Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities

Regulatory Toxicology and Pharmacology

Volumn 67, Issue 1, 2013, Pages 39-52

  Sutter, Andreas ^a   Amberg, Alexander ^b   Boyer, Scott ^c   Brigo, Alessandro ^d   Contrera, Joseph F ^e   Custer, Laura L ^f   Dobo, Krista L ^g   Gervais, Veronique ^h   Glowienke, Susanne ⁱ   Gompel, Jacky van ^j   Greene, Nigel ^g   Muster, Wolfgang ^d   Nicolette, John ^k   Reddy, M Vijayaraj ^l   Thybaud, Veronique ^m   Vock, Esther ⁿ   White, Angela T ^o   Müller, Lutz ^d  

^a BAYER PHARMA AG   (Germany)

^b SANOFI AVENTIS DEUTSCHLAND GMBH   (Germany)

^c ASTRAZENECA R AND D   (Sweden)

^d F HOFFMANN LA ROCHE LTD   (Switzerland)

^e Computational Toxicology Services LLC ^*  (United States)

^f BRISTOL MYERS SQUIBB   (United States)

^g PFIZER INC   (United States)

^h INSTITUT DE RECHERCHES INTERNATIONALES SERVIER   (France)

ⁱ Novartis Institutes for BioMedical Research (NIBR)   (Switzerland)

^j Drug Safety Sciences   (Belgium)

^k ABBOTT LABORATORIES   (United States)

^l MERCK RESEARCH LABORATORIES   (United States)

^m SANOFI   (France)

ⁿ BOEHRINGER INGELHEIM PHARMA GMBH AND CO KG   (Germany)

^o NCSP Safety Assessment PTS Ware   (United Kingdom)

more..

Author keywords

(Q)SAR; Genotoxic impurities; ICH M7; In silico; Mutagenicity

Indexed keywords

2 AMINO 3 METHYLPHENOL; 3 FLUORO 4 ISOPROPOXYPHENYLAMINE; 4 (CYCLOPROPYLOXY)ANILINE; 4 CYANO 3 TRIFLUOROMETHYLANILINE; 4 ETHOXY 2 FLUOROANILINE; 4 METHOXY 2 (TRIFLUOROMETHYL)ANILINE; 5,7 DIMETHYL 2,1,3 BENZOTHIADIAZOL 4 AMINE; AROMATIC AMIDE; AROMATIC AMINE; BENZO[1,2,5]THIADIAZOLE GUANIDINE; CARCINOGEN; DNA; DRUG; MONOCYCLIC AROMATIC AMIDE; MONOCYCLIC AROMATIC AMINE; MUTAGENIC AGENT; N (4 AMINOPHENYL) N [2 (DIMETHYLAMINO)ETHYL]ACETAMIDE; N BROMOSUCCINIMIDE; N IODOSUCCINIMIDE; PEG 3 20,20 DI 4 PHENYLENEDIAMINE; POLYCYLIC AROMATIC AMIDE; POLYCYLIC AROMATIC AMINE; THIONYL CHLORIDE; UNCLASSIFIED DRUG;

AMES TEST; ARTICLE; AUTOMATION; BACTERIAL MUTATION; BIOINFORMATICS; CARCINOGENICITY; CHEMICAL STRUCTURE; COMPUTER MODEL; DATA ANALYSIS SOFTWARE; DATA BASE; DRUG IMPURITY; DRUG INDUSTRY; DRUG SYNTHESIS; EUROPE; GENE INTERACTION; GENOTOXICITY; HAZARD ASSESSMENT; KNOWLEDGE BASE; MUTAGENIC IMPURITY; MUTAGENICITY; NONHUMAN; PATIENT SAFETY; PHYSICAL CHEMISTRY; PRACTICE GUIDELINE; PREDICTION; PRIORITY JOURNAL; QUALITATIVE ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RELIABILITY; REPRODUCIBILITY; SALMONELLA; SENSITIVITY AND SPECIFICITY; STRUCTURE ANALYSIS; TOXICITY TESTING; UNITED STATES; VALIDATION STUDY;

