Latest advances in computational genotoxicity prediction

Expert Opinion on Drug Metabolism and Toxicology

Volumn 8, Issue 12, 2012, Pages 1579-1587

  Naven, Russell T ^a   Greene, Nigel ^a   Williams, Richard V ^b  

^a PFIZER INC   (United States)

^b LHASA LIMITED   (United Kingdom)

Author keywords

Applicability domains; Chemical similarity; Derek for windows; Genotoxic impurities; ICH M7; Leadscope model applier; MC4PC; Toxtree

Indexed keywords

AROMATIC AMINE; FUNCTIONAL GROUP; PTAQUILOSIDE;

AMES TEST; DNA ADDUCT; DRUG IMPURITY; FOOD AND DRUG ADMINISTRATION; GENOTOXICITY; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MUTAGENICITY; PREDICTION; RELIABILITY; REVIEW; SCREENING;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DNA DAMAGE; MODELS, MOLECULAR; MUTAGENICITY TESTS; MUTAGENS; TOXICOLOGY;

EID: 84869429344     PISSN: 17425255     EISSN: 17447607     Source Type: Journal    
DOI: 10.1517/17425255.2012.724059     Document Type: Review

References (43)

1. Ashby J, Tennant RW. Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP. Mutat Res 1991;257(3):229-306
2. Haworth S, Lawlor T, Mortelmans K, et al. Salmonella mutagenicity test results for 250 chemicals. Environ Mutagen 1983;5(Suppl 1):1-142
3. Mortelmans K, Haworth S, Lawlor T, et al. Salmonella mutagenicity tests: II. Results from the testing of 270 chemicals. Environ Mutagen 1986;8(Suppl 7):1-119
4. Zeiger E, Anderson B, Haworth S, et al. Salmonella mutagenicity tests: IV. Results from the testing of 300 chemicals. Environ Mol Mutagen 1988;11(Suppl 12):1-157
5. Zeiger E, Anderson B, Haworth S, et al. Salmonella mutagenicity tests: III. Results from the testing of 255 chemicals. Environ Mutagen 1987;9(Suppl 9):1-109
6. Naven RT, Louise-May S, Greene N. The computational prediction of genotoxicity. Expert Opin Drug Metab Toxicol 2010;6(7):797-807
7. Lynch AM, Sasaki JC, Elespuru R, et al. New and emerging technologies for genetic toxicity testing. Environ Mol Mutagen 2011;52(3):205-23
8. Kirkland D, Aardema M, Henderson L, Müller L. Evaluation of the ability of a battery of three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens I. Sensitivity, specificity and relative predictivity. Mutat Res 2005;584(1-2):1-256
9. Gramatica P. Principles of QSAR models validation: internal and external. QSAR Comb Sci 2007;26(5):694-701
10. Tropsha A, Gramatica P, Gombar VK. The Importance of Being Earnest: validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models. QSAR Comb Sci 2003;22(1):69-77
11. Marchant CA, Briggs KA, Long A. In silico tools for sharing data and knowledge on toxicity and metabolism: derek for windows, meteor, and vitic. Toxicol Mech Methods 2008;18(2-3):177-87
12. Saiakhov RD, Klopman G. Benchmark performance of MultiCASE Inc. software in Ames mutagenicity set. J Chem Inf Model 2010;50(9):1521
13. Valerio LG Jr, Cross KP. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities*. Toxicol Appl Pharmacol 2012;260(3):209-21
14. Benigni R, Bossa C, Tcheremenskaia O, Giuliani A. Alternatives to the carcinogenicity bioassay: in silico methods, and the in vitro and in vivo mutagenicity assays. Expert Opin Drug Metab Toxicol 2010;6(7):809-19
15. Hillebrecht A, Muster W, Brigo A, et al. Comparative evaluation of in silico systems for ames test mutagenicity prediction: scope and limitations. Chem Res Toxicol 2011;24(6):843-54
16. McCarren P, Bebernitz GR, Gedeck P, et al. Avoidance of the Ames test liability for aryl-amines via computation. Bioorg Med Chem 2011;19(10):3173-82
17. Greene N, Judson PN, Langowski JJ, et al. Knowledge-based expert systems for toxicity and metabolism prediction: DEREK, StAR and METEOR. SAR QSAR Environ Res 1999;10(2-3):299-314
18. Snyder RD, Pearl GS, Mandakas G, et al. Assessment of the sensitivity of the computational programs DEREK, TOPKAT, and MCASE in the prediction of the genotoxicity of pharmaceutical molecules. Environ Mol Mutagen 2004;43(3):143-58
19. Kamber M, Flückiger-Isler S, Engelhardt G, 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(4):359-66
20. Snyder RD. Assessment of atypical DNA intercalating agents in biological and in silico systems. Mutat Res 2007;623(1-2):72-82
