Addressing limitations with the MM-GB/SA scoring procedure using the WaterMap method and free energy perturbation calculations.

The MM-GB/SA scoring technique has become an important computational approach in drug design. We, and others, have demonstrated that for congeneric molecules the correlation with experimental data obtained with the physics-based scoring is usually superior to scoring functions from typical docking algorithms. Despite showing good accuracy when applied within a series, much work is necessary to improve the MM-GB/SA method in order to gain greater efficiency in drug design. Here, we investigate the poor estimation of protein desolvation provided by the GB/SA solvation model and the large dynamic range observed in the MM-GB/SA scoring compared to that of the experimental data. In the former, replacing the GB/SA protein desolvation in the MM-GB/SA method by the free energy associated with displacing binding site waters upon ligand binding estimated by WaterMap provides the best results when ranking congeneric series of factor Xa and cyclin-dependent kinase 2 (CDK2) inhibitors. However, the improvement is modest over results obtained with the MM-GB/SA and WaterMap methods individually, apparently due to the high correlation between the free energy liberation of the displaced solvent and the protein-ligand van der Waals interactions, which in turn may be interpretable as estimates of the hydrophobic effect and hydrophobic-like interactions, respectively. As for the large dynamic range, comparisons between MM-GB/SA and FEP calculations indicate that for the factor Xa test set this problem has its origin in the lack of shielding effects of protein--ligand electrostatic interactions; that overly favors ligands that engage in hydrogen bonds with the protein.