Molecular Docking and Receptor-Based 3D-QSAR Studies on Aromatic Thiazine Derivatives as Selective Aldose Reductase Inhibitors

Aromatic thiazine derivatives were proved to be potent aldose reductase inhibitors (ARIs) with high selectivity for aldose reductase (ALR2) over aldehyde reductase (ALR1). Molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies are conducted on a dataset of 44 molecules to explore the interactions between aromatic thiazine derivatives and ALR2. The superposition of ALR2 and ALR1 active sites indicate that residues Leu 300 and Cys 298 from ALR2 may explain the good selectivity of the most active compound 1m. The comparative molecular field analysis (CoMFA) model (q(2) = 0.649, r(2) = 0.934; q(2): cross-validated correlation coefficient, r(2): non-cross-validated correlation coefficient) and comparative molecular similarity indices analysis (CoMSIA) model (q(2) = 0.746, r(2) = 0.971), based on the docking conformations of these compounds, are obtained to identify the key structures impacting their inhibitory potencies. The predictive power of the developed models is further validated by a test set of seven compounds, resulting in predictive r(Pred)(2) values of 0.748 for CoMFA and 0.828 for CoMSIA. 3D contour maps, drawn from 3D-QSAR models, reveal that future modifications of substituents at the C3 and C4 positions of the benzyl ring and the C5 and C7 positions of the benzothiazine-1,1-dioxide core might be favorable for improving the biological activity, which are in good accordance with the C7 modification results reported in our earlier work. The information rendered by 3D-QSAR models could be helpful in the rational design of novel ARIs with good inhibitory activity to treat diabetic complications in the future.