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README.md
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- split: test
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path: data/test-*
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---
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path: data/test-*
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---
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# PSR: Protein Structure Ranking
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## Overview
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This task relates to predicting the three-dimensional structure of a protein
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molecule, given its sequence. A total of around 700 protein targets are included,
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which consist of protein targets from Critical Assessment of Structure
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Prediction (CASP) 5-13.
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We phrase this problem as decoy ranking. For each protein target, we
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include its decoys sets compiled from the CASP decoy sets released for the
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Model Quality Assessment (MQA). We relax those structures with the SCWRL4
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software (Krivov and Dunbrack, 2019) to improve side-chain conformations. For
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each decoy, we calculate the RMSD, TM-score, GDT_TS, and GDT_HA scores to the
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experimentally determined structure using the TM-score software (Zhang and
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Skolnick, 2007).
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## Datasets
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- splits:
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- split-by-year: This dataset contains data in the CASP dataset, but is split
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temporally. More specifically, we randomly split the targets in CASP5-10 and
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randomly sample 50 decoys for each target to generate the training and validation
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sets (508 targets for training, 56 targets for validation), and use the CASP11
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Stage 2 as test set (85 targets total, with 150 decoys for each target, excluding
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the native structures).
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## Citation Information
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```
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@article{townshend2020atom3d,
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title={Atom3d: Tasks on molecules in three dimensions},
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author={Townshend, Raphael JL and V{\"o}gele, Martin and Suriana, Patricia and Derry, Alexander and Powers, Alexander and Laloudakis, Yianni and Balachandar, Sidhika and Jing, Bowen and Anderson, Brandon and Eismann, Stephan and others},
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journal={arXiv preprint arXiv:2012.04035},
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year={2020}
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}
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```
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```
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@article{kryshtafovych2019critical,
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title={Critical assessment of methods of protein structure prediction (CASP)—Round XIII},
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author={Kryshtafovych, Andriy and Schwede, Torsten and Topf, Maya and Fidelis, Krzysztof and Moult, John},
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journal={Proteins: Structure, Function, and Bioinformatics},
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volume={87},
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number={12},
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pages={1011--1020},
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year={2019},
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publisher={Wiley Online Library}
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}
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```
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