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Comparative Quantitative Structure-Activity Relationship Study of Some 1-Aminocyclopentyl-3-Carboxyamides As Ccr2 Inhibitors Using Stepwise Mlr, Fa-Mlr, and Ga-Pls Publisher



Shahlaei M1, 2 ; Madadkarsobhani A3 ; Fassihi A2, 4 ; Saghaie L2, 4 ; Shamshirian D2 ; Sakhi H2
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Authors Affiliations
  1. 1. Department of Medicinal Chemistry, Faculty of Pharmacy, Kermanshah University of Medical Sciences, Kermanshah, Iran
  2. 2. Department of Medicinal Chemistry, Faculty of Pharmacy, Isfahan University of Medical Sciences, 8174673461 Isfahan, Iran
  3. 3. Department of Bioinformatics, Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran
  4. 4. Isfahan Pharmaceutical Sciences Research Center, 8174673461 Isfahan, Iran

Source: Medicinal Chemistry Research Published:2012


Abstract

Multiple linear regression (MLR), factor analysis in combination with multiple linear regression (FA-MLR), and genetic algorithm subset selection partial least square (GA-PLS) regression methods were used for quantitative structure-activity relationships (QSAR) model building. These approaches were employed to investigate the correlation between pIC50 and various physicochemical descriptors of 28 compounds of 1-aminocyclopentyl- 3-carboxyamides including substituted tetrahydropyran moieties as CCR2 inhibitors. The obtained models were validated using cross-validation and external test set. The predictability and robustness of the developed models were considered by some figures of merit such as RMSEP and Y-randomization. MLR, FA-MLR, and GA-PLS have R 2 equal to 0.84, 0.69, and 0.93, respectively. Predicted variance by MLR, FA-MLR, and GA-PLS (R 2 test) is 78, 75, and 78%, respectively. Furthermore, the domain of applicability which indicates the area of reliable predictions is defined. The prediction results by models are in good agreement with the experimental value. © Springer Science+Business Media, LLC 2010.
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