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

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

SUBMITTER: Du-Cuny L 

PROVIDER: S-EPMC3894065 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature