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Statistically Validated Qsar Study of Some Antagonists of the Human Ccr5 Receptor Using Least Square Support Vector Machine Based on the Genetic Algorithm and Factor Analysis Publisher



Shahlaie M1 ; Fassihi A2 ; Pourhossein A3 ; Arkan E4
Authors
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Authors Affiliations
  1. 1. Department of Medicinal Chemistry, Faculty of Pharmacy, Kermanshah University of Medical Sciences, 67346-67149 Kermanshah, Iran
  2. 2. Department of Medicinal Chemistry, Faculty of Pharmacy, Isfahan University of Medical Sciences, 81746-73461 Isfahan, Iran
  3. 3. Department of Chemical Engineering, Science and Research Branch, Islamic Azad University, Kermanshah, Iran
  4. 4. Department of Medical Nanotechnology, School of Advanced Medical Technologies, Tehran University of Medical Sciences, Tehran, Iran

Source: Medicinal Chemistry Research Published:2013


Abstract

Quantitative relationships between molecular structures and CCR5 inhibitory activities of forty two 1-amino-2-phenyl-4-(piperidin-1-yl)-butane derivatives were discovered by chemometrics tools including GA-MLR and FA-MLR as linear models and GA-LS-SVM and FA-LS-SVM as nonlinear models. GA-MLR analysis indicated that the topological (X2A) and geometrical (MAXDN) parameters have the most significant influence on the CCR5 inhibitory activity. FA-MLR model describes the effect of topological, geometrical, and quantum indices on the CCR5 inhibitory activity of the studied molecules. A comparison between the developed statistical methods revealed that FA-LS-SVM represented superior results and it could predict about 95 % of variance in the inhibitory activity data. The resulted models were validated for generalization and predictability by leave-one-out (LOO) cross-validation method. External validation showed high predictability of the calibration models. The predictability of the obtained QSAR models was also investigated by the Tropsha and Roy proposed criteria. Further validation by Y-randomization method confirmed that the obtained models were not due to a chance correlation. The applicability domain of the models was defined by leverage value. None of the studied compounds were outside the domain of the models. © 2012 Springer Science+Business Media, LLC.
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