Literature DB >> 22149888

hERGCentral: a large database to store, retrieve, and analyze compound-human Ether-à-go-go related gene channel interactions to facilitate cardiotoxicity assessment in drug development.

Fang Du1, Haibo Yu, Beiyan Zou, Joseph Babcock, Shunyou Long, Min Li.   

Abstract

The unintended and often promiscous inhibition of the cardiac human Ether-à-go-go related gene (hERG) potassium channel is a common cause for either delay or removal of therapeutic compounds from development and withdrawal of marketed drugs. The clinical manifestion is prolongation of the duration between QRS complex and T-wave measured by surface electrocardiogram (ECG)-hence Long QT Syndrome. There are several useful online resources documenting hERG inhibition by known drugs and bioactives. However, their utilities remain somewhat limited because they are biased toward well-studied compounds and their number of data points tends to be much smaller than many commercial compound libraries. The hERGCentral ( www.hergcentral.org ) is mainly based on experimental data obtained from a primary screen by electrophysiology against more than 300,000 structurally diverse compounds. The system is aimed to display and combine three resources: primary electrophysiological data, literature, as well as online reports and chemical library collections. Currently, hERGCentral has annotated datasets of more than 300,000 compounds including structures and chemophysiological properties of compounds, raw traces, and biophysical properties. The system enables a variety of query formats, including searches for hERG effects according to either chemical structure or properties, and alternatively according to the specific biophysical properties of current changes caused by a compound. Therefore, the hERGCentral, as a unique and evolving resource, will facilitate investigation of chemically induced hERG inhibition and therefore drug development. © MARY ANN LIEBERT, INC.

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Year:  2011        PMID: 22149888      PMCID: PMC3232635          DOI: 10.1089/adt.2011.0425

Source DB:  PubMed          Journal:  Assay Drug Dev Technol        ISSN: 1540-658X            Impact factor:   1.738


  3 in total

1.  Profiling diverse compounds by flux- and electrophysiology-based primary screens for inhibition of human Ether-à-go-go related gene potassium channels.

Authors:  Beiyan Zou; Haibo Yu; Joseph J Babcock; Pritam Chanda; Joel S Bader; Owen B McManus; Min Li
Journal:  Assay Drug Dev Technol       Date:  2010-12       Impact factor: 1.738

Review 2.  Predicting drug-hERG channel interactions that cause acquired long QT syndrome.

Authors:  Michael C Sanguinetti; John S Mitcheson
Journal:  Trends Pharmacol Sci       Date:  2005-03       Impact factor: 14.819

Review 3.  hERG potassium channels and cardiac arrhythmia.

Authors:  Michael C Sanguinetti; Martin Tristani-Firouzi
Journal:  Nature       Date:  2006-03-23       Impact factor: 49.962

  3 in total
  13 in total

1.  Investigation of miscellaneous hERG inhibition in large diverse compound collection using automated patch-clamp assay.

Authors:  Hai-bo Yu; Bei-yan Zou; Xiao-liang Wang; Min Li
Journal:  Acta Pharmacol Sin       Date:  2016-01       Impact factor: 6.150

Review 2.  High throughput screening technologies for ion channels.

Authors:  Hai-bo Yu; Min Li; Wei-ping Wang; Xiao-liang Wang
Journal:  Acta Pharmacol Sin       Date:  2015-12-14       Impact factor: 6.150

3.  In silico prediction of hERG potassium channel blockage by chemical category approaches.

Authors:  Chen Zhang; Yuan Zhou; Shikai Gu; Zengrui Wu; Wenjie Wu; Changming Liu; Kaidong Wang; Guixia Liu; Weihua Li; Philip W Lee; Yun Tang
Journal:  Toxicol Res (Camb)       Date:  2016-01-14       Impact factor: 3.524

4.  Modulation of hERG potassium channel gating normalizes action potential duration prolonged by dysfunctional KCNQ1 potassium channel.

Authors:  Hongkang Zhang; Beiyan Zou; Haibo Yu; Alessandra Moretti; Xiaoying Wang; Wei Yan; Joseph J Babcock; Milena Bellin; Owen B McManus; Gordon Tomaselli; Fajun Nan; Karl-Ludwig Laugwitz; Min Li
Journal:  Proc Natl Acad Sci U S A       Date:  2012-06-28       Impact factor: 11.205

5.  Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

Authors:  Alexandru Korotcov; Valery Tkachenko; Daniel P Russo; Sean Ekins
Journal:  Mol Pharm       Date:  2017-11-13       Impact factor: 4.939

6.  Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods.

Authors:  Sankalp Jain; Vishal B Siramshetty; Vinicius M Alves; Eugene N Muratov; Nicole Kleinstreuer; Alexander Tropsha; Marc C Nicklaus; Anton Simeonov; Alexey V Zakharov
Journal:  J Chem Inf Model       Date:  2021-02-03       Impact factor: 4.956

7.  Quantum Machine Learning Algorithms for Drug Discovery Applications.

Authors:  Kushal Batra; Kimberley M Zorn; Daniel H Foil; Eni Minerali; Victor O Gawriljuk; Thomas R Lane; Sean Ekins
Journal:  J Chem Inf Model       Date:  2021-05-25       Impact factor: 6.162

8.  Global analysis reveals families of chemical motifs enriched for HERG inhibitors.

Authors:  Fang Du; Joseph J Babcock; Haibo Yu; Beiyan Zou; Min Li
Journal:  PLoS One       Date:  2015-02-20       Impact factor: 3.240

9.  Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets.

Authors:  Alex M Clark; Krishna Dole; Anna Coulon-Spektor; Andrew McNutt; George Grass; Joel S Freundlich; Robert C Reynolds; Sean Ekins
Journal:  J Chem Inf Model       Date:  2015-06-03       Impact factor: 4.956

10.  Tox-database.net: a curated resource for data describing chemical triggered in vitro cardiac ion channels inhibition.

Authors:  Sebastian Polak; Barbara Wiśniowska; Anna Glinka; Miłosz Polak
Journal:  BMC Pharmacol Toxicol       Date:  2012-08-13       Impact factor: 2.483

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