Combined use of MC4PC, MDL-QSAR, BioEpisteme, leadscope PDM, and derek for windows software to achieve high-performance, high-confidence, mode of action-based predictions of chemical carcinogenesis in rodents

Toxicology Mechanisms and Methods

Volumn 18, Issue 2-3, 2008, Pages 189-206

  Matthews, Edwin J ^a   Kruhlak, Naomi L ^a   Benz, R Daniel ^a   Contrera, Joseph F ^a   Marchant, Carol A ^b   Yang, Chihae ^c  

^a CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^b LHASA LIMITED   (United Kingdom)

^c Leadscope   (United States)

Author keywords

BioEpisteme; Carcinogenicity; Chemical Carcinogenesis; Computational Toxicology; Derek for Windows; In Silico; Leadscope; MC4PC; MDL QSAR; QSAR software; Quantitative Structure Activity Relationships; SAR

Indexed keywords

CARCINOGEN;

ANALYTICAL PARAMETERS; ARTICLE; CARCINOGENICITY; CHEMICAL CARCINOGENESIS; CHEMICAL STRUCTURE; CHI SQUARE TEST; COMPUTER PROGRAM; EXPERIMENTAL MODEL; EXPERT SYSTEM; FEMALE; GENOTOXICITY; INTERMETHOD COMPARISON; KNOWLEDGE BASE; MALE; MOUSE; NONHUMAN; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; RAT; RODENT; SENSITIVITY AND SPECIFICITY; STRUCTURE ACTIVITY RELATION;

RATTUS; RODENTIA;

EID: 40949145715     PISSN: 15376516     EISSN: 15376524     Source Type: Journal    
DOI: 10.1080/15376510701857379     Document Type: Article

References (59)

