An in silico Approach for Identification of Novel Natural Selective ALR2 Inhibitors from Cynomorium songaricum for Treating Diabetic Complications.

Introduction: Aldose reductase-2 (ALR2) is a key enzyme in the polyol pathway whose overexpression is implicated in several diabetic complications, including neuropathy, nephropathy, retinopathy, and atherosclerotic plaque formation. Under hyperglycemic conditions, the intracellular accumulation of sorbitol and the depletion of NADPH lead to osmotic imbalance and oxidative stress, driven by the formation of reactive oxygen species and advanced glycation end products. Although various ALR2 inhibitors have been developed, their clinical application has been hampered by nonselective inhibition of both ALR2 and the homologous enzyme ALR1.

Method: In this study, we employed a comprehensive in silico approach to evaluate the inhibitory potential of natural compounds from Cynomorium songaricum against ALR2. Our workflow integrated with ADMET, molecular docking with scoring function and glide XP, molecular dynamics (MD) simulations, PCA, FEL, and MM/GBSA. Through this analysis, four natural compounds of C. songaricum (Compound Name: p-Coumaric acid, Vanillic acid, 4-Oxoniobenzoate, and Phloroglucinol) displayed significant bonds formation including hydrogen and hydrophobic bonds with the target protein.

Results: These bonds exhibited the ligand stability. Further, the MD simulation analysis, followed by postsimulation analysis, verified the dynamic stability of these four natural compounds and compared them with the native ligand of the target protein. These natural compounds exhibit particularly stable binding within the ALR2 selectivity pocket, demonstrating an inhibitory effect over ALR1 when compared with the reference inhibitor, Epalrestat.

Conclusion: These promising in silico findings suggest that CID: 8468 and CID: 135 merit further evaluation through in vitro, in vivo, and clinical studies as potential selective inhibitors for the treatment of diabetic complications.