Computational Study of Novel Aldose Reductase Inhibitors as Antidiabetic Potential: A Dual Inhibitor - Sharma Ritu (Asian Journal of Pharmaceutics (AJP), 2025)
Background: Diabetes mellitus is a chronic metabolic disorder marked by hyperglycemia due to insufficient insulin production or action. One major contributor to diabetes-related complications is aldose reductase (AR), which increases sorbitol and fructose accumulation under hyperglycemic conditions. Inhibiting AR is a promising strategy to mitigate such complications. Objectives: The objective is to identify and evaluate potential AR inhibitors (ARIs) through computational molecular docking methods for improved glycemic control. Materials and Methods: A total of 82 compounds were computationally screened against AR (PDB ID: 1ADS) using molecular docking techniques. The workflow included ligand and protein preparation, grid generation, and docking analysis. Standard drugs (pioglitazone and epalrestat) were used for comparison. Results: Docking scores of the compounds ranged from −12.012 to −4.28. Standard drugs pioglitazone and epalrestat scored −12.012 and −10.705, respectively. Based on docking scores and interaction profiles, 22 compounds (RS1–RS22) were selected for further analysis. These compounds formed stable hydrogen bonds with AR, indicating strong binding affinity and potential inhibitory activity. Conclusion: The study highlights several novel compounds as promising ARIs with potential antidiabetic effects. These findings warrant further investigation through in vitro and in vivo studies to validate their efficacy and safety for diabetes treatment.