Elucidating the Structure and Activation Mechanisms of GPCRs Using Modern Computational and AI Tools.

G protein-coupled receptors (GPCRs) form the largest family of membrane-spanning signaling proteins that allow cells to detect and respond to a wide range of extracellular signals. Although they are key drug targets in over a third of FDA-approved medicines, our understanding of the allosteric mechanisms that control GPCR activation and signal transduction remains limited. Recent advances in high-resolution structural techniques, such as cryo-electron microscopy (cryo-EM) and X-ray crystallography, combined with innovative molecular dynamics (MD) simulations and AI-driven structural prediction models, have significantly expanded our knowledge of GPCR conformational states. This review explores the structural basis of GPCR activation, highlighting conserved activation motifs like D(E)RY, NPxxY, and CWxP, as well as changes in transmembrane helices, interaction sites for G proteins and arrestins, and the roles of membrane lipids and allosteric modulators. It discusses the increasing use of machine learning (ML) and deep learning (DL) in structure prediction, ligand bias analysis, free-energy landscape mapping, and conformational classification. Ultimately, the review underscores how combining AI tools with traditional MD and enhanced sampling techniques can deepen our understanding of GPCR activation pathways, aiding rational drug development.