MP6 Quantitative Structure Activity Relationships (QSARs)
Monday, 14 November 2005: 8:00 AM - 5:30 PM in Exhibit Hall

(SER-1117-801357) QSAR evaluation of ER Binding Affinity of Chemicals and Metabolites.

Mekenyan, O¹, Serafimova, R¹, Aladjov, H², Kolanczyk, R², Schmieder, P², Akahori, Y³, Nakai, M³, Jones, J⁴, ¹ Laboratory of Mathematical Chemistry, As. Zlatarov University, Bourgas, Bulgaria² U.S. EPA, Mid-Continent Ecology Division, 6201 Congdon Blvd., 55804, Duluth, MN, USA³ Chemicals Evaluation Research Institute (CERI), 1600 Shimotakano,Sugito-machi,Kitakatsushika-gun, 345-0043, Saitama, Japan⁴ US EPA, ORD, NERL, Ecosystems Research Division, 30605, Athens, GA, USA

ABSTRACT- Chemicals in commerce are assessed for a variety of potential adverse effects. As governments around the globe strive to meet the challenge of assessing chemicals as endocrine disruptors, the need for hypothesis-driven strategies to prioritize chemicals for testing has risen to the forefront. This study describes quantitative structure-activity relationships (QSAR) to predict chemical ER binding as part of a larger research effort using an iterative process of strategic selection of chemicals for testing, in vitro data generation, in silico model development, etc., to facilitate efficient model evaluation and refinement for user-specified levels of predictive certainty. A multi-dimensional formulation of a COmmon REactivity PAttern (COREPA) modeling approach has been used to investigate chemical binding to the human estrogen receptor (hER). A training set of 656 chemicals includes 500 steroid and environmental chemicals (CERI) and 156 to further explore hER-structure interactions (selected J. Katzenellenbogen references). Analysis of reactivity patterns based on the distance between nucleophilic sites resulted in identification of distinct interaction types: a steroid-like A-B type described by frontier orbital energies and distance between nucleophilic sites with specific charge requirements; an A-C type where steric effects are combined with electronic interactions to modulate binding; and mixed A-B-C. Chemicals are grouped by type, then COREPA models are developed for within specific relative binding affinity ranges of >10%, 10 to 0.1%, and 0.1 to 0.001%. The derived models for each interaction type and affinity range combine specific interatomic distances and a COREPA classification node using < 2 discriminating parameters. The interaction types becoming less distinct in the lowest activity range for each chemicals of each type. A battery of models is presented for pre-screening of parent chemicals, or simulated metabolites (i.e., interfacing of toxic effects predictions with a liver tissue metabolism simulator (TIMES) as described in a companion presentation). [Dr. Aladjov is an NRC Post-doctoral appointee; This abstract does not reflect USEPA policy; CERI acknowledges sponsorship by the Ministry of Economy, Trade and Industry, Japan]

Key words: estrogens, ER binders, QSAR, receptor interactions