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Linear and Nonlinear QSAR Study of N2 and O6 Substituted Guanine Derivatives as Cyclin-Dependent Kinase 2 Inhibitors
Author(s) -
Nasser Goudarzi,
Mansour Arab Chamjangali,
Payam Kalhor
Publication year - 2013
Publication title -
isrn analytical chemistry
Language(s) - English
Resource type - Journals
eISSN - 2090-732X
pISSN - 2090-7311
DOI - 10.1155/2013/151464
Subject(s) - quantitative structure–activity relationship , test set , guanine , molecular descriptor , chemistry , nonlinear system , linear regression , biological system , mathematics , linear model , computer science , stereochemistry , statistics , biochemistry , physics , biology , nucleotide , quantum mechanics , gene
The inhibitory activities (pIC50) of N2 and O6 substituted guanine derivatives as cyclin-dependent kinase 2 (CDK2) inhibitors have been successfully modeled using calculated molecular descriptors. Two linear (MLR) and nonlinear (ANN) methods were utilized for construction of models to predict the pIC50 activities of those compounds. The QSAR models were validated by cross-validation (leave-one-out) as well as application of the models for prediction of pIC50 of external set compounds. Also, the models were validated by calculation of statistical parameters and Y-randomization test. Two methods provided accurate predictions, although more accurate results were obtained by ANN model. The mean-squared errors (MSEs) for validation and test sets of MLR are 0.065, 0.069 and of ANN are 0.017 and 0.063, respectively.

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