Computational Study of Novel Aldose Reductase Inhibitors as Antidiabetic Potential: A Dual Inhibitor (Asian Journal of Pharmaceutics (AJP), 2025)
Background: Diabetes mellitus is a chronic metabolic disorder marked by hyperglycemia due to insufficientinsulin production or action. One major contributor to diabetes-related complications is aldose reductase(AR), which increases sorbitol and fructose accumulation under hyperglycemic conditions. Inhibiting ARis a promising strategy to mitigate such complications. Objectives: The objective is to identify and evaluatepotential 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, anddocking analysis. Standard drugs (pioglitazone and epalrestat) were used for comparison. Results: Docking scoresof the compounds ranged from −12.012 to −4.28. Standard drugs pioglitazone and epalrestat scored −12.012and −10.705, respectively. Based on docking scores and interaction profiles, 22 compounds (RS1–RS22) wereselected for further analysis. These compounds formed stable hydrogen bonds with AR, indicating strong bindingaffinity and potential inhibitory activity. Conclusion: The study highlights several novel compounds as promisingARIs with potential antidiabetic effects. These findings warrant further investigation through in vitro and in vivostudies to validate their efficacy and safety for diabetes treatment.