Evaluation of the OECD (Q)SAR Application Toolbox for the profiling of estrogen receptor binding affinities

Abstract

The determination of binding affinities for the estrogen receptor (ER) is used extensively to assess potential hazards to human health and the environment arising from chemicals that can interfere with natural hormone homeostasis. Given the great number of chemicals to which humans and wildlife are exposed, (quantitative) structure–activity relationship (Q)SAR models for the characterization of ER disruptors represent a fast and cost-efficient alternative to experimental testing. In this toxicological context, the freely available Organisation for Economic Co-operation and Development (OECD) (Q)SAR Application Toolbox provides a profiler for the categorical profiling of chemicals according to their ER binding propensities. The aim of this study was to evaluate the predictive performances of this profiler. To achieve such a purpose, prediction results with the ER-profiler were compared with experimental binding affinities relative to two large datasets of chemicals (rat and human). The resulting Cooper statistics indicated that the binding affinities of the majority of chemicals included in the retained datasets could be correctly predicted.

Keywords:

• OECD (Q)SAR Toolbox
• model validation
• estrogen receptor
• endocrine disruption
• structural alerts

Acknowledgements

E.M. is grateful to the French Ministry of Ecology, Energy, Sustainable Development, Transport and Housing (MEDDTL) for financial support. Special thanks are given to Dr Jiazhong Li (University of Lanzhou) for forwarding relevant information, Dr Weida Tong (US Food and Drug Administration) for clarifying experimental details of the ER competitive binding assay, and Alexandre Péry, Rémy Beaudouin, Cleo Tebby, and Céline Brochot from the METO unit of INERIS for providing feedback on the manuscript.