(Q)SAR; GENOTOXIC IMPURITIES; ICH M7; IN SILICO; MUTAGENICITY;

COMPUTER SIMULATION; DNA DAMAGE; DRUG CONTAMINATION; DRUG INDUSTRY; MUTAGENICITY TESTS; MUTAGENS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84883451066     PISSN: 02732300     EISSN: 10960295     Source Type: Journal    
DOI: 10.1016/j.yrtph.2013.05.001     Document Type: Article

References (65)

1. Ashby J., Tennant R.W. Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the US NTP. Mutat. Res. 1991, 257:229-306.
2. Bender A., et al. Similarity searching of chemical databases using atom environment descriptors (MOLPRINT 2D): evaluation of performance. Chem. Inf. Comput. Sci. 2004, 44:1708-1718.
3. Benigni R., Bossa C. Structure alerts for carcinogenicity, and the Salmonella assay system: a novel insight through the chemical relational databases technology. Mutat. Res. 2008, 659:248-261.
4. Bentzien J., et al. An in silico method for predicting Ames activities of primary aromatic amines by calculating the stabilities of nitrenium ions. J. Chem. Inf. Model. 2010, 50:274-297.
5. Advances in Molecular Similarity 1996, JAI Press, London. R. Carbó-Dorca, P.G. Mezey (Eds.).
6. Cheeseman M.A., Machuga E.J., Bailey A.B. A tiered approach to threshold of 919 regulation. Food Chem. Toxicol. 1999, 37:387-412.
7. Contrera J.F., et al. In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL QSAR software. Regul. Toxicol. Pharmacol. 2005, 43:313-323.
8. Devillers J., Mombelli E. Evaluation of the OECD QSAR Application Toolbox and Toxtree for estimating the mutagenicity of chemicals. Part 1. Aromatic amines. SAR QSAR Environ. Res. 2010, 21:753-769.
9. Dobo K.L., et al. In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: an industry survey. Regul. Toxicol. Pharmacol. 2012, 62:449-455.
10. Ellison C.M., et al. Assessment of methods to define the applicability domain of structural alert models. J. Chem. Inf. Model. 2011, 51:975-985.
11. Enoch S.J., et al. The use of a chemistry-based profiler for covalent DNA binding in the development of chemical categories for read-across for genotoxicity. Altern. Lab. Anim. 2011, 39:131-145.
12. European Medicines Agency, 2006. Guideline on the Limits of Genotoxic Impurities.
13. European Medicines Agency, 2007. Question & Answers on the CHMP Guideline on the Limits of Genotoxic Impurities.
14. Greene N., et al. Knowledge-based expert systems for toxicity and metabolism prediction: DEREK, StAR and METEOR. SAR QSAR Environ. Res. 1999, 10:299-314.
15. Hall L.H. A structure-information approach to prediction of biological activities and properties. Chem. Biodivers. 2004, 1:183-201.
16. Hall L.H., Kier L.B. Electrotopological state indices for atom types: a novel combination of electronic, topological and valence state information. J. Chem. Inf. Comput. Sci. 1995, 35:1039-1045.
17. Hansen K., et al. Benchmark data set for in silico prediction of Ames mutagenicity. J. Chem. Inf. Model. 2009, 49:2077-2081.
18. Hillebrecht A., et al. Comparative evaluation of in silico systems for Ames test mutagenicity prediction: scope and limitations. Chem. Res. Toxicol. 2011, 24:843-854.
19. Hodgkin E.E., Richards W.G. Molecular similarity based on electrostatic potential and electric field. Int. J. Quantum Chem. 1987, 32:105-110.
20. Kamber M., et al. Comparison of the Ames II and traditional Ames test responses with respect to mutagenicity, strain specificities, need for metabolism and correlation with rodent carcinogenicity. Mutagenesis 2009, 24:359-366.
