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Title of Journal: Med Chem Res

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Abbravation: Medicinal Chemistry Research

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Springer US

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DOI

10.1007/s00294-002-0291-1

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1554-8120

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A QSAR classification study on inhibitory activiti

Authors: Meimei Chen Xinmei Lai Xuemei Yang
Publish Date: 2013/09/24
Volume: 23, Issue: 4, Pages: 1878-1886
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Abstract

Inhibition of cholesteryl ester transfer protein CETP is considered as a new therapy for treating coronary heart disease Recently a series of compounds with a 2arylbenzoxazole skeleton have been identified as potent CETP inhibitors however some of them can also be noninhibitors Therefore it is highly desirable to have models that can predict whether a compound interacts with CETP In this work a quantitative structure–activity relationship study was developed for modeling and classifying CETP inhibitory activity for a dataset of 84 2arylbenzoxazoles using diverse structural descriptors The stepwise linear discriminant analysis LDA method was then used to explore the best descriptors responsible for inhibitory activity The LDA and nonlinear support vector machine SVM method were employed to establish classification models These models were strictly validated using internal and external approaches The SVM model gave the prediction accuracy of 9265  on the training set and 8125  on the test set as well as that of the LDA model 8235 and 75  In addition petitjeanSC PEOE VSA NEG E nb and vsurf EWmin1 were found to have high correlation with the CETP inhibitory activity Overall the SVM model can act as a fast filter for designing new 2arylbenzoxazoles with better CETP inhibitory activity in future


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