The lack of biologically relevant protein and ligand structures can hinder rational design of small molecules to target G protein-coupled receptors (GPCRs). We have developed original computational approaches for small-molecule drug discovery, which allow us to achieve higher design accuracy for the hit search of difficult GPCR targets. For example, our essential dynamics ensemble docking (EDED) approach can effectively reduce the number of false negatives for virtual screening and improve the accuracy to seek potent compounds. Another example using a machine learning model, GPCRLigNet, is also presented, which demonstrated an enrichment of potentially potent molecules. Incorporation of GPCRLigNet into a high-throughput virtual screening workflow is also shown. Overall, our findings point out directions how to explore the protein conformational space and the small-molecule chemical space with computational approaches for drug design.

Multiscale modeling for exploring chemical space for GPCR drug design

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