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

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

Volume: 14 Issue: 28

Author(s): Khac-Minh Thai and Gerhard F. Ecker

Affiliation:

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

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.

Cite this article as:

Thai Khac-Minh and Ecker F. Gerhard, Predictive Models for hERG Channel Blockers: Ligand-Based and Structure-Based Approaches, Current Medicinal Chemistry 2007; 14 (28) . https://dx.doi.org/10.2174/092986707782794087