Ehrlich Veronika A, Dellafiora Luca, Mollergues Julie, Dall'Asta Chiara, Serrant Patrick, Marin-Kuan Maricel, Lo Piparo Elena, Schilter Benoit, Cozzini Pietro
Chemical Food Safety Group, Food Quality & Safety Department, Nestlé Research Center, Lausanne, Switzerland.
Molecular Modelling Laboratory, Department of Food Science, University of Parma, Parma, Italy.
ALTEX. 2015;32(4):275-86. doi: 10.14573/altex.1412232. Epub 2015 May 18.
Within the framework of reduction, refinement and replacement of animal experiments, new approaches for identification and characterization of chemical hazards have been developed. Grouping and read across has been promoted as a most promising alternative approach. It uses existing toxicological information on a group of chemicals to make predictions on the toxicity of uncharacterized ones. In the present work, the feasibility of applying in vitro and in silico techniques to group chemicals for read across was studied using the food mycotoxin zearalenone (ZEN) and metabolites as a case study. ZEN and its reduced metabolites are known to act through activation of the estrogen receptor α (ERα). The ranking of their estrogenic potencies appeared highly conserved across test systems including binding, in vitro and in vivo assays. This data suggests that activation of ERα may play a role in the molecular initiating event (MIE) and be predictive of adverse effects and provides the rationale to model receptor-binding for hazard identification. The investigation of receptor-ligand interactions through docking simulation proved to accurately rank estrogenic potencies of ZEN and reduced metabolites, showing the suitability of the model to address estrogenic potency for this group of compounds. Therefore, the model was further applied to biologically uncharacterized, commercially unavailable, oxidized ZEN metabolites (6α-, 6β-, 8α-, 8β-, 13- and 15-OH-ZEN). Except for 15-OH-ZEN, the data indicate that in general, the oxidized metabolites would be considered a lower estrogenic concern than ZEN and reduced metabolites.
在动物实验的减少、优化和替代框架下，已开发出识别和表征化学危害的新方法。分组和类推法已被推广为一种最有前景的替代方法。它利用一组化学品的现有毒理学信息来预测未表征化学品的毒性。在本研究中，以食品霉菌毒素玉米赤霉烯酮（ZEN）及其代谢产物为例，研究了应用体外和计算机模拟技术对化学品进行分组以进行类推的可行性。已知ZEN及其还原代谢产物通过激活雌激素受体α（ERα）发挥作用。在包括结合、体外和体内试验在内的各种测试系统中，它们的雌激素活性排名似乎高度保守。这些数据表明，ERα的激活可能在分子起始事件（MIE）中起作用，并可预测不良反应，为建立受体结合模型以识别危害提供了理论依据。通过对接模拟对受体-配体相互作用的研究证明，该模型能够准确地对ZEN及其还原代谢产物的雌激素活性进行排名，表明该模型适用于评估这组化合物的雌激素活性。因此，该模型进一步应用于生物学上未表征、商业上不可用的氧化ZEN代谢产物（6α-、6β-、8α-、8β-、13-和15-OH-ZEN）。除15-OH-ZEN外，数据表明，一般来说，氧化代谢产物的雌激素活性低于ZEN及其还原代谢产物。
