QSAR Studies in Genetic Toxicology: Congeneric and Non Congeneric Chemicals

  • Romualdo Benigni
  • Alessandro Giuliani
Part of the Archives of Toxicology book series (TOXICOLOGY, volume 15)


The Quantitative Structure-Activity Relationship (QSAR) methods are an important tool for the study of biological action mechanisms and for the prediction of chemical activity. The QSAR studies, although originally developed at the end of last century, were spurred on in the Sixties by the contributions of Corwin Hansen, as well as other investigators. It has been found that, for congeneric chemicals, it is possible to quantitatively correlate biological activity with physical chemical properties, such as hydrophobicity, steric and electronic factors (Hansch, 1990). Congeneric chemicals are those agents that share a common skeleton, but have different substituents attached to it. This approach –called extrathermodynamic or the Hansch approach- has been subsequently applied to a large number of situations, and has been highly refined. A great advantage of this method is that the physical chemical properties of most chemicals can be theoretically estimated.


Physical Chemical Property Nitroaromatic Compound QSAR Study Topological Approach National Toxicology Program 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ashby, J. (1985) Fundamental structural alerts to potential carcinogenicity or non-carcinogenicity, Environ. Mutagen., 7: 919–921.PubMedCrossRefGoogle Scholar
  2. Ashby, J., R.W. Tennant, E. Zeiger and S. Stasiewicz (1989) Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 42 chemicals tested for carcinogenicity by the U.S. National Toxicology Program, Mutat. Res., 223: 73–103.PubMedCrossRefGoogle Scholar
  3. Bakale G. and McCreary R.D. (1987) A physico-chemical screening test for chemical carcinogens: the Ke test, Carcinogenesis, 8: 253–264.PubMedCrossRefGoogle Scholar
  4. Bakale G. and McCreary R.D. (1990) Response of the Ke test to NCI/NTP-screened chemicals. I. Non-genotoxic carcinogens and genotoxic non-carcinogens, Carcinogenesis, 11: 1811–1818.PubMedCrossRefGoogle Scholar
  5. Benigni, R., C. Andreoli, and A. Giuliani (1989a) Quantitative structure-activity relationships: principles, and applications to mutagenicity and carcinogenicity. Mutat. Res., 221: 197 – 216.PubMedGoogle Scholar
  6. Benigni R., Andreoli C., and Giuliani A. (1989b) Structure-activity studies of chemical carcinogens: use of an electrophilic reactivity parameter in a new QSAR model, Carcinogenesis, 10: 55–61.PubMedCrossRefGoogle Scholar
  7. Franke R., S. Huebel, and W.J. Streich (1985) Sustructural QSAR approaches and topological pharmacophores, Environ. Health Persp., 61: 275–285.CrossRefGoogle Scholar
  8. Free, S.M., and J.W. Wilson (1964) A mathematical contribution to structure-activity studies. J. Med. Chem. 7: 395–399.PubMedCrossRefGoogle Scholar
  9. Frierson, M.R., G. Klopman, and H.S. Rosenkranz (1986) Structure-activity relationships (SAR’s) among mutagens and carcinogens: a review, Environ. Mutagenesis, 8: 283–327.CrossRefGoogle Scholar
  10. Hansch C. (1977) On the predictive value of QSAR, in J.A. Keverling Buisman (Ed) Biological activity and chemical structure, Elsevier, Amsterdam.Google Scholar
  11. Hansch C. (Ed) (1990) Comprehensive medicinal chemistry, Vol. 4, Quantitative Drug Design, Pergamon Press, Oxford.Google Scholar
  12. Klopman G. (1984) Artificial intelligence approach to structure-activity studies: Computer automated structure evaluation of biological activity of organic molecules, J. Am. Chem. Soc., 106: 7315–7321.CrossRefGoogle Scholar
  13. Klopman G., M.R. Frierson, and H.S. Rosenkranz (1990) The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the Gene-Tox data base, Mutat. Res., 228: 1–50.PubMedGoogle Scholar
  14. Lopez de Compadre R.L., A. Kumar Debnath, A.J. Shusterman, and C. Hansch (1990) LUMO energies and hydrophobicity as determinants of mutagenicity by nitroaromatic compounds in Salmonella typhimurium. Environ. Mol. Mutagenesis, 15: 44–55.CrossRefGoogle Scholar
  15. Martin, Y.C. (1981) A practitioner’s perspective of the role of quantitative structure- activity analysis in medicinal chemistry. J. Med. Chem., 24: 229–237.PubMedCrossRefGoogle Scholar
  16. Rosenkranz H.S. and G. Klopman (1990) The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the National Toxicology Program data base, Mutat. Res., 228: 51–80.PubMedCrossRefGoogle Scholar
  17. Shusterman A.J., A. Kumar Debnath, C. Hansch, G.W. Horn, F.R. Fronczek, A.C. Greene, and S.F. Watkins (1990) Mutagenicity of dimethyl heteroaromatic triazenes in the Ames test. The role of hydrophobicity and electronic effects. Mol. Pharmacol., december: 939–944.Google Scholar
  18. Stouch T.R. and Jurs P.C. (1985) Computer-assisted studies of molecular structure and genotoxic activity by pattern recognition techniques, Environ. Health Perspect., 61: 329–343.PubMedCrossRefGoogle Scholar
  19. Topliss J.G. and R.P. Edwards (1979) Chance factors in studies of quantitative structure-activity relationships, J. Med. Chem., 22: 1238–1244.PubMedCrossRefGoogle Scholar
  20. Tute M.S. (1990) Hystory and objectives of quantitative drug design. in C.A. Ramsden (Ed) Comprehensive medicinal chemistry, Vol. 4, Quantitative drug design, Pergamon Press, Oxford.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Romualdo Benigni
    • 1
  • Alessandro Giuliani
    • 1
  1. 1.Istituto Superiore di Sanita’Laboratory of Comparative Toxicology and EcotoxicologyRomeItaly

Personalised recommendations