In silico docking and interaction analysis of KazMeI with α-glucosidase as a potential antidiabetic agent

Abstract

The present study focuses on the molecular docking and interaction analysis of the Kazcaine (1-(2-ethoxyethyl)-4-ethynyl-4-benzoyloxypiperidine) derivative KazMeI with the α-glucosidase enzyme (PDB ID: 5NN4), the principal therapeutic target in the treatment of type 2 diabetes mellitus. For crystal structure modeling of human lysosomal acid-alpha-glucosidase, GAA/N-acetyl-cysteine complex was utilized. The ligand structure was designed in ChemDraw, geometry-optimized using a Python-based MM2 molecular mechanics force field, and converted to PDBQT format in AutoDockTools v1.5.6. The protein structure was prepared by removing water molecules, adding polar hydrogens, and centering the docking grid at coordinates (–6.152, –33.636, 91.204 Å). Docking simulations performed in AutoDock4.2 using the Lamarckian Genetic Algorithm produced ten conformations with highly consistent binding orientations. The lowest binding free energy (ΔG) was –7.00 kcal/mol, corresponding to an inhibition constant (Ki) of 7.37 μM, indicating moderate yet biologically relevant affinity. Interaction analysis revealed that KazMeI  forms hydrophobic and π–π stacking contacts with Leu286, Pro285, Leu291, and Trp613, and hydrogen bonding with Ser601 and Thr286, while the quaternary ammonium group interacts electrostatically with Arg600. These results confirm the predicted antidiabetic potential of the patented derivative KazMeI compound (Utility Model Patent No. 9796, Kazakhstan, 2024) and support its further development as a lead α-glucosidase inhibitor.

Keywords: Autodock, Pymol, ChemDraw, molecular docking, α-glucosidase, Kazcaine derivative, antidiabetic agents