Flexible Blind Self-Docking on PDBBind (unseen receptors)
1.6Ligand RMSD (25p)FABIND+
Evaluation results
| Method | Links | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FABIND+strategy=REGRESSION2024.03 | 1.6 | 3.3 | 8.9 | 7 | 34.7 | 63.2 | 0.5 | 1.5 | 4.2 | 5.1 | 58.3 | 77.1 | |
| FABIND+strategy=SAMPLING, number of samples=102024.03 | 1.6 | 3.2 | 9 | 7.4 | 33.3 | 61.8 | 0.6 | 1.4 | 4.3 | 5.7 | 59 | 75 | |
| FABIND+strategy=SAMPLING, number of samples=402024.03 | 1.6 | 3.3 | 8.8 | 7.1 | 35.4 | 61.1 | 0.6 | 1.5 | 4.9 | 5.3 | 58.3 | 76.3 | |
| FABINDType=Deep learning-based method2024.03 | 2.2 | 3.4 | 8.3 | 7.7 | 19.4 | 60.4 | 0.9 | 1.5 | 4.7 | 5.9 | 57.6 | 75.7 | |
| DIFFDOCKType=Deep learning-based method, number of samples=402024.03 | 2.8 | 6.4 | 16.3 | 12 | 17.2 | 42.3 | 1 | 2.7 | 14.2 | 9.8 | 43.3 | 62.6 | |
| E3BINDType=Deep learning-based method2024.03 | 3 | 6.1 | 10.2 | 10.1 | 6.3 | 38.9 | 1.2 | 2.3 | 7 | 7.6 | 43.8 | 66 | |
| DIFFDOCKType=Deep learning-based method, number of samples=102024.03 | 3.2 | 6.4 | 16.5 | 11.8 | 14.2 | 38.7 | 1.1 | 2.8 | 13.3 | 9.3 | 39.7 | 62.6 | |
| QVINA-WType=Traditional docking software2024.03 | 3.4 | 10.3 | 28.1 | 16.9 | 15.3 | 31.9 | 1.3 | 6.5 | 26.8 | 15.2 | 35.4 | 47.9 | |
| GLIDEType=Traditional docking software2024.03 | 3.4 | 18 | 31.4 | 19.6 | 19.6 | 28.7 | 1.1 | 17.6 | 29.1 | 18.1 | 29.4 | 40.6 | |
| TANKBINDType=Deep learning-based method2024.03 | 3.4 | 5.7 | 10.8 | 10.5 | 3.5 | 43.7 | 1.2 | 2.6 | 8.4 | 8.2 | 40.9 | 70.8 | |
| GNINAType=Traditional docking software2024.03 | 4.5 | 13.4 | 27.8 | 16.7 | 13.9 | 27.8 | 2 | 10.1 | 27 | 15.1 | 25.7 | 39.5 | |
| SMINAType=Traditional docking software2024.03 | 4.8 | 10.9 | 26 | 15.7 | 9 | 25.7 | 1.6 | 6.5 | 25.7 | 13.6 | 29.9 | 41.7 | |
| EQUIBINDType=Deep learning-based method2024.03 | 5.9 | 9.1 | 14.3 | 11.3 | 0.7 | 18.8 | 2.6 | 6.3 | 12.9 | 8.9 | 16.7 | 43.8 | |
| VINAType=Traditional docking software2024.03 | 7.9 | 16.6 | 27.1 | 18.7 | 1.4 | 12 | 2.4 | 15.7 | 26.2 | 16.1 | 20.4 | 37.3 |