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Classification of blocker and non-blocker of hERG potassium ion channel using a support vector machine 被引量:1
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作者 xuan shouyi LIANG Hu +1 位作者 WANG Zhi YAN AiXia 《Science China Chemistry》 SCIE EI CAS 2013年第10期1413-1423,共11页
The human ether-a-go-go related gene (hERG) channel is responsible for the repolarization during the action potential, and blockage of that may result in severe cardiotoxicity and sudden death. In this study, a data... The human ether-a-go-go related gene (hERG) channel is responsible for the repolarization during the action potential, and blockage of that may result in severe cardiotoxicity and sudden death. In this study, a dataset containing 1969 compounds was compiled from literature and FDA-approved drugs. Using a support vector machine (SVM), two groups of computational models were built to distinguish whether a compound is a blocker or non-blocker of hERG potassium ion channel. These mod- els fit generally satisfactory. The 100 models built with MACCS fingerprints (Model Group A) showed an average accuracy of 90% and an average matthews correlation coefficient (MCC) value of 0.77 on the test sets. The 100 models built with selected MOE descriptors (Model Group B) showed an average accuracy of 89% and an average MCC value of 0.74 on the test sets. Molecular hydrophobicity and lipophilicity were found to be very important factors which lead to block the hERG potassium ion channel. Some other molecular properties such as electrostatic properties, features based on van der Waals surface area, the number of rigid bonds and molecular surface rugosity also played important roles in blocking bERG potassium ion channel. 展开更多
关键词 classification models hERG potassium ion channel MACCS fingerprints MOE descriptors support vector machine(SVM)
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