i) cyclopropyllysine (K CP ), which bears an additional methylene group adjacent to the N ε amino group; (ii) benzylamine (K ba ), an analog with a larger but highly nucleophilic side chain; (iii) meta-aminophenylalanine (F 3a ), a significantly larger aromatic lysine analog that possesses the terminal N ε amino group with a weaker nucleophilic character; (iv) para-aminophenylalanine (F 4a ), another aniline derivative with less nucleophilic N ε amino group; (v) pyridylalanine (A P ), which possesses a nucleophilic pyridine functionality; and (vi) tyrosine (Y), an electron-rich aromatic system with a potential to undergo O-or C-methylation (Fig. 1c).</p><!><p>Fmoc-and Boc-protected cyclopropyllysine (Fmoc-K CP (Boc)-OH, 1) was synthesized in nine steps using a modification of the reported procedure (Fig. 2) 21 . To install an alcohol on the side chain, perbenzylation of L-glutamic acid 2 produced a tetra-substituted compound that underwent selective reduction of the side chain ester in the presence of DIBAL-H to afford the intermediate 3. Swern oxidation was applied to give the amino aldehyde, which reacted directly with t-butyl diethylphosphonoacetate via Horner-Wadsworth-Emmons reaction to produce the α,β-unsaturated t-butyl ester 4. 1 H NMR data confirmed that 4 exists as the E-isomer. Diazomethane was then generated in situ and distilled directly into a solution of 4 containing catalytic amounts of palladium(II) acetate, to yield the α,β-cyclopropyl t-butyl ester, which was selectively hydrolyzed with TFA to yield compound 5. The 13 C NMR spectrum of 5 revealed an ~1:1 "doubling" of many of the signals into small doublets. This finding was indicative of either diastereomeric cyclopropylation whereby the methylene is added above or below the alkene plane in roughly equal percentages or that the compound had some form of hindered rotation that resulted in two identical molecules with nearly identical conformations. The latter is unlikely as there are no stereotypical bond-types that form rotamers, and nonspecific cyclopropylation is the more reasonable explanation as two different diastereomers are formed due to the chiral C α of the backbone. The Boc-protected cyclopropyl amine 6 was then produced through a Curtius rearrangement after refluxing in t-butanol. Subsequently, deprotection of the benzyl group on amine/carboxylate with Pd/C under hydrogen atmosphere, followed by the Fmoc-protection of the free amine afforded Fmoc-K CP (Boc)-OH 1. The presence of 13 C "doubling" was also present in the final building block 1. High-resolution 2D 1 H-13 C HSQC-TOCSY spectra were able to produce 1 H spectra of each of the two diastereomers from the projection of the cross-peaks. These 1 Hs exhibited very small but noticeable differences in chemical shift (Supplementary Fig. 1). Furthermore, exploring the effect of temperature on the lineshape of the 1 H signals from 25 °C to 50 °C revealed no significant effects, further supporting the explanation of diastereomers versus rotamers for the observed spectral doubling (Supplementary Fig. 2). The other five Fmoc-protected lysine analogs, i.e. Fmoc-K ba (Boc)-OH, Fmoc-F 3a (Boc)-OH), Fmoc-F 4a (Boc)-OH, Fmoc-A P -OH, and Fmoc-Tyr( t Bu)-OH, are commercially available. All sterically demanding lysine analogs were incorporated into histone peptides using solid-phase peptide synthesis; H4K20 analogs (GGAKRHRKVLRDNIQ), H3K4 analogs (sequence ARTKQTARKSTGGKA), and H3K9 analogs (sequence ARTKQTARKSTGGKA) were synthesized. All histone peptides were purified by preparative HPLC, and the purity of synthetic histone peptides bearing lysine analogs was confirmed by analytical HPLC and ESI-MS analyses (Supplementary Tables 1-2 and Supplementary Figs. 3-13).</p><p>We examined histone peptides bearing lysine and its sterically demanding analogs as potential substrates for human KMTs employing MALDI-TOF MS assays. Enzymatic assays with SETD8 (2 µM) and SAM cosubstrate (200 µM) showed different degrees of methylation of H4K20 peptides (100 µM) after 1 hour at 37 °C. While natural sequence H4K20 underwent quantitative monomethylation, cyclopropyl-containing H4K CP 20 peptide appeared to be monomethylated to a comparatively lesser extent (60% of H4K CP 20me) (Fig. 3a). Under the same conditions, none of the other five aromatic lysine analogs were observed to be methylated within limits of detection in the presence of SETD8 (Fig. 3). Increased amounts of SETD8/SAM and prolonged incubation at 37 °C resulted in almost complete formation of the monomethylated H4K CP 20me product (Supplementary Fig. 14), but still did not lead to appearance of detectable amounts of the monomethylated products of the remaining five lysine analogs (Supplementary Figs. 15-19). As expected, control experiments in the absence of SETD8 or SAM verified that monomethylation of H4K CP 20 is SETD8-catalyzed and also requires the presence of SAM cosubstrate (Supplementary Figs. 20-21). MALDI-TOF analyses of SETD7-catalyzed methylation of H3K4 peptides showed that none of histone peptides that contain sterically demanding lysine analogs was methylated within limits of detection (only traces of H3K CP 4 were observed); SETD7 in the presence of SAM indeed catalyzed the formation of monomethylated H3K4 with a natural sequence (Supplementary Fig. 22). At high concentration of SETD7 (10 µM) and SAM (1 mM) and longer incubation (3 hours), an increased amount of the monomethylated H3K CP 4me product was observed (Supplementary Fig. 23). Despite being monomethyltransferases, SETD7 and SETD8 appear to have somewhat different abilities to accept substrates other than lysine. In line with our work on γ-thialysine 18 , SETD8 seems to have a slightly broader substrate scope than SETD7, possibly due to subtle differences of the active sites (e.g. positioning of Y273 in SETD8 and Y305 in SETD7).</p><p>Our recent investigations demonstrated that, in contrast to monomethyltransferases SETD8 and SETD7, H3K9 trimethyltransferases G9a and GLP appear to exhibit a somewhat broader substrate scope for the enzymatic methylation reaction. Enzymatic studies of natural and unnatural H3K9 peptide sequences (100 µM) in the presence of G9a/GLP (2 µM) and SAM (500 µM) at 37 °C showed that both enzymes do have a potential to catalyze methylation of H3K CP 9, minor methylation of H3K ba 9 (traces detected), whereas we did not observe any www.nature.com/scientificreports www.nature.com/scientificreports/ methylated products with other four bulkier lysine analogs within limits of detection (Fig. 3b and Supplementary Fig. 24). H3K CP 9 underwent predominant GLP-catalyzed dimethylation (75%), while monomethylated (10%) and trimethylated (10%) products were also observed after 1 hour under standard conditions; longer incubation times led to slightly increased amounts of H3K CP 9me3 (Supplementary Fig. 25). Under the same conditions, H3K CP 9me2 (60%) and H3K CP 9me3 (40%) were formed in the presence of G9a after 1 hour, whereas equal amounts of both methylated products were found after 3 hours at 37 °C (Supplementary Fig. 26). Notably, increased amounts of GLP (10 µM) and SAM (1 mM) afforded almost exclusive formation of H3K CP 9me3 and significant (55%) monomethylation of H3K ba 9 after 5 hours at 37 °C, whereas other sterically demanding lysine analogs were still not methylated within detection limits (Supplementary Fig. 27). Control experiments in the absence of G9a/GLP or SAM additionally confirmed that both the enzyme and the cosubstrate are required for methylation on H3K CP 9 to occur (Supplementary Figs. 28-29).</p><p>To establish the substrate efficiency of lysine-and K CP -containing histone peptides, we carried out enzyme kinetics analysis, employing the MALDI-TOF MS assays 22 . Both enzymes preferentially catalyze methylation of natural histone sequences, however, bulkier K CP -containing peptides still underwent favorable kinetics profiles (Table 1 and Supplementary Fig. 30). The lower substrate efficiencies for H4K CP 20 and H3K CP 9 compared to natural sequences were a result of higher K M values, implying a less favorable association of bulkier K CP in a narrow binding pocket of KMTs.</p><p>Next, we carried out competition studies between histone peptides that bear lysine and its analogs. In the presence of SETD8, SAM and equimolar amounts of H4K20 and H4K CP 20, we observed the formation of both monomethylated products, albeit a comparatively larger degree of monomethylation of H4K20 was found (70% of H4K20me, 40% of H4K CP 20me). This result implies that H4K20 and H4K CP 20 do compete for binding with SETD8, and that H4K20 possesses a somewhat higher binding affinity, which presumably leads to being a better substrate for SETD8. It is also possible that subtle differences in sterics and electronics of H4K CP 20 when compared to H4K20 do contribute to observed differences in the degree of methylation in the competition experiment. In line with observations that sterically demanding lysine analogs do not undergo SETD8-catalyzed methylation, we found that they also do not significantly inhibit monomethylation of H4K20 (Supplementary Fig. 31). These results are in agreement with inhibition and binding studies of related aromatic lysine analogs that exhibited limited ability to associate with SETD8 23 . Similarly, we observed that H3K CP 9 competes with H3K9 for G9a-catalyzed methylation, however, other bulkier lysine analogs do not significantly inhibit G9a-catalyzed methylation of H3K9 (Supplementary Fig. 32).</p><p>We then moved on to investigate in more detail whether the histone peptides bearing unnatural lysine analogs that are not substrates for methyltransferase catalysis, have an ability to inhibit KMT-catalyzed methylation of H3K4 and H3K9. Inhibition studies were carried out employing MALDI-TOF MS assays [24][25][26] . Initially, all unnatural histone peptides were screened for inhibition at 100 µM (Fig. 4). For H3K4 analogs it was found that all peptides have a very limited ability (IC 50 > 100 µM) to inhibit SETD7's methyltransferase activity, at most 11% inhibition was observed at 100 µM of H3F 4a 4. From the peptides bearing unnatural lysine analogs at position 9, we were pleased to find that H3F 3a 9 showed significant inhibition against G9a (IC 50 = 14.8 µM) and GLP (IC 50 = 26.0 µM), whereas other histone peptides showed a limited inhibition activity (Fig. 4 and Supplementary Figs. 33-34). For inhibition of GLP by H3K CP 9, we found that IC 50 ≈ 100 µM, whereas for the other analogs we observed IC 50 > 100 µM for both GLP and G9a.</p><p>Having shown that H3K CP 9 acts as a substrate for GLP, 1D and 2D NMR spectra were acquired to further elucidate the chemical structure of the methylated H3K CP 9 product (Fig. 5). To characterize the methylated H3K CP 9 product of GLP-catalyzed reaction, 1 H NMR and 1 H- 13 C HSQC (Heteronuclear Single Quantum Coherence) spectra of the H3K CP 9 peptide were recorded prior to enzymatic reaction (Supplementary Fig. 35). We verified by NMR spectroscopy that GLP-catalyzed methylation of lysine residue in the H3K9 peptide gives indicative signals in the 1 H NMR spectrum, as also previously examined (Fig. 5a) 15,27 . The appearance of a triplet at 2.62 ppm was assigned to the SAH-CH 2 γ, a characteristic coproduct signal that appears during the methylation reaction of lysine residues by KMTs. In addition, a new resonance at 3.03 ppm indicated the formation of the trimethylated species of lysine residue at position 9. These data were also supported by 1 H- 13 C HSQC analysis (Fig. 5h). GLP-catalyzed methylation of histone peptides that bear unnatural lysine analogs was also examined by NMR spectroscopy (Fig. 5). As shown in Fig. 5b, 1 H NMR data of H3K CP 9 in the presence of SAM and GLP after 1 h at 37 °C showed new resonance peaks of the dimethylated product (H3K CP 9me2) at 2.73 ppm and the trimethylated product (H3K CP 9me3) at 2.99 ppm. A triplet of SAH-CH 2 γ was also observed at 2.62 ppm. A conversion of the cyclopropyllysine residue at position 9 to di-and trimethylated products was additionally confirmed by multiplicity-edited HSQC. The resonance at 2.73 ppm in the 1 H NMR spectrum is in a correlation with ( 13 C: 43.1 ppm) and represents the dimethylated product, whereas the resonance at 2.99 ppm is in a correlation with ( 13 C: 52.5 ppm) and represents the trimethylated product (Fig. 5i). The methylene protons of the attached cyclopropyl were unable to be observed due to very low concentration, however, chemical shift changes and the addition of new resonances for the cyclopropyl methylene indicate a transformation in the vicinity of the cyclopropyl group. Control reactions with H3K9 and H3K CP 9 in the absence of GLP showed no formation of methylated products and SAH, again demonstrating that methylation reactions are GLP-catalyzed (Supplementary Figs. 36-37). After showing that the H3K CP 9 peptide is dimethylated and trimethylated in the presence of GLP and SAM by NMR, we tested whether GLP catalyzed methylation of H3K ba 9, H3F 3a 9 , H3F 4a 9, H3A P 9 and H3Y9 peptides, and whether GLP mediated the conversion of SAM to SAH. In line with results from MALDI-TOF MS assays, a lack of new characteristic resonances, namely a triplet at 2.62 ppm (SAH-CH 2 γ) and a singlet in the range of 2.5-3.1 ppm (NMe, NMe 2 or NMe 3 ), indicates that these sterically demanding lysine analogs were not methylated in the presence of GLP (Fig. 5c-g and Supplementary Figs. 38-41).</p><p>To gain additional insight into KMT-catalyzed methylation of bulkier lysine analogs, we carried out quantum mechanical/molecular mechanical (QM/MM) molecular dynamics and free energy studies on SETD8 and GLP in complex with K CP and F 3a . The free-energy profiles for the monomethylation reactions in SETD8 involving H4K20, two diastereoisomers of K CP (see the structure inserted in Fig. 6b and Supplementary Fig. 42) and F 3a are plotted in Fig. 6a. The free energy barriers for the methyl transfers obtained here are 20.0 and 19.3 kcal mol −1 for the two diastereoisomers of K CP , respectively, that are quite similar to the barrier when H4K20 was used as ). The active site structures of the reactant complexes for the methylations (Fig. 6b and Supplementary Fig. 42) show that the lone pair of electrons on N ζ of K CP can be aligned with the transferable methyl group even with the constrains of the three-membered rings. The free-energy profile for the methylation reaction in SETD8 involving F 3a shows that the free energy barrier becomes much higher (25.1 kcal mol −1 ), suggesting that the methylation reaction could not occur with this sterically demanding lysine analog even if this molecule was able to bind to the active site (Fig. 6c,d). The active site structure demonstrates that the transferable methyl group from SAM could not be aligned with the lone pair of electrons on N ζ for the methyl transfer to F 3a . In fact, the N ζ H 2 group is expected to be a part of the conjugated system containing the benzene ring, and one of the hydrogen atoms on N ζ (rather than the lone pair of electrons) would point to the transferable methyl group. Indeed, the distribution map on the right shows that the angle (θ) between the direction of electron lone pair on N ζ and the C M -S bond is between 45 and 120 degrees. In order to have the methylation reaction to occur, the N ζ H 2 group needs to undergo some rotations so that the lone pair of electrons can be aligned with the methyl group. Figure 6d shows that this is the case near the transition state where the N ζ H 2 group has undergone rotations with the lone pair of electrons pointing to the transferable methyl group.</p><p>The free energy profiles for the first, second and third methylation reactions in GLP involving K CP are given in Fig. 7a. As evident from Fig. 7a, all the free energy barriers are rather low and similar (~18-19 kcal mol −1 ), suggesting that GLP is a trimethyltransferase for K CP , in agreement with the experiments. Figure 7b shows that for the reactant complex of the first methyl transfer, the transferable methyl group from SAM can be aligned with the lone pair of electrons on N ζ . By contrast, for the reactant complex of the third methyl transfer the transferable methyl group from SAM cannot be well aligned with the lone pair of electrons on N ζ (Fig. 7c). Nevertheless, the free energy barrier is rather low as well for the third methyl transfer to K CP (18.4 kcal mol −1 ), indicating that the www.nature.com/scientificreports www.nature.com/scientificreports/ methylation can still occur. The structure near the transition state for the third methyl transfer is plotted in Fig. 7d (and Supplementary Fig. 43). It is of interest to note that there seems to be some additional transition state stabilization through the interactions involving one of the methyl groups and Y1124. Such interactions may lower the free energy barrier, leading to the third methyl transfer. A similar explanation has been used to understand the substrate/product specificities of Suv4-20h2 28 .</p><p>The free energy profile for the first methyl transfer to F 3a in GLP shows that the free energy barrier for the methyl transfer is quite high (23.6 kcal mol −1 ), suggesting that GLP cannot catalyze the methylation reaction for F 3a , as already verified experimentally (Supplementary Fig. 44). Similar to the case involving SETD8, the active site structure shows that the transferable methyl group from SAM cannot be aligned with the lone pair of electrons on N ζ in GLP for the methyl transfer to F 3a (Supplementary Fig. 45).</p><!><p>Overall, our combined synthetic, enzymatic and computational studies, which examine histone peptides that contain sterically demanding lysine analogs, reveal that human histone lysine methyltransferases exhibit a limited ability to catalyze methylation of bulky lysine analogs. Although members of human KMTs do have an ability to catalyze methylation of cyclopropyl-containing lysine (K CP ) and to a lesser extent benzylamine-containing glycine (K ba ), they cannot methylate significantly bulkier and less nucleophilic aminophenylalanine, pyridine and tyrosine residues. Despite the biomedical importance of members of KMT family of enzymes, basic molecular requirements for efficient KMT catalysis are only partially understood. Our work provides an important insight into chemical aspects of KMT catalysis by highlighting that human KMTs can accommodate and catalyze methylation of lysine analogs that possess a slightly larger side chain (e.g. K CP ). Furthermore, we showed that the H3F 3a 9 peptide has an ability to inhibit G9a and GLP methyltransferase activity. This peptide may serve as a starting point for the development of more potent peptide-based inhibitors of G9a and GLP. Along with recent work that has demonstrated that KMTs accept chemically diverse SAM analogs as cosubstrates [29][30][31] , our study shows that KMTs also possess an ability to catalyze methylation of substrates that mimic lysine. It is envisioned that similar approaches that rely on modern experimental and computational tools will advance our fundamental understanding of epigenetic processes that play essential roles in human health and disease. www.nature.com/scientificreports www.nature.com/scientificreports/ Methods expression and purification of KMts. Proteins expression and purification were performed as described 15 . Briefly, the four human proteins (SETD8, SETD7, G9a and GLP) were expressed in E. coli BL21 (DE3)pLysS-rosetta cells in TB growth medium supplemented with Kanamycin and chloramphenicol. Cells were grown at 37 °C until an OD 600 of 0.5-0.6. The temperature was then reduced to 16 °C and isopropyl β-D-1-thiogalacttopyranoside (IPTG) was added. Cells were then harvested and lysed by sonication. Purification of the N-terminally his6-tagged KMTs was carried out using Ni-NTA affinity chromatography. Further purification was carried out using size-exclusion chromatography (SEC) using a Superdex-75 preparative grade column on an AKTA system. Protein was separated by SDS-PAGE on a 4-15% gradient polyacrylamide gel (Bio-Rad) and the concentrations were determined using the Nanodrop DeNovix DS-11 spectrophotometer.</p><p>Histone peptides synthesis. The peptides, carboxylated at their C termini for SETD8, G9a and GLP, were synthesized manually using a cartridge (6 mL, 20 µm, Screening Devices B.V., The Netherlands). Amino acids residues protected with acid labile moieties employing fluorenylmethyloxycarbonyl (Fmoc) chemistry. Deprotected peptide H4K20 and its unnatural bulkier lysine derivatives for SETD8 substrate examination were prepared possessing the residues (GGAKRHRK 20 VLRDNIQ). Deprotected peptide H3K4 and its unnatural bulkier lysine derivatives for SETD7 substrate examination were prepared possessing the residues (ARTK 4 QTARKSTGGKA). Deprotected peptide H3K9 and its lysine analogs for G9a and GLP were prepared bearing the residues (ARTKQTARK 9 STGGKA). From a loading batch 0.5 mmol/g, a capacity of 0.21 mmol (100 mg) per each synthesis was employed to obtain the required sequence. All standard amino acids (3.0 equivalents) were coupled using HOBt (3.6 equivalents) and DIPCDI (3.3 equivalents) in dimethylformamide (DMF) for 1 h at room temperature. In case of cyclopropylamine peptide substrate, (1.5 equivalents) of the protected unnatural amino acid was used for the coupling. Fmoc deprotection was performed using 20% piperidine in DMF for 30 min. Modified amino acid residues at position 20 of H4 and positions 9 and 4 of H3 coupled with elongated time overnight to ensure efficient coupling. The Fmoc deprotection and the coupling of the residues were monitored using Kaiser test on few resin-beads. Coupling of the amino acids and Fmoc-deprotection were performed by rolling on a rotating-mixer RM-5 (CAT Zipperer, Staufen, Germany). After the final Fmoc removal, peptides were cleaved from the resin using a 2.5% triisopropylsilane (TIS) and 2.5% water in 95% trifluoroacetic acid (TFA). The peptides were precipitated in cold diethyl ether (−20 °C) and purified via preparative HPLC. The yields of SPPS were estimated as isolated yields, in which the molecular weights of individual peptides were calculated as TFA salts at Lys and Arg positions. The peptides were purified by RP-HPLC on a Phenomenex Gemini-NX C18 column and their purities were assessed using analytical HPLC. Bruker instrument in the reflectron positive mode. For regular methyltransferase standard conditions experiment which carried out in 30 µL total volume, the mixture contains peptide (100 µM), SAM (200 µM), SETD8 or SETD7 (2 µM), in assay buffer 50 mM Tris at optimal pH 8.0. In case of G9a and GLP, similar conditions were used, except (500 µM) of SAM was added to the reaction mixture. Samples were incubated in an Eppendorf vial 1.5 mL using thermomixer for 1 h at 37 °C. A 5 µL aliquot of the solution was mixed with 5 µL of MeOH, after which 5 µL of this mixture was mixed with 5 µL of α-cyano-4-hydroxycinamic acid matrix (CHCA, 5 mg/mL in 125:125 µL acetonitrile/water). The spots were placed on a stainless steel MALDI plate (MS 96 target ground steel BC of Bruker, Germany). The mass corresponding to one monomethylation observed as +14 Da, dimethylation observed as +28 Da and trimethylation observed as +42 Da. Data from a set of 100 laser shots (3×) were accumulated to give an acceptable spectrum. The enzymatic activity was determined by taking the peak areas of each methylation state, including all isotopes and adducts, and was annotated using FlexAnalysis software (Bruker Daltonics, Germany). None-enzyme and none-SAM controls experiments were carried out to ensure that the conditions of MS assay did not affect the noticeable methylation states. Methylated peptide substrates were repeated five times and the unmethylated substrates were triplicated. Sequences of the examined peptides are given in (Supplementary Table 1). inhibition studies. A mixture of histone peptide (0-100 µM final conc.) and SETD7, G9a or GLP (100 nM final conc.) was preincubated for 5 minutes at 37 °C in 18 µL of 50 mM glycine pH 8.8 containing 2.5% glycerol as assay buffer. Then 2 µL of a pre-mixture of SAM (20 µM final conc.) and 21-mer H3 histone peptide (residues 1-21, 5 µM final conc.) was added to afford a final assay mixture (20 µL) and the enzymatic reaction was incubated for an additional 30 minutes at 37 °C before quenching with 20 μL of MeOH. The quenched reaction (1 μL) was mixed with a solution of saturated α-cyano-4-hydroxycinnamic acid (5 μL) and spotted on the MALDI plate for crystallisation. The enzymatic activity was determined by taking the peak areas of each methylation state (including all isotopes and adducts) and is expressed relative to a control reaction in the absence of unnatural histone peptides. Each inhibition experiment was carried out in replicate. nMR assays. NMR enzymatic experiments for methyl transferase activities were performed with G9a.</p><p>Incubations by an Eppendorf vials using thermomixer were carried out in 50 mM Tris-d 11 .HCl (pD 8.0) and 37 °C for 1 h. The samples (300 µL) typically contained G9a (8 μM) and SAM (2 mM), and H3K9 peptide (400 μM) or any of its sterically demanding analogs H3K cp 9/H3F 3a 9/H3F 4a 9/H3A p 9/H3Y9 peptide. After 1 h, the sample diluted to 550 μL and measured by 1 H NMR at 298 K. Controls were run in parallel at the same time. NMR spectra were acquired using a Bruker Avance III 500 MHz NMR spectrometer equipped with a Prodigy BB cryoprobe. The probe temperature was at 298 K in all instances. The 1D 1 H spectra were acquired in manual mode, whereas subsequent 2D experiments were acquired in full automation mode. Analysis parameters for 1 H NMR acquisition were: numbers of scans (NS) 256, relaxation delay 4 seconds, and spectral width (SW) 10 ppm. All the 1D experiments were performed with suppression of residual water signal by presaturation during the relaxation delay using presaturation (pulse program zgpr). Analysis parameters for 2D HSQC acquisition were: NS is 32, relaxation delay 1.5 seconds, acquired size 512, spectral width (SW) for 1 H was 11 ppm and 13 C was 160 ppm. When processing HSQC, additional measures such as a t1 noise reduction produced cleaner spectra. Spectral resolution for HSQC was enhanced by apodization. NMR data were processed using MestreNova software (version 10.0.2). All the spectra were phase and baseline corrected.</p><p>QM/MD methods. To understand the experimental observations, the QM/MM free energy (potential of mean force) and MD simulations were undertaken for SETD8 and GLP to calculate the free energy profiles of the methyl transfers from SAM to some of the unnatural amino acid residues. Three-membered and six-membered rings were introduced into lysine sidechain using the CHARMM program 32 . The QM part of the systems included a portion (-CH 2 -CH 2 -S + (Me) -CH 2 -) of SAM and the lysine analog chains, and the rest of the system was described by MM. To separate the QM and MM parts, the link-atom approach 33 was applied; a modified TIP3P water model 34 was used for the solvent. The QM/MM simulations were based on the stochastic boundary molecular dynamics method 35 , which partitions the system into a reaction zone and a reservoir region. The reaction zone was further divided into a reaction region and a buffer region. The radius r for reaction region was 20 Å with the buffer region extended over 20 Å ≤ r ≤ 22 Å. The N ζ atom of the lysine analogs was used the reference center for partitioning the system. The final systems for the QM/MM simulations had around 5300 atoms (including roughly 900-1000 water molecules). For the QM atoms, the DFTB3 method 35 was used. This semi-empirical approach has been used on a number of systems previously with reasonable results obtained 36 . The PARAM27 of all-hydrogen CHARMM potential function 37 was adopted here for the MM atoms.</p><p>The reactant complexes of the methylation were generated based on the crystal structures of the enzyme complexes (SETD8: PDB ID = 2BQZ; GLP: PDB ID = 3HNA); SAM was generated by adding a methyl group to SAH. The methyl lysine was changed to lysine by removing the methyl group manually. The two three-membered rings and one six-membered ring were introduced to the lysine sidechain to generate the three lysine analogs with steric constrains. The stochastic boundary systems were first optimized based on the steepest descent (SD) and adopted-basis Newton-Raphson (ABNR) methods and then gradually heated from 50.0 to 298.15 K in 50 ps. The time step used for integration of the equation of motion was 1-fs, and for every 50 fs the coordinates were saved for analyses. 1.5 ns QM/MM MD simulations were performed for each of the reactant complexes 28,38 .</p><p>To determine the changes of the free energy (potential of mean force) as a function of the reaction coordinate for the methyl transfer in SETD8 and GLP, respectively, the umbrella sampling method 39 along with the Weighted Histogram Analysis Method (WHAM) 40</p>

