Evaluation of QSAR models for the prediction of ames genotoxicity : A retrospective exercise on the chemical substances registered under the EU REACH regulation

Antonio Cassano (1) , Giuseppa Raitano (2) , Enrico Mombelli (1) , Alberto Fernandez , Josep Cester , Alessandra Roncaglioni (2) , Emilio Benfenati (2)

1 INERIS - Institut National de l'Environnement Industriel et des Risques
2 IRCCS - Istituto di Ricovero e Cura a Carattere Scientifico

We evaluated the performance of seven freely available quantitative structure-activity relationship models predicting Ames genotoxicity thanks to a dataset of chemicals that were registered under the EU Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation. The performance of the models was estimated according to Cooper's statistics and Matthew's Correlation Coefficients (MCC). The Benigni/Bossa rule base originally implemented in Toxtree and re-implemented within the Virtual models for property Evaluation of chemicals within a Global Architecture (VEGA) platform displayed the best performance (accuracy = 92%, sensitivity = 83%, specificity = 93%, MCC = 0.68) indicating that this rule base provides a reliable tool for the identification of genotoxic chemicals. Finally, we elaborated a consensus model that outperformed the accuracy of the individual models.

Keywords: QSAR; GENOTOXICITY; MUTAGENICITY; AMES TEST; REACH REGULATION; IN SILICO

Domains: Life Sciences [q-bio]; Toxicology

Antonio Cassano, Giuseppa Raitano, Enrico Mombelli, Alberto Fernandez, Josep Cester, et al.. Evaluation of QSAR models for the prediction of ames genotoxicity : A retrospective exercise on the chemical substances registered under the EU REACH regulation. Journal of Environmental Science and Health, Part C, 2014, 32 (3), pp.273-298. ⟨10.1080/10590501.2014.938955⟩. ⟨ineris-01855014⟩