An Integrated Ligand- and Structure-Based Virtual Screening and Experimental Strategy for the Prediction of Chemically Diverse GLP-1R Agonists

The glucagon-like peptide-1 receptor (GLP-1R) plays a central role in metabolic regulation and is a major therapeutic target for obesity and diabetes. Peptide agonists, like semaglutide, targeting GLP-1R, remain among the most effective regulators of glucose metabolism and appetite. Nonetheless, recent reports of weight regain after treatment discontinuation sustain the interest in expanding the chemical diversity of GLP-1R ligands through drug discovery strategies. However, the structural complexity and conformational plasticity of class B1 G protein-coupled receptors (GPCRs) make conventional single-method virtual screening approaches prone to bias and limited chemotype recovery. Using an integrated ligand- and structure-based virtual screening pipeline, combining complementary ligand-based descriptors, multifingerprint similarity, electrostatic similarity, pharmacophore modeling, and multiconformation docking under a consensus-driven selection strategy, we identified three chemically distinct GLP-1R agonists comprising one nonpeptidic molecule (GQB47810), and two peptides (neuromedin C and DPDPE). Among them, DPDPE showed the greatest effectiveness, reaching nearly 100% of the maximal GLP-1 response, although with lower potency (EC50 = 4.3 μM). Further in vitro characterization confirmed that DPDPE behaved as a full agonist and exhibited dual agonistic activity at GLP-1R and at the glucose-dependent insulinotropic polypeptide receptor (GIPR, EC50 = 4.3 μM). Site-directed mutagenesis of the predicted binding site, with cell-surface expression measured for every mutant, and whole-cell competition binding against 125I-GLP-1 are consistent with direct engagement of the receptor. These findings establish a consensus-driven computational framework for chemotype-diverse agonist discovery at conformationally flexible GPCR targets and reveal a pentapeptide with GLP-1-like efficacy as a promising lead for next-generation small peptide therapeutics.