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Molecules 2010, 15(3), 1987-1999; doi:10.3390/molecules15031987

QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity

National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
Author to whom correspondence should be addressed.
Received: 21 December 2009 / Revised: 29 January 2010 / Accepted: 19 March 2010 / Published: 22 March 2010
(This article belongs to the Special Issue Molecular Diversity Feature Papers)
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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.
Keywords: reproductive toxicity; modeling; CAESAR program; counter propagation neural networks reproductive toxicity; modeling; CAESAR program; counter propagation neural networks
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Novič, M.; Vračko, M. QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity. Molecules 2010, 15, 1987-1999.

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