A Computational Approach Predicting CYP450 Metabolism and Estrogenic Activity of an Endocrine Disrupting Compound


Jason B. Harris, Melanie L. Eldridge, Gary Sayler, Fu-Min Menn, Alice C. Layton, Jerome Baudry


Endocrine disrupting chemicals influence growth and development through interactions with the hormone system, often through binding to hormone receptors such as the estrogen receptor. Computational methods can predict endocrine disrupting chemical activity of unmodified compounds, but approaches predicting activity following metabolism are lacking. The present study uses a well-known environmental contaminant, PCB-30 (2,4,6-trichlorobiphenyl), as a prototype endocrine disrupting chemical and integrates predictive (computational) and experimental methods to determine its metabolic transformation by cytochrome P450 3A4 (CYP3A4) and cytochrome P450 2D6 (CYP2D6) into estrogenic byproducts. Computational predictions suggest that hydroxylation of PCB-30 occurs at the 3- or 4-phenol positions and leads to metabolites that bind more strongly than the parent molecule to the human estrogen receptor alpha (hER-α). Gas chromatography-mass spectrometry experiments confirmed that the primary metabolite for CYP3A4 and CYP2D6 is 4-hydroxy-PCB-30, and the secondary metabolite is 3-hydroxy-PCB-30. Cell-based bioassays (bioluminescent yeast expressing hER-α) confirmed that hydroxylated metabolites are more estrogenic than PCB-30. These experimental results support the applied model’s ability to predict the metabolic and estrogenic fate of PCB-30, which could be used to identify other endocrine disrupting chemicals involved in similar pathways.

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Harris J, Eldridge M, Sayler G, Layton A, Baudry J. 2014. A computational approach predicting CYP450 metabolism and estrogenic activity of an endocrine disrupting compound (PCB-30). Environmental Toxicology & Chemistry 33:1615-1623.