The increasing number and size of public databases is facilitating the collection of chemical structures and associated experimental data for QSAR modeling. However, the performance of QSAR models is highly dependent not only on the modeling methodology, but also on the quality of the data used. In this study we developed robust QSAR models for endpoints of environmental interest with the aim of helping the regulatory process. We used the publicly available PHYSPROP database that includes a set of thirteen common physicochemical and environmental fate properties, including logP, melting point, Henry’s coefficient, and biodegradability among others. Curation and standardization workflows have been applied to use the highest quality data and generate QSAR-ready structures. The developed models are in agreement with the five OECD principles that requires QSARs to be simple and reliable. These models were applied to a set of ~700k chemicals to produce predictions for display on the EPA CompTox Chemistry Dashboard. In addition to the predictions, this free web and mobile application provides access to the experimental data used for training as well as detailed reports including general model performances, specific applicability domain and prediction accuracy, and the nearest neighboring structures used for prediction. The dashboard also provides access to model QMRFs (QSAR modeling report format) which is a downloadable pdf containing additional details about the modeling approaches, the data, and molecular descriptor interpretation.

Free online access to experimental and predicted chemical properties through the EPA’s CompTox Chemistry Dashboard

253rd National Meeting (2017)

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.