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from mpi4py import MPI |
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from mpi4py.futures import MPICommExecutor |
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import warnings |
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from Bio.PDB import PDBParser, PPBuilder, CaPPBuilder |
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from Bio.PDB.NeighborSearch import NeighborSearch |
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from Bio.PDB.Selection import unfold_entities |
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import numpy as np |
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import dask.array as da |
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from rdkit import Chem |
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import os |
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import re |
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import sys |
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punctuation_regex = r"""(\(|\)|\.|=|#|-|\+|\\|\/|:|~|@|\?|>>?|\*|\$|\%[0-9]{2}|[0-9])""" |
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molecule_regex = r"""(\[[^\]]+]|Br?|Cl?|N|O|S|P|F|I|b|c|n|o|s|p|\(|\)|\.|=|#|-|\+|\\|\/|:|~|@|\?|>>?|\*|\$|\%[0-9]{2}|[0-9])""" |
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max_seq = 2046 |
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max_smiles = 510 |
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chunk_size = '1G' |
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def parse_complex(fn): |
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try: |
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name = os.path.basename(fn) |
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parser = PDBParser() |
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with warnings.catch_warnings(): |
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warnings.simplefilter("ignore") |
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structure = parser.get_structure('protein',fn+'/'+name+'_protein.pdb') |
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ppb = CaPPBuilder() |
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seq = [] |
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xyz_receptor = [] |
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for pp in ppb.build_peptides(structure): |
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seq.append(str(pp.get_sequence())) |
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xyz_receptor += [tuple(a.get_vector()) for a in pp.get_ca_list()] |
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seq = ''.join(seq) |
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suppl = Chem.SDMolSupplier(fn+'/'+name+'_ligand.sdf') |
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mol = next(suppl) |
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smi = Chem.MolToSmiles(mol) |
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atom_order = [int(s) for s in list(filter(None,re.sub(r'[\[\]]','',mol.GetProp("_smilesAtomOutputOrder")).split(',')))] |
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tokens = list(filter(None, re.split(molecule_regex, smi))) |
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masked_tokens = [re.sub(punctuation_regex,'',s) for s in tokens] |
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k = 0 |
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token_pos = [] |
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for i,token in enumerate(masked_tokens): |
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if token != '': |
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token_pos.append(tuple(mol.GetConformer().GetAtomPosition(atom_order[k]))) |
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k += 1 |
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else: |
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token_pos.append((np.nan, np.nan, np.nan)) |
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return name, seq, smi, xyz_receptor, token_pos |
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except Exception as e: |
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print(e) |
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return None |
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if __name__ == '__main__': |
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import glob |
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filenames = glob.glob('data/pdbbind/v2020-other-PL/*') |
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filenames.extend(glob.glob('data/pdbbind/refined-set/*')) |
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filenames = sorted(filenames) |
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comm = MPI.COMM_WORLD |
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with MPICommExecutor(comm, root=0) as executor: |
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if executor is not None: |
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result = executor.map(parse_complex, filenames) |
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result = list(result) |
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names = [r[0] for r in result if r is not None] |
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seqs = [r[1] for r in result if r is not None] |
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all_smiles = [r[2] for r in result if r is not None] |
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all_xyz_receptor = [r[3] for r in result if r is not None] |
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all_xyz_ligand = [r[4] for r in result if r is not None] |
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import pandas as pd |
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df = pd.DataFrame({'name': names, 'seq': seqs, 'smiles': all_smiles, 'receptor_xyz': all_xyz_receptor, 'ligand_xyz': all_xyz_ligand}) |
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df.to_parquet('data/pdbbind.parquet') |
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