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WS Branham1 *, RM Blair1 *, S Dial1 , C Moland1 , B Hass1 , H Fang1 , W Tong1 , L Shi1 , R Perkins1 , DM Sheehan1 *
Division of Genetic and Reproductive Toxicology or R.O.W. Sciences Inc., National Center for Toxicological Research, Jefferson, AR 1
Consumption of phytoestrogens in soy-based food products or as dietary supplements is of interest because of both the potentially beneficial and adverse effects of these compounds in endocrine target tissues. While the hazards of exposure to potent estrogens in developing reproductive tracts are well characterized, little is known about the effects of weak estrogens including the phytoestrogens. We have established several QSAR models to predict the RBA's of a wide variety of compounds. The ER model is statistically robust with high self-consistency (r2>0.9) and predictive ability (q2>0.68) and has potential utility to predict estrogenic activity of large numbers of chemicals. The model is based on Comparative Molecular Field Analysis (CoMFA), using RBA data from assays measuring ligand binding to rat ER to predict the RBA's of untested chemicals. CoMFA models are under development for estrogen binding proteins in human serum [Sex Hormone Binding Globulin; SHBG] and rat amniotic fluid [-fetoprotein; AFP]. For ER, RBAs are evenly distributed across six orders of magnitude. RBA's for phytoestrogens appear much lower for SHBG and AFP. Prediction of RBA's for a wide range of chemicals will be useful to prioritize chemicals for testing and to guide dose selection prior to animal testing.
This abstract is being presented on Monday, August 2 at 8:00 AM to 10:15 AM at CUB 2nd Floor Ballroom.