Scientific Reports - Nature

PPAR\xce\xb1 activation inhibits endothelin-1-induced cardiomyocyte hypertrophy by prevention of NFATc4 binding to GATA-4

Peroxisome proliferator-activated receptor alpha (PPAR\xce\xb1) has been implicated in the pathogenesis of cardiac hypertrophy, although its mechanism of action remains largely unknown. To determine the effect of PPAR\xce\xb1 activation on endothelin-1 (ET-1)-induced cardiomyocyte hypertrophy and explore its molecular mechanisms, we evaluated the interaction of PPAR\xce\xb1 with nuclear factor of activated T-cells c4 (NFATc4) in nuclei of cardiomyocytes from neonatal rats in primary culture. In ET-1-stimulated cardiomyocytes, data from electrophoretic mobility-shift assays (EMSA) and co-immunoprecipitation (co-IP) revealed that fenofibrate (Fen), a PPAR\xce\xb1 activator, in a concentration-dependent manner, enhanced the association of NFATc4 with PPAR\xce\xb1 and decreased its interaction with GATA-4, in promoter complexes involved in activation of the rat brain natriuretic peptide (rBNP) gene. Effects of PPAR\xce\xb1 overexpression were similar to those of its activation by Fen. PPAR\xce\xb1 depletion by small interfering RNA abolished inhibitory effects of Fen on NFATc4 binding to GATA-4 and the rBNP DNA. Quantitative RT-PCR and confocal microscopy confirmed inhibitory effects of PPAR\xce\xb1 activation on elevation of rBNP mRNA levels and ET-1-induced cardiomyocyte hypertrophy. Our results suggest that activated PPAR\xce\xb1 can compete with GATA-4 binding to NFATc4, thereby decreasing transactivation of NFATc4, and interfering with ET-1 induced cardiomyocyte hypertrophy.

ppar\xce\xb1_activation_inhibits_endothelin-1-induced_cardiomyocyte_hypertrophy_by_prevention_of_nfa

Introduction<!>Chemicals and antibodies<!>Primary culture and studies of rat cardiomyocytes<!>Immunoprecipitation and Western blotting<!>Electrophoretic mobility shift assay<!>RNA isolation and quantitative RT-PCR<!>Microscopic evaluation<!>Statistical analysis<!>Activated PPAR\xce\xb1 co-IP of NFATc4 from nuclei of cardiomyocytes<!>Increased NFATc4 co-IP with PPAR\xce\xb1 accompanied by decreased NFATc4\xe2\x80\x93GATA-4 interaction in cardiomyocyte nuclei<!>Effects of PPAR\xce\xb1 activation or overexpression on NFATc4 binding to rBNP promoter in cardiomyocytes stimulated by ET-1<!>Effects of Fen concentration on interaction of NFATc4 with GATA-4 and rBNP promoter<!>Effects of activation or overexpression of PPAR\xce\xb1 on ET-1-induced elevation of BNP mRNA levels and cardiomyocyte surface area<!>Effects of PPAR\xce\xb1 depletion on Fen inhibition of ET-1-induced BNP mRNA elevation and cardiomyocyte surface area<!>Discussion

