In Silico Studies of (Z)-3-(2-Chloro-4-Nitrophenyl)-5-(4-Nitrobenzylidene)-2-Thioxothiazolidin-4-One Derivatives as PPAR-γ Agonist: Design, Molecular Docking, MM-GBSA Assay, Toxicity Predictions, DFT Calculations and MD Simulation Studies

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Date

2024

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World Scientific

Abstract

Diabetes mellitus, a metabolic disorder, arises from insufficient insulin levels or increased insulin resistance. An alternative approach to address this pathogenesis involves targeting PPAR-γ, which activates glucose homeostasis and improves peripheral glucose utilization. In this study, we aimed to investigate the designed 2-thioxothiazolidin-4-one derivatives (T1-25) and assess their potential as PPAR-γ regulators by an in silico approach. Physicochemical properties and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiles were evaluated. Docking studies were performed using Schrödinger software, with the protein target being PPAR-γ (PDB ID: 2ZNO). Additionally, MD simulation studies were conducted, and the key interactions in the protein-ligand complexes were identified. The results demonstrate the drug-likeness of compounds T11, T24 and T25, with docking scores of -7.953 kcal/mol, -7.973 kcal/ mol and -8.212 kcal/mol, respectively, and exhibit significant activity against PPAR-γ agonist and compared with the standard drug Pioglitazone (-7.367 kcal/mol). The density functional calculations were also performed to determine the geometrical properties, thermal parameters, chemical reactivity descriptors and molecular electrostatic potential of the compounds using the B3LYP functional and 6-31G++ basis sets. The energy difference between the highest occupied molecular orbitals and lowest unoccupied molecular orbitals for all the investigated compounds is in the range of 2.8-3.4 eV which allows for easy transfer of electrons and reactivity. Further research and development of these designed compounds could contribute to the advancement of effective antidiabetic treatments. © 2024 World Scientific Publishing Company.

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Keywords

DFT, Diabetes mellitus, MD simulations, molecular docking, PPAR-γ, thiazolidinediones

Citation

Journal of Computational Biophysics and Chemistry, 2024, 23, 1, pp. 117-136

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