eMolTox: prediction of molecular toxicity with confidence

Changge Ji; Fredrik Svensson; Azedine Zoufir; Andreas Bender

doi:10.1093/bioinformatics/bty135

eMolTox: prediction of molecular toxicity with confidence

Bioinformatics. 2018 Jul 15;34(14):2508-2509. doi: 10.1093/bioinformatics/bty135.

Authors

Changge Ji^{1

2}, Fredrik Svensson^{2

3}, Azedine Zoufir², Andreas Bender²

Affiliations

¹ Shanghai Engineering Research Center for Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China.
² Department of Chemistry, Center for Molecular Informatics, Cambridge, UK.
³ IOTA Pharmaceuticals, St John's Innovation Centre, Cambridge, UK.

PMID: 29522123
DOI: 10.1093/bioinformatics/bty135

Abstract

Summary: In this work, we present eMolTox, a web server for the prediction of potential toxicity associated with a given molecule. A total of 174 toxicology-related in vitro/vivo experimental datasets were used for model construction and Mondrian conformal prediction was used to estimate the confidence of the resulting predictions. Toxic substructure analysis is also implemented in eMolTox. eMolTox predicts and displays a wealth of information of potential molecular toxicities for safety analysis in drug development.

Availability and implementation: The eMolTox Server is freely available for use on the web at http://xundrug.cn/moltox.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Carcinogens / toxicity
Humans
Mutagens / toxicity
Software*
Toxicology / methods*

Substances

Carcinogens
Mutagens