Prediction of rodent carcinogenicity of aromatic amines: a quantitative structure-activity relationships model

Abstract

The aromatic amines are widely used industrial chemicals and can be found in tobacco smoke as well as in products generated during cooking. In a previous study, we established quantitative structure-activity relationship (QSAR) models linking the carcinogenic potency of non-heterocyclic carcinogenic aromatic amines to a series of molecular determinants. We also found that QSAR models for carcinogenic potency were inadequate in describing the difference between carcinogenic and non-carcinogenic amines [Benigni,R., Giuliani,A., Franke,R. and Gruska,A. (2000) CHEM: Rev., 100, 3697-3714]. In this paper, we derived specific QSAR models for separating active from inactive amines. It appeared that hydrophobicity (as measured by the octanol/water partition coefficient, logP) played a major role in modulating the potency of the carcinogens, whereas mainly electronic (reactivity) and steric characteristics separated the carcinogens from the non-carcinogens. Interestingly, a similar pattern was previously demonstrated by us regarding their mutagenic activity [Benigni,R., Passerini,L., Gallo,G., Giorgi,F. and Cotta-Ramusino,M. (1998) ENVIRON: Mol. Mutagen., 32, 75-83]. Based on the QSAR models found, the molecular determinants of the mechanisms of action of aromatic amines are discussed in detail. The QSAR models obtained can be used directly for estimating the carcinogenicity of other non-heterocyclic aromatic amines for which experimental data are not available. With the QSARs in Benigni et al. (2000) and the present results, a two-step prediction of carcinogenicity of aromatic amines is possible: (i) step 1, yes/no activity from the discriminant functions; and (ii) step 2, if the answer from step 1 is yes then prediction of the degree of potency from the equations in Benigni et al. (2000). Thus, QSAR models can contribute to the following: the direct synthesis of safer chemicals; the estimation of the risk posed by amines present in the environment; setting priorities for further experimentation, thus also reducing the use of experimental animals. Whereas the quality of in vivo experimental data is often questioned, the robustness and interpretability of the present results strongly support the reliability of the rodent carcinogenicity assay.

Simple and α,β-unsaturated aldehydes: Correct prediction of genotoxic activity through structure-activity relationship models

“…This effort has produced QSAR models for predicting the aneugenicity of halogenated aliphatic compounds [Benigni et al, 1993;Crebelli et al, 1995], and for predicting the carcinogenicity of aromatic amines [Benigni et al, 2000;Franke et al, 2001;Benigni and Passerini, 2002]. We feel that additional QSAR models should be generated for individual chemical classes, since there is evidence that these models are much more reliable than the general structure-activity models (and software) aimed at predicting the activity of all types of chemicals at the same time [Benigni, 2003b[Benigni, , 2005Benigni and Zito, 2004].…”

Structural motifs modulating the carcinogenic risk of aromatic amines

“…These chemicals have considerable environmental and industrial importance, and toxicological data have been reported for a large number of them [Lai et al, 1996;Sugimura, 1997;Vineis and Pirastu, 1997;Skog et al, 1998;Woo and Lai, 2001]. In previous work we have performed QSAR investigations on the activity and the potency of the aromatic amines, for both mutagenic (Salmonella) and carcinogenic (rat and mouse) endpoints [Benigni et al, 2000[Benigni et al, , 2007aFranke et al, 2001]. In the present investigation the effect of structural motifs on the carcinogenic potency of aromatic amines in rats and mice are investigated by using the software program EVAL.…”

Use of QSARs in international decision-making frameworks to predict health effects of chemical substances.

“…In such examples the assumption is made that structurally similar chemicals may act by similar mechanisms of action. Good examples are provided by Franke et al (2001), who demonstrated both the modeling of activity (carcinogenic vs. noncarcinogenic) and the potency of aromatic amines (from the carcinogenicity potency database). As with all class-based QSARs, their use is restricted by the domain of the QSAR.…”