<p>Cardiac hypertrophy is thought to be an adaptive response of the heart to preserve pump function under adverse conditions, and prolonged hypertrophy is a major predictor of arrhythmias and sudden death or heart failure [1–4]. Evidence is increasing that endothelin-1 (ET-1)1, a 21-amino acid peptide, contributes to the adaptive process by inducing transcription of several genes, including atrial natriuretic factor (ANF), brain natriuretic peptide (BNP), and cardiac α- and β-myosin heavy chain [5–10]. Several nuclear factor of activated T-cells (NFAT)-related signaling systems, e.g., calcineurin/NFAT [11], PI3K/Akt/GSK3, NFATc4 [12], are believed to participate in ET-1-induced cardiomyocyte hypertrophy. The calcineurin/NFATc4 pathway has been of special interest for its role in cardiac hypertrophy [13], and reversal of ET-1-induced cardiac hypertrophy by expression of a dominant-negative NFATc4 protein supported an important role of NFATc4 [11].</p><p>Peroxisome proliferator-activated receptors (PPARs) are family of nuclear receptor transcription factors that bind specific DNA sequences known as PPAR response elements (PPREs) [14–16]. Among the three PPAR isoforms [17,18], PPARα and PPARγ share 60–80% identity of amino acid sequences in their ligand- and DNA-binding domains [19], and both are present in cardiomyocytes. Evidence suggests that PPARα activation inhibited cardiomyocyte hypertrophy via different pathways; a PPARα activator, fenofibrate (Fen) was reported to suppress ET-1-induced cardiac hypertrophy by down-regulation of AP-1-binding capability and inhibition of p38 signaling [20,21]. Atorvastatin inhibited cardiac hypertrophy through inhibition of negative cross-talk between PPARα and nuclear factor-kappaB (NF-κB) [22], but the molecular mechanism of inhibition of cardiomyocyte hypertrophy by activated PPARα is not clear. In T lymphocytes, PPARγ associated with NFAT to form a complex that inhibited transcription of IL-2 and IL-4 [23,24]. In cardiomyocytes, association of PPARγ with NFATc4 partially inhibited hypertrophy induced by ET-1 [25].</p><p>Based on the interaction between PPARγ and NFATc4 in cardiomyocytes, we hypothesized that such a link may also exist between PPARα and NFATc4. To clarify this hypothesis, we employed co-immunoprecipitation (co-IP) and electrophoretic mobility-shift assays (EMSA) to investigate the association of PPARα and NFATc4 in cardiomyocyte nuclei, and in particular, its effects on NFATc4 binding to the rat BNP (rBNP) promoter. We also evaluated the effect of this interaction on the association of NFATc4 with its cofactor GATA-4, and whether it will interfere with ET-1-induced cardiomyocyte hypertrophy.</p><!><p>Fenofibrate, endothelin-1, DMSO, and 5-bromodeoxyuridine were purchased from Sigma–Aldrich, mouse monoclonal antibodies against PPARα (ab2779) from Abcam, rabbit polyclonal antibodies against NFATc4 (sc-13036) or GATA-4 (sc-9053), and normal (rabbit and mouse) IgG from Santa Cruz, mouse monoclonal antibodies against α-tubulin from Sigma–Aldrich, and HRP-conjugated secondary antibodies (goat anti-rabbit and goat anti-mouse) from Promega.</p><!><p>Primary cultures of neonatal rat cardiomyocytes were obtained from the hearts of 1- to 3-day-old Sprague-Dawley (SD) rats using the optimized repetitive trypsinization method established in our laboratory [26]. Briefly, after decontaminated with 75% ethanol, the hearts were removed from rats to a Luminer flow hood immediately. The ventricles were excised and chopped into small pieces, then digested with repetitive trypsinization (0.08% trypsin solution). After differential adhesion, cardiomyocytes were seeded in DMEM supplied with 10% (vol/vol) fetal bovine serum and 0.1 mM 5-bromodeoxyuridine. All experimental procedures conformed to the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health (NIH Publication No. 85-23, revised 1996) and we confirmed that Institutional Ethics Review Board of Sun Yat-sen University approved this study (Approved No. 20080401003). Cardiomyocytes in 6-well plates (2 × 105 cells/ cm2) were transfected with 4 μg PPARα-EGFP plasmid (kindly provided by Dr. Ruifang Li-Department of Pharmacology, Henan University of Science and Technology, PR China) using 10 μl Lipofectamine 2000 (Invitrogen), according to the manufacturer's instructions. Three 25-nucleotide duplex siRNAs for PPARα (siR-NA169, siRNA168, siRNA167) and non-target siRNA were purchased from Invitrogen. Rat cardiomyocytes were transfected with 100 pmol PPARα-specific or non-target siRNA using 5 μl Lipofectamine 2000 (Invitrogen) and harvested at indicated time thereafter.</p><!><p>Nuclear extracts were prepared using the CelLytic™ NuCLEAR™ Extraction Kit (Sigma–Aldrich), according to the manufacturer's instructions. Protein concentrations were measured using a BCA Protein Assay Kit (Pierce). Nuclear proteins (200 μg) were immunoprecipitated with anti-PPARα or anti-GATA-4 antibodies or normal (rabbit and mouse) IgG (control). Immunoprecipitated proteins bound to protein G-agarose beads (Pierce) were separated by SDS–PAGE in 8% gels and transferred to PVDF membranes (Millipore), which were blocked with 5% nonfat milk (Bio-Rad), reacted with antibodies against NFATc4, and then with appropriate horse-radish peroxidase-conjugated secondary antibodies. Blots were developed using enhanced chemiluminescence (Pierce) and exposed to X-ray films.</p><!><p>Assays were conducted according to instructions of "The LightShift™ Chemiluminescent EMSA kit" (Pierce). Briefly, nuclear extracts were prepared using the Nuclear Extract Kit (Active Motif), according to the manufacturer's instructions. Sequence of oligonucleotide used for EMSA was 5′-AGGGTGGGAAAACTGGGGGTTC-3′ (3′-biotinylated by Shanghai Sangon) from the region (−330/−351) of rat BNP promoter containing a putative binding site (underlined) for nuclear factor NFATc4 (GGAAAAT) (11). Mutant sequence (without biotinylation) was 5′-AGGGTGGTAGCACTGGGG GTTC-3′. Each 20-μl binding reaction was incubated for 20 min at room temperature with 1 μg of poly (dI.dC), 0.05% Nonidet P-40, 5 mM MgCl2, 2.5% glycerol, 1 pmol of biotin-end-labeled probe DNA, and 4 μg nuclear protein (determined by Bradford assay). For supershift assays, NFATc4 antibodies (2 μg) were incubated (4 °C, 1 h) in binding mixture (20 μl) before addition of the biotinylated probe. Bound complexes and free probe were separated by electrophoresis in6%non-denaturingpolyacrylamidegel at100 Vfor1 h, transferred to positively charged nylon membrane (Biodyne PLUS, supplied by PALL), immediately cross-linked to membrane with UV (254 nm), and detected using Stabilized Streptavidin–Horseradish Peroxidase Conjugate (Pierce), according to the manufacturer's instructions.</p><!><p>Total cell RNA, isolated using TRIzol reagent (Invitrogen), and reverse transcribed, was the template for quantitative PCR using an iCycler iQ system (Bio-Rad) with sequence-specific primer pairs and intercalated SYBR Green (Takara) as fluorescent probe. Results were evaluated using iCycler iQ real-time detection system software (Bio-Rad). Primers were: BNP, 5′-TTTGGGCAGAAGATAGACCG-3′ (forward) and 5′-AGAAGAGCCGCAGGCAGAG-3′ (reverse); GAPDH, 5′-AGGAGTAAGAAACCCTGGAC-3′ (forward) and 5′-CTGGGATGGA ATTGTGAG-3′ (reverse).</p><!><p>Rhodamine phalloidin (Invitrogen), prepared in methanol according to the manufacturer's specifications and stored at −20 °C, was used to visualize actin fibers by fluorescence microscopy as previously described [27,28]. Cardiomyocytes grown on coverslips were fixed with 4% paraformaldehyde in PBS (15 min, room temperature) and incubated with 0.1% rhodamine–phalloidin plus 0.1% saponin in PBS for 1 h at room temperature. Cells were washed with PBS, mounted in "Prolong Gold Anti-fade Reagent" with DAPI (Invitrogen), and inspected using a confocal microscope (Zeiss 710). The cell surface area of at least 60 cardiomyocytes from 10 randomly selected fields in three independent experiments was measured by a Leica QWin-Plus software (Leica Microsystem, Germany).</p><!><p>Data are presented as means ± S.E.M. Multiple group comparisons test was performed with one-way analysis of variance (ANOVA) followed by a Bonferroni post-hoc test with Graphpad Prism Software (Version 5.03). Criterion for statistical significance was P < 0.05.</p><!><p>To explore a potential interaction of PPARα with NFATc4 in cardiomyocyte nuclei, proteins immunoprecipitated with anti-PPARα antibodies from nuclear extracts were analyzed by immunoblotting with antibodies against NFATc4 and PPARα, each of which reacted with a single protein band consistent with the molecular size of PPARα (50 kDa) or dephosphorylated NFATc4 (140 kDa). Neither protein was immunoprecipitated with non-immune IgG (Fig. 1A). Incubation of cells for 1 h with 10 μM Fen significantly enhanced IP of NFATc4 with PPARα. The effect of Fen was more significant after incubation of cells for 3 h with 100 nM ET-1, which itself did not alter co-IP of NFATc4 with PPARα (Fig. 1B). Results were similar in cells overexpressing PPARα-EGFP (80 kDa) for 24 h (Fig. 1C).</p><!><p>Consistent with the report of Kakita et al. [29], our data showed that co-IP of NFATc4 with antibodies against GATA-4 from cardiomyocyte nuclei was significantly (P < 0.01) enhanced by incubation cells with 100 nM ET-1, reaching a peak between 1 and 6 h (Fig. 2A). Activation of PPARα by treatment of cardiomyocytes with 10 μM Fen for 1 h, or overexpression of PPARα for 24 h decreased the enhanced interaction of NFATc4 and GATA-4 induced by ET-1. Without ET-1 stimulation, however, neither activation nor overexpression of PPARα affected the association of NFATc4 with GATA-4 (Fig. 2B and C).</p><!><p>Binding of NFATc4 to the target BNP DNA sequence regulates BNP transcription [13]. To determine whether the PPARα/NFATc4 interaction affected this function, we used EMSA to assess DNA binding by NFATc4. In Fig. 3A, binding of NFATc4 to the −330/−351bp region of rat BNP DNA was increased after 100 nM ET-1 treatments, reaching a peak between 1 and 6 h. Without nuclear extract, no retarded band was seen (Fig. 3A, lane1). Incubation of cells 1 h with Fen or overexpression of PPARα (24 h) alone had relatively little effect on NFATc4 binding to DNA. In cells treated with ET-1, however, either Fen or overexpression of PPARα clearly decreased DNA-binding by NFATc4 (Fig. 3B). In competition assays with a 400-fold molar excess of unlabeled (cold) normal (N) and mutant (M) probes, the former completely abolished the shifted band, whereas the latter was without effect (Fig. 3C). The shifted band was markedly diminished by anti-NFATc4 antibodies, consistent with the specificity of this DNA binding (Fig. 3C).</p><!><p>As shown in Fig. 4, Fen, in a concentration-dependent manner, enhanced co-IP of NFATc4 with antibodies against PPARα. Inhibition by Fen of co-IP of NFATc4 with GATA-4 and DNA binding to the rBNP promoter, was similarly concentration-dependent, suggesting that in ET-1-induced cardiomyocyte hypertrophy, PPARα and GATA-4 competition for interaction with NFATc4 might result in Fen inhibition of NFATc4 binding to DNA.</p><!><p>To evaluate effects of PPARα and NFATc4 interaction on BNP transcription, BNP mRNA was quantified by real-time RT-PCR, showing a significant increase after incubation of cardiomyocytes with 100 nM ET-1, peaking between 12 and 36 h (Fig. 5A). After treatment with Fen (1 h) or overexpression of PPARα (24 h), elevation in BNP mRNA levels induced by ET-1 was significantly suppressed (Fig. 5B), and the increase in cardiomyocyte size seen after 48 h of ET-1 exposure was also much less after activation or overexpression of PPARα. (Fig. 5C and D)</p><!><p>To perturb the PPARα interaction with NFATc4, three different duplex siRNAs (167–169) were used to deplete PPARα. Cell lysates were prepared 72 h after siRNA transfection for Western blot analyses, which suggested that siRNA168 was the most effective, with no significant effect of the non-target siRNA (Fig. 6A). We used siRNA168, therefore, in experiments like that shown in Fig. 6, where PPARα depletion blocked the inhibitory effects of Fen on interaction of NFATc4 with GATA-4 (Fig. 6B) and rBNP promoter (Fig. 6C). The decrease in levels of BNP mRNA (Fig. 6D) and cell size caused by Fen in ET-1-stimulated cardiomyocytes were attenuated (Fig. 6E and F) by siRNA-induced depletion of PPARα. These results suggested that interaction of activated PPARα and NFATc4 could diminish binding of NFATc4 to DNA by blocking its association with GATA-4 in ET-1-stimulated cardiomyocytes.</p><!><p>PPARs are known widely for their roles in lipid metabolism and inflammation. Agonist ligands for PPARα and PPARγ have been used clinically for the management of dyslipidemia and control of glycemia in patients with type 2 diabetes [30,31]. More recently, attention to pleiotropic effects of these agents has grown with evidence that PPARγ is a negative regulator of cardiomyocyte hypertrophy through its interaction with NFATc4, an important transcription factor that is both necessary and sufficient for development of cardiomyocyte hypertrophy [13,25,32–34]. Proof of PPARα participation in the pathophysiology of hypertensive heart diseases [35–38], suggested that PPARα ligands could be useful beyond their hypolipidaemic effects, in the management of disorders associated with hypertrophy and myocardial remodeling.</p><p>Multiple signaling systems function as downstream effectors of ET-1 [39–42], including the calcineurin/NFAT pathway, which is important for cardiomyocyte hypertrophy [13]. In a current model for the calcineurin/NFATc4 pathway in cardiomyocyte hypertrophy, NFATc4 is usually hyperphosphorylated and sequestered in the cytoplasm. Actions of ET-1, angiotenin II (AngII), and possibly other hypertrophic stimuli lead to elevation of intracellular Ca2+ and activation of cytoplasmic calcineurin. Activated calcineurin dephosphorylates NFATc4, resulting in its translocation to the nucleus, where it interacts with molecules such as GATA-4 to bind to a target sequence in the promoter of hypertrophic genes and trigger gene transcription [13,43].</p><p>Here, we identified by co-IP a interaction of PPARα and NFATc4 in nuclei of cardiomyocytes. This interaction was enhanced by Fen, an activator of PPARα, or by overexpression of PPARα-EGFP. Association of NFATc4 with PPARα was significantly increased by Fen treatment of ET-1-stimulated cardiomyocytes, suggesting a novel mechanism of action of PPARα in cardiomyocyte hypertrophy induced by ET-1 through the NFATc4 pathway. To understand better how PPARα regulated NFATc4 function, we investigated two important actions of NFATc4 on binding to its target gene and its interaction with cofactors.</p><p>It had been reported that the binding of NF-AT3 (analogous to NFATc4) at a position −927 nucleotides upstream of the human BNP gene, which is a marker of cardiac hypertrophy and heart failure, was involved in the activation of the promoter [13,44]. Promoter analysis based on transcription factor-binding sites, revealed a putative binding site for NFATc4 in region −330 to −351bp of the rat BNP promoter; EMSA confirmed this. Although a supershifted band was not observed with anti-NFATc4 antibodies, the shifted band was markedly diminished by the antibodies. One possible reason for the lack of a supershifted band was shielding the DNA binding site after NFATc4 binding with the antibody. These data are consistent with the findings of Zhu et al. [45]. We showed that binding of NFATc4 to this site was increased in a time-dependent manner by ET-1 treatment. The enhanced binding was clearly decreased by activation or overexpression of PPARα, suggesting that interaction of NFATc4 with PPARα interfered with its binding to the BNP promoter.</p><p>GATA-4, a zinc-finger transcription factor was an important role in cardiac hypertrophy [46–49]. GATA-4 also acted synergistically with NF-AT3 to activate the BNP promoter in cardio myocytes [13]. Consistent with the report of Kakita et al. that ET-1 translocated NFATc into nuclei and enhanced its interaction with GATA-4 [24], the association of NFATc4 and GATA-4 was significantly increased in nuclei of cardiomyocytes after ET-1 stimulation. The interaction between NFATc4 and GATA-4 was markedly decreased by PPARα activation or overexpression, indicating the interaction of NFATc4 with PPARα decreased its association with GATA-4. Our data also showed that Fen or overexpression of PPARα significantly attenuated increases in BNP mRNA and cardiomyocyte size induced by ET-1, consistent with a significant contribution of PPARα to ET-1-induced BNP transcription and cardiomyocyte hypertrophy.</p><p>In addition, using siRNA to deplete cells of PPARα (without affecting PPARβ/δ or PPARγ), we showed that PPARα siRNA failed to block the enhanced interaction of NFATc4 with BNP promoter or GATA-4, resulting from Fen and ET-1 co-stimulation. Quantitative RT-PCR and confocal microscopy similarly confirmed the effects of PPARα siRNA on elevation of BNP mRNA content and cardiomyocyte hypertrophy.</p><p>Although the mechanism by which NFATc4 binding to PPARα decreased its binding to GATA-4 remains to be determined, it is possible that the two molecules compete for the same binding site. Molkentin et al. [13] reported that NF-AT3 interacted with GATA-4 through its Rel-homology domain, which also mediated DNA binding. In our study, Fen activation of PPARα apparently enhanced its interaction with NFATc4 while, in a concentration-dependent manner, decreasing NFATc4 interactions with GATA-4 and the BNP promoter (Fig. 4), consistent with the notion that PPARα and GATA-4 competed for binding to the Rel-homology domain of NFATc4.</p><p>Overall, our data fit a model (Fig. 7) in which PPARα can participate in transcription complexes with NFATc4 that interfere with an NFATc4–GATA-4 interaction in cardiomyocytes, thereby decreasing its transactivation potential and preventing induction of cardiomyocyte hypertrophy by ET-1. These findings provide novel mechanistic insight into a role for PPARα in cardiac hypertrophy, and suggest that interference with interactions of nuclear transcription factors could be a useful therapeutic approach to prevent cardiac hypertrophy.</p>

PubMed Author Manuscript

Vibrational Probes of Molybdenum Cofactor\xe2\x80\x93Protein Interactions in Xanthine Dehydrogenase

The pyranopterin dithiolene (PDT) ligand is an integral component of the molybdenum cofactor (Moco) found in all molybdoenzymes with the sole exception of nitrogenase. However, the roles of the PDT in catalysis are still unknown. The PDT is believed to be bound to the proteins by an extensive hydrogen bonding network, and it has been suggested that these interactions may function to fine-tune Moco for electron and atom transfer reactivity in catalysis. Here, we use resonance Raman (rR) spectroscopy to probe Moco-protein interactions using heavy atom congeners of lumazine; molecules that bind tightly to both wt-XDH and its Q102G and Q197A variants following enzymatic hydroxylation to the corresponding violapterin product molecules. The resulting enzyme-product complexes possess intense NIR absorption, allowing high quality rR spectra to be collected on wt-XDH and the Q102G and Q197A variants. Small negative frequency shifts relative to wt-XDH are observed for low-frequency Moco vibrational. These results are interpreted in the context of weak hydrogen bonding and/or electrostatic interactions between Q102 and the \xe2\x88\x92NH2 terminus of the PDT, and between Q197 and the terminal oxo of the Mo\xe2\x89\xa1O group. The Q102A, Q102G, and Q197A, Q197E variants do not appreciably affect the kinetic parameters kred, and kred/KD, indicating a primary role for these glutamine residues is to stabilize and coordinate Moco in the active site of XO family enzymes, but not directly affect catalytic throughput. Raman frequency shifts between wt XDH and its Q102A variant suggest the changes in the electron density at the Mo ion that accompany Mo oxidation during electron transfer regeneration of the catalytically competent active site are manifest in distortions at the distant PDT amino terminus. This implies a primary role for the PDT as a conduit for facilitating enzymatic electron transfer reactivity in xanthine oxidase family enzymes.

vibrational_probes_of_molybdenum_cofactor\xe2\x80\x93protein_interactions_in_xanthine_dehydrogenase

INTRODUCTION<!>Enzyme Preparation and Characterization.<!>Preparation of the XDH Enzyme-Product Complexes.<!>Electronic Absorption Spectroscopy.<!>Resonance Raman Spectroscopy.<!>Computational Details.<!>Electronic Absorption Spectroscopy.<!>Resonance Raman Spectroscopy.<!>Rapid reaction kinetics of XDH variants.<!>CONCLUSIONS

