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.