21. United States Food and Drug Administration. Guidance for Industry, Genotoxic and Carciniogenic Impurities in Drug Substance and Drug Products: recommended Approaches. 2008.Available from: http://www.fda.gov/downloads/Drugs/ Guidance ComplianceRegulatoryInformation/Guidances/ucm079235.pdf
22. European Medicines Agency. Guideline on the Limits of Genotoxic Impurities. 2006.Available from: http://www.emea.europa.eu/docs/en-GB/document- library/Scientific-guideline/2009/09/WC500002903.pdf
23. Muller L, Mauthe RJ, Riley CM, et al. A rationale for determining, testing, and controlling specific impurities in pharmaceuticals that possess potential for genotoxicity. Regul Toxicol Pharmacol 2006;44(3):198-211
24. Dobo KL, Greene N, Fred C, et al. In silico methods combined with expert knowledge rule out mutagenic potential of pharmaceutical impurities: an industry survey. Regul Toxicol Pharmacol 2012;62(3):449-55
25. Dobo KL, Greene N, Cyr MO, et al. The application of structure-based assessment to support safety and chemistry diligence to manage genotoxic impurities in active pharmaceutical ingredients during drug development. Regul Toxicol Pharmacol 2006;44(3):282-93
26. Glowienke S, Hasselgren C. Use of Structure Activity Relationship (SAR) evaluation as a critical tool in the evaluation of the genotoxic potential of impurities, in genotoxic impurities: strategies for identification and control. John Wiley & Sons, Inc; Hoboken, NJ, USA:2011. p. 97-120
27. McCarren P, Springer C, Whitehead L. An investigation into pharmaceutically relevant mutagenicity data and the influence on Ames predictive potential. J Cheminform 2011;3:51
28. Ono A, Takahashi M, Hirose A, et al. Validation of the (Q)SAR combination approach for mutagenicity prediction of flavor chemicals. Food Chem Toxicol 2012;50(5):1538-46
29. Pearl GM, Livingston-Carr S, Durham SK. Integration of computational analysis as a sentinel tool in toxicological assessments. Curr Top Med Chem 2001;1(4):247-55
30. White AC, Mueller RA, Gallavan RH, et al. A multiple in silico program approach for the prediction of mutagenicity from chemical structure. Mutat Res 2003;539(1-2):77-89
31. Sushko I, Novotarskyi S, K€orner R, et al. Applicability domains for classification problems: benchmarking of distance to models for Ames mutagenicity set. J Chem Inf Model 2010;50(12):2094-111
32. Dragos H, Gilles M, Alexandre V. Predicting the predictability: a unified approach to the applicability domain problem of QSAR models. J Chem Inf Model 2009;49(7):1762-76
33. Ellison CM, Sherhod R, Cronin MT, et al. Assessment of methods to define the applicability domain of structural alert models. J Chem Inf Model 2011;51(5):975-85
34. Hewitt M, Ellison CM. Developing the applicability domain of in silico models: relevance, importance and methodology. In: Cronin MTD, Madden JC, editors. In silico toxicology: principles and applications. Royal Society of Chemistry; Cambridge, UK:2010. p. 301-33
35. Weaver S, Gleeson MP. The importance of the domain of applicability in QSAR modeling. J Mol Graph Model 2008;26(8):1315-26
36. Kuhne R, Ebert RU, Schuurmann G. Chemical domain of QSAR models from atom-centered fragments. J Chem Inf Model 2009;49(12):2660-9
37. Sheridan RP, Feuston BP, Maiorov VN, Kearsley SK. Similarity to molecules in the training set is a good discriminator for prediction accuracy in QSAR. J Chem Inf Comput Sci 2004;44(6):1912-28
38. Netzeva TI, Worth A, Aldenberg T, et al. Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop. Altern Lab Anim 2005;33(2):155-73
39. Jaworska J, Nikolova-Jeliazkova N, Aldenberg T. QSAR applicabilty domain estimation by projection of the training set descriptor space: a review. Altern Lab Anim 2005;33(5):445-59
40. Fioravanzo E, Bassan A, Pavan M, et al. Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities. SAR QSAR Environ Res 2012;23(3-4):257-77
41. Ellison CM, Enoch SJ, Cronin MT, et al. Definition of the applicability domains of knowledge-based predictive toxicology expert systems by using a structural fragment-based approach. Altern Lab Anim 2009;37(5):533-45
42. Harbach PR, Zimmer DM, Mazurek JH, Bhuyan BK. Mutagenicity of the antitumor antibiotic CC-1065 and its analogues in mammalian (V79) cells and bacteria. Cancer Res 1988;48(1):32-6
43. O'Donovan MR, Mee CD, Fenner S, et al. Boronic acids-a novel class of bacterial mutagen. Mutat Res 2011;724(1-2):1-6