Science Inventory

Development of a QSAR Model for Thyroperoxidase Inhbition and Screening of 72,524 REACH substances - (Eurotox 2016)

Citation:

Rosenberg, S., N. Nikolov, M. Dybdahl, Steve Simmons, K. Crofton, Eric Watt, K. Paul-Friedman, R. Judson, AND E. Wedebye. Development of a QSAR Model for Thyroperoxidase Inhbition and Screening of 72,524 REACH substances - (Eurotox 2016). Presented at EUROTOX 2016, Seville, SPAIN, September 04 - 07, 2016. https://doi.org/10.23645/epacomptox.5189476

Impact/Purpose:

Poster presentation at EUROTOX2016 in Seville, Spain on Development of a QSAR Model for Thyroperoxidase Inhbition and Screening of 72,524 REACH substances

Description:

hyroid hormones (THs) are involved in multiple biological processes and are critical modulators of fetal development. Even moderate changes in maternal or fetal TH levels can produce irreversible neurological deficits in children, such as lower IQ. The enzyme thyroperoxidase (TPO) plays a key role in the synthesis of THs, and inhibition of TPO by xenobiotics results in decreased TH synthesis. Recently, a high-throughput screening assay for TPO inhibition (AUR-TPO) was developed and used to test the ToxCast Phase I and II chemicals. In the present study, we used the results from AUR-TPO to develop a Quantitative Structure-Activity Relationship (QSAR) model for TPO inhibition. The training set consisted of 898 discrete organic chemicals: 134 inhibitors and 764 non-inhibitors. A five times two-fold cross-validation of the model was performed, yielding a balanced accuracy of 78.7%. More recently, an additional ~800 chemicals were tested in the AUR-TPO assay. These data were used for a blinded external validation of the QSAR model, demonstrating a balanced accuracy of 85.7%. Overall, the cross- and external validation indicate a robust model with high predictive performance. Next, we used the QSAR model to predict 72,526 REACH pre-registered substances. The model could predict 49.5% (35,925) of the substances in its applicability domain and of these, 8,863 (24.7%) were predicted to be TPO inhibitors. Predictions from this screening can be used in a tiered approach to prioritize potential thyroid disrupting chemical substances for further evaluation. This abstract does not necessarily reflect U.S. EPA policy

Record Details:

Record Type:DOCUMENT( PRESENTATION/ POSTER)
Product Published Date:09/07/2016
Record Last Revised:07/26/2017
OMB Category:Other
Record ID: 337033