Journal Article

Deep learning reveals endogenous sterols as allosteric modulators of the GPCR-Gα interface

Sharma, Deepak, Mittal, Aayushi, Ghosh, Tarini Shankar, Murugan, Arul Natarajan, Arora, Sakshi, Gautam, Vishakha, Dixit, Nilesh Kumar, Sengupta, Debarka, Mohanty, Sanjay Kumar, Gaur, Aakash, Duari, Subhadeep, Gupta, Shashi Kumar, Farooqi, Namra, Kumar, Suvendu, Ahuja, Gaurav, Subramanian, Karthika, Solanki, Saveena, Sharma, Anmol Kumar

2025

Overview

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for unbiased cavity identification, cavity-specific ligand design, synthesis, and validation across GPCR topology. Here, we developed Gcoupler, an AI-driven generalized computational toolkit that leverages an integrative approach combining de novo ligand design, statistical methods, Graph Neural Networks, and bioactivity-based ligand prioritization for rationally predicting high-affinity ligands. Using Gcoupler, we interrogated intracellular metabolites that target and regulate the GPCR-Gα interface (Ste2p-Gpa1p), affecting pheromone-induced programmed cell death in yeast. Our computational analysis, complemented by experimental validations, including genetic screening, multi-omics, site-directed mutagenesis, biochemical assays, and physiological readouts, identified endogenous hydrophobic metabolites, notably sterols, as direct intracellular allosteric modulators of Ste2p. Molecular simulations coupled with biochemical signaling assessment in site-directed Ste2p mutants further confirmed that metabolites binding to GPCR-Gα obstruct downstream signaling, possibly via a cohesive effect. 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 evolutionary relevance of this mechanism.

• Publisher: eLife Sciences Publications Ltd,eLife Sciences Publications, Ltd
• Subject: Allosteric properties / Allosteric Regulation / Animal models / Animals / Animals, Newborn / Apoptosis / Biochemistry and Chemical Biology / Biological activity / Cardiomegaly - pathology / Cell death / Cell Line / Computational Biology - methods / Computer applications / Deep Learning / G protein-coupled receptors / Genetic screening / GPCR / Graph Neural Networks / Graphs / GTP-Binding Protein alpha Subunits, Gq-G11 - genetics / GTP-Binding Protein alpha Subunits, Gq-G11 - metabolism / Humans / Hydrophobicity / Hypertrophy / Interfaces / Intracellular / Intracellular signalling / Ligands / mating / Metabolites / Metabolomics / Molecular Docking Simulation / Molecular Dynamics Simulation / Mutation / Myocytes, Cardiac - metabolism / Myocytes, Cardiac - pathology / Neonates / Neural networks / Phenotypes / Pheromones / Primary Cell Culture / programmed cell death / Proteins / Rats / Receptors, G-Protein-Coupled - metabolism / Receptors, Mating Factor - genetics / Receptors, Mating Factor - metabolism / Saccharomyces cerevisiae Proteins - genetics / Saccharomyces cerevisiae Proteins - metabolism / Site-directed mutagenesis / Software / Statistical methods / Sterols / Tools and Resources / yeast