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QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity

Reproductive toxicity is an important regulatory endpoint, which is required in registration procedures of chemicals used for different purposes (for example pesticides). The in vivo tests are expensive, time consuming and require large numbers of animals, which must be sacrificed. Therefore an effo...

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Detalles Bibliográficos
Autores principales: Novič, Marjana, Vračko, Marjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6257250/
https://www.ncbi.nlm.nih.gov/pubmed/20336027
http://dx.doi.org/10.3390/molecules15031987
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author Novič, Marjana
Vračko, Marjan
author_facet Novič, Marjana
Vračko, Marjan
author_sort Novič, Marjana
collection PubMed
description Reproductive toxicity is an important regulatory endpoint, which is required in registration procedures of chemicals used for different purposes (for example pesticides). The in vivo tests are expensive, time consuming and require large numbers of animals, which must be sacrificed. Therefore an effort is ongoing to develop alternative In vitro and in silico methods to evaluate reproductive toxicity. In this review we describe some modeling approaches. In the first example we describe the CAESAR model for prediction of reproductive toxicity; the second example shows a classification model for endocrine disruption potential based on counter propagation artificial neural networks; the third example shows a modeling of relative binding affinity to rat estrogen receptor, and the fourth one shows a receptor dependent modeling experiment.
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spelling pubmed-62572502018-12-04 QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity Novič, Marjana Vračko, Marjan Molecules Review Reproductive toxicity is an important regulatory endpoint, which is required in registration procedures of chemicals used for different purposes (for example pesticides). The in vivo tests are expensive, time consuming and require large numbers of animals, which must be sacrificed. Therefore an effort is ongoing to develop alternative In vitro and in silico methods to evaluate reproductive toxicity. In this review we describe some modeling approaches. In the first example we describe the CAESAR model for prediction of reproductive toxicity; the second example shows a classification model for endocrine disruption potential based on counter propagation artificial neural networks; the third example shows a modeling of relative binding affinity to rat estrogen receptor, and the fourth one shows a receptor dependent modeling experiment. Molecular Diversity Preservation International 2010-03-22 /pmc/articles/PMC6257250/ /pubmed/20336027 http://dx.doi.org/10.3390/molecules15031987 Text en © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Review
Novič, Marjana
Vračko, Marjan
QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity
title QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity
title_full QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity
title_fullStr QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity
title_full_unstemmed QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity
title_short QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity
title_sort qsar models for reproductive toxicity and endocrine disruption activity
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6257250/
https://www.ncbi.nlm.nih.gov/pubmed/20336027
http://dx.doi.org/10.3390/molecules15031987
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