WITHDRAWN: Structural insight for (6-oxo-3-pyridazinyl)-benzimidazoles derivatives as angiotensin II receptor antagonists: QSAR, pharmacophore identification and kNNMFA approach

Molecular Modeling Studies of Thiophenyl C-Aryl Glucoside SGLT2 Inhibitors as Potential Antidiabetic Agents

A QSAR study on thiophenyl derivatives as SGLT2 inhibitors as potential antidiabetic agents was performed with thirty-three compounds. Comparison of the obtained results indicated the superiority of the genetic algorithm over the simulated annealing and stepwise forward-backward variable method for feature selection. The best 2D QSAR model showed satisfactory statistical parameters for the data set (r (2) = 0.8499, q (2) = 0.8267, and pred_r (2) = 0.7729) with four descriptors describing the nature of substituent groups and the environment of the substitution site. Evaluation of the model implied that electron-rich substitution position improves the inhibitory activity. The good predictive 3D-QSAR models by k-nearest neighbor (kNN) method for molecular field analysis (MFA) have cross-validated coefficient q (2) value of 0.7663 and predicted r (2) value of 0.7386. The results have showed that thiophenyl groups are necessary for activity and halogen, bulky, and less bulky groups in thiophenyl nucleus enhanced the biological activity. These studies are promising for the development of novel SGLT2 inhibitor, which may have potent antidiabetic activity.

Molecular Modeling Studies of Substituted 2,4,5-Trisubstituted Triazolinones Aryl and Nonaryl Derivatives as Angiotensin II AT1Receptor Antagonists

The development of new therapies to treat hypertension and cardiovascular diseases. A series of 2,4,5-trisubstituted triazolinones aryl and nonaryl derivatives were subjected toGroup-based QSAR,k-nearest neighbourmolecular field analysis, and pharmacophore mapping. Multiple linear regression (MLR) methodology coupled with feature selection method namely simulated annealing, was applied to derive Group based QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The best physicochemical descriptors, namely, R1chiV1, R2T_N_O_3, R2chlorines count, R2T_C_N_4, and R2SssNHE index, contribute significantly to the biological activity. The statistically significant best Group-based QSAR model hasr2=0.8357andq2=0.7266with pred_r2=0.8138. The 3D-QSAR studies were performed using the simulated annealing selectionk-nearest neighbormolecular field analysis approach; a leave-one-out cross-validated correlation coefficientq2=0.7461and predicate activity pred_r2=0.7790were obtained. Contour maps using this approach showed that steric, electrostatic, and hydrophobic effects dominantly determine binding affinities. Pharmacophore hypotheses were generated by the mol sign module and found to contain common features like hydrogen bond donor acceptor, donor, positive, negative ionizable, and hydrophobic features. This model can be used for preliminary screening of large number of substituted 3H-1,-2,-4 triazolinone aryl and nonaryl derivatives. The information rendered by 3D-QSAR models may lead to a better understanding of structural requirements of triazolinone aryl and nonaryl derivatives and also aid in designing novel potent antihypertensive molecules.