QSAR Studies of Sodium/Glucose Co-Transporter 2 Inhibitors as Potent Anti-Diabetic Drug Agents

Abstract

A novel class of therapeutic agents, the sodium-glucose co-transporter 2 (SGLT2) inhibitors, is emerging as a promising avenue for type 2 diabetes management. A dataset comprising 1807 SGLT2 inhibitors was subjected to a quantitative structure-activity relationship (QSAR) investigation using the AutoQSAR module of Schrodinger Maestro 12.8. Of these compounds, 1355 were designated as the training set for model development, followed by comprehensive evaluation through a battery of internal and external cross-validation techniques. Subsequently, a subset of 452 compounds served as an independent test set for external validation. The resultant QSAR model exhibited promising statistical performance, as evidenced by the calculated predicted R² and Q² values, at 0.873 and 0.781, respectively. Furthermore, the predictive correlation coefficient attained a commendable value of 0.84. Notably, this model demonstrates its efficacy in forecasting inhibitory activity and furnishes valuable insights that can be harnessed for the design of novel SGLT2 inhibitors in future endeavors.