<p>R. capsulatus xanthine dehydrogenase (RcXDH) is a pyranopterin molybdenum enzyme1–3 that possesses broad substrate specificity1, 3–4 and a high degree of sequence homology with the mammalian molybdenum hydroxylase, xanthine oxidoreductase (XOR). XDH and XOR belong to the xanthine oxidase (XO) family of pyranopterin molybdenum enzymes, possess nearly identical coordination geometries about the Mo center,5–6 and catalyze the formal oxidative hydroxylation of a variety of purine and aldehyde substrates.1, 3–4, 7–8 XDH, like all molybdenum enzymes except nitrogenase, possesses an MoOn(PDT) (PDT = pyranopterin dithiolene ligand) molybdenum cofactor (Moco) that is comprised of an oxo-molybdenum species coordinated by the ene-1,2-dithiolate side chain of the pyranopterin. The global importance of Moco and the PDT resides in that fact that the Moco biosynthesis pathway traces back to the last universal common ancestor (LUCA) of cells, with obvious implications for the origin of life on Earth.9 The PDT is also referred to as molybdopterin (MPT) in the literature.10 Recent bioinformatics and computational data have been used to show that the pyranopterin in XO family enzymes possesses a larger out-of-plane distortion when compared to pyranopterins found in enzymes that belong to the sulfite oxidase (SO) family of pyranopterin Mo enzymes.11 This study has been used to suggest that the pyranopterin in XDH is in the fully reduced tetrahydro oxidation state (Figure 1).11 Interestingly, the roles of the PDT component of Moco in enzymatic catalysis are still unknown, but it has been suggested to (1) function as an anchor for the molybdenum ion, (2) serve as a conduit for electron transfer between the Mo ion and other redox partners, (3) contribute two redox equivalents for substrate transformations,12 and (4) modulate the Mo reduction potential.1, 10, 13–16</p><p>The first coordination sphere geometry about the oxidized Mo(VI) ion in XDH and XOR is roughly square pyramidal (Figure 1A), with the Mo ion being ligated by the dithiolene side chain of the PDT, an axial oxo ligand, and equatorial sulfido and hydroxide ligands. The coordination sphere is unusual for a metalloprotein in that the Mo ion is not ligated to the protein by any amino acid residues. As a result, hydrogen bonding interactions, including those involving the PDT, likely contribute to stabilizing and coordinating Moco in the active site of XO family enzymes.17 X-ray crystallographic studies suggest that Moco is tightly bound to the protein via fifteen different hydrogen bonding interactions that are highly conserved.5–6, 18–19 These hydrogen bonding interactions between Moco and various protein residues may play a role in fine-tuning PDT and cofactor contributions to enzymatic catalysis.1</p><p>Previously, we used 4-thiolumazine and 2,4-dithiolumazine (Figure 1B) as reducing substrates to produce strong near-infrared (NIR) absorbing Mo(IV)-product complexes with both mammalian xanthine oxidase and RcXDH.16, 20 These studies were important since they showed that high quality resonance Raman (rR) spectra could be obtained in order to directly probe Moco coordination in XO and XDH. Since the extremely red-shifted NIR band does not appreciably overlap with the intrinsic absorption features of the reduced enzyme, this results in rR spectra that are devoid of contributions from the highly absorbing 2Fe2S clusters and FAD, which are the additional redox chromophores found in XO family enzymes. In this manuscript, we use a combination of enzyme kinetics, electronic absorption and resonance Raman (rR) spectroscopies, and vibrational frequency calculations to probe the effects of potential hydrogen bonding or electrostatic interactions between Q197 and the Mo≡O group of Moco, and between Q102 and the −NH2 terminus of the pyranopterin in RcXDH.</p><p>R. capsulatus XDH is comprised of two subunits, XDHA and XDHB. X-ray crystallographic studies indicate that Q102 is potentially hydrogen bonded (3.09 Å) to the −NH2 terminus of the PDT (Figure 1A),5–6, 18–19 and the putative hydrogen bond between the pyranopterin of Moco and Q102 is the only one that derives from the XDHA subunit. Q102 lies in proximity to one (Fe/S I) of the two 2Fe2S clusters in XDH and is specifically oriented for direct contact with the pterin ring of the PDT. Thus, a hydrogen bonding interaction between Q102 and the PDT may mediate electronic communication between the pyranopterin and Fe/S I as part of an electron transfer chain21 that sequentially removes reducing equivalents from the enzyme. Q102 may also function as an anchor to connect the PDT to the protein. Q197 is poised for a hydrogen bonding interaction (2.78 Å) to the terminal oxo of the Moco Mo≡O moiety and may contribute the stabilizing the coordination of Moco in the protein. Additionally, Q197 may also modulate the Mo redox potential by controlling the effective nuclear charge of the Mo ion during catalysis and the pKa of the equatorial sulfido ligand. Both Q102 and Q197 are highly conserved in all XOR and even the related aldehyde oxidoreductase2–3 (AOX) enzymes, and a primary impetus for this work is to obtain a better understand of the function of the pyranopterin and Moco in XO/XDH and related enzymes through spectral and kinetic probing of wt enzyme and specific Q102 and Q197 variants.</p><!><p>Wild-type R. capsulatus XDH was expressed in E. coli6 and RcXDH variants were produced as reported previously.19 The enzyme activity of the reductive half reaction of XDH was performed using a stopped-flow instrument (Applied Photophysics SX20, United Kingdom). Samples were prepared anaerobically in air-tight syringes using 50 mM Tris, 1 mM EDTA buffer (pH 8,0). Measurements where performed at a constant temperature of 20°C. 10 μM XDH was mixed with different xanthine concentrations (12.5; 25; 50; 125; 250; 500 μM) in the stopped-flow system. The reduction of the FAD was followed with a diode array detector at 465 nm. Data were fitted to a double exponential decay in a time range of 1 s to obtain the observed rate constant. Metal content analysis was performed using an Optima 2100DV inductively coupled plasma-optical emission (ICP-OES) spectrometer (Perkin-Elmer, Fremont, CA). Protein samples were incubated overnight in a 1:1 mixture with 65% nitric acid (Suprapur, Merck, Darmstadt, Germany) at 100 °C. Protein samples were diluted 10-fold with ultrapure water (Millipore) prior to ICP-OES analysis. The multielement standard solution XVI (Merck) was used as a reference. pH assays were conducted at 25°C in 1 ml cuvettes in 100 mM CAPS, 100 mM KCl (pH 9–10); 50 mM Tris, 100 mM NaCl (pH 7–9) and 100 mM MES, 100 mM KCl (pH 5.5–6.5) using 500 μM NAD and varying concentrations of xanthine (25, 50, 75, 100, 200, 500 μM). The reaction was followed for 1 min at 340 nm with a Shimadzu UV-2401PC UV-VIS recording spectrophotometer. Circular dichroism spectroscopy was used to construct thermal denaturation curves of wt XDH and Q102 and Q197 variants at 218 nm and at temperatures ranging from 25°C to 80°C. Signals were recorded using a 0.1 cm cuvette at 1°C/min and a data integration time of 8 sec using a Jasco (J-815) CD-Spectropolarimeter. Protein concentration was adjusted to 1 μM (ε465 = 31600 M−1cm−1).</p><!><p>The reducing substrates 4-thiolumazine20, 22–24 and 2,4-dithiolumazine20 were synthesized as described previously. The reduced XDHred-4-thioviolapterin product complex was prepared by addition of the reducing substrate 4-thiolumazine (8.3 mM, 15 μL) to oxidized RcXDH (143 μM, 60 μL) in BICINE buffer (50mM, pH=8.3, 120 μL). This reaction mixture was subsequently incubated for 5 minutes at room temperature under aerobic conditions to ensure complete substrate turnover, and then made anaerobic by bubbling with a stream of nitrogen gas for 15 minutes. The anaerobic reaction mixture was then treated with 15 μL of an anaerobic 0.4 M sodium dithionite solution to produce the reduced Mo(IV)-P species. The Mo(IV)-P species for the enzyme variants were produced in the same manner, with the initial concentrations of XDH Q197A as 185 μM and XDH Q102G as 170 μM. The production of reduced wt XDHred-2,4-thioviolapterin product complex complex with 2,4-thiolumazine was performed in a similar manner, as were the reduced enzyme-product complexes with the Q197A and Q102G variants. Spectrophotometric measurements were used to confirm the formation of XDHred-4-thioviolapterin (wtred-4-TV), Q197Ared-4-thioviolapterin (Q197Ared-4-TV), Q102Gred-4-thioviolapterin (Q102Gred-4-TV), XDHred-2,4-thioviolapterin (wtred-2,4-TV), Q197Ared-2,4-thioviolapterin (Q197Ared-2,4-TV) and Q102Gred-2,4-thioviolapterin (Q102Gred-2,4-TV) through the appearance of the characteristic metal-to-ligand charge transfer (MLCT) band in the near-infrared (NIR) region of the spectrum (720–740 nm).</p><!><p>Electronic absorption spectra were collected on a double-beam Hitachi U-4100 UV-vis-NIR spectrophotometer (Hitachi High-Technology Corporation) capable of scanning a wavelength region between 185 and 3200 nm. The samples were measured in a 1 cm path length, black-masked, quartz cuvette (Starna Cells, Inc.) equipped with a Teflon stopper. The instrument was calibrated with reference to the instrument's 656.10 nm deuterium line.</p><!><p>Room temperature solution resonance Raman spectra were collected on a commercial DXR Smart Raman Instrument (Thermo Fisher Scientific Inc.). The aqueous buffered samples were sealed in 1.5–1.8 mm diameter capillary tubes and mounted onto a capillary tube holder in the 180° back scattering accessory chamber. A 780 nm diode laser was used as the excitation source and the excitation power was 140 mW. A buffer background and an external standard sample (Na2SO4) were collected before the enzyme data collection. Instrument spectral precision is listed at ±0.25cm−1. Raman shifts were calibrated externally against the standard Na2SO4 peak at 992 cm−1, and internally against the high frequency 1293 cm−1 4-TV and 1296 cm−1 2,4-TV vibrations of the bound product molecules. A cubic spline function was fit to the 1293 cm−1 4-TV and 1296 cm−1 2,4-TV vibrational bands of the product molecules, respectively, to determine peak maxima. The Raman shift calibrated against these high frequency vibrations results in an estimated error of ~ ±0.3 cm−1 across the 4-TV data sets and ~ ±0.2 cm−1 across the 4-TV data sets. Subtraction of the buffer background was performed to yield the final resonance Raman spectrum.</p><!><p>Spin-restricted gas phase geometry optimizations, vibrational frequency calculations, and TDDFT excited state calculations for the XDHred-product complexes were performed at the density functional theory (DFT) level of theory using the Gaussian 09W suite.25 All calculations used the B3LYP hybrid exchange-correlation functional. A 6–31G* basis set was used for all light atoms, and the LANL2DZ basis set, which includes an effective core potential, was used for Mo. Electron density difference maps (EDDMs) were generated using GaussSum (version 2.1.6).26–27 Computed vibrational modes were plotted using ChemCraft (version 1.7).28 CASSCF calculations, employing an 8-electron, 8-orbital active space, were performed using the ORCA software suite (version 3.0.3).29–30 A B3LYP hybrid functional was used in conjunction with the def2-TZVPP basis set for Mo and S atoms, and def2-SVP for all light atoms. The resulting molecular orbital depictions were rendered in ChemCraft.</p><!><p>Room temperature electronic absorption spectra of reduced wt, Q197A, and Q102G RcXDH Mo-product (Mo(IV)-P) complexes with 4-TV are shown in Figure 2. The corresponding electronic absorption spectra for the Mo(IV)-P complexes with 2,4-TV are virtually identical and are given in Figure S1. We note that the absorption energy and band shape of the Mo(IV)→product MLCT transition show that the Mo(IV)-P CT complexes that are formed with 4-TV and 2,4-TV are virtually unaffected by the potentially H-bonding variants Q197A and Q102G (Figure 1). This provides evidence that Q197A and Q102G do not adversely affect product binding; an expected result considering that both Q197 and Q102 are remote from the substrate binding pocket.</p><p>CASSCF calculations have been used to probe the nature of the near-infrared (NIR) charge transfer transition observed in these Mo(IV)-P CT complexes. The CASSCF results support an MLCT assignment for the lowest energy transition in the XDHred-product complexes Mo(IV)-4-TV and Mo(IV)-2,4-TV, with a Mo(xy) → product(π*) one-electron promotion being responsible for generating the MLCT excited state (Figure 2, bottom). Transition energies have also been computed for the MLCT state in Mo(IV)-4-TV (Ecalc: 12,800 cm−1; Eexp: 13,600 cm−1) and Mo(IV)-2,4-TV (Ecalc: 12,700 cm−1; Eexp: 13,100 cm−1), providing additional support for the assignment of this band as an Mo(xy) → product(π*) MLCT transition. The orbital nature of the MLCT state relative to the low-spin d2 Mo(IV) ground state configuration is important, since the MLCT state possesses hole character on the Mo ion. As such, the MLCT state closely mimics the Mo(IV) → Mo(V) electron transfer process that occurs in the oxidative, electron transfer half reactions of XO family enzymes to ultimately regenerate the catalytically competent oxidized Mo(VI) state (Figure 1A). Importantly, the only appreciable PDT contributions to the Mo(xy) donor orbital (Figure 2, bottom) are localized on the ene-1,2-dithiolate sulfur atoms. This bonding interaction has been described previously in the small molecule analog complex Tp*MoO(bdt) (Tp* = hydrotris(3,5-dimethylpyrazol-1-yl)borate; bdt = benzene-1,2-dithiolate).31–32 Removal of an electron from the donor orbital is anticipated to result in molecular distortions within the S-Mo-S dithiolene fragment, leading to resonance Raman enhancement of low-frequency Mo-dithiolene core vibrations31–32 that may be kinematically coupled to other low-frequency Moco modes. In this way, resonance Raman spectroscopy of wt XDH and its Q197A, and Q102G variants provides a means of making detailed low-frequency Moco vibrational assignments and sensitively probing specific Moco - protein interactions.</p><!><p>Low frequency (200 – 400 cm−1) vibrational Raman spectra for reduced Mo(IV)-4-TV and Mo(IV)-2,4-TV forms of wt, Q197A, and Q102G Rc XDH were collected on resonance with the NIR MLCT band and are presented in Figure 3. These data are also summarized in Table 1. The relative intensities and frequencies of vibrational Bands A-D in enzyme-product complexes of wt, Q102G, and Q197A XD are observed to be very similar, and. this indicates that the respective potential energy distributions for these normal modes are essentially identical. Using substrates that can be converted to Mo(IV)-P complexes with NIR absorbing MLCT transition is important, since it dramatically reduces the spectral overlap with the strongly absorbing 2Fe2S centers and FADH, which form part of the electron transfer chain in all XO family enzymes, including XDH. We note that XDHox, XDHred, the 4-thiolumazine and 2,4-dithiolumazine substrates, and the 4-TV and 2,4-TV products do not produce resonantly enhanced Raman vibrations with laser excitation at 780 nm (12,821 cm−1). Thus, the rR data presented in Figure 3 derive solely from the reduced Mo-P complex. Since the low frequency rR spectra of Mo(IV)-4-TV and Mo(IV)-2,4-TV in Figure 3 are very similar, this further indicates that (1) no gross changes have occurred in the pyranopterin or product binding sites as a function of these specific mutations, (2) these modes do not have dominant contributions from the Mo bound product, (3) they represent modes primarily associated with Moco, and (4) the observed vibrational frequency shifts are observed to be small.20</p><p>Low frequency resonance Raman spectra of small molecule analogs for the active sites of pyranopterin Mo enzymes are typically quite simple and display two vibrations. These have been assigned as arising from symmetric S-MoS stretching and bending modes, which have been observed to be mixed due to their similar frequencies.31, 33 The situation is quite different for XDH and XO,20 where six low-frequency vibrations are observed (Figure 3). Here, we consider the experimental rR data for these XDH Mo(IV)-P CT complexes in the context of the small molecule analog resonance Raman data and DFT frequency calculations. This allows us to make quality vibrational frequency assignments (Table 1 and Figure 4) for four of these bands (bands A-D in Figure 4).</p><p>Band A occurs at 234 cm−1 in Mo(IV)-4-TV, and has previously been assigned as a dithiolene folding + Mo≡O rocking mode. Our work here supports the prior assignment by providing additional evidence that this mode possesses both the Mo≡O rocking and pyranopterin terminal − NH2 twisting character that is observed in the DFT calculated vibrational mode. The Mo≡O rocking contribution to this normal mode is supported by the 2 cm−1 shift in the vibrational frequency as a function of the Q197A substitution. A similar Mo≡O---H hydrogen bond has been postulated to occur between the Mo≡O oxo moiety and an active site Trp from resonance Raman studies on R. capsulatus dimethyl sulfoxide reductase.34 There may also be some product out-of-plane bending character that contributes to this normal mode since there is a small 1–2 cm−1 difference in the Band A vibrational frequency of 4-TV compared to 2,4-TV. A schematic diagram of the normal mode displacements is shown in Figure 4 with the view oriented in a plane orthogonal to the apical Mo≡O bond.</p><p>Relatively larger (4 cm−1) spectral shifts are observed between Mo(IV)-4-TV and Mo(IV)-2,4-TV for Band B. Again, we attribute this to a small degree of product character being admixed into this vibrational mode, and this is observed in the DFT computed vibrational mode descriptions. The admixture of product character in this normal mode was also evident in the comparison of wt XOR and wt XDH resonance Raman spectra with 4-TV and 2,4-TV as enzyme bound product molecules.35 In the prior Raman study, the normal mode associated with Band B appeared to possess some product character since this band was also observed to shift by ~ 4 cm−1 as a function of the nature of the product, which is bound to the Mo ion as the enolate tautomer (Figure 1B).35 Here, we find that band B possesses dominant Mo-Sdithiolene and Mo-SH core vibrations (Table 1). The small negative frequency shifts observed relative to wt enzyme in the Q197A and Q102G variants are consistent with additional pyranopterin terminal − NH2 rocking and Mo≡O rocking contributions to this mode that would be affected by changes in hydrogen bonding due to the amino acid substitutions.</p><p>The 326 cm−1 mode (Band C) observed for wt Mo(IV)-4-TV XDH was also probed in earlier work that compared wt XOR and wt XDH resonance Raman spectra with both 4-TV and 2,4-TV bound product molecules.20 This mode is assigned as primarily arising from the symmetric Sdithiolene-Mo-Sdithiolene core stretching vibration by analogy to small molecule oxomolybdenum-dithiolene analog compounds31, 33 and this is additionally supported by comparison with our DFT frequency calculations. We note that a small 2 cm−1 shift to lower frequency is observed for this mode in the Q197A variant. Interestingly, inspection of the DFT calculated vibrational mode reveals an additional, albeit small, Mo≡O rocking contribution to this mode. This adds additional support to our hypothesis that the terminal Mo≡O oxo ligand is involved in a weak electrostatic or Mo≡O---H-(NH)-R hydrogen bonding interaction with Q197.</p><p>The higher frequency observed for Band D, coupled with its near invariance as function of the nature of the violapterin product bound to the Mo ion, indicates that this is a nearly pure Moco vibration with no bound product character. DFT frequency calculations support this assignment, with asymmetric Sdithiolene-Mo-Sdithiolene + Mo-SS-H stretching contributions dominating in the vibrational mode description. The asymmetric stretching nature of this band is also consistent with its relatively lower resonance Raman enhancement relative to the symmetric stretch of Band C. The frequency of Band D is not sensitive to the Q197A mutation, suggesting a reduction in Mo≡O rocking character contributing to this vibration compared with Band C. This observation is also evident in the computed normal mode description of this vibration. In contrast, the 2–3 cm−1 shift to lower frequency for the Q102G variants with either 4-TV or 2,4-TV as enzyme bound product supports pyranopterin terminal −NH2 character being admixed into this predominantly Mo-S stretching vibration.</p><p>The bathochromic shifts observed for vibrational Bands A-D in the Q197A and Q120G variants relative to wt RcXDH point to the elimination of weak Moco-protein hydrogen bonding interactions in these variants that are present in the wt protein. This red shift is most consistent with Moco bending contributions to these normal modes in vicinity of Q197 and Q102, and reflects a reduction in vibrational force constants that accompany the loss of hydrogen bonding. The magnitude of the observed vibrational frequency shifts are in accord with what has been observed for weak hydrogen bonding interactions,36 including weak protein-flavin hydrogen bonding,37 and weak hydrogen bonding interactions between amino acid residues and heme cofactors in metalloproteins.38–40</p><p>The observation of multiple low-frequency vibrations in the resonance Raman spectra of these XDH-product intermediates, and their Q197A and Q102G variants, with optical pumping into a Mo(IV)→product charge transfer excited state is important, since only two low-frequency vibrational modes are observed in Tp*MoO(dithiolene) small molecule analog Raman spectra.31–32 However, multiple low-frequency vibrations have also been observed in blue copper proteins and related small molecule analog compounds.41–44 The observation of multiple resonantly enhanced low-frequency vibrations in blue copper proteins has been attributed to a mechanical, or kinematic coupling that mixes low-frequency protein bending modes with a dominant Cu-S vibrational mode that is distorted and resonantly enhanced with optical excitation into a SCys→Cu charge transfer excitation. This vibrational mode mixing was shown to be a function of the potential energy distribution (PED)41, 43 of the Cu–SCys distortions being dispersed over multiple low-frequency normal modes with vibrational frequencies similar to the S-Mo-S stretch. A related allosteric coupling has been suggested to be very important in modulating the magnitude of the electronic coupling matrix element between the T1 Cu and the trinuclear Cu cluster in multicopper oxidases.42 Our Raman data strongly suggest a similar kinematic coupling/vibrational mode mixing is occurring in the reduced RcXDH enzyme-product complexes studied here. Such structural modulation of the electronic coupling by low frequency Moco vibrational modes may serve to increase the electron transfer rate in key pyranopterin molybdenum enzyme catalytic intermediates.44–45 Specifically, bovine XOR and RcXDH20 we now have evidence for long-range kinematic coupling between a symmetric S-Mo-S dithiolene chelate distortion and the pyranopterin, as well as coupling between this S-Mo-S symmetric stretch and the Mo≡O moiety of Moco.</p><!><p>Site-directed mutagenesis of Q197 and Q102 has been performed in order to gain additional insight into how these glutamine residues affect the XDH reductive half reaction. Specifically, the Q197A and Q197E variants have been produced in order to compare their kinetic parameters with wt enzyme. A series of rapid reaction kinetic experiments has allowed us to obtain values for the rate of substrate reduction, kred, and the equilibrium dissociation constant, KD (Figure S2). The Q197E variant is observed to possess a small, approximately 2-fold reduction in kred when compared with wt enzyme. The different nature of the amino acid side chains in wt, Q197E, and Q197A suggests that these variants may result in the elimination of a hydrogen bonding interaction between the glutamine amide − NH2 and the terminal oxo of the Mo≡O group (Figure 1A). However, we observe that the effects on kred are rather small. Certainly, the simple elimination of a potential hydrogen bond in Q197A shows that hydrogen bonding to Mo≡O does not affect kred. The KD for the Q197E variant with xanthine as substrate is essentially the same as that observed for wt enzyme. Since Q197 is positioned above the Mo≡O group, Q197 does not appear to play a critical role in substrate binding. The KD is also not noticeably affected in the Q197A variant. The pH dependence of Kcat/KM show maximum catalytic efficiencies at pH=8.0 for wt enzyme and pH=7.5 for Q197A (Figure S3). The kinetic parameters obtained for the Q102A and Q102G variants are also quite similar to those of the wt enzyme, indicating that any disruption in a putative electron transfer pathway that involves Q102 mediating electron transfer between Fe/S I and the PDT does not affect overall catalytic efficiency in the reductive half reaction. In summary, our kinetic studies indicate minor changes in kred and kred/KD between wt enzyme and the Q102 and Q197 variants studied here, consistent with Q102 and Q197 possessing weak hydrogen bonding or electrostatic interactions with Moco.</p><!><p>The observed pattern of frequency shifts between wt enzyme and the Q197A and Q102G variants is consistent for both Mo(IV)-4-TV and Mo(IV)-2,4-TV enzyme-product complexes, and this has allowed the assignment of low-frequency wt XDH, Q197A, and Q102G vibrational modes. These assignments are consistent with the presence of either weak hydrogen bonding or electrostatic interactions existing between Moco and the glutamines Q102 and Q197 that do not appreciatively affect the kinetic parameters kred or kred/KD (Figure S2, Table S1).</p><p>The Mo(IV)→product charge transfer character20 present in the NIR MLCT band for XO and XDH product complexes leads to resonance enhancement of low-frequency vibrations that reflect the nature of Moco distortions that are coupled to a formal one-electron oxidation of the Mo4+-(product) ground state upon forming the Mo5+-(product)1– charge transfer excited state. Remarkably, this effect appears to extend all the way to the −NH2 terminus of the pyranopterin, and supports a hypothesis that the PDT acts as an electron transfer conduit that connects the Mo center to a spinach ferredoxin type 2Fe/2S cluster proximal to the PDT of Moco.</p><p>With respect to the postulated roles of the PDT in catalysis, our work suggests that hydrogen bonding interactions involving Q197 and Q102 function to partially anchor Moco to the protein. Our work further supports a hypothesis that the PDT functions as a conduit for electron transfer between the Mo ion and the proximal Fe/S I in XOR, XDH, and other members of the xanthine oxidase family of pyranopterion Mo enzyemes.1, 10,13–15, 20 Future studies will focus on other potential Moco - protein hydrogen bonds in XDH and in other pyranopterin enzymes in a concentrated effort to further define the role of the PDT in pyranopterin Mo enzyme mediated catalysis.</p>

