Category formation case studies

Issues in Toxicology

Volumn , Issue , 2013, Pages 127-154

  Enoch, S J ^a   Przybylak, K R ^a   Cronin, M T D ^a  

^a LIVERPOOL JOHN MOORES UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84897506013     PISSN: 17577179     EISSN: 17577187     Source Type: Book Series    
DOI: 10.1039/9781849734400-00127     Document Type: Article

References (25)

1. The OECD QSAR Toolbox. (available from: http://www.qsartoolbox.org/)
2. B. N. Ames, E. G. Gurney, J. A. Miller and H. Bartsch, Carcinogens as frameshift mutagens: Metabolites and derivatives of 2-acetylaminofluorene and other aromatic amine carcinogens. Proc. Natl. Acad. Sci. U. S. A, 1972, 69, 3128.
3. A. O. Aptula, G. Patlewicz and D. W. Roberts, Skin sensitization: Reaction mechanistic applicability domains for structure-activity relationships. Chem. Res. Toxicol., 2005, 18, 1420.
4. D. W. Roberts, G. Patlewicz, P. S. Kern, F. Gerberick, I. Kimber, R. J. Dearman, C. A. Ryan, D. A. Basketter and A. O. Aptula, Mechanistic applicability domain classification of a local lymph node assay dataset for skin sensitization. Chem. Res. Toxicol., 2007, 20, 1019.
5. H. J. M. Verhaar, C. J. van Leeuwen and J. L. M Hermens, Classifying environmental pollutants. 1: Structure-activity relationships for prediction of aquatic toxicity, Chemosphere, 1992, 25, 471.
6. S. J. Enoch, C. M. Ellison, T. W. Schultz and M. T. D Cronin, A review of the electrophilic reaction chemistry involved in covalent protein binding relevant to toxicity. Crit. Rev. Toxicol., 2011, 41, 783.
7. I. Tsakovska, I. Pajeva, A. Petko and A. Worth, Recent advances in the molecular modeling of estrogen receptor-mediated toxicity, in Advances in Protein Chemistry and Structural Biology, ed. C. Christov, Academic Press, Burlington, 2011, p. 217.
8. M. Novic and M. Vracko, QSAR models for reproductive toxicity and endocrine disruption activity. Molecules, 2010, 15, 1987.
9. X. Xu, W. Yang, Y. Li and Y. Wang, Discovery of estrogen receptor modulators: a review of virtual screening and SAR efforts. Expert Opin. Drug Discov., 2010, 5, 21.
10. M. R. Servos, Review of the aquatic toxicity, estrogenic responses and bioaccumulation of alkylphenols and alkylphenol polyethoxylates. Water Qual. Res. J. Can., 1999, 34, 123.
11. E. Mombelli, Evaluation of the OECD (Q)SAR Application Toolbox for the profiling of estrogen receptor binding affinities. SAR QSAR Environ. Res., 2012, 23, 37.
12. G. T. Ankley, R. S. Bennett, R. J. Erickson, D. J. Hoff, M. W. Hornung, R. D. Johnson, D. R. Mount, J. W. Nichols, C. L. Russom, P. K. Schmieder, J. A. Serrano, J. E. Tietge and D. L. Villeneuve, Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environ. Toxicol. Chem., 2010, 29, 730.
13. P. K. Schmieder, G. T. Ankley, O. Mekenyan, J. D. Walker and S. Bradley, Quantitative structure-activity relationship models for prediction of estrogen receptor binding affinity of structurally diverse chemicals. Environ. Toxicol. Chem., 2003, 22, 1844.
14. Y. Sakuratani, H. Q. Zhang, S. Nishikawa, K. Yamazaki, T. Yamada, J. Yamada, K. Gerova, G. Chankov, O. Mekenyan and M. Hayashi, Hazard Evaluation Support System (HESS) for predicting repeated dose toxicity using toxicological categories. SAR QSAR Environ. Res., 24, 617.
15. Y. Sakuratani, S. Sato, S. Nishikawa, J. Yamada, A. Maekawa and M. Hayashi, Category analysis of the substituted anilines studied in a 28-day repeat-dose toxicity test conducted on rats: Correlation between toxicity and chemical structure. SAR QSAR Environ. Res., 2008, 19, 681.
16. T. Yamada, Y. Tanaka, R. Hasegawa, Y. Sakuratani, J. Yamada, E. Kamata, A. Ono, A. Hirose, Y. Yamazoe, O. Mekenyan and M. Hayashi, A category approach to predicting the repeated-dose hepatotoxicity of allyl esters. Reg. Toxicol. Pharmacol., 2013, 65, 189.
17. Y. Sakuratani, H. Q. Zhang, S. Nishikawa, K. Yamazaki, T. Yamada, J. Yamada and M. Hayashi, Categorization of nitrobenzenes for repeated dose toxicity based on adverse outcome pathways. SAR QSAR Environ. Res., 2013, 24, 35.
18. M. Hayashi and Y. Sakuratani, Development of an evaluation support system for estimating repeated dose toxicity of chemicals based on chemical structure, in New Horizons in Toxicity Prediction, ed. A. G. E. Wilson, Royal Society of Chemistry, Cambridge, UK, 2011, p. 26.
19. V. Facchini and L. A. Griffiths, The involvement of the gastro-intestinal microflora in nitrocompound-induced methaemoglobinaemia in rats and its relationship to nitro group reduction. Biochem. Pharmacol., 1981, 30, 931.
20. G. Sabbioni, Hemoglobin binding of nitroarenes and quantitative structure-activity relationships. Chem. Res. Toxicol., 1994, 7, 267.
21. T. P. Bradshaw, D. C. McMillan, R. K. Crouch and D. J. Jollow, Identification of free radicalsproduced in rat erythrocytes exposed to hemolytic concentrations of phenylhydroxylamine. Free Rad. Biol. Med., 1995, 18, 279.
22. M. Kiese, Methemoglobinemia: A Comprehensive Treatise. CRC, Cleveland, OH, 1974.
23. Toxmatch software. (available from http://ihcp.jrc.ec.europa.eu/).
24. S. J. Enoch, M. T. D. Cronin, J. C. Madden and M. Hewitt, Formation of structural categories to allow for read-across for teratogenicity. QSAR Combi. Sci., 2009, 28, 696.
25. G. C. Briggs, R. K. Freeman and S. J. Yaffe, Drugs in Pregnancy and Lactation. 6th ed., Lippincott Williams and Wilkins, Philadelphi., 2002.