The Catch-22 of Predicting hERG Blockade Using Publicly Accessible Bioactivity Data

Journal of Chemical Information and Modeling
Vishal B SiramshettyRobert Preissner

Abstract

Drug-induced inhibition of the human ether-à-go-go-related gene (hERG)-encoded potassium ion channels can lead to fatal cardiotoxicity. Several marketed drugs and promising drug candidates were recalled because of this concern. Diverse modeling methods ranging from molecular similarity assessment to quantitative structure-activity relationship analysis employing machine learning techniques have been applied to data sets of varying size and composition (number of blockers and nonblockers). In this study, we highlight the challenges involved in the development of a robust classifier for predicting the hERG end point using bioactivity data extracted from the public domain. To this end, three different modeling methods, nearest neighbors, random forests, and support vector machines, were employed to develop predictive models using different molecular descriptors, activity thresholds, and training set compositions. Our models demonstrated superior performance in external validations in comparison with those reported in the previous studies from which the data sets were extracted. The choice of descriptors had little influence on the model performance, with minor exceptions. The criteria used to filter bioactivity data, the activity ...Continue Reading

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Citations

Jan 29, 2019·Chemical Biology & Drug Design·Yanmin ZhangHaichun Liu
Aug 9, 2019·Chemical Biology & Drug Design·Yanmin ZhangHaichun Liu
Feb 18, 2020·Frontiers in Pharmacology·Yiwei WangShengyong Yang
Dec 29, 2020·Chemical Research in Toxicology·Marcus W H WangTimothy E H Allen
Feb 19, 2021·Circulation Research·Natalia A TrayanovaJulie K Shade
Jun 11, 2021·Molecular Diversity·Anita RáczKároly Héberger
Dec 2, 2020·Journal of Chemical Information and Modeling·Vishal B SiramshettyAlexey V Zakharov
Aug 24, 2021·Journal of Chemical Information and Modeling·Kuo Hao LeeLei Shi
Sep 11, 2021·Journal of Chemical Information and Modeling·Teresa Maria CreanzaGiuseppe Felice Mangiatordi

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