We have utilized a validated (standardized) estrogen receptor (ER) competitive-binding assay to determine the ER affinity for a large, structurally diverse group of chemicals. Uteri from ovariectomized Sprague-Dawley rats were the ER source for the competitive-binding assay. Initially, test chemicals were screened at high concentrations to determine whether a chemical competed with [3H]-estradiol for the ER. Test chemicals that exhibited affinity for the ER in the first tier were subsequently assayed using a wide range of concentrations to characterize the binding curve and to determine each chemical's IC50 and relative binding affinity (RBA) values. Overall, we assayed 188 chemicals, covering a 1 x 10(6)-fold range of RBAs from several different chemical or use categories, including steroidal estrogens, synthetic estrogens, antiestrogens, other miscellaneous steroids, alkylphenols, diphenyl derivatives, organochlorines, pesticides, alkylhydroxybenzoate preservatives (parabens), phthalates, benzophenone compounds, and a number of other miscellaneous chemicals. Of the 188 chemicals tested, 100 bound to the ER while 88 were non-binders. Included in the 100 chemicals that bound to the ER were 4-benzyloxyphenol, 2,4-dihydroxybenzophenone, and 2,2'-methylenebis(4-chlorophenol), compounds that have not been shown previously to bind the ER. It was also evident that certain structural features, such as an overall ring structure, were important for ER binding. The current study provides the most structurally diverse ER RBA data set with the widest range of RBA values published to date.

Understanding structural requirements for a chemical to exhibit estrogen receptor (ER) binding has been important in various fields. This knowledge has been directly and indirectly applied to design drugs for human estrogen replacement therapy, and to identify estrogenic endocrine disruptors. This paper reports structure-activity relationships (SARs) based on a total of 230 chemicals, including both natural and xenoestrogens. Activities were generated using a validated ER competitive binding assay, which covers a 10 6 -fold range. This study is focused on identification of structural commonalities among diverse ER ligands. It provides an overall picture of how xenoestrogens structurally resemble endogenous 17 -estradiol (E 2 ) and the synthetic estrogen diethylstilbestrol (DES). On the basis of SAR analysis, five distinguishing criteria were found to be essential for xenoestrogen activity, using E 2 as a template: (1) H-bonding ability of the phenolic ring mimicking the 3-OH, (2) H-bond donor mimicking the17 -OH and O-O distance between 3-and 17 -OH, (3) precise steric hydrophobic centers mimicking steric 7R-and 11 -substituents, (4) hydrophobicity, and (5) a ring structure. The 3-position H-bonding ability of phenols is a significant requirement for ER binding. This contributes as both a H-bond donor and acceptor, although predominantly as a donor. However, the 17 -OH contributes as a H-bond donor only. The precise space (the size and orientation) of steric hydrophobic bulk groups is as important as a 17 -OH. Where a direct comparison can be made, strong estrogens tend to be more hydrophobic. A rigid ring structure favors ER binding. The knowledge derived from this study is rationalized into a set of hierarchical rules that will be useful in guidance for identification of potential estrogens.

Endocrine disruptors (EDs) have a variety of adverse effects in humans and animals. About 58,000 chemicals, most having little safety data, must be tested in a group of tiered assays. As assays will take years, it is important to develop rapid methods to help in priority setting. For application to large data sets, we have developed an integrated system that contains sequential four phases to predict the ability of chemicals to bind to the estrogen receptor (ER), a prevalent mechanism for estrogenic EDs. Here we report the results of evaluating two types of QSAR models for inclusion in phase III to quantitatively predict chemical binding to the ER. Our data set for the relative binding affinities (RBAs) to the ER consists of 130 chemicals covering a wide range of structural diversity and a 6 orders of magnitude spread of RBAs. CoMFA and HQSAR models were constructed and compared for performance. The CoMFA model had a r2 = 0.91 and a q2LOO = 0.66. HQSAR showed reduced performance compared to CoMFA with r2 = 0.76 and q2LOO = 0.59. A number of parameters were examined to improve the CoMFA model. Of these, a phenol indicator increased the q2LOO to 0.71. When up to 50% of the chemicals were left out in the leave-N-out cross-validation, the q2 remained significant. Finally, the models were tested by using two test sets; the q2pred for these were 0.71 and 0.62, a significant result which demonstrates the utility of the CoMFA model for predicting the RBAs of chemicals not included in the training set. If used in conjunction with phases I and II, which reduced the size of the data set dramatically by eliminating most inactive chemicals, the current CoMFA model (phase III) can be used to predict the RBA of chemicals with sufficient accuracy and to provide quantitative information for priority setting.

Consumption of phytoestrogens and mycoestrogens in food products or as dietary supplements is of interest because of both the potential beneficial and adverse effects of these compounds in estrogen-responsive target tissues. Although the hazards of exposure to potent estrogens such as diethylstilbestrol in developing male and female reproductive tracts are well characterized, less is known about the effects of weaker estrogens including phytoestrogens. With some exceptions, ligand binding to the estrogen receptor (ER) predicts uterotrophic activity. Using a well-established and rigorously validated ER-ligand binding assay, we assessed the relative binding affinity (RBA) for 46 chemicals from several chemical structure classes of potential phytoestrogens and mycoestrogens. Although none of the test compounds bound to ER with the affinity of the standard, 17beta-estradiol (E(2)), ER binding was found among all classes of chemical structures (flavones, isoflavones, flavanones, coumarins, chalcones and mycoestrogens). Estrogen receptor relative binding affinities were distributed across a wide range (from approximately 43 to 0.00008; E(2) = 100). These data can be utilized before animal testing to rank order estimates of the potential for in vivo estrogenic activity of a wide range of untested plant chemicals (as well as other chemicals) based on ER binding.

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