Atom-based 3D QSAR studies on novel N-β-d-xylosylindole derivatives as SGLT2 inhibitors

Abstract

Sodium-dependent glucose cotransporter 2 (SGLT2) have emerged as a novel drug target for hyperglycemia, a major complication of type 2 diabetes, with a multitude of therapeutic potential for their inhibitors. A series of N-β-d-xylosylindole derivatives has been reported as SGLT2 inhibitors. Therefore, to determine the structural requisite of these SGLT2 inhibitors, 3D pharmacophore models and atom-based 3D QSAR models have been developed using the PHASE module of Schrodinger. The best six-featured pharmacophore hypothesis with two hydrogen bond acceptors, two hydrogen bond donors, one hydrophobic features, and one aromatic ring yielded a 3D QSAR model. The derived model have significant PLS values as R 2 = 0.9527, correlation coefficient of training set, and Q 2 = 0.9045, correlation coefficient of test set, indicating the model have good predictive power. The results provide detailed insights of N-β-d-xylosylindole derivatives which can afford guidance for rational drug design of novel potent SGLT2 inhibitors.