Gcoupler: An AI-enhanced tool unveiled Endogenous Intracellular Allosteric Modulators of Evolutionary Conserved GPCR-Gα Interface

ABSTRACT Traditionally, the exogenous allosteric modulators of G protein-coupled receptors (GPCRs) have been extensively investigated due to their pharmacological significance. However, to date, only a handful of endogenous intracellular allosteric modulators are known, that too with inconclusive binding information and their associated phenotypes. This limitation primarily stems from the non-availability of robust computational techniques that entail unbiased cavity identification across GPCR protein topology, cavity-specific ligand design, their synthesis, and cross-validation. Here, we introduce Gcoupler, which leverages an integrative approach combining de novo ligand design, statistical methods, and Graph Neural Networks for rationally predicting high-affinity ligands. Gcoupler offers an efficient and comparatively faster route to explore allosteric sites of GPCRs, including the GPCR-Gα interface. We tested and validated the applicability of Gcoupler in decrypting the cellular metabolites that could intracellularly modulate the Ste2 (GPCR)-mediated pheromone-induced cell death in yeast. Our rigorous interrogation using Gcoupler and experimental approaches, including yeast genetic screening, RNA sequencing, high-resolution metabolomics, and functional assays, identified endogenous hydrophobic metabolites, mainly specific sterols, as intracellular allosteric modulators of Ste2p signaling. Elevated intracellular levels of these metabolites, either naturally, through genetic alterations, or exogenous treatment, rescue the pheromone-induced programmed cell death. Computational insights revealed that these metabolites harbor high binding affinity to the conserved GPCR-Gα interface and might trigger a cohesive response that potentially obstructs downstream signaling. Finally, by utilizing isoproterenol-induced, GPCR-mediated human and neonatal rat cardiac hypertrophy models, we observed that elevated metabolite levels attenuate hypertrophic response, reinforcing the functional and evolutionary relevance of this mechanism. In summary, our study reports a robust computational approach for efficiently exploring the allosteric sites in GPCRs.