Using macromolecular electron densities to improve the enrichment of active compounds in virtual screening

Abstract

The quest for more effective virtual screening algorithms is hindered by the scarcity of training data, calling for innovative approaches. This study presents the first use of experimental electron density (ED) data for improving active compound enrichment in virtual screening, supported by EDs ability to reflect the time-averaged behavior of ligands and solvents in the binding pocket. Experimental ED-based grid matching score (ExptGMS) was developed to score compounds by measuring the degree of matching between their binding conformations and a series of multi-resolution experimental ED grids. The efficiency of ExptGMS was validated using both in-silico tests with the Directory of Useful Decoys-Enhanced dataset and wet-lab tests on Covid-19 3CLpro-inhibitors. ExptGMS improved the active compound enrichment in top-ranked molecules by approximately 20%. Furthermore, ExptGMS helped identify four new and active inhibitors of 3CLpro, with the top showing an IC50 value of 1.9 {micro}M. To facilitate the use of ExptGMS, we developed an online database containing experimental ED grids for over 17,000 proteins.