title: Integration of QSAR and SAR methods for the mechanistic interpretation of predictive models for carcinogenicity.
abstract: The knowledge-based Toxtree expert system (SAR approach) was integrated with the statistically based counter propagation artificial neural network (CP ANN) model (QSAR approach) to contribute to a better mechanistic understanding of a carcinogenicity model for non-congeneric chemicals using Dragon descriptors and carcinogenic potency for rats as a response. The transparency of the CP ANN algorithm was demonstrated using intrinsic mapping technique specifically Kohonen maps. Chemical structures were represented by Dragon descriptors that express the structural and electronic features of molecules such as their shape and electronic surrounding related to reactivity of molecules. It was illustrated how the descriptors are correlated with particular structural alerts (SAs) for carcinogenicity with recognized mechanistic link to carcinogenic activity. Moreover, the Kohonen mapping technique enables one to examine the separation of carcinogens and non-carcinogens (for rats) within a family of chemicals with a particular SA for carcinogenicity. The mechanistic interpretation of models is important for the evaluation of safety of chemicals.
authors.affiliation: National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana, Slovenia.
authors.forename: Natalja
authors.initials: N
authors.lastname: Fjodorova
authors.affiliation: National Institute of Chemistry, Hajdrihova 19, SI-1001 Ljubljana, Slovenia.
authors.forename: Marjana
authors.initials: M
authors.lastname: Novič
keywords: (quantitative) structure-activity relationships; Counter propagation artificial neural network; Dragon descriptors; Kohonen maps; Toxtree application; carcinogenicity; mechanistic interpretation of model; non-congeneric chemicals; structural alerts