| dataset_info: | |
| features: | |
| - name: input_ids | |
| sequence: int16 | |
| - name: coords | |
| sequence: | |
| sequence: float64 | |
| - name: labels | |
| dtype: int64 | |
| splits: | |
| - name: train | |
| num_bytes: 60578601712 | |
| num_examples: 3820837 | |
| - name: val | |
| num_bytes: 3036676376 | |
| num_examples: 192371 | |
| - name: test | |
| num_bytes: 10230362892 | |
| num_examples: 648372 | |
| download_size: 12182948798 | |
| dataset_size: 73845640980 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: val | |
| path: data/val-* | |
| - split: test | |
| path: data/test-* | |
| # Residue identity prediction | |
| ## Overview | |
| Understanding the structural role of individual amino acids is important for engineering new proteins. | |
| We can understand this role by predicting the substitutabilities of different amino acids at a given protein site based on the surrounding structural environment. | |
| We generate a novel dataset consisting of atomic environments extracted from nonredundant structures in the PDB. | |
| We formulate this as a classification task where we predict the identity of the amino acid in the center of the environment based on all other atoms. | |
| ## Datasets | |
| - splits: | |
| - split-by-cath-topology: split by CATH 4.2 topology class at the domain level (NOTE: only indices available for download currently due to size of dataset) | |
| ## Citation Information | |
| ``` | |
| @article{townshend2020atom3d, | |
| title={Atom3d: Tasks on molecules in three dimensions}, | |
| 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}, | |
| journal={arXiv preprint arXiv:2012.04035}, | |
| year={2020} | |
| } | |
| ``` |