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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...

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Autores principales: Pizzo, Fabiola, Gadaleta, Domenico, Lombardo, Anna, Nicolotti, Orazio, Benfenati, Emilio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
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.
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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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