Premium
Pred‐hERG: A Novel web‐Accessible Computational Tool for Predicting Cardiac Toxicity
Author(s) -
Braga Rodolpho C.,
Alves Vinicius M.,
Silva Meryck F. B.,
Muratov Eugene,
Fourches Denis,
Lião Luciano M.,
Tropsha Alexander,
Andrade Carolina H.
Publication year - 2015
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201500040
Subject(s) - herg , computer science , identification (biology) , web server , drug discovery , computational biology , drug development , channel (broadcasting) , data mining , the internet , bioinformatics , drug , world wide web , pharmacology , biology , medicine , potassium channel , computer network , botany
The blockage of the hERG K(+) channels is closely associated with lethal cardiac arrhythmia. The notorious ligand promiscuity of this channel earmarked hERG as one of the most important antitargets to be considered in early stages of drug development process. Herein we report on the development of an innovative and freely accessible web server for early identification of putative hERG blockers and non-blockers in chemical libraries. We have collected the largest publicly available curated hERG dataset of 5,984 compounds. We succeed in developing robust and externally predictive binary (CCR≈0.8) and multiclass models (accuracy≈0.7). These models are available as a web-service freely available for public at http://labmol.farmacia.ufg.br/predherg/. Three following outcomes are available for the users: prediction by binary model, prediction by multi-class model, and the probability maps of atomic contribution. The Pred-hERG will be continuously updated and upgraded as new information became available.