Identification of free fatty acid receptor 2 agonists using virtual screening

Abstract

Structure- and ligand-based virtual-screening methods (docking, 2D- and 3D-similarity searching) were analyzed for their effectiveness in virtual screening against FFAR2. To evaluate the performance of these methods, retrospective virtual screening was performed. Statistical quality of the methods was evaluated by BEDROC and RIE. The results revealed that electrostatic similarity search protocol using EON (ET combo) outperformed all other protocols with outstanding enrichment of >95% in top 1% and 2% of the dataset with an AUC of 0.958. Interestingly, the hit lists that are obtained from different virtual-screening methods are generally highly complementary to hits found from electrostatic similarity searching. These results suggest that considering electrostatic similarity searching first increases the chance of identifying more (and more diverse) active compounds from a virtual-screening campaign. Accordingly, prospective virtual screening using electrostatic similarity searching was used to identify novel FFAR2 ligands. The discovered compounds provide new chemical matter starting points for the initiation of a medicinal chemistry campaign.

Keywords: Electrostatic similarity searching; FFAR; GPCR; Ligand-based; Virtual screening.