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  1. Maulana AF, Maksum IP, Sriwidodo S, Rukayadi Y
    J Mol Model, 2024 Apr 18;30(5):136.
    PMID: 38634946 DOI: 10.1007/s00894-024-05934-z
    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.

  2. Maksum IP, Rustaman R, Deawati Y, Rukayadi Y, Utami AR, Nafisa ZK
    J Mol Model, 2024 Jul 09;30(8):260.
    PMID: 38981921 DOI: 10.1007/s00894-024-06060-6
    CONTEXT: Diabetes mellitus (DM) is a metabolic disorder disease that causes hyperglycemia conditions and associated with various chronic complications leading to mortality. Due to high toxicity of conventional diabetic drugs, the exploration of natural compounds as alternative diabetes treatments has been widely carried out. Previous in silico studies have highlighted berberine, a natural compound, as a promising alternative in antidiabetic therapy, potentially acting through various pathways, including the inhibition of the FOXO1 transcription factor in the gluconeogenesis pathway. However, the specific mechanism by which berberine interacts with FOXO1 remains unclear, and research in this area is relatively limited. Therefore, this study aims to determine the stability of berberine structure with FOXO1 based on RMSD, RMSF, binding energy, and trajectory analysis to determine the potential of berberine to inhibit the gluconeogenesis pathway. This research was conducted by in silico method with molecular docking using AutoDock4.2 and molecular dynamics study using Amber20, then visualized by VMD.

    METHODS: Docking between ligand and FOXO1 receptor was carried out with Autodock4.2. For molecular dynamics simulations, the force fields of DNA.OL15, protein.ff14SB, gaff2, and tip3p were used.

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