Mechanistic QSAR of aromatic amines: new models for discriminating between homocyclic mutagens and nonmutagens, and validation of models for carcinogens.

ABSTRACT

Because of its environmental and industrial importance, the aromatic amines are the single chemical class most studied for its ability to induce mutations and cancer. The large database of mutagenicity and carcinogenicity results has been studied with Quantitative Structure-Activity Relationship (QSAR) approaches by several authors, leading to models for the following (a) the mutagenic potency in Salmonella thyphimurium; (b) the carcinogenic potency in rodents; and (c) the discrimination between rodent carcinogens and noncarcinogens. However, satisfactory models for the discrimination between mutagens and nonmutagens are lacking. The present work provides new QSARs for mutagenic/nonmutagenic homocyclic aromatic amines in S. typhimurium strains TA98 and TA100. The two new models are validated by checking their ability to predict the mutagenicity of further aromatic amines not included in the training set, and not used to generate the QSAR models. In addition, we also validated previous QSAR models for the carcinogenicity/noncarcinogenicity of the aromatic amines with external data. The mechanistic implications of the models are discussed in light of the other QSARs for the aromatic amines. The results of the analysis point to two QSAR models (one for mutagenicity and one for rodent carcinogenicity) as reliable tools for the in silico characterization of the risk posed by the aromatic amines.