Structure-Based Discovery of Orthosteric Non-Peptide GLP-1R Agonists via Integrated Virtual Screening and Molecular Dynamics
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
The development of orally bioavailable non-peptidomimetic glucagon-like peptide-1 receptor agonists (GLP-1RAs) offers a promising therapeutic avenue for the treatment of type 2 diabetes mellitus (T2DM) and obesity. An extensive in silico approach combining structure-based drug design, and ligand-based strategies together with pharmacokinetic properties and drug-likeness predictions, is implemented to identify novel non-peptidic GLP-1RAs from the COCONUT and Marine Natural Products (CMNPD) libraries. More than 700,000 compounds were screened by shape-based similarity filtering in combination with precision docking against the orthosteric site of the GLP-1 receptor (PDB ID: 6X1A). The docked candidates were further assessed with the molecular mechanics MM-GBSA tool to check the binding affinities; the final list of candidates was validated by running a 500 ns long MD simulation. Twenty final hits were identified, ten from each database. The hits contained compounds with reported antidiabetic effect but with no evidence of GLP-1 agonist activity including hits 1, 6, 7, 10. These findings proposed a novel mechanism for these hits through GLP-1 activity and positioned the other hits as potential promising scaffolds. Among the studied compounds—especially hits 1, 5, and 9, possessed strong and stable interactions with critical amino acid residues such as TRP-203, PHE-381, and GLN-221 at the active site of the 6X1A-substrate along with favorable pharmacokinetic profiles. Moreover, the RMSF and RMSD plots further suggested the possibility of stable interactions. Specifically, hit 9 possessed the best docking score with a ΔG_bind value of −102.78 kcal/mol, surpassing even the control compound in binding affinity. The ADMET profiling also showed desirable drug-likeness and pharmacokinetic characteristics for hit 9. The pipeline of computational integration underscores the potential of non-peptidic alternatives in natural product libraries to pursue GLP-1-mediated metabolic therapy into advanced preclinical validation.