Prediction of Estrogenic Bioactivity of Environmental Chemical Metabolites

The US 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. We used commercially available software to predict metabolites
of 50 parent compounds, out of which 38 chemicals are known to have
estrogenic metabolites, and 12 compounds and their metabolites are
negative for estrogenic activity. Three ER QSAR models were used to
determine potential estrogen 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 estrogenicity 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
estrogenic metabolites were predicted as potential biotransformation
products derived from the parent chemical. The QSAR models estimated
stronger estrogenic 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 estrogenicity 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.