Abstract
The blockage of the voltage dependent ion channel encoded by human ether-a-go-go related gene (hERG) may lead to drug-induced QT interval prolongation, which is a critical side-effect of non-cardiovasular therapeutic agents. Therefore, identification of potential hERG channel blockers at the early stage of drug discovery process will decrease the risk of cardiotoxicity-related attritions in the later and more expensive development stage. Computational approaches provide economic and efficient ways to evaluate the hERG liability for large-scale compound libraries. In this review, the structure of the hERG channel is briefly outlined first. Then, the latest developments in the computational predictions of hERG channel blockers and the theoretical studies on modeling hERG-blocker interactions are summarized. Finally, the challenges of developing reliable prediction models of hERG blockers, as well as the strategies for surmounting these challenges, are discussed.
Keywords: hERG, QT prolongation, ADME/T, QSAR, QSPR, homology modeling, pharmacophore modeling, molecular docking.
Current Topics in Medicinal Chemistry
Title:Recent Developments in Computational Prediction of hERG Blockage
Volume: 13 Issue: 11
Author(s): Sichao Wang, Youyong Li, Lei Xu, Dan Li and Tingjun Hou
Affiliation:
Keywords: hERG, QT prolongation, ADME/T, QSAR, QSPR, homology modeling, pharmacophore modeling, molecular docking.
Abstract: The blockage of the voltage dependent ion channel encoded by human ether-a-go-go related gene (hERG) may lead to drug-induced QT interval prolongation, which is a critical side-effect of non-cardiovasular therapeutic agents. Therefore, identification of potential hERG channel blockers at the early stage of drug discovery process will decrease the risk of cardiotoxicity-related attritions in the later and more expensive development stage. Computational approaches provide economic and efficient ways to evaluate the hERG liability for large-scale compound libraries. In this review, the structure of the hERG channel is briefly outlined first. Then, the latest developments in the computational predictions of hERG channel blockers and the theoretical studies on modeling hERG-blocker interactions are summarized. Finally, the challenges of developing reliable prediction models of hERG blockers, as well as the strategies for surmounting these challenges, are discussed.
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Cite this article as:
Wang Sichao, Li Youyong, Xu Lei, Li Dan and Hou Tingjun, Recent Developments in Computational Prediction of hERG Blockage, Current Topics in Medicinal Chemistry 2013; 13 (11) . https://dx.doi.org/10.2174/15680266113139990036
DOI https://dx.doi.org/10.2174/15680266113139990036 |
Print ISSN 1568-0266 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4294 |
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