کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
229706 465042 2013 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
3D QSAR kNN-MFA studies on 6-substituted benzimidazoles derivatives as Nonpeptide Angiotensin II Receptor Antagonists: A rational approach to antihypertensive agents
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
3D QSAR kNN-MFA studies on 6-substituted benzimidazoles derivatives as Nonpeptide Angiotensin II Receptor Antagonists: A rational approach to antihypertensive agents
چکیده انگلیسی

The present article is an attempt to the 3D QSAR studies for the 40 molecules of 6-substituted benzimidazoles Nonpeptide Angiotensin II Receptor Antagonists by using k-Nearest Neighbor Molecular Field Analysis (kNN-MFA) combined with various selection procedures. Molecular field analysis was applied for the generation master grid maps derived from the best model has been used to display the contribution of electrostatic potential and steric, hydrophobic field based on aligned structures. Partial least square methodology coupled with various feature selection methods, viz. stepwise (SW), genetic algorithm (GA) and simulated annealing (SA) were applied to derive QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. By using kNN-MFA approach, various 3D QSAR models were generated to study the effect of steric, electrostatic and hydrophobic descriptors on Ang II activity. The best model B with good external and internal predictivity for the training and test set has shown cross-validation (q2) and external validation (pred_r2) values of 0.8269 and 0.7647, respectively. For this model training and test sets were selected using sphere exclusion method and the descriptors were selected using simulated annealing method. The summary of the selected model can be given as: k = 4, r2 = 0.8753, F test = 74.643, r2_se = 0.2143, q2_se = 0.4365, pred_r2se = 0.2165 and descriptors at the grid points S_1018, E_563, S_2083, E_1460, E_160, H_2234, H_2491 and H_1146 play an important role in the design of new molecule. Contour maps using this approach showed that steric, electrostatic and hydrophobic effects dominantly determine binding affinities. The information rendered by 3D QSAR models may lead to a better understanding of structural requirements of antihypertensive activity and can help in the design of novel potent molecules.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Saudi Chemical Society - Volume 17, Issue 2, April 2013, Pages 167–176
نویسندگان
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