Computational and biophysical analysis uncovers a dynamic allosteric site in the vasopressin V2 receptor, highlighting a conformation-aware platform for GPCR-targeted drug discovery.
Allostery governs the functional dynamics of proteins by regulating their conformational transitions. A major challenge lies in identifying dynamic allosteric sites, which are often not discernible from static structural data. Here, we developed an integrative computational framework combining molecular dynamics (MD) simulations, Markov state modeling (MSM), and mutual information (MI) analysis to investigate the vasopressin V2 receptor (V2R). Through multiple-replica MD simulations, we reconstructed the receptor's conformational landscape, which was statistically refined using MSM to determine equilibrium populations and transition kinetics. Key structural motifs associated with activation were quantitatively characterized. Candidate allosteric sites were systematically prioritized through MI-based residue interaction network analysis, highlighting pharmacologically targetable regions. Our methodology uncovered an unexplored dynamic allosteric site on the V2R intracellular interface, whose functional relevance was confirmed through structure-guided mutagenesis and BRET-based signaling assays. This approach establishes a conformation-aware platform for detecting dynamic binding pockets, providing a transformative approach for G protein-coupled receptor (GPCR)-targeted drug discovery.
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Qiao et al. (2025) studied this question.
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