Dataset Description: The interaction of 72 kinase inhibitors with 442 kinases covering >80% of the human catalytic protein kinome.
Task Description: Regression. Given the target amino acid sequence/compound SMILES string, predict their binding affinity.
Dataset Statistics: 0.3.2 Update: 25,772 DTI pairs, 68 drugs, 379 proteins. Before: 27,621 DTI pairs, 68 drugs, 379 proteins.
[1] Davis, M., Hunt, J., Herrgard, S. et al. Comprehensive analysis of kinase inhibitor selectivity. Nat Biotechnol 29, 1046–1051 (2011).
[2] Huang, Kexin, et al. “DeepPurpose: a Deep Learning Library for Drug-Target Interaction Prediction” Bioinformatics.
Variants: DAVIS-DTA
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Drug Discovery | SMT-DTA | SSM-DTA: Breaking the Barriers of … | 2022-06-20 |
| Drug Discovery | DeepPurpose | DeepPurpose: a Deep Learning Library … | 2020-04-19 |
| Drug Discovery | DeepDTA | DeepDTA: Deep Drug-Target Binding Affinity … | 2018-01-30 |
Recent papers with results on this dataset: