Given the high attention to endocrine disrupting chemicals (EDC), there is an urgent need for the development of rapid and reliable approaches for the screening of large numbers of chemicals with respect to their endocrine disruption potential. This study aimed at the assessment of the correlation between the predicted results of a battery of in silico tools and the reported observed adverse effects from in vivo reproductive toxicity studies. We used VirtualToxLab (VTL) software and the EndocrineDisruptome (ED) online tool to evaluate the binding affinities to nuclear receptors of 17 pesticides, 7 of which were classified as reprotoxic substances under Regulation (EC) No 1272/2008 on the classification, labelling and packaging of substances and mixtures (CLP). Then, we aligned the results of the in silico modelling with data from ToxCast assays and in vivo reproductive toxicity studies. We combined results from different in silico tools in two different ways to improve the characteristics of their predictive performance. Reproductive toxicity can be caused by various mechanisms; however, in this study, we demonstrated that the use of a battery of in silico tools for assessing the binding to nuclear receptors can be useful for identifying hazardous compounds and for prioritizing further studies.
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