Identification and Evaluation of Novel SGLT-2 Inhibitors having Anti-diabetic Potential

Aims: Diabetes mellitus poses a major global health challenge, and the current treatment modalities mostly have side effects and decreasing efficacy. Sodium-glucose cotransporter-2 (SGLT-2) inhibitors have emerged as promising agents for managing type 2 diabetes, yet the search for more effective and safer compounds persists. Methodology: In this study, a dataset of 1807 active SGLT-2 inhibitors was analyzed by using an integrated in silico approach, employing Schrodinger Maestro 12.8 for pharmacophore modeling, ADME profiling, molecular docking, and binding free energy analysis. For MD simulation and DFT calculations, Gromacs and Gaussian 09 software are used, respectively. Pharmacophore hypotheses were generated via the PHASE module, followed by virtual screening of the ZINCPharmer database. Out of 144 potential hits, we shortlisted 15 compounds based on their pharmacokinetic properties. Result: Molecular docking with the hSGLT2 enzyme (PDB ID: 7VSI) identified ZINC77285189 and ZINC59047505 as lead candidates. These two compounds showed superior docking scores with excellent binding free energies, which were validated using MD simulation and DFT studies. Conclusion: We propose that both these compounds be experimentally validated and can be developed into SGLT-2-targeted anti-diabetic therapeutics.