21. Karelson M. Molecular Descriptors in QSAR/QSPR 2000, J. Wiley & Sons, New York.
22. Kier L.B., Hall L.H. Database organization and similarity searching with E-state indices. SAR QSAR Environ. Res. 2001, 12:55-74.
23. Kirkland D., et al. Evaluation of the ability of a battery of 3 in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens. I. Sensitivity, specificity and relative predictivity. Mutat. Res. 2005, 584:1-256.
24. Kirkland D., Speit G. Evaluation of the ability of a battery of three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens III. Appropriate follow-up testing in vivo. Mutat. Res. 2008, 654:114-132.
25. Klopman G. Artificial intelligence approach to structure-activity studies, computer automated structure evaluation of biological activity of organic molecules. J. Am. Chem. Soc. 1984, 106:7315-7320.
26. Klopman G. MULTICASE. 1. A hierarchical computer automated structure evaluation program. Quant. Struct. Act. Relat. 1992, 11:176-184.
27. Klopman G., Mc Gonigal M.J. Computer simulation of physical-chemical properties of organic molecules 1. Molecular system identification. J. Chem. Inf. Comput. Sci. 1981, 21:48-52.
28. Kroes R., Renwick A.G., Cheeseman M., Kleiner J., Mangelsdorf I., Piersma A., Schilter B., Schlatter J., van Schothorst F., Vos J.G., Würtzen G. Structure-based thresholds of toxicological concern (TTC): guidance for application to substances present at low levels in the diet. Food Chem. Toxicol. 2004, 42:65-83.
29. Lahl U., Gundert-Remy U. The use of (Q)SAR methods in the context of REACH. Toxicol. Mech. Methods 2008, 18:149-158.
30. McCann J., et al. Detection of carcinogens in the Salmonella/microsome test. Assay of 300 chemicals. Proc. Natl. Acad. Sci. USA 1975, 72:5135-5139.
31. McCann J., Ames B.N. Detection of carcinogens as mutagens in the Salmonella/microsome test: Assay of 300 chemicals: Discussion. Proc. Nat. Acad. Sci. USA 1976, 73:950-954.
32. Müller L., et al. A rationale for determining, testing, and controlling specific impurities in pharmaceuticals that possess potential for genotoxicity. Regul. Toxicol. Pharmacol. 2006, 44:198-211.
33. Pavan M., Worth A.P. Publicly-accessible QSAR software tools developed by the joint research centre. SAR QSAR Environ. Res. 2008, 19:785-799.
34. Raymond J.W., Willett P. Maximum common subgraph isomorphism algorithms for the matching of chemical structures. J. Comput. Aided Mol. Des. 2002, 16:521-533.
35. Ridings J.E., et al. Computer prediction of possible toxic action from chemical structure: an update on the DEREK system. Toxicology 1996, 106:267-279.
36. Saiakhov R.D., Giles Klopman Benchmark performance of MultiCASE Inc. Software in Ames Mutagenicity Set. J. Chem. Inf. Model. 2010, 50:1521.
37. Sanderson D.M., Earnshaw C.G. Computer prediction of possible toxic action from chemical structure; the DEREK system. Hum. Exp. Toxicol. 1991, 10:261-273.
38. Serafimova, R. et al., 2010. Review of QSAR Models and Software Tools for Predicting Genotoxicity and Carcinogenicity. JRC Scientific and technical report, 1-58.
39. Snyder R.D. An update on the genotoxicity and carcinogenicity of marketed pharmaceuticals with reference to in silico predictivity. Environ. Mol. Mutagen. 2009, 50:435-450.
40. Tou J.T., Gonzalez R.C. Pattern Recognition Principles 1974, Addison-Wesley Publishing Company, London-Amsterdam-Dom Mills, Ontario-Sydney-Tokyo.
