Shannon Smith

Structure-based drug discovery has become a valuable tool during early stages in pharmacological development campaigns. This project develops a computational pipeline for structure-based virtual screening in G-protein coupled receptors (GPCRs), a protein family targeted for countless disease indications. Inhibition of the protease-activated receptor 4 (PAR4) GPCR has demonstrated promise as a target in anti-platelet drug development. The goal of this screening effort is to obtain new chemistries for drug development that probes PAR4 deeper in the transmembrane region of the binding pocket, a feature critical for PAR4 inhibition. This pipeline uses an array of computational tools, including multiple-template comparative modeling in Rosetta, DOCK ultra-large screening libraries, Rosetta ligand docking and machine learning-based cheminformatics to prune new small-molecule chemistry. For broader impact, this protocol is general enough to be used across the GPCR super-family and potentially towards other protein targets for small molecule development.