PubMed Author Manuscript

Isolated Neutral [4]Helicene Radical Provides Insight into Consecutive Two-Photon Excitation Photocatalysis

Direct activation of strong bonds in readily available, benchtop substrates offer a straightforward simplification, albeit in most cases existing catalytic systems are limited to unlock such activation. In recent years, a surge of in-situ generated organic radicals that can act as potent photoinduced electron transfer (PET) agents have proved to be a powerful manifold for the activation of remarkably stable bonds. Herein we document the use of N,N′-di-n-propyl-1,13-dimethoxyquinacridine ( n Pr-DMQA • ), an isolated and stable neutral helicene radical, as a highly photoreducing species. This isolable doublet state open shell radical offers a unique opportunity to shed light on the mechanism behind PET reactions of organic radicals. Experimental and spectroscopic studies revealed that this doublet radical has a long lifetime of 4.6 ± 0.2 ns, an estimated excited state oxidation potential of -3.31 V vs SCE, and can undergoes PET with organic substrates. The strongly photoreducing nature of the n Pr-DMQA • was experimentally confirmed by the demonstration of photo activation of electron rich aryl bromides and chlorides. We further demonstrated that n Pr-DMQA • can be photochemically generated from its cation analog ( n Pr-DMQA + ) allowing catalytic functionalization of aryl halide via a consecutive photoexcitation mechanism (ConPET). Dehalogenation, photo-Arbuzov, photo-borylation and C-C bond formation reactions with aryl chlorides and bromides are reported herein, as well as the α-arylation of carbonyl using cyclic ketones. The latter transformation exhibits the facile synthesis of α-arylated cyclic ketones as critical feedstock chemical for diverse useful molecules, especially in the biomedical enterprises.

isolated_neutral_[4]helicene_radical_provides_insight_into_consecutive_two-photon_excitation_photoca

INTRODUCTION<!>RESULTS AND DISCUSSION<!>Photocatalytic dehalogenation of aryl halides.<!>Table 1: Substrate scope for the photoredox reductive dehalogenation of aryl halides enabled by neutral helicene radical.<!>Table 2: Scope for the reductive functionalization of aryl halides under photoredox condition catalyzed by neutral helicene radical.<!>CONCLUSIONS

<p>Over the past decade, photoredox catalysis has received a fast and growing interest from the world of synthetic chemistry. 1 By combining visible light with a photocatalyst (PC), a large variety of efficient and selective transformations have been achieved under mild conditions, during which the excited state PC is involved in a single electron transfer (SET) with a substrate or a co-catalyst. However, SET with conventional photocatalyst is usually limited to reduction potential down to -2.0 V vs. Saturated Calomel electrode (SCE). 2 In recent years, several elegant reports have shown that open shell doublet radicals, generated in-situ, either electrochemically 3 or photochemically, can act as potent photoreducing agents. 4 For example, a two-photon excitation process, commonly purported as consecutive photoelectron transfer (conPET) pathway, is proposed as the photochemical generation pathway of potent photoreducing organic radicals (Figure 1a, left). 5 In that process, the excited state of a close shell single photocatalyst PC* (neutral or cationic) is generated upon the first excitation. Then, a sacrificial electron donor can act as a reductant and participate in SET with PC* to generate PC • radicals (anionic or neutral). A second successive photoexcitation generates the radical excited state PC • * that can act as super photoreducing agent (E1/2 red * = -2.3 to -3.4 V vs SCE) (Figure 1a). 6 This concept of two-photon excitation process has been reported with numerous notable photocatalysts such as PDI, 7 DCA, 8 anthraquinone, 9 Rhodamine 6G, 10 benzo[ghi]perylene (BPI), 11 4-DPAIPN, 12 3-CzEPAIPN, 13 Mes-Acr, 14 and Deazaflavin 15 (Figure 1b). As a common benchmark reaction, photoredox C(sp 2 )-X bond activation in aryl bromides and chlorides, Birch reduction, and sulfonamide cleavage showcased the extreme photoreducing ability of radical photocatalysts in most cases. Despite these convincing reports, an intriguing aspect of photoactive open shell doublet radicals generated in-situ is that alternative mechanisms cannot be completely ruled out. For example, Leonori et. al. recently reported that α-aminoalkyl radical, generated via SET between alkyl amines and a close shell excited PC*, can initiate halogen atom transfer (XAT) (Figure 1a, right). 16,17 Therefore, the concept of super photoreducing radicals in conPET systems is weakened due to the common usage of amine as the sacrificial electron donor. Furthermore, a recent study by Nocera and colleagues questioned the viability for radicals generated in-situ during conPET or electrophotocatalysis to act as efficient photocatalysts, due to their short-lived excited state which should hamper their participation in bimolecular reactions with substrates. They concluded that, instead, a close shell singlet species, such as a Meisenheimer complex or side product impurities, formed from the reactive open shell doublet radical can act as the super reducing photoreagent (Figure 1a, top). 18 To date, stable and isolatable radicals able to undergo photoinduced electron transfer during an organic transformation remain elusive. Therefore, the synthesis and isolation of such photoactive organic radicals are of great interest in order to shed light on the ability for open shell doublet species to act as photoreducing agents.</p><p>As part of our ongoing interest in the photochemical properties of the helical carbenium system, we recently reported the use of N,N′-di-n-propyl-1,13-dimethoxyquinacridinium ( n Pr-DMQA + ) tetrafluoroborate 19 as an organic photoredox catalyst for photoreductions and photooxidations under red light (λmax = 640 nm). 20 Several fundamental organic transformations involving either oxidative quenching or reductive quenching pathways have been demonstrated. During these studies, we identified the neutral helicene radical ( n Pr-DMQA • ) as a possible radical intermediate in the reductive quenching photocycle. In our contemporary studies, we reported the chemical synthesis, isolation, and characterization of n Pr-DMQA • as part of a family of neutral quinolinoacridine radicals from their quinolinoacridinium cation analogs. 21,22 Our studies showed that these radicals are highly persistent in their solid form as well as in solution for several months under inert conditions, and reversibly oxidize back to the cation upon exposure to air.</p><p>We now report that the stable helicene radical n Pr-DMQA • , first observed by Larsen et. al. 22 and isolated by our group, 21 is a highly photoactive species with strong absorptions of light in the visible region. The excited state oxidation potential of this helicene radical has been estimated to be -3.31 V vs SCE which makes it one of the strongest photoreductants. This radical can be made on gram scale, isolated, purified and stored in a glovebox, which allowed us to investigate its photophysical and photochemical properties, as well as its ability to act as a strong photoreducing agent without questioning the involvement of impurities or side products. Furthermore, the closed shell cation counterpart, n Pr-DMQA + , is photoactive in red light, while n Pr-DMQA • is not, which offers a unique opportunity to probe the mechanism for the photoactivation of aryl bromides and chlorides under blue light excitation.</p><!><p>Photophysical properties of n Pr-DMQA • radical. We recently reported that the chemical reduction of n Pr-DMQA + allows the synthesis and isolation of the stable double state organic radical n Pr-DMQA • . 21 Interestingly this radical was found to possess strong absorption of light in the visible region (391 nm, 440 nm, 467 nm, and 557 nm) and exhibits emission maxima at 593 nm (Figure 2a, and Figure S1 -S3). The life-time of the excited state was determined using time correlated single photon counting (TCSPC, see Supporting information). Excitation of n Pr-DMQA • resulted in a strong emission band characteristic of n Pr-DMQA • * (λ𝑚𝑎𝑥 𝑒𝑚 = 593 nm) whose average lifetime (τ) was measured to be 4.6 ± 0.2 ns (Figure 2b, and Figure S5 -S9). 23 Interestingly, the fluorescence lifetime of the open shell doublet radical was found to be longer than its singlet cation analog (5.7 ns for n Pr-DMQA + *). 24 A multi nanosecond scale excited state lifetime is suitable for bimolecular electron transfer suggesting that the doublet neutral radical n Pr-DMQA • could act as an effective PET agent. 25 As previously oberved, 20d, 21 the cyclic voltammogram of the n Pr-DMQA scaffold in acetonitrile revealed the presence of two reversible events, E1/2 ( n Pr-DMQA ++• / n Pr-DMQA + ) = + 1.27 V and E1/2 ( n Pr-DMQA + / n Pr-DMQA • ) = -0.85 V vs SCE when recorded between -1.5 V and + 1.5 V vs. SCE (Figure 2c, i) trace). However, when the potential window is extended to reach -2.0 V vs. SCE, an irreversible event at E1/2 ( n Pr-DMQA • / n Pr-DMQA -) = -1.84 V vs SCE is observed, which then triggers the generation of an intermediate with an irreversible event at + 0.67 V vs SCE (Figure 2c, ii) trace). Laursen et. al. have previously assigned this intermediate as the neutral close shell singlet n Pr-DMQA-H, which forms by reaction between acetonitrile and the highly reactive n Pr-DMQA -. Based on the electrochemical and photophysical properties of n Pr-DMQA • (E1/2 ox (C + /C • )= -0.85 V vs SCE, E1/2 red (C • /C -) = -1.84 V vs SCE, , and excitation energy E0,0 = 2.15 eV at λex =557 nm and E0,0 = 2.46 eV at λex = 440 nm, the excited state redox potentials of this helicene radical are estimated to be E*1/2 ox (C + / C •* )= -3.03 V vs SCE (λex = 557 nm), E*1/2 ox (C + / C •* ) = -3.31 V vs SCE (λex = 440 nm), and E*1/2 red (C •* /C -) = + 0.45 V vs SCE (see supplementary information). As a result, n Pr-DMQA • can be described as a mild photooxidant and one of the most potent photoreductant.</p><p>Considering recent reports suggesting that in-situ generated close-shell singlets can be involved during photochemical transformations, 18 we turned our focus on n Pr-DMQA-H. Following Lacour et. al. synthetic protocol, 26 we have synthesized and studied the electro-and photophysical properties of this neutral close shell singlet (see supporting information). The absorption spectroscopy reveals a photo inactive species that possesses an absorption at 316 nm and no emission. The cyclic voltammogram of n Pr-DMQA-H (Figure 2c, iii) traces) reveals an irreversible oxidation event at +0.67 V vs SCE, followed by a reversible oxidation at + 1.27 V vs SCE which was assigned to the n Pr-DMQA ++• / n Pr -DMQA + redox couple. Importantly, no event is observed at negative potential during the first cycle (solid trace), however the reversible event associated to n Pr-DMQA + / n Pr-DMQA • appears after the second cycle (doted trace) suggesting that n Pr-DMQA + is electrochemically generated from the oxidation of n Pr-DMQA-H. Consistent with these electrochemical data and the previous observation by Lacour, UV-Vis spectroscopy monitoring of the colorless n Pr-DMQA-H revealed the slow formation of the green n Pr-DMQA + upon exposure to air in acetonitrile (see Figure 2d, left). 27 Interestingly, n Pr-DMQA-H was stable in acetonitrile in absence of oxygen and in the dark, but undergoes photoinduced homolysis to form n Pr-DMQA • when irradiated with a 440 nm LED. This conversion was also monitored by UV-Vis spectroscopy (Figure S12). These results support that even if formed during photocatalysis (vide-infra), the closed shell single n Pr-DMQA-H is expected to convert back to n Pr-DMQA • via photolysis and/or to n Pr-DMQA + under oxidative conditions, undermining its involvement as a possible photoinduced electron transfer agent. S15 and S17). However, under 440 nm irradiation we observed the disappearance of the radical n Pr-DMQA • absorption band and the appearance of the cation n Pr-DMQA + absorption bands (Figure 3a). These observations suggest that the excited state n Pr-DMQA • * can undergo an oxidative quenching process via SET with aryl halide to generate an aryl radical anion and n Pr-DMQA + . The photoredox properties of n Pr-DMQA • discussed above also suggest that in presence of a suitable donor (E1/2 > +0.45 V vs SCE), reductive quenching of n Pr-DMQA • * can be observed resulting in the formation of the highly reactive n Pr-DMQAwhich will then rapidly convert to the stable singlet closed shell n Pr-DMQA-H (vide-supra). UV-Vis spectroscopy monitoring of a solution of n Pr-DMQA • and a large excess of pyrrolidine under 440 nm LED irradiation revealed the rapid and quantitative formation of n Pr-DMQA-H (Figure 3b). A large excess of amine was required to drive the reaction toward the formation of n Pr-DMQA-H and overcome the reverse photolysis of n Pr-DMQA-H back to n Pr-DMQA • .</p><p>To further probe the viability of a photoexcited direct SET between n Pr-DMQA • and aryl halides we performed a stoichiometric photo-Arbuzov reaction using different light sources (440 nm and 640 nm), different DMQA species ( n Pr-DMQA • , n Pr-DMQA + , n Pr-DMQA-H), and different aryl bromide substrates with a range of reduction potentials (4-bromo benzonitrile 2a, E1/2 red = -1.94 V vs SCE; and 4-bromo anisole 2b, E1/2 red = -2.90 V vs SCE) (Figure 3c, and supporting information). Equimolar amounts of aryl bromide and DMQA species were irradiated for 16 h with visible light in presence of 3.0 equivalent of the aryl radical trapping agent, triethyl phosphite P(OEt)3. Using DMQA + , under either 440 nm or 640 nm irradiation, did not produced any aryl activated product consistent with the mild photoreducing potential of this singlet cation species (See Figure 3c, entry 1 -2). On the other hand, when the doublet neutral radical n Pr-DMQA • was irradiated under 440 nm both aryl halides were activated, with a higher yield for the less electron rich bromo benzonitrile (3a, <90% yield) and 3b, 50% yield, Figure 3c, entry 3). Furthermore, the red color of the reaction mixture, characteristic of the helicene radical, turned to the blue/green color of the helicenium ion supporting the previously observed reversibility between radical and cationic form of the DMQA system. Importantly, no product formation for the electron rich 4-bromo anisole was observed when red light irradiation (640 nm) was used (Figure 3c, entry 4), consistent with the weak absorption of n Pr-DMQA • at wavelength higher than 600 nm (Figure 1c). However, full conversion was detected under red light with the more easily reducible 4-bromo benzonitrile suggesting that an alternative pathway to PET maybe involved with this easily activated substrate (Figure 3c, entry 4). Finally, we noted a similar outcome when using n Pr-DMQA-H (Figure 3c, entry 5 -6), which supports the formation of n Pr-DMQA • under light. These results substantiated our hypothesis that the doublet neutral helicene radical n Pr-DMQA • * can undergo rapid PET with substrates such as electron rich aryl bromide under 440 nm light.</p><p>To further support these observations and the ability for n Pr-DMQA • to undergo single electron transfer with aryl halides, we performed transient absorption measurements using a home-built apparatus with broadband detection (see supporting information). Transient absorption data was collected for the neutral radical in acetonitrile and in an acetonitrile/4-bromo anisole (3.0 equiv.) solution. Figure 3d (i) presents the transient absorption data for the n Pr-DMQA • neutral radical in acetonitrile. The region corresponding to the maximum of the negative ground state bleach signal has been omitted due to pump scatter. Stimulated emission signal expected appear at the maximum of the fluorescence emission is not evident as it is overlapped with the strong excited state absorption signal. Two excited state absorptions that appear as positive signals with maxima at 523 nm and 588 nm are present in the data on either side of the ground state bleach. Both excited state absorption contributions fully decay by 48 ps as shown in Figure 3d (i). At longer delay times, the only remaining signal arises from the recovery of the ground state bleach, which corresponds to the 4.6 ± 0.2 ns excited state lifetime measured by TCSPC. Figure 3d (ii) presents the transient absorption for the n Pr-DMQA • neutral radical in acetonitrile in the presence of an aryl halide. In comparison to the n Pr-DMQA • alone in acetonitrile, the addition of the aryl halide produces significant changes in the transient absorption data. Both samples have similar nanosecond ground state recoveries (negative signal centered at 558 nm) consistent with the measured fluorescent lifetime, with different dynamics evident for the positive going contributions on either side of the ground state bleach. The positive signal features in the neutral radical in acetonitrile data decay within tens of picoseconds. In contrast, the signal for the neutral radical in the presence of an aryl halide has positive features that persist for nanoseconds. The maxima of the lower energy positive feature in the data with the aryl halide is peaked at 615 nm rather than 588 nm for the acetonitrile-only solution. This indicates the in-situ generation of the cation n Pr-DMQA + photoproduct whose S0 to S1 transition is peaked at 616 nm. The persistence of the cation photoproduct signal is consistent with the previously measured excited state lifetime of 5.7 ns. Photocatalytic activity of n Pr-DMQA radical and mechanism. Inspired by the stoichiometric photo-Arbuzov experiment and our previous reports on the photoactivity of n Pr-DMQA + , we questioned if n Pr-DMQA • can be photochemically generated from n Pr-DMQA + in presence of a light source and an electron donor, allowing the use of n Pr-DMQA • as potent photoreducing agent for catalytic transformations. Consistent with our previous observation, the successful generation of the helicene radical n Pr-DMQA • was detected in an EPR experiment, as well as using UV-Vis spectroscopy, in presence of three different electron donors under both blue and red-light sources (Figure 4a, and Figure S24 -S28). Next, we attempted the catalytic reductive dehalogenation of 4-bromobenzonitrile (E1/2 = -1.94 V and BDE = 80 kcal/mol) 28 and 4-bromoanisole (E1/2 = -2.90 V and BDE > 85 kcal/mol) in presence of pyrrolidine with n Pr-DMQA + or n Pr-DMQA • as a photocatalyst under either blue or red light (Figure 4b, and supporting information). In case of 4-bromo anisole, both PCs induced a dehalogenation reaction under blue light with similar yields. The near identical yield for both PCs supports a mechanism during which n Pr-DMQA + and n Pr-DMQA • are involved in the photocatalytic cycle (Figure 4b). However, no product was detected with either PCs when low energy light was employed, consistent with the fact that n Pr-DMQA • has little to no absorption in red light, and that n Pr-DMQA +* is not reductive enough to undergo PET with aryl halides. Similarly, with the electron poor bromobenzonitrile, both PCs afforded full conversion under blue light (Figure 4b). However, unlike with anisole, some conversions were detected with both n Pr-DMQA + and n Pr-DMQA • under low energy red light. We recently, reported that photochemically generated ammonium radical can initiate XAT mechanism with electron poor substrate such as 4-bromobenzonitrile but not with 4-bromoanisole. In the present system, pyrrolidine acts as an electron donor and forms pyrrolidinium radical during the photoreduction of n Pr-DMQA + to n Pr-DMQA • or n Pr-DMQA • to n Pr-DMQA -. The lower yield observed in red light compared to blue light for bromobenzonitrile supports that single electron transfer between n Pr-DMQA •* and aryl halides is the most effective mechanistic pathway. Together, these observations suggest that for electron poor substrate such as bromobenzonitrile both SET and XAT mechanism are accessible pathways in blue light while XAT is the only viable mechanism under red light. On the other hand, for electron rich species such as 4-bromo anisole, SET from n Pr-DMQA •* is the only sustainable mechanism. Interestingly, at the end of the catalytic transformations under blue light, the reaction mixtures were a pale almost colorless solution which rapidly turn to the green color of n Pr-DMQA + when exposed to air. This observation suggests that at high conversion (excess amine and low concentration of aryl halide) n Pr-DMQA-H generated from n Pr-DMQA •* build up in solution and can be considered as an off-cycle catalytic resting state.</p><p>Based on these experimental results and previous reports, we proposed a plausible conPET pathway for the photoactivation of electron rich aryl halides using n Pr-DMQA + as photocatalyst under blue light (Figure 4c). First the photoexcitation of n Pr-DMQA + results in an excited cationic n Pr-DMQA + * under blue light irradiation. A single electron transfer (SET) from the sacrificial electron donor D (pyrrolidine, DIPEA or enamine) generates the neutral helicene radical n Pr-DMQA • . As the radical species is photoactive in the blue light region the second photoexcitation leads to the excited state helicene radical, n Pr-DMQA • *. Now the electrochemical potential of this excited neutral radical (E1/2 red < -3.31 V vs SCE in CH3CN, τ = 4.6 ± 0.2 ns) is strong enough to reduce aryl chlorides and bromides via SET closing the catalytic cycle by regenerating the cationic helicenium n Pr-DMQA + . Finally, after reduction the aryl halide radical anion fragmentate to the corresponding aryl radical which can abstract a hydrogen to form the dehalogenated product, or be further coupled with suitable substrates (phosphites, boranes, pyrroles or carbonyls). In a non-productive pathway, the excited state helicene radical n Pr-DMQA • * can also generate n Pr-DMQAvia SET with pyrrolidine, followed by the generation of n Pr-DMQA-H which can fragmentate back to n Pr-DMQA • .</p><!><p>With the photo-excited behavior of n Pr-DMQA • and a probable mechanism for consecutive photoelectron transfer elucidated, we sought to use this neutral helicene radical as a photoreducing catalyst for the functionalization of aryl halides. At first, reductive dehalogenation of aryl halides was performed as the benchmark reaction to evaluate the extent of the extremely potent reducing behavior of the helicene radical. Dehalogenation of 4-bromo anisole (E1/2 red = -2.9 V vs SCE) was optimized using n Pr-DMQA-BF4 as the photocatalyst under a 440 nm light source. Pyrrolidine was identified as an efficient sacrificial electron donor for the generation of n Pr-DMQA • from n Pr-DMQA + , in situ. After optimization (see Table S1), we observed that 5.0 mol% n Pr-DMQA-BF4 as the photocatalyst in presence of 440 nm blue light and 3.0 equiv. of pyrrolidine furnished the desired hydrodebrominated product (anisole) in 94% yield within 16 h.</p><p>Following the identification of optimal reaction conditions, the competency of this strong radical photoreductant has been demonstrated by the reduction of a wide range of electronically diverse aryl chlorides and bromides (Table 1). Successful dehalogenation of a variety of electron rich and electron poor aryl chlorides with reduction potential of -2.9 V vs SCE and lower have been demonstrated in good to excellent yields (4a-4f, 81-99 % yield). We then focused on diverse electron rich aryl bromides (4g-4l, 90-98 % yield) along with a myriad of functional group containing substrates (4m-4s, 71-99 % yield) for excellent hydrodebromination reaction. Polyaromatic substrates and heteroaromatic bromides were also found to be efficient substrates for reductive dehalogenation (4t-4x, 80-96 % yield). Furthermore, the bisreduction of polyhalogenated arenes gave the corresponding bis-dehalogenated products in moderate yield (4y and 4z, 73 % and 78 % yield, respectively). In general, aryl halides bearing nitrile (4c, 4o), ester (4d, 4n), trifluoromethyl (4e, 4s), ketone (4m), free acid (4p), free hydroxy (4q) and free amine (4r) groups were well tolerated and found to be excellent substrate for this neutral helicene radical catalyzed photoredox dehalogenation method.</p><!><p>Photocatalytic functionalization of aryl halides. After successful examination of hydrodehalogenation reaction, we decided to extend this radical photocatalysis to other arene-functionalization processes (Table 2). Aryl phosphonates are important structural motifs found in many pharmaceutically active molecules 29 and easily accessed by photo-Arbuzov reaction using triethyl phosphite, P(OEt)3. 30 Addition of 3.0 equiv of P(OEt)3 to the optimal reaction condition of hydrodehalogenation reaction furnished aryl phosphonates in high isolated yields (Table 2 and S2). Using ConPET enable by n Pr-DMQA • allow us to expand scope of reactions towards less reactive aryl bromides or aryl chlorides bearing very negative reduction potentials. Electron rich aryl halides with substituents in ortho, meta and para position demonstrated excellent reaction yields (7a-7c, 81-91 % yield). Aryl bromides and chlorides with electron withdrawing groups also showed good conversion to the desired product (7d-7f, 76-89 % yield). In addition to that, polyaromatic substrate (7g, 90% yield) and heteroaromatic substrates furnished the corresponding aryl phosphonate in excellent yields (7h-7j, 84-92 % yield). Following the photo-Arbuzov reaction, borylation reaction for synthesis of aryl borate which is considered as important coupling partner in late-stage derivatization, 31 was examined with this established ConPET using n Pr-DMQA • . The addition of dipinacol diborane to optimized reductive dehalogenation condition ended up with the formation of aryl borate in good yields (7k-7l, 79-86 % yield). Furthermore, we explored the photoredox generation of aryl radicals from aryl halides for C-C bondforming reactions with arene such as N-methyl pyrrole. The desired arylated products were isolated in good yields in presence of 3.0 equiv. of N-methyl pyrrole (7m-7n, 88-90 % yield). During these transformations, dehalogenation was detected as side reaction. The use of DIPEA (Di-isopropylethylene diamine) as electron donor instead of pyrrolidine was found to give more selective result (see supporting information).</p><!><p>Photocatalytic α-arylation of cyclic ketones. The α-arylated cyclic ketone scaffolds are medicinally significant as well as critical building blocks for numerous pharmaceutical agents and bioactive natural products. 32 Unsurprisingly, transition-metal catalyzed α-arylation of carbonyls are well established reactions in classic organic chemistry. Typically, expensive transition metal catalysts and ligands, harsh reaction condition or multistep protocols are employed in the synthesis of medicinally relevant α-arylated cyclic ketones. 33 Nonetheless, considering the medicinal impact of such metal-mediated methods for the synthesis of pharmaceutical drug molecules, a completely organic catalyst based direct α-arylation reaction is in high demand. 34 Recently, our group reported photoredox α-arylation of carbonyl compounds using an electron rich acridinium as photocatalyst. However, scope of aryl halide was limited mainly to aryl iodides with moderate to good yields due to the lower excited state potential of our acridinium photocatalyst. 35 Using the present DMQA system as conPET photocatalyst for α-arylation of carbonyls would allow to expand the reaction scope to electron rich aryl bromides. In our contemporary report, 35 we demonstrated that in-situ enamine formation via condensation reaction between the carbonyl and the amine moieties was required. We further demonstrated that the cyclic amine, pyrrolidine, provided the highest yield due to the rapid enamine formation, and that both the pyrrolidine and its enamine analog acted as sacrificial electron donor. The EPR analysis of n Pr-DMQA-BF4 in presence of enamine confirms the formation of n Pr-DMQA • in a photoexcited state. Furthermore, using a readily available enamine (1-pyrrolidino-1-cyclohexene) as sacrificial electron donor instead of pyrrolidine, under optimized condition of reductive dehalogenation, resulted in the formation α-arylated of cyclohexanone, 85% yield. (See supporting information). Literature studies showed that enamine radical cations mainly exhibit the C-center free radical property due its high spin population, 36 which can lead to radical recombination pathway for generation of alpha-substituted product. Hence, to develop the helicene radical catalyzed α-arylation of carbonyls we employed cyclohexanone and pyrrolidine with aryl bromides. Optimizations under catalytic condition showed that 4bromoethyl benzoate (1.0 equiv.) in presence of 5 mol% of n Pr-DMQA-BF4 and combination of cyclohexanone with pyrrolidine (3.0 equiv. each) furnished the desired alpha-arylated product in 86 % yield (See Table S4).</p><p>With these optimal conditions for the alpha-arylation of cyclic ketones in hand, we examined the scope with respect to the aryl bromide component. As shown in Table 3, para-substituted bromoarenes containing functional groups like ester, carbonyl and free acid generated the corresponding alpha-arylated product in very good yields (8a-8d, 84-88% yield). Medicinally significant functional groups like nitrile and trifluoromethyl substituted arylbromides were also evaluated. Gratifyingly, substitution in para or meta position did not affect the product yield neither in nitrile (8e and 8f, 86 and 82 % yield) nor in trifluoromethyl containing substrates (8g and 8h, 75 and 76% yield). Fluorinated bromobenzene and unsubstituted bromobenzene were also well accommodated, furnishing alpha-arylated adducts in good yield (8i and 8j, 81 and 80% yield). In addition, polyaromatic and heteroaromatic bromoarene like 9bromophenanthrene and bromoindole were also found to be excellent substrate for this transformation (8k and 8l, 74 and 76% yield). Finally, as a demonstration that this method can be extended to the installation of multiple chiral centers containing arenes, alpha-arylation can be accomplished using this new protocol to provide the corresponding alpha-arylated cyclic ketone in excellent efficiencies (8m and 8n, 82 and 80% yield). Similar to aryl bromides, different cyclic ketones were also evaluated with respect to the optimal conditions. As shown in Table 3, a series of differentially substituted cyclohexanone-derived substrates were readily coupled with an aryl radical. It is of note that incorporation of both alkyl and aryl substituents at positions 4 of the cyclohexanone ring is well-tolerated (8o-8s, 78−84% yield). As expected, the presence of single substituent at the 4-position in the cyclohexanone ring induced higher levels of diastereoselectivity in product. Disubstituted cyclohexanones at the 4-position of the ring also successfully transformed to the corresponding alpha-arylated derivatives in good yield (8t and 8u, 86 and 82 % yield). Spirocyclic cyclohexanone derivative and heteroatom containing cyclic ketone were also well tolerated in optimal reaction condition (8v and 8w, 80 and 78 % yield). Interestingly, cyclopentanone was also found to be an efficient ketone substrate for this transformation with an excellent yield (8x, 85% yield).</p><p>Table 3: Helicene radical catalyzed photoredox ɑ-arylation of cyclic ketones using aryl bromides.</p><p>a Reactions were run on 0.2 mmol scale. Isolated yields are reported. See Supplementary Information for details.</p><!><p>While several reports have supported the involvement of openshell doublet radicals as potent photoreducing species, the isolation of a stable photoactive radical that can allow an extensive mechanistic study of photoinduced electron transfer during an organic transformation has remained elusive. Herein, we have reported that N,N′-di-n-propyl-1,13-dimethoxyquinacridine ( n Pr-DMQA • ), a stable and isolable open shell doublet radical, is a photoactive neutral helicene radical. The facile synthesis and isolation of this helicene radical asl allowed us to investigate its photophysical properties, photochemical reactivities and photocatalytic abilities. First, we reported that n Pr-DMQA • possess strong absorption of light in the visible region (391nm, 440 nm, 467 nm, and 557 nm), exhibits emission maxima at 593 nm, and an excited state lifetime of 4.6 ± 0.2 ns. The photophysical and electrochemical properties of n Pr-DMQA • suggest that this radical possesses an estimated excited state oxidation potential of -3.31 V vs SCE (E1/2(C + /C • *)) and excited state reduction potential of + 0.45 V vs SCE (E1/2(C • */ C -)). Monitoring by UV-Visible spectroscopy the irradiation of n Pr-DMQA • in acetonitrile at 440 nm in presence of electron acceptor (aryl halide) or electron donor (amine) revealed that in both cases photoinduced electron transfer occurred leading to the formation of the cationic n Pr-DMQA + and the anionic n Pr-DMQArespectively. The anionic n Pr-DMQAwas found to rapidly convert to the photo-inactive closed shell singlet n Pr-DMQA-H. These observations were further supported by transient absorption spectroscopy which showed that n Pr-DMQA* • undergoes efficient single electron transfer with an aryl halides electron acceptor -. We then probed the photoreducing ability of n Pr-DMQA • using stoichiometric photo-Arbuzov reaction with an electron poor (4-bromo benzonitrile) and an electron rich (4-bromo anisole) aryl bromide, under both 440 and 640 nm. The results obtained, coupled to the control experiments using n Pr-DMQA + and n Pr-DMQA-H, substantiate that the helicene radical is a potent photoreducing agent under 440 nm irradiation. Similar results were obtained for the catalytic dehydrogenation of the same aryl bromides. Experimental and spectroscopic studies suggest that the neutral helicene radical act as a strongly reducing species and is photochemically regenerated from the cationic helicenium analog, implying that a consecutive photoexcitation mechanism is the most viable mechanistic pathway. The strongly photoreducing nature of a neutral helicene radical n Pr-DMQA • was further used for the well-studied photo-dehalogenation, photo-Arbuzov, photo-borylation and C-C bond formation reactions. Additionally, this catalytic system was used in synthesis alpha-arylated cyclic ketones which is considered as an important building block for medicinal chemistry. In summary, we believe that the conPET process enabled by this neutral helicene radical, together with its operational simplicity and sustainability, will help to understand radical photoredox catalysis as well as considered as alternative way for streamline the synthesis of complex functionality in both academia and industry.</p>

