Rapid Classification of CYP3A4 Inhibition Potential Using Support Vector Machine Approach

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

Journal Name: Letters in Drug Design & Discovery

Volume 4 , Issue 3 , 2007


Become EABM
Become Reviewer
Call for Editor

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

Rights & PermissionsPrintExport Cite as

Article Details

VOLUME: 4
ISSUE: 3
Year: 2007
Page: [192 - 200]
Pages: 9
DOI: 10.2174/157018007780077462
Price: $65

Article Metrics

PDF: 7