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, Giuseppa Raitano, Enrico Mombelli, Alberto Fernández, Josep Cester, Alessandra Roncaglioni, Emilio Benfenati

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)273-298
Number of pages26
JournalJournal of Environmental Science and Health - Part C Environmental Carcinogenesis and Ecotoxicology Reviews
Volume32
Issue number3
DOIs
Publication statusPublished - Jul 1 2014

Keywords

  • QSAR

ASJC Scopus subject areas

  • Health, Toxicology and Mutagenesis
  • Cancer Research
  • Medicine(all)

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