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Letters in Drug Design & Discovery

Author(s): Diansong Zhou, Ruifeng Liu, Sara A. Otmani, Scott W. Grimm, Randy J. Zauhar and Ismael Zamora

DOI: 10.2174/157018007780077462

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Rapid Classification of CYP3A4 Inhibition Potential Using Support Vector Machine Approach

Page: [192 - 200] Pages: 9

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Abstract

The CYP3A4 inhibition SVM classification model achieved high prediction accuracy, which can be used as high throughput computational filter for identifying CYP3A4 inhibition liability. Its demonstrated that the distance to the separating surface in the feature space can be used as valuable confidence index for the prediction of each compound.

Keywords: CYP3A4, Inhibition, QSAR, Support Vector Machine