Evaluation of a novel method of predicting estrogen activity of a group of structurally diverse compounds

The number of environmental chemicals found to have some level of endocrine activity has led to concern about the possible effects these compounds could have on human health and the health of other species, populations, and possibly whole ecosystems. The United States Environmental Protection Agency has been charged with testing a large number of these compounds, called endocrine-disrupting chemicals or hormonally active agents for hormonal activity. Limited testing resources have led to a call for alternate methods of screening, possibly for use in prioritizing this list to assist in efficient allocation of resources for further testing. This study describes a computational method, the categorical structure activity relationship (cat-SAR) program, which has demonstrated high predictivity for the estrogen-like activity of a set of diverse chemical structures. The data set for this model was taken from a set of 122 compounds assayed for estrogenicity with the ESCREEN assay, an in vitro assay for estrogenicity. Two endpoints were modeled. The model for relative proliferative potency demonstrated an 82% correct prediction rate, while the relative proliferative effect achieved an 86% correct rate of prediction in model validation. Preliminary evaluation of fragments upon which the models were based suggested a sound mechanistic basis. The models also compared similarly to previous ESCREEN models developed using a different methodology. Based on the results described herein, the cat-SAR method would be a useful approach in screening compounds for estrogen activity as well as for investigating their mechanism of action