Dynamics, allostery, and signalling bias in g protein–coupled receptors

G protein-coupled receptors (GPCRs) are central to cellular signal transduction and represent the most intensively targeted protein family in pharmacology. This thesis presents a comprehensive computational analysis of Class A GPCR dynamics, with a focus on activation mechanisms, biased signaling, and allosteric regulation. Conventional MD simulations struggle to capture large-scale, long-timescale motions. To address these limitations, we employed the Anisotropic Network Model–Langevin Dynamics (ANM-LD) framework to model 30 conformational transitions across 25 GPCRs, including dual activation pathways for five receptors. These simulations generated dynamic ensembles of intermediate states, validated using hallmark collective variables such as TM6 tilt and TM7 shift. Covibrational mode analysis revealed distinct dynamical signatures for G protein– and ß-arrestin–bound states, highlighting pathway-specific encoding of collective motions. Mechanistic insights into biased signaling revealed that key hinge residues, including the DRY and NPxxY motifs, were identified as critical mediators of pathway-selective transitions. GNM-based transfer entropy (GNM-TE) analysis demonstrated strong receptor-driven information flow from the orthosteric binding site in both signaling states. A newly developed metric, the Differential Coupling Score, captured structural segments involved in signaling bias. Additionally, ensemble-level comparisons across 300 structures revealed conserved allosteric scaffolds and dynamic diversity associated with ligand type and signaling partner. In particular, Helix 8 and TM7-IC emerged as flexible hubs modulating pathway-specific communication. These findings provide a unified and generalizable framework for decoding GPCR dynamics and guiding the design of biased ligands and allosteric modulators.