Abstract
G protein-coupled receptors (GPCRs) are a prominent class of therapeutic targets for which structure-based drug discovery (SBDD) has traditionally been challenging to apply. However, recent artificial intelligence (AI)-powered breakthroughs have opened new avenues. Here, we discuss the impact of computational models on hit discovery and lead optimization for GPCRs. We also provide best practices for generating and validating predictive models for prospective use.