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ProTox-II: a webserver for the prediction of toxicity of chemicals
Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that inco...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031011/ https://www.ncbi.nlm.nih.gov/pubmed/29718510 http://dx.doi.org/10.1093/nar/gky318 |
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author | Banerjee, Priyanka Eckert, Andreas O Schrey, Anna K Preissner, Robert |
author_facet | Banerjee, Priyanka Eckert, Andreas O Schrey, Anna K Preissner, Robert |
author_sort | Banerjee, Priyanka |
collection | PubMed |
description | Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity. |
format | Online Article Text |
id | pubmed-6031011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60310112018-07-10 ProTox-II: a webserver for the prediction of toxicity of chemicals Banerjee, Priyanka Eckert, Andreas O Schrey, Anna K Preissner, Robert Nucleic Acids Res Web Server Issue Advancement in the field of computational research has made it possible for the in silico methods to offer significant benefits to both regulatory needs and requirements for risk assessments, and pharmaceutical industry to assess the safety profile of a chemical. Here, we present ProTox-II that incorporates molecular similarity, pharmacophores, fragment propensities and machine-learning models for the prediction of various toxicity endpoints; such as acute toxicity, hepatotoxicity, cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, adverse outcomes pathways (Tox21) and toxicity targets. The predictive models are built on data from both in vitro assays (e.g. Tox21 assays, Ames bacterial mutation assays, hepG2 cytotoxicity assays, Immunotoxicity assays) and in vivo cases (e.g. carcinogenicity, hepatotoxicity). The models have been validated on independent external sets and have shown strong performance. ProTox-II provides a freely available webserver for in silico toxicity prediction for toxicologists, regulatory agencies, computational and medicinal chemists, and all users without login at http://tox.charite.de/protox_II. The webserver takes a two-dimensional chemical structure as an input and reports the possible toxicity profile of the chemical for 33 models with confidence scores, and an overall toxicity radar chart along with three most similar compounds with known acute toxicity. Oxford University Press 2018-07-02 2018-04-30 /pmc/articles/PMC6031011/ /pubmed/29718510 http://dx.doi.org/10.1093/nar/gky318 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Banerjee, Priyanka Eckert, Andreas O Schrey, Anna K Preissner, Robert ProTox-II: a webserver for the prediction of toxicity of chemicals |
title | ProTox-II: a webserver for the prediction of toxicity of chemicals |
title_full | ProTox-II: a webserver for the prediction of toxicity of chemicals |
title_fullStr | ProTox-II: a webserver for the prediction of toxicity of chemicals |
title_full_unstemmed | ProTox-II: a webserver for the prediction of toxicity of chemicals |
title_short | ProTox-II: a webserver for the prediction of toxicity of chemicals |
title_sort | protox-ii: a webserver for the prediction of toxicity of chemicals |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6031011/ https://www.ncbi.nlm.nih.gov/pubmed/29718510 http://dx.doi.org/10.1093/nar/gky318 |
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