Discovery of New Dual-Target Agents Against PPAR-γ and α-Glucosidase Enzymes with Molecular Modeling Methods: Molecular Docking, Molecular Dynamic Simulations, and MM/PBSA Analysis

Abstract

Type 2 diabetes mellitus (T2DM) has become a serious public health problem both in our country and worldwide, being the most prevalent type of diabetes. The combined use of drugs in the treatment of T2DM leads to serious side effects, including gastrointestinal problems, liver toxicity, hypoglycemia, and treatment costs. Hence, there has been a growing emphasis on drugs that demonstrate dual interactions. Several studies have suggested that dual-target agents for peroxisome proliferator-activated receptor-γ (PPAR-γ) and alpha-glucosidase (α-glucosidase) could be a potent approach for treating patients with diabetes. We aim to develop new antidiabetic agents that target PPAR-γ and α-glucosidase enzymes using molecular modeling techniques. These compounds show dual interactions, are more effective, and have fewer side effects. The molecular docking method was employed to investigate the enzyme-ligand interaction mechanisms of 159 newly designed compounds with target enzymes. Additionally, we evaluated the ADME properties and pharmacokinetic suitability of these compounds based on Lipinski and Veber’s rules. Compound 70, which exhibited favorable ADME properties, demonstrated more effective binding energy with both PPAR-γ and α-glucosidase enzymes (-12,16 kcal/mol, -10.07 kcal/mol) compared to the reference compounds of Acetohexamide (-9.31 kcal/mol, -7.48 kcal/mol) and Glibenclamide (-11.12 kcal/mol, -8.66 kcal/mol). Further, analyses of MM/PBSA binding free energy and molecular dynamics (MD) simulations were conducted for target enzymes with compound 70, which exhibited the most favorable binding affinities with both enzymes. Based on this information, our study aims to contribute to the development of new dual-target antidiabetic agents with improved efficacy, reduced side effects, and enhanced reliability for diabetes treatment.