Computational analysis and molecular dynamics simulation of metformin derivatives as potential α-glucosidase inhibitors for type 2 diabetes

Type 2 Diabetes Mellitus (T2DM) is a progressive metabolic disorder that necessitates safer and more effective therapeutic strategies. Inhibition of α-glucosidase plays a crucial role in reducing postprandial hyperglycemia. This study applied an integrated computational workflow, supported by previously reported in vitro data, to evaluate metformin-derived analogues as potential α-glucosidase inhibitors. Nine derivatives were screened, and four candidates (MET1, MET2, MET3, and MET8) were selected based on molecular docking, molecular dynamics (MD) simulations, and ADMET predictions. Docking against Geobacillus sp. α-glucosidase (PDB ID: 2ZE0 ) revealed higher binding affinities than metformin. One hundred-nanosecond MD simulations confirmed that MET1 and MET3 formed the most stable complexes with minimal RMSD fluctuations (~2 Å). MM/GBSA analysis showed that MET2 (ΔG_total = −29.06 kcal·mol −1 ) and MET3 (ΔG_total = −24.96 kcal·mol −1 ) exhibited the strongest thermodynamic stabilization through hydrogen bonding and π-stacking interactions with catalytic residues Tyr63, Glu256, and Asp326. SwissADME and ProTox-III evaluations indicated favorable oral bioavailability, drug-likeness, and low toxicity. These findings highlight MET2 and MET3 as promising α-glucosidase inhibitor scaffolds for future optimization and experimental validation, offering potential therapeutic benefits in the management of T2DM.