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Predictive Models for hERG Channel Blockers: Ligand-Based and Structure-Based Approaches

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Abstract:

Acquired long QT syndrome caused by drugs that block the human ether-a-go-go-related-gene (hERG) K+ channel causes severe side effects and thus represents a major problem in clinical studies of drug candidates. Therefore, early prediction of hERG K+ channel affinity of drug candidates is becoming increasingly important in the drug discovery process. Both structure-based and ligand-based approaches have been undertaken to shed more light on the molecular basis of drug-channel interaction. In this article, in silico approaches for prediction of interaction with hERG are reviewed. Special attention is drawn to the in vitro biological testing systems as well as to consensus approaches for improvement of predictive power.

Keywords: LQTS; QSAR; TdP; classification; hERG; homology model; potassium channel

Document Type: Research Article

DOI: http://dx.doi.org/10.2174/092986707782794087

Affiliations: Emerging Field Pharmacoinformatics,Department of Medicinal Chemistry, University of Vienna, Althanstrasse 14, A-1090,Vienna, Austria.

Publication date: December 1, 2007

More about this publication?
  • Current Medicinal Chemistry covers all the latest and outstanding developments in medicinal chemistry and rational drug design. Each issue contains a series of timely in-depth reviews written by leaders in the field covering a range of the current topics in medicinal chemistry. Current Medicinal Chemistry is an essential journal for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important developments.
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