Table 3.
Optimization of binding affinity predictor models based on the regression model ΔGcalc = w1P1 + w2P2 + …. + Q
| Properties (PN) | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 |
|---|---|---|---|---|---|---|
| ICs_total | 0.07782 | - | - | - | - | - |
| ICs_charged/charged | - | - | / | - | - | 0.09420 |
| ICs_charged/polar | - | - | / | - | - | / |
| ICs_charged/apolar | - | - | 0.11627 | - | - | 0.10038 |
| ICs_polar/polar | - | - | −0.12655 | - | - | −0.19522 |
| ICs_polar/apolar | - | - | 0.23595 | - | - | 0.22609 |
| ICs_apolar/apolar | - | - | / | - | - | / |
| ICs_hydrophil/hydrophil | - | - | - | 0.09055 | - | - |
| ICs_hydrophil/hydrophob | - | - | - | 0.05726 | - | - |
| ICs_hydrophob/hydrophil | - | - | - | 0.06037 | - | - |
| BSA_total | - | 0.00278 | - | - | - | - |
| BSA_polar | - | - | - | - | 0.00131 | - |
| BSA_apolar | - | - | - | - | 0.00400 | - |
| %NIS_polar | - | - | - | - | - | / |
| %NIS_apolar | - | - | - | - | - | −0.18786 |
| %NIS_charged | - | - | - | - | - | −0.13872 |
| Intercept (Q) | 4.78839 | 5.66032 | 5.13766 | 4.90452 | 5.44809 | 15.9433 |
| R | −0.59 | −0.46 | −0.67 | −0.60 | −0.48 | −0.73 |
| p-value | <0.0001 | <0.0001 | <0.0001 | <0.0001 | <0.0001 | <0.0001 |
| RMSE (kcal mol−1) | 2.25 | 2.46 | 2.08 | 2.22 | 2.45 | 1.89 |
The weights wN are reported for each properties PN used to train Model N. Properties that have not been used for training the Model or have been evaluated as not relevant from the Akaike's An Information Criterion (AIC) evaluation are reported as ‘-’ and ‘/’, respectively. At the bottom of the table, the correlation coefficient and prediction error (expressed as R and RMSE) are reported.