Effects of Variable Docking Conditions and Scoring Functions on Corresponding Protein-Aligned Comparative Molecular Field Analysis Models Constructed from Diverse Human Protein Tyrosine Phosphatase 1B Inhibitors

Abstract

The effects of variable docking conditions and scoring functions on corresponding protein-aligned comparative molecular field analysis (CoMFA) models have been assessed. To this end, a group of diverse inhibitors were docked into the active site of human protein tyrosine phosphatase 1B (h-PTP 1B). The docked structures were utilized to construct corresponding protein-aligned CoMFA models by employing probe-based (H+, OH, CH3) energy grids and genetic partial least squares (G/PLS) statistical analysis. A total of 48 different docking configurations were evaluated, of which some succeeded in producing self-consistent and predictive CoMFA models. However, the best CoMFA model coincided with docking the un-ionized ligands into the hydrated form of the binding site via the PLP1 scoring function and restricted docking settings (r2(LOO) = 0.647, r2(PRESS) against 27 test compounds = 0.617). Interestingly, the most significant CoMFA models were orthogonal and corresponded to significantly different docked conformers/poses. To utilize the predictive potentials of the best CoMFA models collectively, it was decided to combine them in a single quantitative structure-activity relationship (QSAR) model. The combination model illustrated excellent statistical properties (r2(LOO) = 0.890, r2(PRESS) against 27 test compounds = 0.750).