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Updated: Jun 2, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Joint effects of heterogeneous estrogenic chemicals in the E-screen--exploring the applicability of concentration
Elisabete Silva1, Nissanka Rajapakse, Martin Scholze
1Centre for Toxicology, School of Pharmacy, University of London, London WC1N1AX, UK. elisabete.silva@pharmacy.ac.uk
Abstract:
In the last few years, significant advances have been made toward understanding the joint action of endocrine disrupting chemicals (EDCs). A number of studies have demonstrated that the combined effects of different types of EDCs (e.g., estrogenic, antiandrogenic, or thyroid-disrupting agents) can be predicted by the model of concentration addition (CA). However, there is still limited information on the effects of mixtures of large numbers of chemicals with varied structural features, which are more representative of realistic human exposure scenarios. The work presented here aims at filling this gap. Using a breast cancer cell proliferation assay (E-Screen), we assessed the joint effects of five mixtures, containing between 3 and 16 estrogenic agents, including compounds as diverse as steroidal hormones (endogenous and synthetic), pesticides, cosmetic additives, and phytoestrogens. CA was employed to predict mixture effects, which were then compared with experimental outcomes. The effects of two of the mixtures tested were additive, being accurately predicted by CA. However, for the three other mixtures, CA slightly overestimated the experimental observations. In view of these results, we hypothesized that the deviations were due to increased metabolism of steroidal estrogens in the mixture setting. We investigated this by testing the impact of two such mixtures on the activation and expression of steroidal estrogen metabolizing enzymes, such as cytochrome P450 (CYP) 1A1, CYP 1B1, and CYP 3A4. Activation of CYP 1B1 and, consequently, a reduction in the levels of steroidal estrogens in the mixture could contribute to the shortfall from the additivity prediction that we observed.
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