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Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data
BACKGROUND: The potential for a compound to cause hepatotoxicity and nephrotoxicity is a matter of extreme interest for human health risk assessment. To assess liver and kidney toxicity, repeated-dose toxicity (RDT) studies are conducted mainly on rodents. However, these tests are expensive, time-co...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635184/ https://www.ncbi.nlm.nih.gov/pubmed/26550029 http://dx.doi.org/10.1186/s13065-015-0139-7 |
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author | Pizzo, Fabiola Gadaleta, Domenico Lombardo, Anna Nicolotti, Orazio Benfenati, Emilio |
author_facet | Pizzo, Fabiola Gadaleta, Domenico Lombardo, Anna Nicolotti, Orazio Benfenati, Emilio |
author_sort | Pizzo, Fabiola |
collection | PubMed |
description | BACKGROUND: The potential for a compound to cause hepatotoxicity and nephrotoxicity is a matter of extreme interest for human health risk assessment. To assess liver and kidney toxicity, repeated-dose toxicity (RDT) studies are conducted mainly on rodents. However, these tests are expensive, time-consuming and require large numbers of animals. For early toxicity screening, in silico models can be applied, reducing the costs, time and animals used. Among in silico approaches, structure–activity relationship (SAR) methods, based on the identification of chemical substructures (structural alerts, SAs) related to a particular activity (toxicity), are widely employed. RESULTS: We identified and evaluated some SAs related to liver and kidney toxicity, using RDT data on rats taken from the hazard evaluation support system (HESS) database. We considered only SAs that gave the best percentages of true positives (TP). CONCLUSIONS: It was not possible to assign an unambiguous mode of action for all the SAs, but a mechanistic explanation is provided for some of them. Such achievements may help in the early identification of liver and renal toxicity of substances. |
format | Online Article Text |
id | pubmed-4635184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-46351842015-11-07 Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data Pizzo, Fabiola Gadaleta, Domenico Lombardo, Anna Nicolotti, Orazio Benfenati, Emilio Chem Cent J Research Article BACKGROUND: The potential for a compound to cause hepatotoxicity and nephrotoxicity is a matter of extreme interest for human health risk assessment. To assess liver and kidney toxicity, repeated-dose toxicity (RDT) studies are conducted mainly on rodents. However, these tests are expensive, time-consuming and require large numbers of animals. For early toxicity screening, in silico models can be applied, reducing the costs, time and animals used. Among in silico approaches, structure–activity relationship (SAR) methods, based on the identification of chemical substructures (structural alerts, SAs) related to a particular activity (toxicity), are widely employed. RESULTS: We identified and evaluated some SAs related to liver and kidney toxicity, using RDT data on rats taken from the hazard evaluation support system (HESS) database. We considered only SAs that gave the best percentages of true positives (TP). CONCLUSIONS: It was not possible to assign an unambiguous mode of action for all the SAs, but a mechanistic explanation is provided for some of them. Such achievements may help in the early identification of liver and renal toxicity of substances. Springer International Publishing 2015-11-05 /pmc/articles/PMC4635184/ /pubmed/26550029 http://dx.doi.org/10.1186/s13065-015-0139-7 Text en © Pizzo et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Pizzo, Fabiola Gadaleta, Domenico Lombardo, Anna Nicolotti, Orazio Benfenati, Emilio Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
title | Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
title_full | Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
title_fullStr | Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
title_full_unstemmed | Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
title_short | Identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
title_sort | identification of structural alerts for liver and kidney toxicity using repeated dose toxicity data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4635184/ https://www.ncbi.nlm.nih.gov/pubmed/26550029 http://dx.doi.org/10.1186/s13065-015-0139-7 |
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