QSAR Models for Reproductive Toxicity and Endocrine Disruption Activity

Molecules

Marjana Novič¹ 

[1] National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia

关键词: reproductive toxicity;    modeling;    CAESAR program;    counter propagation neural networks;   

DOI  :  10.3390/molecules15031987

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.