Validated QSAR analysis of some diaryl substituted pyrazoles as CCR2 inhibitors by various linear and nonlinear multivariate chemometrics methods.
Quantitative relationships between structures of 26 diaryl substituted pyrazoles as CCR2 inhibitors and their activities were investigated by four linear and nonlinear methods namely MLR, PLS, GRNN and LS-SVM. The obtained models were able to describe about 83%, 87%, 86%, and 0.91% of the variance in the experimental activity of molecules in training set, respectively. The accuracy and predictability of the proposed models were illustrated using various evaluation techniques. Some of them were: cross-validation, validation through an external test set, and Y-randomization. Furthermore, various criteria suggested by Tropsha and Roy were applied for evaluation of predictability of developed models. A comparison between the four different developed methods indicates that LS-SVM can be preferred as supreme model.
Arkan
Elham
E
Department of Medical Nanotechnology, School of Advanced Medical Technologies, Tehran University of Medical Sciences, Tehran, Iran.
Shahlaei
Mohsen
M
Pourhossein
Alireza
A
Fakhri
Kambiz
K
Fassihi
Afshin
A
D048088:Informatics; D016018:Least-Squares Analysis; D016014:Linear Models; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D011720:Pyrazoles / Q000737:chemistry* / Q000494:pharmacology*; D021281:Quantitative Structure-Activity Relationship; D054390:Receptors, CCR2 / Q000037:antagonists & inhibitors*
D011720:Pyrazoles; D054390:Receptors, CCR2