ChemRxiv

Preparation of different thin film catalysts by direct current magnetron sputtering for hydrogen generation

In this study, thin films of Co, Ni, Pd, and Pt were prepared on Co 3 O 4 support material in pellet form using the direct current (DC) magnetron sputtering method for use as catalysts for hydrogen generation from NaBH 4 .Characterization of the catalysts was carried out using X-ray diffraction (XRD), scanning electronic microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). According to cross-sectional SEM images, catalyst thicknesses were observed in the range of approximately 115.3–495.8 nm. The particle sizes were approximately 25.0, 21.4, 33.9, and 9.5 nm for Ni-Co 3 O 4 , Co-Co 3 O 4 , Pd-Co 3 O 4 , and Pt-Co 3 O 4 catalysts, respectively. The increase in NaOH initial concentration provides an increase in the rate of hydrogen generation for Co, Ni, and Pd catalysts. A maximum hydrogen generation rate of 1653 mL/g cat .min was obtained for the Pt-Co 3 O 4 catalyst.

preparation_of_different_thin_film_catalysts_by_direct_current_magnetron_sputtering_for_hydrogen_gen

1. Introduction<!>2.1. Synthesis of support material<!>2.2. Catalyst preparation with coating deposition<!><!>2.3. Characterization<!>2.4. Measurement of hydrogen generation rate<!>3.1. Characterization of the catalysts<!><!>3.1. Characterization of the catalysts<!><!>3.1. Characterization of the catalysts<!><!>3.1. Characterization of the catalysts<!><!>3.2. Hydrogen generation of the catalysts<!><!>4. Conclusions

