Diabetes mellitus is a multifactorial metabolic disorder characterized by chronic hyperglycemia and impaired metabolism of proteins, fats, and carbohydrates due to inadequate insulin secretion or function. The condition causes severe physical distress and imposes financial burdens on individuals and healthcare systems. Common symptoms include polyuria, polydipsia, and polyphagia. The global prevalence of diabetes has more than doubled over the past 30 years. Although several classes of antidiabetics are available, many are associated with side effects, high cost, limited accessibility and reduced effectiveness over long-term use. This study focuses on utilizing computational methods to investigate the potential antidiabetic effects of phytochemical compounds derived from Gongronema latifolium on the peroxisome proliferator-activated receptor gamma (PPARγ), a receptor involved in insulin regulation. The target protein structure (6t1s) was obtained from the Protein Data Bank and prepared using Chimera 1.10.1, PyMol 2.3.0, and AutoDock Tools 1.5.6. A reference ligand (EDK) was similarly prepared. Phytochemicals from Gongronema latifolium were sourced from the PubChem database and DrugBank database, then screened for drug-likeness using Lipinski’s Rule of Five and toxicity criteria via DataWarrior. Selected compounds were further prepared for docking. Docking protocol validation was conducted, and molecular docking was performed using AutoDock Vina 4.2.6 on Ubuntu Linux 20.04. Results were analyzed in Excel and visualized with PyMol. The reference ligand demonstrated a mean binding energy of -11.9 kcal/mol. The top ten phytochemicals, with binding energies ranging from -10.1 to -9.4 kcal/mol, showed promising binding affinities. In conclusion, the front-runners can be predicted to have antidiabetic effects; however, camptothecin exhibited the highest binding affinity of -10.1 kcal/mol, indicating its potential as an antidiabetic agent targeting the PPARγ receptor.
Oranu et al. (Wed,) studied this question.