Aug 2026· Journal of Chemical Information and Modeling· Vol 66, pp. 10956 - 10970· 0 citations· 60 references
Medicine
Abstract
Understanding how allosteric modulators influence protein dynamics is essential for guiding drug design. This work analyses a total of 45 μs of classical molecular dynamics simulations for four class A G-protein-coupled receptors (GPCRs), namely the Complement C5a receptor (C5AR1), the Purinergic Receptor P2Y (P2RY1), and the Cannabinoid Receptors 1 and 2 (CNR1/CNR2). Protein dynamics is essential to detect the shallow extrahelical binding sites, such as the one found in P2RY1. Current methods for computing Allosteric Communication Networks (ACNs) produce complex outputs requiring expert interpretation. To address this, we focus on the shortest paths of information transfer between the orthosteric and G-protein binding sites in Class A GPCRs. Our retrospective analysis reveals state- and bias ligand-dependent residue interactions along these communication pathways. Furthermore, focusing on the predicted binding site of allosteric modulator EC21a at cannabinoid receptors, the ACN framework was used to prioritize two residues for mutational analysis that may contribute to allosteric communication.
This study provides potential lead compounds for the design of small-molecule allosteric drugs targeting class B1 GPCRs and performs conformational sampling and combined dynamic pocket detection algorithms, MDpocket and FTMove, to identify six characteristic cryptic pockets within the dynamic trajectories.
Zhi Dong, Long Cheng, Qingxin Shi et al.· International Journal of Bio...· 0 citations
This study maps the landscape of GPCR classification and function by translating the majority of the GPCR structures into structure graphs and analyzing over 2 million structural contacts to capture key aspects of the structural communication within the GPCR superfamily with implications in drug discovery.
Sara Gentile, Angelo Felline, Sara Mazzali et al.· JACS Au· 0 citations
This work developed an interpretable probabilistic framework that extracts residue-level dependencies from MD ensembles using Bayesian network modeling (BNM) and establishes a generalizable and interpretable framework for uncovering GPCR allosteric communication networks and discovering modulators that exploit these ne...
These results provide the first atomistic model of SPM binding to GPR101 and establish an RBFE-guided framework for designing next-generation pro-resolving mediator analogs with enhanced pro-resolving effects and stability.
D. Hasselstrøm, Majd Awad, T. Hansen et al.· ACS Omega· 0 citations
GaMD ensemble docking improved early AM enrichment across all four targets under at least one program, and the Boltz-2 deep-learning program showed minimal sensitivity to GaMD templates and underperformed conventional docking, suggesting its affinity predictions complement rather than replace physics- and empirical-bas...
T. D. Thompson, Ying-Long Miao· bioRxiv· 0 citations
This work uncovers key dynamic features of the static and recognition pathway interaction of the ornithine decarboxylase-antizyme isoforms system and reveals critical determinants of binding specificity and partner selection that static structures alone cannot capture.
Baolin Guo, Qian Xue, Fan Yang et al.· Journal of Chemical Informat...· 0 citations
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