The United States Environmental Protection Agency’s (EPA) Endocrine Disruptor Screening Program (EDSP) is using in vitro data generated from ToxCast/Tox21 high-throughput screening assays to assess the endocrine activity of environmental chemicals. Considering that in vitro assays may have limited metabolic capacity, inactive chemicals that are biotransformed into metabolites with endocrine bioactivity may be missed for further screening and testing. Therefore, there is a value in developing novel approaches to account for metabolism and endocrine activity of both parent chemicals and their associated metabolites. The authors used commercially available software to predict metabolites of 50 parent compounds, out of which 38 chemicals are known to have oestrogenic metabolites, and 12 compounds and their metabolites are negative for oestrogenic activity. Three ER QSAR models were used to determine potential oestrogen bioactivity of the parent compounds and predicted metabolites, the outputs of the models were averaged, and the chemicals were then ranked based on the total oestrogenicity of the parent chemical and metabolites. The metabolite prediction software correctly identified known estrogenic metabolites for 26 out of 27 parent chemicals with associated metabolite data, and 39 out of 46 oestrogenic metabolites were predicted as potential biotransformation products derived from the parent chemical. The QSAR models estimated stronger oestrogenic activity for the majority of the known estrogenic metabolites compared to their parent chemicals. Finally, the three models identified a similar set of parent compounds as top ranked chemicals based on the oestrogenicity of putative metabolites. This proposed in silico approach is an inexpensive and rapid strategy for the detection of chemicals with estrogenic metabolites and may reduce potential false negative results from in vitro assays.
Authors: Pinto CL, Mansouri K, Judson R, Browne P. ;Full Source: Chemical Research in Toxicology. 2016 Sep 19;29(9):1410-27. doi: 10.1021/acs.chemrestox.6b00079. Epub 2016 Aug 31. ;