A critical assessment of combined ligand- and structure-based approaches to hERG channel blocker modeling

Lei Du-Cuny, Lu Chen, Shuxing Zhang

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

Blockade of human ether-à-go-go related gene (hERG) channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining quantitative structure-activity relationship (QSAR) modeling, pharmacophore analysis, and molecular docking. Our consensus models demonstrated high-predictive capacity and improved enrichment and could correctly classify 91.8% of 147 hERG blockers from 351 inactives. To further enhance our modeling effort, hERG homology models were constructed, and molecular docking studies were conducted, resulting in high correlations (R2 = 0.81) between predicted and experimental pIC50s. We expect our unique models can be applied to efficient screening for hERG blockades, and our extensive understanding of the hERG-inhibitor interactions will facilitate the rational design of drugs devoid of hERG channel activity and hence with reduced cardiac toxicities.

Original languageEnglish (US)
Pages (from-to)2948-2960
Number of pages13
JournalJournal of Chemical Information and Modeling
Volume51
Issue number11
DOIs
StatePublished - Nov 28 2011

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • Computer Science Applications
  • Library and Information Sciences

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