Abstract
In this chapter, a range of computational tools for applying QSAR and grouping/read-across methods are described, and their integrated use in the computational assessment of genotoxicity is illustrated through the application of selected tools to two case-study compounds—2-amino-9H-pyrido[2,3-b]indole (AαC) and 2-aminoacetophenone (2-AAP). The first case study compound (AαC) is an environment pollutant and a food contaminant that can be formed during the cooking of protein-rich food. The second case study compound (2-AAP) is a naturally occurring compound in certain foods and also proposed for use as a flavoring agent. The overall aim is to describe and illustrate a possible way of combining different information sources and software tools for genotoxicity and metabolism prediction by means of a simple stepwise approach. The chapter is aimed at researchers and assessors who have a basic knowledge of computational toxicology and some familiarity with the practical use of computational tools. The emphasis is on how to evaluate the data generated by multiple tools, rather than the practical use of any specific tool.
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Worth, A.P., Lapenna, S., Serafimova, R. (2013). QSAR and Metabolic Assessment Tools in the Assessment of Genotoxicity. In: Reisfeld, B., Mayeno, A. (eds) Computational Toxicology. Methods in Molecular Biology, vol 930. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-059-5_6
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