Predicting Alkylbenzimidazole Derivatives as Angiotensin II Receptor Antagonists: 3d Qsar by kNN-MFA Approach

Three dimensional quantitative structure-activity relationship (3D-QSAR) studies have been performed on a series of 2-alkylbenzimidazole derivatives using the kNN-MFA Approach (k-nearest neighbour molecular field analysis). The QSAR models were generated using 14 compounds. By using kNN-MFA approach, various 3D QSAR models were generated to study the effect of steric and electrostatic descriptors on angiotensin II receptor antagonists-activity. The kNN-MFA model generated from template based alignment showed q (cross validated r ) of 0.6836 with three descriptors namely S_363, H_1096, E_1204 and E_971. A non2 2 cross validated r of 0.8753, F value of 88.532 and number nearest neighbours k of four were observed with this 2 model and exhibited good external prediction with r _pred of 0.8211. Statistical significance of the model 2 indicated by Z score value of 6.55423 and of >0.001. The generated models provide insight into the influence of various interactive fields on the activity and, thus, can help in designing and forecasting the antihypertensive activity of novel molecules.