41. Valerio L.G. In silico toxicology for the pharmaceutical sciences. Toxicol. Appl. Pharmacol. 2009, 241:356-370.
42. Valerio L.G., Cross K.P. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities. Toxicol. Appl. Pharmacol. 2012, 260:209-221.
43. Worth, A. et al., 2011. The Use of Computational Methods in the Toxicological Assessment of Chemicals in Food: Current Status and Future Prospects. JRC Scientific report, 1-143.
44. Zeiger E. Carcinogenicity of mutagens: predictive capability of the Salmonella mutagenesis assay for rodent carcinogenicity. Cancer Res. 1987, 47:1287-1296.
45. Zeiger E. Identification of rodent carcinogens and noncarcinogens using genetic toxicity tests: premises, promises, and performance. Regul. Toxicol. Pharmacol. 1998, 28:85-95.
46. BG-Chemie, http://www.bgchemie.de (accessed December 24, 2012).
47. DEREK, https://www.lhasalimited.org/derek_nexus/ (accessed December 24, 2012).
48. EPA IRIS database, http://www.epa.gov/iris (accessed December 24, 2012).
49. ICH M7 Draft Consensus Guideline: Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk. http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Multidisciplinary/M7/M7_Step_2.pdf (accessed March 12, 2013).
50. INCHEM, http://www.inchem.org (accessed December 24, 2012).
51. Japan Existing Chemical Database, http://dra4.nihs.go.jp/mhlw_data/jsp/SearchPageENG.jsp (accessed December 24, 2012).
52. Leadscope Model Applier, http://www.leadscope.com/ (accessed December 24, 2012).
53. Leadscope Toxicity Databases, http://www.leadscope.com/toxicity_databases/ (accessed December 24, 2012).
54. Marchant, C.A. et al., 2008. Validating Alerts for the Prediction of Mutagenicity Presented at SOT 47th Annual Meeting. 16th - 20th March 2008, Washington, USA. https://www.lhasalimited.org/library/item/validating_alerts_for_the_prediction_of_mutagenicity/ (accessed 24 December 2012).
55. MCASE/MC4PC, http://www.multicase.com/products/prod01.htm (accessed December 24, 2012).
56. NTP, http://ntp-server.niehs.nih.gov (accessed December 24, 2012).
57. Organisation for Economic Co-operation and Development, 2007. Guidance document on the validation of (quantitative) structure-activity relationships (Q)SAR] models. ENV/JM/MONO(2007)2, http://search.oecd.org/officialdocuments/displaydocumentpdf/?cote=env/jm/mono%282007%292&doclanguage=en (accessed March 6, 2013).
58. QSAR Model Reporting Format, Version 1.2, EUROPEAN COMMISSION, JOINT RESEARCH CENTRE, May 2008, http://ihcp.jrc.ec.europa.eu/our_labs/predictive_toxicology/qsar_tools/qrf/QMRF_version_1.2.pdf (accessed March 12, 2013).
59. QSAR Prediction Reporting Format (QPRF), version 1.1, EUROPEAN COMMISSION, JOINT RESEARCH CENTRE, May 2008, http://ihcp.jrc.ec.europa.eu/our_labs/predictive_toxicology/qsar_tools/qrf/QPRF_version_1.1.pdf (accessed March 12, 2013).
60. Scifinder, https://scifinder.cas.org (accessed December 24, 2012).
61. SciQSAR, http://www.scimatics.com/jsp/qsar/key_features.jsp. (accessed December 24, 2012).
62. Scopus, http://www.scopus.com (accessed December 24, 2012).
63. TOXNET, http://toxnet.nlm.nih.gov (accessed December 24, 2012)/.
64. VITIC, https://viticnexus.lhasalimited.org/Vitic1-0/ (accessed December 24, 2012).
65. Williams, R.V. et al., 2008. Validating Alerts in DEREK for Windows. Presented at SCARLET Workshop on in silico Methods for Carcinogenicity & Mutagenicity. 2nd - 4th April 2008, Milan, Italy. http://www.scarlet-project.eu/results_PSs.html (accessed 24 December 2012).