<p>The reduction of greenhouse gas emissions worldwide and the use of alternative fuels in transportation have become a forced option. According to recent research, hydrogen is an innovative fuel option for the automotive field and could replace conventional petroleum-derived liquid mixtures in passenger cars over time. However, the generation and storage of hydrogen are important issues arising from the use of hydrogen energy. Compared to physical hydrogen storage methods, chemical hydrides have superior properties for hydrogen generation. Sodium borohydride (NaBH 4 ), which is a hydrogen storage material suitable for hydrogen generation, is the most remarkable chemical hydride due to its high hydrogen content and adjustable hydrogen release properties [1–11]. In the alkaline solution of NaBH 4 the catalysts act as an on/off switch to provide hydrogen release [2]. This situation enables hydrogen production at the desired time. The catalytic hydrolysis reaction of NaBH 4 is as follows:</p><p>A wide variety of catalysts are used for the hydrolysis of NaBH 4 . Supported thin film catalysts are more easily recoverable than powder catalysts, and they do not aggregate [12]. Various methods enabling effective thin film catalysts such as pulsed laser deposition (PLD), electroplating, electroless plating, induced chemical reduction, and dip coating are used to obtain supported catalysts [13–17]. In addition to these methods, the direct current (DC) magnetron sputtering method can be used for thin film catalyst production. Because of its homogeneous wide area coating, good reproducibility, and high deposition rate, the DC magnetron sputtering method is the most attractive for industrial development [18]. The catalysts prepared by the sputtering method are deposited with precise control onto the support materials as thin, compact catalytic films, and because this low-cost method does not require precursors, the emission of toxic by-products is avoided. Film composition, structure, and morphology can be changed by varying sputtering parameters such as power, inert or reactive gas flow, partial pressure, and distance between the target and surface. A DC sputtering system is used for the coating of conductive materials, while a radio frequency (RF) sputtering system is used for nonconductive materials. When the uppermost layer needs to be active for catalysts, it is unnecessary for the metal to penetrate deeply into the substrate, and catalysts can be prepared more easily by DC sputtering[12,19]. Furthermore, DC sputtering is the cheapest method because DC power supplies are simpler to manufacture than those used in RF. In the magnetron process, in addition to an electrical field for acceleration of ionized argon atoms, a magnetic field is applied perpendicular to this field. By means of the magnetic field, electrons move along the helical orbit and, thus, increase the ion concentration on the target [20].</p><p>Very few studies have reported on catalysts for hydrolysis of NaBH 4 prepared by the sputtering method. In a study by Arzac et al., a cobalt catalyst was prepared on nickel foam by a magnetron sputtering method. They compared the hydrogen generation rates of catalysts having different film thicknesses and coated for different durations for sodium borohydride and ammonia boron hydrolysis. They reported that the highest activity for hydrogen generation from sodium borohydride was obtained from the catalyst coated for 4 h [12]. In addition, Co-based thin film catalysts are generally prepared by the different coating methods mentioned above. Therefore, the preparation of different thin film catalysts using the sputtering method for the hydrolysis reaction of NaBH 4 is an important working area.</p><p>In this study, Co 3 O 4 synthesized in powder form was pelletized and coated separately with Ni, Co, Pd, and Pt metals via a DC magnetron sputtering technique applied for 20 min. The prepared catalysts were characterized by XRD, XPS, and SEM-EDS techniques. Afterwards, hydrogen generation and measurement experiments were carried out with a system designed by our group [21].</p><!><p>Cobalt (II,III) oxide (Co 3 O 4 ) powder support material was prepared by a chemical method as previously reported [22]. The Co 3 O 4 synthesized in powder form was then pelletized by applying 10 tons of pressure with a manual press. The diameter and the thickness of the pellets were 13 mm and 0.2 mm, respectively. Pellets were then coated with Ni, Co, Pd, and Pt using the DC magnetron sputtering method.</p><!><p>The catalysts were coated using a DC magnetron sputtering system (GSL-1100X-SPC-16M), and the conditions of the coating are given in Table 1. The distance between the substrate and the target was 40 mm, and targets with a diameter of 50.8 mm (Evochem and Quorum technologies, Ontario, Canada; 99.95% pure, 0.1–3mm thick) were used for sputtering. A mass flow controller was used to generate Ar gas flow into the chamber. The coating pressure of the vacuum level was maintained at 2.0–4.0×10 -2 Mbar, and current of 20 mA was applied for 20 min which led to the formation of plasma.</p><!><p>The coating condition of DC magnetron sputtering.</p><!><p>The preparedcatalysts were examined by X-raydiffraction (XRD) using a PANalytical Empyrean X-ray diffractometer. The surface and cross-sectional morphology were examined by Quanta FEG 250 scanning electron microscope (SEM), and elemental composition of the coatings was determined by energy-dispersive X-ray spectrometry (EDS).The surface electronic states of the coated Ni, Co, Pd, and Pt metals were analysed by X-ray photoelectron spectroscopy (XPS) using the Specs-Flex X-ray photoelectron spectrometer.</p><!><p>The activities of the catalysts were evaluated using a system designed by our group, as previously reported [21–22]. In all experiments, the effects of NaOH (99.99% pure) concentrations were investigated by stabilizing 10 wt% NaBH 4 (98% pure) solution with different initial concentrations of NaOH(1, 10 wt%) at 25 °C.</p><!><p>The XRD patterns of the Co-Co 3 O 4 , Ni-Co 3 O 4 ,Pd-Co 3 O 4 , and Pt-Co 3 O 4 catalysts, which were compared with the diffraction pattern of Co 3 O 4 , are shown in Figure 1. According to the XRD results, Co 3 O 4 with a polycrystalline cubic structure was obtained. Characteristic peaks of Ni corresponding to (111) and (200) planes for 2ϴ values of 44.5 and 55.8° may overlap with the (400) and (422) planes of Co 3 O 4 , respectively; (002) and (101) plane peaks were observed for Co. Three diffraction peaks corresponding to the (111), (200), and (220) planes for 2ϴ values of 40.4, 46.9, and 68.6° were observed for Pd. In addition, the three peaks detected for Pt were assigned to diffraction from the (111), (200), and (220) planes for 2ϴ values of 39.6, 45.4, and 70°, respectively. The grain sizes of the prepared catalysts were calculated from the XRD data using the Scherrer equation [23]. The grain sizes were approximately 25.0, 21.4, 33.9, and 9.5 nm for Ni-Co 3 O 4 , Co-Co 3 O 4 , Pd-Co 3 O 4 , and Pt-Co 3 O 4 catalysts, respectively. The (111) planes at around 2ϴ value of 45° were selected to calculate the grain sizes of Ni and Co catalysts. Similarly, the (111) planes at around 2ϴ value of 40° were selected to calculate the grain size of Pd and Pt catalysts.</p><!><p>XRD patterns of the support material and catalysts.</p><!><p>The SEM image given in Figure 2a shows surface morphologies (particle nature) for the Co 3 O 4 support material in pellet form. Particle formation with homogeneous dispersion was observed in Co 3 O 4 support material, according to the EDS analysis given for Co 3 O 4 in Figure 2b. In addition, Figure 2c shows the prepared Co 3 O 4 pellet.</p><!><p>a) SEM image b) EDS analysis c) photo for Co 3 O 4 pellet.</p><!><p>Figures 3–6 show SEM images of prepared catalysts from both the surface and cross sectional areas as well as the EDS results for the catalysts.</p><p>Figures 3a–c show the surface and cross sectional SEM images and EDS analysis of Co-Co 3 O 4 . According to Figure 3a, particle formation was observed with nonhomogeneous dispersion for Co-Co 3 O 4 . The Co layer thickness was clearly observed from the cross sectional SEM images of the catalyst (Figure 3b). Catalyst thickness was approximately 115.3 nm. According to the EDS spectrum (Figure 3c), Co and O elements were detected for the catalyst.</p><!><p>A) Surface B) cross sectional SEM images, and C) EDS analysis result for Co-Co 3 O 4 catalyst.</p><!><p>Figures 4a–c show the surface and cross sectional SEM images and EDS analysis of Ni-Co 3 O 4 . According to Figure 4a, particle formation was observed with nonhomogeneous dispersion for Ni-Co 3 O 4 . The Ni layer thickness was clearly observed from the cross sectional SEM images of the catalyst (Figure 4b). Catalyst thickness was approximately 267.4 nm. According to the EDS spectrum(Figure4c) Ni, Co, and O elements were detected for the catalyst. A low nickel-coating ratio was observed in this case.</p><p>Figures 5a–c show the surface and cross sectional SEM images and EDS analysis of Pd-Co 3 O 4 .According to Figure5a, particle formation had homogeneous dispersion compared to Co- and Ni-based catalysts for Pd-Co 3 O 4 . In addition, the Pd particle sizes were larger than Ni and Co particles. This confirms the average particle size results calculated for the catalysts using XRD data. The Pd layer thickness was clearly observed from cross sectional SEM images of the catalyst (Figure 5b). Catalyst thickness was approximately 495.8 nm. According to the EDS spectrum (Figure 5c) Pd, Co, and O elements were detected for the catalyst, and a severe peak of Pd was observed.</p><p>Figures 6a–c show the surface and cross sectional SEM images and EDS analysis of Pt-Co 3 O 4 . Homogeneous particle formation was observed for Pt-Co 3 O 4 catalyst, similar to the Pd-Co 3 O 4 catalyst (Figure 6a). The Pt layer thickness was clearly observed from the cross sectional SEM images of the catalyst (Figure 6b). Catalyst thickness was approximately 285.5 nm. According to the EDS spectrum (Figure 6c), Pt, Co, and O elements were detected for the catalyst, and a severe peak of Pt was observed.</p><p>Figure 7 illustrates the XPS spectra of general and Co 2p, Ni 2p, Pd 3d, and Pt 4d–4f level photoemission signals of the catalysts. Figures 7a, 7c, 7e, and 7g show the XPS spectra of general elements. According to Figure 7b, two prominent peaks were observed for Co 2p 3/2 and Co 2p 1/2 (779.6 eV and 795.5 eV, respectively). Two shake-up satellites at 802.8 and 787.2 eV indicate the presence of Co 3 O 4 [24]. Two peaks of 2p 3/2 and 2p 1/2 for Ni were observed at 852.7 and 870.6 eV, respectively (Figure 7d) [25]. Figure 7f shows 334.5 eV(3d 5/2 ) and 338.8 eV(3d 3/2 ) corresponding to the Pd metal and Pd +2 states, respectively [26]. The peaks located at binding energies of 316.3 and 333.2 eV (Figure 7h) can be attributed to the Pt 4d 5/2 and Pt 4d 3/2 regions, respectively [27].Furthermore, Figure 7i shows Pt 4f 7/2 and Pt 4f 5/2 peaks, demonstrating the reduction of Pt(IV) to Pt(0) [28].</p><!><p>A) Surface B) cross sectional SEM images, and C) EDS analysis result for Ni-Co 3 O 4 catalyst.</p><p>A)Surface B) cross sectional SEM images, and C) EDS analysis result for Pd-Co 3 O 4 catalyst.</p><p>A) Surface B) cross sectional SEM images, and C) EDS analysis result for Pt-Co 3 O 4 catalyst.</p><p>XPS spectrums for; Co-Co 3 O 4 catalyst (a) general spectrum (b) Co 2p, Ni- Co 3 O 4 catalyst (c) general spectrum (d) Ni 2p, Pd- Co 3 O 4 catalyst (e) general spectrum (f) Pd 3, Pt- Co 3 O 4 catalyst (g) general spectrum (h) Pt 4d (i) Pt 4f electron regions.</p><!><p>Figures 8–11 show the amounts of hydrogen generated from NaBH 4 hydrolysis at 1 wt% and 10 wt% NaOH initial concentrations. All the experiments were performed at 25°C and 10 wt% NaBH 4 . The hydrogen generation rates of the catalysts for 1% and 10%NaOH initial concentrations are given in Table 2. Increasing the initial NaOH concentration for Ni, Co, and Pd-Co 3 O 4 catalysts caused an increase in the hydrogen generation rate (Figures 8–10). This increase was more than 2.5 times for the Pd-Co 3 O 4 catalyst. An increase in the hydrogen generation rate of the Pd-based catalyst following an increase in the NaOH initial concentration was observed in a previous study by our group and was attributed to inclusion of the hydroxyl ion inNaBH 4 hydrolysis [21]. Similarly, the increase in NaOH initial concentration for Ni- and Co-based catalysts had a positive effect [22].The Co-Co 3 O 4 catalyst was the most active among the three catalysts. The hydrogen generation rate for the Co-Co 3 O 4 catalyst at an initial concentration of 10% NaOH was 945 mL/g cat .min. InRakap et al. the activity of a Co-Ni-P/Pd-TiO 2 catalyst prepared with an electroplating method was investigated at 25°C, and the hydrogen generation rate was 460 mL/g cat .min [29]. Similarly, in a study by Krishnan et al., the hydrogen generation rate of a Co-B catalyst prepared on Ni foam was 300 mL/g cat .min [30]. In contrast, when the initial concentration of NaOH for the Pt catalyst increased from 1% to 10%, a decrease in the hydrogen generation rate was observed (Figure 11). The highest hydrogen generation rate was obtained from the Pt-Co 3 O 4 catalyst in 1% NaOH initial concentration (1653 mL/g cat .min). At an initial concentration of 10% NaOH in the Pt-Co 3 O 4 catalyst, the hydrogen generation rate decreased due to the reduced amount of free water required for the reaction and the low solubility of the reaction by-product NaBO 2 [21]. Hydrogen generation rates from the NaBH 4 hydrolysis of Ni-, Co-, Pd-, and Pt-based catalysts prepared in this work, and catalysts prepared using different thin film methods described in the literature, were compared in Table 3 [12–17, 29–33]. As shown in Table 3, hydrogen generation rates changed significantly depending on the catalysts used as well as the thin film preparation techniques. In this study, the efficiency of thin film catalysts prepared by the DC magnetron sputtering method for noble and nonnoble metals was investigated, and promising results were observed.</p><!><p>Time-dependent volumes of hydrogen generated at two different NaOH initial concentrations for Co-Co 3 O 4 catalyst.</p><p>Time-dependent volumes of hydrogen generated at two different NaOH initial concentrations for Ni-Co 3 O 4 catalyst.</p><p>Time-dependent volumes of hydrogen generated at two different NaOH initial concentrations for Pd-Co 3 O 4 catalyst.</p><p>Time-dependent volumes of hydrogen generated at two different NaOH initial concentrations for Pt-Co 3 O 4 catalyst.</p><p>H2 generation rate (HGR) of catalysts at two different NaOH initial concentrations.</p><p>HGRs for hydrolysis of NaBH 4 catalyzed by various catalysts in the literature.</p><!><p>In this study, Ni, Co, Pd, and Pt metals supported by a Co 3 O 4 pellet were prepared using a DC magnetron sputtering method for hydrogen generation from the hydrolysis of NaBH 4 . The SEM images for the catalysts illustrated surface morphologies and cross sectional areas. The Pd and Pt particles have nearly uniform size, and good dispersions were obtained. Catalyst layer thicknesses were clearly observed at 115.3, 267.4, 495.8, and 285.5 nm for Co, Ni, Pd, and Pt, respectively. According to the XRD results, the highest particle size obtained from a Pd-based catalyst was approximately 33.9 nm. The hydrogen generation rates of the catalysts were investigated at 1% and 10% NaOH initial concentrations. An increase in the NaOH initial concentration provides an increase in the rate of hydrogen generation for Co, Ni, and Pd catalysts. The minimum hydrogen generation rates were observed with a Pd-based catalyst. The reason may be that the Pd-based catalyst has a higher average particle size and a higher catalyst thickness than other catalysts. The highest hydrogen generation rate was obtained from the Pt-Co 3 O 4 catalyst in 1% NaOH initial concentration (1653 mL/g cat .min).</p>

PubMed Open Access

Comparative Studies of Mammalian Acid Lipases: Evidence for a New Gene Family in Mouse and Rat (Lipo)

At least six families of mammalian acid lipases (E.C. 3.1.1.-) catalyse the hydrolysis of triglycerides in the body, designated as LIPA (lysosomal), LIPF (gastric), LIPJ (testis) and LIPK, LIPM and LIPN (epidermal), which belong to the AB hydrolase superfamily. In this study, in silico methods were used to predict the amino acid sequences, secondary and tertiary structures, and gene locations for acid lipase genes and encoded proteins using data from several mammalian genome projects. Mammalian acid lipase genes were located within a gene cluster for each of the 8 mammalian genomes examined, including human (Homo sapiens), chimpanzee (Pons troglodytes), rhesus monkey (Macacca mulatta), mouse (Mus musculus), rat (Rattus norvegicus), cow (Bos taurus), horse (Equus caballus) and dog (Canis familaris), with each containing 9 coding exons. Human and mouse acid lipases shared 44-87% sequence identity and exhibited sequence alignments and identities for key amino acid residues and conservation of predicted secondary and tertiary structures with those previously reported for human gastric lipase (LIPF) (Roussel et al., 1999). Evidence for a new family of acid lipase genes is reported for mouse and rat genomes, designated as Lipo. Mouse acid lipase genes are subject to differential mRNA tissue expression, with Lipa showing wide tissue expression, while others have a more restricted tissue expression in the digestive tract (Lipf), salivary gland (Lipo) and epidermal tissues (Lipk, Lipm and Lipn). Phylogenetic analyses of the mammalian acid lipase gene families suggested that these genes are products of gene duplication events prior to eutherian mammalian evolution and derived from an ancestral vertebrate LIPA gene, which is present in the frog, Xenopus tropicalis.

comparative_studies_of_mammalian_acid_lipases:_evidence_for_a_new_gene_family_in_mouse_and_rat_(lipo

Introduction<!>In silico mammalian acid lipase gene and protein identification<!>Predicted Structures and Properties of Mouse Acid Lipases<!>Mouse Acid Lipase Gene Expression<!>Phylogenetic Studies and Sequence Divergence<!>Alignments of Mouse Acid Lipase Amino Acid Sequences<!>Predicted Secondary and Tertiary Structures for Mammalian Acid Lipases<!>Predicted Gene Locations and Exonic Structures for Mammalian Acid Lipase Genes<!>Comparative Mouse Acid Lipase Gene Expression and Transcripts<!>Sequence Identities and Phylogeny of Mammalian Acid Lipases<!>Conclusions<!>

