Proposed molecular mechanism of non-competitive inhibition using molecular dynamics simulations between α-glucosidase enzyme and mangostin compound as antidiabetic.

CONTEXT: Further understanding of the molecular mechanisms is necessary since it is important for designing new drugs. This study aimed to understand the molecular mechanisms involved in the design of drugs that are inhibitors of the α-glucosidase enzyme. This research aims to gain further understanding of the molecular mechanisms underlying antidiabetic drug design. The molecular docking process yielded 4 compounds with the best affinity energy, including γ-Mangostin, 1,6-dimethyl-ester-3-isomangostin, 1,3,6-trimethyl-ester-α-mangostin, and 3,6,7-trimethyl-ester-γ-mangostin. Free energy calculation with molecular mechanics with generalized born and surface area solvation indicated that the 3,6,7-trimethyl-γ-mangostin had a better free energy value compared to acarbose and simulated maltose together with 3,6,7-trimethyl-γ-mangostin compound. Based on the analysis of electrostatic, van der Waals, and intermolecular hydrogen interactions, 3,6,7-trimethyl-γ-mangostin adopts a noncompetitive inhibition mechanism, whereas acarbose adopts a competitive inhibition mechanism. Consequently, 3,6,7-trimethyl-ester-γ-mangostin, which is a derivative of γ-mangostin, can provide better activity in silico with molecular docking approaches and molecular dynamics simulations. METHOD: This research commenced with retrieving protein structures from the RCSB database, generating the formation of ligands using the ChemDraw Professional software, conducting molecular docking with the Autodock Vina software, and performing molecular dynamics simulations using the Amber software, along with the evaluation of RMSD values and intermolecular hydrogen bonds. Free energy, electrostatic interactions, and Van der Waals interaction were calculated using MM/GBSA. Acarbose, used as a positive control, and maltose are simulated together with test compound that has the best free energy. The forcefields used for molecular dynamics simulations are ff19SB, gaff2, and tip3p.

In Silico Study of Mangostin Compounds and Its Derivatives as Inhibitors of α-Glucosidase Enzymes for Anti-Diabetic Studies.

Diabetes is a chronic disease with a high mortality rate worldwide and can cause other diseases such as kidney damage, narrowing of blood vessels, and heart disease. The concomitant use of drugs such as metformin, sulfonylurea, miglitol, and acarbose may cause side effects with long-term administration. Therefore, natural ingredients are the best choice, considering that their long-term side effects are not significant. One of the compounds that can be used as a candidate antidiabetic is mangostin; however, information on the molecular mechanism needs to be further analyzed through molecular docking, simulating molecular dynamics, and testing the in silico antidiabetic potential. This study focused on modeling the protein structure, molecular docking, and molecular dynamics simulations and analyses. This process produces RMSD values, free energies, and intermolecular hydrogen bonding. Based on the analysis results, all molecular dynamics simulations can occur under physiological conditions, and γ-mangostin is the best among the test compounds.