Computational identification of isoflavonoids as novel PPAR-γ agonists for the treatment of type 2 diabetes mellitus.

BackgroundThe management of type 2 diabetes mellitus (T2DM) using peroxisome proliferator-activated receptor gamma (PPAR-γ) agonists is currently limited by the adverse effects of thiazolidinediones (TZDs), such as fluid retention and weight gain. This necessitates the search for safer natural alternatives.MethodsThis study applied an integrated multi-layer in silico pipeline to screen 19 isoflavonoids from the FooDB database against the PPAR-γ crystal structure (PDB: 3DZY). The workflow combined molecular docking (Glide SP), structural interaction fingerprint (SIFt) validation and density functional theory (DFT) for electronic characterization followed by ADMET profiling and prediction of PASS bioactivity. Molecular dynamics (MD) simulations (100 ns) and MM-GBSA binding free energy calculations were performed to explore dynamic stability and thermodynamic affinity of the complex.ResultsGenistin (FDB012221) and daidzin (FDB012225) were identified as lead candidates with docking score of -10.837 and -10.125 kcal/mol respectively. DFT analysis revealed that FDB012221has better kinetic stability with a large HOMO-LUMO gap of 7.80 eV, in addition, it was identified as drug-like by ADMET profiling, showing 58% human intestinal absorption and PASS analysis predicted. Molecular dynamics (MD) simulations validated the stable complex formation and FDB012221retained consistent hydrogen bonds with HIS435 (91%) and LEU325 (94%)further, the MM-GBSA values were -60 kcal/mol indicating strong thermodynamic binding.ConclusionFDB012221 is a potent PPAR-γ agonist with high binding affinity, electronic stability and a favorable pharmacokinetic profile. This isoflavonoid is a potential natural scaffold for the development of safer therapies for T2DM and is recommended for further in-vitro and in-vivo validation.