<p>At least six mammalian acid lipase genes have been reported, including LIPA, encoding lysosomal acid lipase/cholesteryl ester hydrolase (E.C.3.1.1.13) (Anderson & Sando, 1991; Anderson et al., 1994; Ameis et al, 1994); LIPF, encoding a gastric lipase (E.C.3.1.1.3) (Bodmer et al., 1987; Lohse et al., 1997) ; LIPJ, expressed in testis (Thierry-Mieg & Theirry-Mieg, 2006) and three other genes (LIPK, LIPM and LIPN), which are expressed in epidermal cells of the body (Toulza et al, 2007) and form part of an acid-lipase gene complex on human chromosome 10 (Deloukas et al., 2004). Acid lipases have the capability to withstand acid conditions and lack any significant homology (<20%) with previously described neutral lipases (Bodmer et al., 1987), including endothelial lipase (LIPE) (Hirata et al., 1999; Jaye et al., 1999), hepatic lipase (LIPC) (Martin et al., 1998), lipoprotein lipase (LIPL) (Wion et al., 1987) and pancreatic lipase (LIPP) (Lowe et al., 1989), which perform specialized roles in lipid metabolism in various tissues and cells of the body.</p><p>LIPA catalyses the deacylation of triacylglycerols and cholesteryl esters of lysosomal low density lipoproteins (LDLs), an essential intracellular lipid catabolic process (Goldstein et al., 1975; Wang et al., 2008). Two major genetic diseases, a severe infantile-onset Wolman disease (Patrick & Lake, 1969; Hoeg et al., 1984) and a milder late-onset cholesteryl ester storage disease (CESD) (Assmann et al.,, 1973), are caused by mutations of the LIPA gene. LIPF is involved with the metabolism of dietary triglycerides under acidic conditions, being synthesized by gastric chief cells in the fundic mucosa of the stomach and responsible for 30% of triglyceride digestion in humans (Bodmer et al., 1987). Structures for other acid lipase genes have been determined, including LIPJ, LIPK, LIPM and LIPN, and derived from whole genome sequences for human chromosome 10 (Deloukas et al., 2004; Toulza et al., 2007) and mouse chromosome 19 (The MGC Project Team, 2004; Carninci et al., 2005), which contain acid lipase gene clusters in each case. Human LIPK, LIPM and LIPN genes are specifically expressed in epidermal cells and may play a role in differentiated keratinocyte cells in the body (Toulza et al., 2007). Mammalian acid lipase genes usually contain 9 coding exons of DNA encoding enzyme sequences which undergo exon shuffling generating several acid lipase isoproteins (Thierry-Mieg and Thierry-Mieg, 2006). Predictive three-dimensional structural analyses of human LIPA have been undertaken using the human gastric lipase as a model, and key residues and sequences have been identified (Roussel et al., 1999).</p><p>This paper reports the predicted gene structures and amino acid sequences for several mammalian acid lipase genes and proteins, including human (Homo sapiens), chimpanzee (Pons troglodytes), rhesus monkey (Macacca mulatta), mouse (Mus musculus), rat (Rattus norvegicus), cow (Bos taurus), horse (Equus caballus) and dog (Canis familaris). Predicted secondary and tertiary structures for mammalian acid lipases are also described, as well as the structural, phylogenetic and evolutionary relationships of these genes and enzymes with other mammalian lipase gene families. In addition, evidence for a new family of acid lipase genes is reported for mouse and rat genomes, designated as Lipo.</p><!><p>BLAST (Basic Local Alignment Search Tool) studies were undertaken using web tools from the National Center for Biotechnology Information (NCBI) (http://blast.ncbi.nlm.nih.gov/Blast.cgi) (Altschul et al, 1997). Protein BLAST analyses used mammalian acid lipase amino acid sequences previously described (Table 1). Non-redundant protein sequence databases for several mammalian and vertebrate genomes were examined using the blastp algorithm, including human (Homo sapiens) (International Human Genome Sequencing Consortium, 2001); chimpanzee (Pan troglodytes) (Chimpanzee Sequencing & Analysis Consortium, 2005); orangutan (Pongo abelii) (Orangutan Genome Project, 2007); rhesus monkey (Mucaca mulatta) (Gibbs et al., 2007), horse (Equus caballus) (Horse Genome Project, 2008), cow (Bos Taurus) (Bovine Genome Project, 2008); mouse (Mus musculus) (Mouse Genome Sequencing Consortium, 2002); rat (Rattus norvegicus) (Rat Genome Sequencing Consortium, 2004); guinea pig (Cavia porcellus) (MGC Project Team, 2004); (dog (Canis familiaris) Dog Genome Project, 2005); and frog (Xenopus tropicalis) (Xenopus tropicalis Genome Project, 2005). This procedure produced multiple BLAST 'hits' for each of the protein databases which were individually examined and retained in FASTA format, and a record kept of the sequences for predicted mRNAs and encoded acid lipase-like proteins . These records were derived from annotated genomic sequences using the gene prediction method: GNOMON and predicted sequences with high similarity scores generated.</p><p>BLAT analyses were subsequently undertaken for each of the predicted acid amino acid sequences using the UC Santa Cruz genome browser [http://genome.ucsc.edu/cgi-bin/hgBlat] (Kent et al. 2003) with the default settings to obtain the predicted locations for each of the mammalian acid lipase genes, including predicted exon boundary locations and gene sizes (see Table 1). Structures for mouse acid lipase isoforms were obtained using the AceView website (http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html?human) to examine predicted gene and protein structures to interrogate this database of mouse mRNA sequences for mouse Lipa, Lipf, Lipk, Lipm, Lipn and Lipo1 genes(Thierry-Mieg and Thierry-Mieg, 2006).</p><!><p>Predicted secondary and tertiary structures for mouse acid lipases were obtained using the PSIPRED v2.5 web site tools provided by Brunel University [http://bioinf.cs.ucl.ac.uk/psipred/psiform.html] (McGuffin et al. 2000) and the SWISS MODEL web tools [http://swissmodel.expasy.org], respectively (Guex & Peitsch 1997; Kopp & Schwede 2004). The reported tertiary structure for human gastric lipase (LIPF) (Roussel et al., 1999) served as the reference for the predicted mouse acid lipase tertiary structures, with a modeling range of residues 22-395 (LIPA); 20-395 (LIPF); 27-394 (LIPK); 40-409 (LIPM); 28-398 (LIPN); and 24-392 (LIPO1). Theoretical isoelectric points and molecular weights for mammalian acid lipases were obtained using Expasy web tools (http://au.expasy.org/tools/pi_tool.html). SignalP 3.0 web tools were used to predict the presence and location of signal peptide cleavage sites (http://www.cbs.dtu.dk/services/SignalP/) for each of the predicted mammalian acid lipase sequences (Emanuelsson et al 2007). The NetNGlyc 1.0 Server was used to predict potential N-glycosylation sites for human, mouse and rat acid lipases (http://www.cbs.dtu.dk/services/NetNGlyc/). Predictions of subcellular locations for mammalian acid lipases were conducted using PSORT 11 (http://psort.ims.u-tokyo.ac.jp/form2.html) (Horton & Nakai, 1997).</p><!><p>The mouse genome browser (http://genome.ucsc.edu) (NCBI37/mm9 2007 assembly) (Kent et al. 2003) was used to examine GNF Expression Atlas 2 data using various expression chips for mouse acid lipase genes Lipa, Lipf, Lipk, Lipm, Lipn and Lipo1 (using GenBank ID AI747699) (http://biogps.gnf.org). Mouse chip expression 'heat maps' were examined for comparative gene expression levels among mouse tissues showing high (red); intermediate (black); and low (green) expression levels.</p><!><p>Alignments of acid lipase protein sequences and percentages of sequence identities were assembled using BioEdit v.5.0.1 and the default settings (Hall, 1999). Alignment ambiguous regions, including the amino and carboxyl termini, were excluded prior to phylogenetic analysis (BioEdit v.5.0.1) yielding alignments of 365 residues for comparisons of mammalian LIPA, LIPF, LIPJ, LIPK, LIPM, LIPN and LIPO sequences with the frog (Xenopus tropicalis) LIPA sequence (Table 1). Evolutionary distances were calculated using the Kimura option (Kimura, 1983) in TREECON (Van de Peer & de Wachter, 1994). Phylogenetic trees were constructed from evolutionary distances using the neighbor-joining method (Saitou & Nei, 1987). Tree topology was reexamined by the boot-strap method (100 bootstraps were applied) of resampling and only values that were highly significant (≥90) are shown (Felsenstein, 1985).</p><!><p>Amino acid sequence alignments for five previously reported mouse acid lipases [LIPA, LIPF, LIPK, LIPM and LIPN (Carninci et al., 2005)] are shown in Figure 1 together with predicted sequences for four new acid lipases (designated LIPO1, LIPO2, LIPO3 and LIPO4). The relative values of sequence identities (41-60%) and comparisons of amino acid sequence alignments for the mouse LIPA, LIPF, LIPK, LIPM, LIPN and LIPO1 sequences strongly suggest that these proteins are products of distinct but related gene families, whereas the predicted mouse LIPO1, LIPO2, LIPO3 and LIPO4 sequences exhibited higher levels of identities (76-96%), indicating that these are members of the same family, designated as LIPO (or Lipo for the gene family) (Table 2).</p><p>Amino acid sequences for these nine mouse acid lipase proteins contained between 395 (LIPF) and 422 (LIPM) residues with the latter exhibiting extended N- and C-termini (Figure 1). The results of three dimensional structural studies for human LIPF were used to identify key residues which are likely to contribute to the catalytic and structural features for these enzymes (sequence numbers refer to mouse LIPA) (Roussel et al., 1999). These included the catalytic triad for the active site (Ser172; Asp343; His372); the active site motif (Gly-Xaa-Ser-Yaa-Gly) (residues 172-176); residues Leu89 and Gln175 (replaced with 175Glu for chicken LIPA) which stabilize the 'oxyanion' transition state during catalysis; and cysteine residues which form a disulfide bond (Cys248/Cys257 [37] to support the enzyme's structure.</p><p>The hydrophobic N-terminus signal peptide function (residues 1-18 for mouse LIPA) has been retained for all of the mouse acid lipase sequences examined, although these vary in length from 18 for LIPA (residues 1-18) to 33 (residues 1-33 for LIPM) (Figure 1). The mannose-6-phosphate containing N-glycosylation site (residues 161-3: Asn-Lys-Thr for mouse LIPA) (Sleat et al., 2006) was not present for other mouse acid lipase sequences, with the exception of mouse LIPN, which supports the reported microlocalization of LIPA within lysosomes (Goldstein et al., 1975). A basic amino acid 'patch' at the mouse LIPA C-terminus (residues 394Lys-395Lys) is present only within the LIPA sequence, which may interact with lysosomal UDP-N-acetylglucosamine phosphotransferase, causing phosphorylation of specific LIPA residues, which are proposed to target this enzyme for lysosomal location (Baranski et al., 1990). Two other high probability N-glycosylation sites predicted for mouse LIPA (Asn36-Val37-Ser38; and Asn273-274Met-275Ser) were also observed for all other human, mouse and rat acid lipase sequences examined. Other high probability N-glycosylation sites are described in Table 3 and Figure 1, including site 2 for human LIPA (72Asn-73His-74Ser) and mouse LIPO1 and LIPO3 sequences; site 3 for mouse LIPA (99Asn-100Ser-101Ser), mouse LIPF (98Asn-99Asn-100Ser), human LIPJ (68Asn-69Asn-70Ser), mouse LIPM (113Asn-114Asn-115Ser) and mouse LIPN (102Asn-103Gly-104Ser); site 5 for human LIPF (185Asn-186Pro-187Ser) and mouse LIPO3 (183Asn-184Gln-185Ser); site 8 for human LIPA (321Asn-322Gln-323Ser), human LIPJ (288Asn-289Gln-290Ser), human LIPN (320Asn-321Gln-322Ser) as well as mouse and rat LIPO sequences (316Asn-317Gln-318Ser for mouse LIPO1); site 9 for human LIPF (327Asn-328Val-329Thr) and LIPK (327 Asn-328Ile-329Thr); site 10 for mouse LIPO sequences (357Asn-358Leu-359Thr); and site 11 for human LIPN (413Asn-414Leu-415Ser). Four N-glycosylation sites have been previously identified for human LIPJ by three dimensional studies (Roussel et al., 1999) which may contribute to the stability and activity of this enzyme in acid environments. Individual differences were observed for the theoretical isoelectric points (pI) of the human, mouse and rat acid lipases examined, with higher values (pI values > 8) predicted for human LIPK, mouse LIPK and LIPM and rat LIPK, LIPM and LIPN, as compared with the other acid lipases examined, which exhibited lower predicted pI values (Table 1).</p><!><p>Analyses of predicted secondary structures for mammalian acid lipase sequences were compared with the previously reported secondary structure for human LIPF, or human gastric lipase, and the predicted structure for human LIPA (Roussel et al., 1999) (Figure 1). Similar α-helix β-sheet structures were observed for all of the mammalian acid lipases examined, particularly near key residues or functional domains, including the α-helix within the N-terminal signal peptides, the β-sheet and α-helix structures surrounding the active site Ser172 (for mouse LIPA) and the α-helix enclosing the lysosomal targeting signal residues (Asn-Lys-Thr residues 159-161 for mouse LIPA). The pattern of secondary structures were very similar to those reported for human LIPF and predicted for human LIPA and are numbered according to Roussel and coworkers (1999). These have been previously described as globular enzymes which are α/β hydrolase-like, contain a core domain between residues 26-200 and 326-396 (see Figure 1 for mouse LIPA), and a central β-sheet composed of 8 strands, designated as β1 – β8, and 6 α-helices, designated as α1, αA, αB1/B2, αC1/C2, αE and αF, with 3 helices on each side of the central β-sheet. In addition, a 'Cap' domain is described for human LIPF and LIPA with 8 helices (designated as αe1-αe8) within residues 203-329 for human LIPA (Roussel et al., 1999). This domain may serve as a 'lid' for the active site Ser174, restricting access to the aqueous environment but enabling cholesteryl ester and other substrate entry when the 'lid' opens. All of these secondary structures have been retained for the mammalian acid lipases examined however these are based on predictions and may not reflect fully structures in vivo.</p><p>The predicted tertiary structures for mouse LIPF, LIPK, LIPA, LIPM, LIPN and LIPO1 were sufficiently similar to the previously reported human LIPF (gastric acid lipase) and the predicted human LIPA structures (Roussel et al., 1999) (Figure 2) to enable predictions of these tertiary structures which were based on incomplete sequences for these enzymes (residues 22-393 for mouse LIPA). The predictions observed suggest that the secondary and tertiary structures for human LIPF and LIPA resemble those for each of the six mouse acid lipase proteins examined, reflecting conservation of the major structural features for these enzymes.</p><!><p>Table 1 summarizes the predicted locations for mammalian acid lipase genes based upon BLAT interrogations of several mammalian genomes using the reported sequences for human and mouse acid lipases, LIPA (Anderson et al., 1994; Ameis et al, 1994), LIPF (Bodmer et al., 1987; Lohse et al., 1997), LIPJ, LIPK, LIPM and LIPN) (Deloukas et al., 2004; Toulza et al, 2007), and the predicted sequences for rat acid lipases (see Table 1 for sources) and the UC Santa Cruz Genome Browser (Kent et al. 2003). The mammalian acid lipase genes were located in a gene cluster in each case, although the gene order underwent changes for different species, including an addition of one (rat) or four (mouse) acid lipase genes, designated as LIPO (Lipo for the gene family). Supplementary Table 1 also provides data for other mammalian acid lipases genes, including those predicted for chimpanzee, orangutan, horse, cow, guinea pig and dog genomes. These BLAT interrogations of mammalian genomes with the corresponding acid lipase sequences suggested that the gene cluster was syntenic for chromosomes 10 (human, chimp and orangutan), 9 (rhesus monkey), 19 (mouse), 1 (rat and horse) and 26 (cow and dog). Figure 1 summarizes the predicted exonic start sites for human, mouse and rat acid lipase genes with each having 9 coding exons, in identical or similar positions to those reported for the human acid lipase genes (Deloukis et al., 2004).</p><!><p>Figure 3 illustrates the comparative predicted structures of mRNA mouse acid lipase gene transcripts (http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html?mouse) for the major transcript isoform in each case (Theirry-Mieg & Thierry-Mieg, 2006). There were 9 introns present for the mRNA transcripts for all mouse acid lipase genes with the exception of Lipo1, which contained 10 introns, and 9 coding exons. Mouse Lipa and Lipo1 transcripts were encoded on the minus strand whereas other mouse acid lipases were encoded on the positive strand (Table 1; Figure 3). With the exception of mouse Lipn transcripts, mouse acid lipase transcripts contained extended 3′-noncoding sequences.</p><p>Figure 4 presents 'heat maps' showing comparative gene expression for various mouse tissues obtained from GNF Expression Atlas Data using the U74a (Lipa), GNF1N (Lipf, Lipk Lipn and Lipo) and U74b (Lipm) mouse chips (http://genome.ucsc.edu; http://biogps.gnf.org). These data supported a broad tissue expression for mouse Lipa (Du et al., 1996); mouse Lipf expression in tissues associated with digestion, including pancreas, stomach and salivary gland (Bodmer et al., 1987; and Lipk, Lipm and Lipn expression at higher levels particularly in epidermal tissues, but also in tongue, trachea, liver and kidney (Lipk), trachea, bone marrow and eye (Lipm) and in liver and kidney (Lipn). In contrast, Lipo expression (data available only for the Lipo1 gene) showed higher levels only in the salivary gland. Mouse acid lipase gene expression levels were compared with the expression for average mouse gene (see Table 1) (Theirry-Mieg & Thierry-Mieg, 2006) (http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html?mouse). Average or higher expression levels were observed for mouse Lipa, Lipf and Lipo1 acid lipase genes, while Lipj, Lipk, Lipm and Lipn showing lower than average expression in the mouse. Similar results were observed for human acid lipase genes with LIPA and LIPF having much higher levels of expression than the average human gene and the other acid lipase genes, LIPJ, LIPK, LIPM and LIPN.</p><!><p>Table 2 summarizes the percentages of identity for human and mouse acid lipase family sequences (and the rat LIPO sequence) which are ≥ 74% identical in comparison with the 44-62% identities observed comparing sequence identities between acid lipase families. This supports a proposal for at least 7 mammalian acid lipase gene families, namely LIPA, LIPF, LIPJ, LIPK, LIPM, LIPN and LIPO (designated as Lipo for mouse and rat genes for consistency with other rodent acid lipase genes).</p><p>Phylogenetic trees (Figure 5) were constructed from alignments of mammalian acid lipase-like amino acid sequences with the frog (Xenopus tropicalis) LIPA sequence. The dendrogram showed clustering of the sequences into 7 mammalian acid lipase gene family groups. This is consistent with these gene families being present throughout mammalian evolution and of an origin of more than ~100 million years ago, which corresponds to the time of appearance for the eutherian mammalian common ancestor (Woodburne et al., 2003; Donoghue & Benton, 2007). Figure 5 also shows the number of times a clade (sequences common to a node or branch) occurred in the bootstrap analyses with replicate values of 90 or more (which are highly significant) for the 100 replicates undertaken in each case. Of particular interest are the nodes demonstrating highly significant separations for each of the mammalian acid lipase gene family sequences (LIPA, LIPF, LIPJ, LIPK, LIPM, LIPN and LIPO) sequences during mammalian evolution, which supports the separate family status for each of these genes. There were however species differences in the distribution of these mammalian gene families, with LIPJ apparently absent in rodents (mouse, rat and guinea pig), while the Lipo gene family was found only in mouse and rat genomes among the mammalian species studied (Table 1; Figure 5). The highly significant clustering of the mammalian LIPA clade with the single frog acid lipase sequence reported (designated as frog LIPA) (Table 1) suggests that LIPA may have served as a primordial gene for subsequent gene duplication events generating the 7 families of mammalian acid lipases. The sequence and timing however for these proposed acid lipase gene duplication events remain to be determined.</p><!><p>The results of this present study support previous studies for at least 6 mammalian acid lipase genes and encoded acid lipases, namely LIPA (encoding lysosomal lipase), LIPF (encoding gastric lipase), LIPJ (encoding a human testis lipase), and LIPK, LIPM and LIPN (encoding epidermal lipases). This report also reports evidence for a new acid lipase gene family in mouse and rat (designated as Lipo), for which the mouse genome contains 4 Lipo-like genes, designated as Lipo1, Lipo2, Lipo3 and Lipo4, whereas the rat genome contains a single Lipo gene. All of these mammalian acid lipase sequences share key conserved sequences and predicted secondary and tertiary structures that have been reported for human LIPJ and LIPA (Roussel et al., 1999), including active site and catalytic transition state supporting residues, as well as disulfide bond forming cysteine residues. A specific N-glycosylation site involved in the localization of mammalian LIPA within lysosomes was also conserved within mammalian LIPA sequences. Comparative gene expression data showed that human and mouse LIPA and LIPF genes are expressed at higher levels than those for the average gene (as defined by Theirry-Mieg & Thierry-Mieg, 2006; http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/index.html?mouse) . This is consistent with key metabolic roles for these enzymes in lysosomal cholesterol ester and triglyceride metabolism and in gastric triglyceride metabolism, respectively. A high level of expression for mouse Lipo1 was also observed in the salivary gland, which may indicate a supporting role for this acid lipase in triglyceride hydrolysis, either during mastication of food or the subsequent digestion in the stomach . Phylogeny studies using several mammalian acid lipases (human, chimp, orangutan, mouse, rat, guinea pig, horse, cow and dog) indicated that these genes have apparently appeared prior to the eutherian common ancestor more than 100 million years ago, and may have evolved from one or more vertebrate acid lipase gene common ancestors, which include the vertebrate LIPA gene.</p><!><p>Supplementary Table 1: Other mammalian acid lipase (LIPA, LIPF, LIPJ, LIPK, LIPM, LIPN and LIPO) genes and proteins. 1RefSeq: the reference amino acid sequence; 2predicted Ensembl amino acid sequence; and 3BLAT predicted amino acid sequences are shown (see http://www.ncbi.nlm.nih.gov ); GenBank IDs are derived from NCBI sources http://www.ncbi.nlm.nih.gov/genbank/; Ensembl ID was derived from Ensembl genome database http://www.ensembl.org ; 4unknown chromosomal location for cow LIPN gene; 5result not available; bps refers to base pairs of nucleotide sequences; pI refers to theoretical isoelectric points; the number of coding exons are listed. Sources for acid lipase sequences were provided by the above sources (see Table 1).</p>

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