Open Access

Prediction of mutagenicity, carcinogenicity, developmental toxicity, and skin sensitisation with Caesar program for a set of conazoles


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1. EU REACH Regulation Services [displayed 8 November 2011]. Available at http://www.intertek.com/reach/Search in Google Scholar

2. Tsakovska I, Worth A. The use of computational methods for the assessment of chemicals in REACH. Int J BIOautomation 2009;13:151-62.Search in Google Scholar

3. European Chemical Agency (ECHA). Guidance on information requirements and chemical safety assessment [displayed 30 April 2012]. Available at http://echa.europa.eu/guidance-documents/guidance-on-informationrequirements-and-chemical-safety-assessmentSearch in Google Scholar

4. Benfenati E, Diaza RG, Cassano A, Pardoe S, Gini G, Mays C, Knauf R, Benighaus L. The acceptance of in silico models for REACH: Requirements, barriers, and perspectives. Chem Cent J 2011;5:58-69.10.1186/1752-153X-5-58320189421982269Search in Google Scholar

5. Benfenati E, Gini G, Hoffmann S, Luttik R. Comparing invivo for chemical assessment: Problems and prospects. Altern Lab Anim 2010;38:153-66.10.1177/02611929100380020120507186Search in Google Scholar

6. Moudgal CJ, Young D, Nichols T, Martin T, Harten P, Venkatapathy R, Stelma G, Siddhanti S, Baier-Anderson C, Wolfe M. Application of QSARs and VFARs to the rapid risk assessment process at US EPA. SAR QSAR Environ Res 2008;19:579-87.10.1080/1062936080234894418853303Search in Google Scholar

7. Mezey PG, Carbo R, Girones X. Fundamentals of molecular similarity. New York: Kluwer Academic/ Plenum Publishers; 2001.Search in Google Scholar

8. Benfenati E. The CAESAR project for in silico models for the REACH legislation. Chem Cent J 2010;4(Suppl 1):I1.10.1186/1752-153X-4-S1-I1291332720678179Search in Google Scholar

9. Benfenati E, Benigni R, Demarini DM, Helma C, Kirkland D, Martin TM, Mazzatorta P, Ouedraogoarras G, Richard AM, Schilter B, Schoonen WGEJ, Snyder RD, Yang C. Predictive models for carcinogenicity and mutagenicity: Frameworks, state-of-the-art, and perspectives. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 2009;27:57-90.10.1080/1059050090288559319412856Search in Google Scholar

10. Organisation for Economic Co-operation and Development Guidance (OECD). Guidance document on the validation of (Q)SAR models Publications Series on Testing and Assessment No. 6 [displayed 5 July 2012]. Available at http://www.oecd.org/officialdocuments/displaydocumentpdf/?cote=env/jm/mono(2007)2&doclanguage=enSearch in Google Scholar

11. Zarn JA, Bruschweiler BJ, Schlatter JR. Azole fungicides affect mammalian steroidogenesis by inhibiting sterol 14α- demethylase and aromatase. Environ Health Perspect 2003;111:255-61.10.1289/ehp.5785124138012611652Search in Google Scholar

12. Trosken ER, Fischer K, Volkel W, Lutz WK. Inhibition of human CYP19 by azoles used as antifungal agents and aromatase inhibitors, using a new LC-MS/MS method for the analysis of estradiol product formation. Toxicology 2006;219:33-40.10.1016/j.tox.2005.10.02016330141Search in Google Scholar

13. Bolčič-Tavčar M, Vračko M. Assessing the reproductive toxicity of some (con)azole compounds using Structure- Activity Relationship (SAR) approach. SAR QSAR Environ Res 2010;20:711-25.10.1080/1062936090343858620024805Search in Google Scholar

14. European Food Safety Authority (EFSA). PRAPeR publications [displayed 5 July 2012]. Available at http://www.efsa.europa.eu/en/supporting/pub/174e.htmSearch in Google Scholar

15. Regulation (EC) No 1272/2008 of the European Parliament and of the Council of 16 December 2008 on classifi cation, labelling and packaging of substances and mixtures, amending and repealing Directives 67/548/EEC and 1999/45/ EC, and amending Regulation (EC) No 1907/2006 [displayed 5 July 2012]. Available at http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2008:353:0001:1355:en:PDFSearch in Google Scholar

16. CAESAR project [displayed 8. November 2011]. Available at http://www.caesar-project.euSearch in Google Scholar

17. Ferrari T, Gini G. An open source multistep model to predict mutagenicity from statistical analysis and relevant structural alerts. Chem Centl J 2010;4(Suppl 1):S2.10.1186/1752-153X-4-S1-S2291332920678181Search in Google Scholar

18. Kazius J, McGuire R, Bursi R. Derivation and validation of toxicophores for mutagenicity prediction. J Med Chem 2005;48:312-20.10.1021/jm040835a15634026Search in Google Scholar

19. Fjodorova N, Vračko M, Novič M, Roncaglioni A, Benfenati E. New public QSAR model for carcinogenicity. Chem Cent J 2010;4(Suppl 1):S3.10.1186/1752-153X-4-S1-S3291333020678182Search in Google Scholar

20. Cassano A, Manganaro A, Martin T, Young D, Piclin N, Pintore M, Bigoni D, Benfenati E. CAESAR models for developmental toxicity. Chem Cent J 2010;4(Suppl 1):S4.10.1186/1752-153X-4-S1-S4291333120678183Search in Google Scholar

21. Arena VC, Sussman NB, Mazumdar S, Yu S, Macina OT. The utility of Structure-Activity Relationship (SAR) models for prediction and covariate selection in developmental toxicity: comparative analysis of logistic regression and decision tree models. SAR QSAR Environ Res 2004;15:1-18.10.1080/106293603200016963315113065Search in Google Scholar

22. Chaudhry Q, Piclin N, Cotterill J, Pintore M, Price NR, Cretien JR, Roncaglioni A. Global QSAR models for skin sensitisers for regulatory purposes. Chem Cent J 2010;4(Suppl 1):S5.10.1186/1752-153X-4-S1-S5291333220678184Search in Google Scholar

23. Gerberick GF, Ryan CA, Kern PS, Schaltter H, Dearman RJ, Kimber I, Patlewicz GY, Basketter DA. Compilation of historical local node data for evaluation of skin sensitization alternative methods. Dermatitis 2005;16:157-202.Search in Google Scholar

24. Bishop CM. Neural Networks for Pattern Recognition. Oxford: Oxford University Press; 1995.10.1201/9781420050646.ptb6Search in Google Scholar

ISSN:
0004-1254
Languages:
English, Slovenian
Publication timeframe:
4 times per year
Journal Subjects:
Medicine, Basic Medical Science, other