Table 1. Docking Power and Screening Power of RTMScore on CASF-2016 Data Set When Using the Unbiased Pocket Selection Method, Compared with Other State-of-the-Art Models.
| Docking
Power (Success Rate) |
Forward
Screening Power |
||||
|---|---|---|---|---|---|
| Model Name | Without native poses | With native poses | EF1% | Top1 success rate | Reference |
| RTMScore1-unBiased | 0.877 | 0.909 | 24.84 | 0.509 | This work |
| RTMScore1-Biased | 0.937 | 0.986 | 28.78 | 0.737 | (171) |
| DeepDock | 0.870 | – | 16.41 | 0.439 | (170) |
| PIGNet | 0.870 | – | 19.6 | 0.554 | (172) |
| DeepBSP | 0.872 | 0.885 | – | – | (173) |
| OnionNet-SFCT | – | 0.937 | 15.50 | 0.421 | (174) |
| ΔLin_F9XGB | – | 0.867 | 12.61 | 0.404 | (154) |
| ΔVinaXGB | – | 0.916 | 13.14 | 0.368 | (152) |
| ΔVinaRF20 | 0.849 | 0.891 | 11.73 | 0.421 | (149) |
| KORP-PL | 0.856 | 0.891 | 22.23 | 0.421 | (175) |
| GlideScore-SP | 0.846 | 0.877 | 11.44 | 0.368 | (23) |
| ChemPLP@GOLD | 0.832 | 0.860 | 11.91 | 0.351 | (176) |
| AutoDock Vina | 0.846 | 0.902 | 7.70 | 0.298 | (22) |