In Silico Evaluation of 5-Arylidine Glitazone Esters as Potential Antidiabetic Agents: ADMET, Molecular Docking, Dynamics, MMGBSA and DFT Studies.

Diabetes Mellitus remains a severe cause of death globally. In our present study, we report an in silico study of our previously synthesized 5-arylidine glitazone esters 3ai-ev to find an alternative treatment for T2DM. To this end, computational methods such as ADMET, Molecular docking, dynamics, MMGBSA, and DFT were employed to investigate drug-like characteristics, safety, binding affinity, stability, free binding energy, and the electronic properties of compounds 3ai-ev. The results showed that all compounds exhibited favorable physicochemical and pharmacokinetic properties. Molecular docking showed that all compounds are the best inhibitors of SGLT2 when compared to other enzymes. Alaninate 3biii emerged as the most potent inhibitor with a docking score of -9.322 kcal/mol, followed by butanoate 3civ, norvalinate 3eiii, valinate 3div, and glycinate 3av with docking scores of -9.322, -8.787, -8.710, and -8.135 kcal/mol. Parento algorithm trade-off analysis between synthetic yield and binding affinity confirmed that compound 3biii has a higher synthetic yield than all compounds. In addition, molecular dynamics confirmed the stability of compounds 3ai-ev using both RMSD and RSMF fluctuations, while MMGBSA revealed favorable free binding energy. Furthermore, DFT provided the acceptable electronic properties using the HOMO-LUMO energy gap, which is very significant towards the development of new anti-diabetic drugs.