Evaluation of Advanced Structure-Based Virtual Screening Methods for Computer-Aided Drug Discovery

Abstract

Computational virtual screening has become an essential platform of drug discovery for the efficient identification of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is stil required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structure- activity relationship (QSAR). Our results show that the ensemble-average fre energy estimation, including implicit solvation energy terms, significantly improves the hit that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.