2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors.

ABSTRACT: Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q² = 0.565 (cross-validated correlation coefficient) and r² = 0.888 (non-cross-validated co

SUBMITTER: Zhao M 

PROVIDER: S-EPMC5467385 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature