Literature DB >> 11532881

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

R Franke1, A Gruska, A Giuliani, R Benigni.   

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.

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Year:  2001        PMID: 11532881     DOI: 10.1093/carcin/22.9.1561

Source DB:  PubMed          Journal:  Carcinogenesis        ISSN: 0143-3334            Impact factor:   4.944


  5 in total

1.  Improving prediction of carcinogenicity to reduce, refine, and replace the use of experimental animals.

Authors:  Todd Bourcier; Tim McGovern; Lidiya Stavitskaya; Naomi Kruhlak; David Jacobson-Kram
Journal:  J Am Assoc Lab Anim Sci       Date:  2015-03       Impact factor: 1.232

2.  A radial-distribution-function approach for predicting rodent carcinogenicity.

Authors:  Aliuska Helguera Morales; Miguel Angel Cabrera Pérez; Maykel Pérez González
Journal:  J Mol Model       Date:  2006-01-19       Impact factor: 1.810

3.  Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses.

Authors:  Natalja Fjodorova; Marjan Vračko; Marjan Tušar; Aneta Jezierska; Marjana Novič; Ralph Kühne; Gerrit Schüürmann
Journal:  Mol Divers       Date:  2009-08-15       Impact factor: 2.943

4.  Prediction of carcinogenicity for diverse chemicals based on substructure grouping and SVM modeling.

Authors:  Kazutoshi Tanabe; Bono Lučić; Dragan Amić; Takio Kurita; Mikio Kaihara; Natsuo Onodera; Takahiro Suzuki
Journal:  Mol Divers       Date:  2010-02-26       Impact factor: 2.943

Review 5.  Use of QSARs in international decision-making frameworks to predict health effects of chemical substances.

Authors:  Mark T D Cronin; Joanna S Jaworska; John D Walker; Michael H I Comber; Christopher D Watts; Andrew P Worth
Journal:  Environ Health Perspect       Date:  2003-08       Impact factor: 9.031

  5 in total

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