BPS2026 – Illuminating GPCR signaling with integrative modeling, structural dynamics, and AI-driven discovery

Understanding how ligands drive efficacy in G protein-coupled receptor (GPCR) signaling requires connecting experimentally derived high-resolution structural snapshots with the underlying dynamics and kinetics of receptor-G protein activation. Because no single technique can provide this complete picture, we integrate experimental and computational data from multiple sources to dissect these mechanisms. I will present two recent advances from my laboratory: (1) an integrative Bayesian framework that refines molecular dynamics (MD) ensembles of GPCR-G protein complexes using single-molecule kinetic measurements, and (2) statistical analyses of long-timescale MD simulations of experimentally derived intermediate states that reveal how ligands with different efficacy and safety profiles modulate conformational transitions along the activation pathway. These approaches define, at atomic resolution, the distinct kinetic landscapes that link ligand efficacy to receptor-G protein dynamics, offering new mechanistic insight and guiding strategies for the design of safer therapeutics.