1. Anderson, T.W. 1984. An Introduction to Multivariate Statistical Analysis, Second Edition, John Wiley & Sons, New York.
2. Ashby, J. 1996. Prediction of rodent carcinogenicity for 30 chemicals. Environ. Health Perspec. 104:1101-1104.
3. Ashby, J., and Tennant, R. W. 1994. Prediction of rodent carcinogenicity for 44 chemicals. Mutagenesis 9:7-15.
4. Benigni, R. 1997. The first U.S. National Toxicology Program exercise on the prediction of rodent carcinogenicity: definitive results. Mut. Res. 387:35-45.
5. Benigni, R. 2005. Structure activity relationship studies of chemical mutagens and carcinogens: mechanistic investigations and prediction approaches. Chem. Rev. 105:1767-1800.
6. Benigni, R., Netzeva, T. I., Benfenati, E., Bossa, C., Franke, R., Helma, C., Hulzebos, E., Marchant, C., Richard, A., Woo, C. T., and Yang, C. 2007. The expanding role of predictive toxicology: an update on the (Q)SAR models for mutagens and carcinogens. J. Environ. Sci. Health Part C Environ. Carcinogen. Ecotoxicol. Rev. 25:53-97.
7. Bristol, D. W., Wachsman, J. T., and Greenwell, A. 1996. The NIEHS predictive-toxicology evaluation project: chemcarcinogenicity bioassay. Environ. Health Perspec. 104:1001-1010.
8. Contrera, J. F., Jacobs, A. C., and DeGeorge, J. J. 1997. Carcinogenicity testing and the evaluation of regulatory requirements for pharmaceuticals. Regul. Toxicol. Pharmacol. 25:130-145.
9. Contrera, J. F., Kruhlak, N. L., Matthews, E. J., and Benz, R. D. 2007. Comparison of MC4PC and MDL-QSAR rodent carcinogenicity predictions and the enhancement of predictive performance by combining QSAR models. Regul. Toxicol. Pharmacol. 49:172-182.
10. Contrera, J. F., Matthews, E. J., and Benz, R. D. 2003. Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices. Regul. Toxicol. Pharmacol. 38:243-259.
11. Contrera, J. F., Matthews, E. J., Kruhlak, N. L., and Benz, R. D. 2005. In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL-QSAR software. Regul. Toxicol. Pharmacol. 43:313-323.
12. Cooper, J. A., Saracci, R., and Cole, P. 1979. Describing the validity of carcinogen screening tests. Br. J. Cancer 39:87-89.
13. Cross, K. C., Myatt, G., Yang, C., Fligner, M. A., Verducci, J. S., and Blower, P. E. 2003. Finding discriminating structural features by reassembling common building blocks. J. Med. Chem. 46:4770-4775.
14. Danish Environmental Protection Agency. 2006. QSAR Danish Ministry of the Environment, http://ecb.jrc.it./. Accessed November 2007.
15. Dearden, J. C., Barratt, M. D., Benigni, R., Bristol, D. W., Combes, R. D., Cronin, M. T. D., Judson, P. N., Payne, M. P., Richard, A. M., Tichy, M., Worth, A. P., and Yourick, J. J. 1997. The development and validation of expert systems for predicting toxicity. The report and recommendations of an ECVAM/ECB workshop 24. Alternat. Lab. Anim. 25:223-252.
16. Dearfield, K. L., and Moore, M. M. 2005. Use of genetic toxicology information for risk assessment. Environ. Molec. Mutagen. 46:236-245.
17. Environmental Protection Agency Carcinogenicity Guidance, Guideline Number: 870.4300 and Number: 870.4200. http://www.epa.gov/pesticides/regulating/ studyprofile templates/studyprofiletemplatelist.htm. Accessed November 2007.
18. European Commission Workshop. 2005. Consultation meeting on consensus modeling and battery approaches in (Q)SAR. September 26-27, Barza, Italy.
19. FDA/CFSAN. Carcinogenicity guidance: Redbook II. http://vm.cfsan.fda.gov/ ~redbook/red-ivc6.html. Accessed November 2007.
20. FDA/CR.DE Carcinogenicity guidance. http://www.fda.gov/Cder/guidance/ 4804fnl.htm. Accessed November 2007.
21. FDA/CR/ICSAS.DE http://www.fda.gov/cder/ Offices/OPS IO/default.htm. Accessed November 2007.
22. Fix, E., and Hodges, J. 1951. Discriminatory analysis, nonparametric discrimination: consistency properties. Technical Report 4, USAF School of Aviation Medicine, Randolph Field, Texas.
23. Geladi, P., and Kowalski, B. 1986. Partial least-squares regression: a tutorial. Anal. Chim. Acta 185:1-17.
24. Gold, L. S., Slone, T. H., Manley, N. B., Garfinkel, G. B., Ames, B. N. The Carcinogenic Potency Database (CPDB). http://potency.berkeley.edu/. Accessed November 2007.
25. Hall, L. H., and Kier, L. B. 1995. Electrotopological state indices for atom types: A novel combination of electronic, topological and valence state information. J. Chem. Inf. Comput. Sci. 35:1039-1045.
26. Hanley, J. A. 1989. Receiver operating characteristic (ROC) methodology: the state of the art. Crit. Rev. Diagn. Imaging 29:307-335.
27. Haseman, J. K. 1983. A re-examination of false-positive rates for carcinogenicity studies. Fundamen. App. Toxicol. 3:334-339.
28. Haseman, J. K., Winbush, J. S., and O'Donnell, M. W. 1986. The use of dual negative control groups to estimate false-positive rates in laboratory animal carcinogenicity studies. Fundamen. App. Toxicol. 7:573-584.
29. Judson, P. N., Marchant, C. A., and Vessey, J. D. 2003. Using argumentation for absolute reasoning about the potential toxicity of chemicals. J. Chem. Infor. Computer Sci. 43:1364-1370.
30. Kendall, M. G., Stuart, A., Ord, J. K. 1983. The Advanced Theory of Statistics, Vol 3. Fourth Edition, Macmillan Publishing, New York.
31. Kier, L. B., Hall, L. H. 1999. In: Molecular Structure Description: The Electrotopological State, ed. Lemont, B. Academic Press, New York.
32. Klopman, G. 1992. Multicase: a hierarchical computer automated structure evaluation program. QSAR. 11:176-184.
33. Kruhlak, N. L., Contrera, J. F., Benz, R. D., and Matthews, E. J. 2007. Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products. Adv. Drug Deliv. Rev. 59:43-55.
34. Lusted, L. B. 1971. Signal detectability and medical decision-making. Science 171:1217-1219.
35. Marchant, C. A. 1997. Prediction of rodent carcinogenicity using the DEREK system for 30 chemicals currently being tested by the National Toxicology Program. The DEREK Collaborative Group. Environ. Health Perspec. 104(Suppl 5):1065-1073.
36. Matthews, E. J., and Contrera, J. F. 1998. A new highly specific method for predicting the carcinogenic potential of pharmaceuticals in rodents using enhanced MCASE QSAR-ES software. Regul. Toxicol. Pharmacol. 28:242-264.
37. Matthews, E. J., and Contrera, J. F. 2007. In silico approaches to explore toxicity end points: Issues and concerns for estimating human health effects. Expert Opin. Drug Metab. Toxicol. 3:125-134.
38. Matthews, E. J., Kruhlak, N. L., Benz, R. D., and Contrera, J. F. 2007a. A comprehensive model for reproductive and developmental toxicity hazard identification: I. Development of a weight of evidence QSAR database. Regul. Toxicol. Pharmacol. 47:115-135.
39. Matthews, E. J., Kruhlak, N. L., Benz, R. D., Ivanov, J., Klopman, G., and Contrera, J. F. 2007b. A comprehensive model for reproductive and developmental toxicity hazard identification: II. Construction of QSAR models to predict activities of untested chemicals. Regul. Toxicol. Pharmacol. 47:136-155.
40. Matthews, E. J., Kruhlak, N. L., Cimino, M. C., Benz, R. D., and Contrera, J. F. 2006a. An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: I. Identification of carcinogens using surrogate endpoints. Regul. Toxicol. Pharmacol. 44:83-96.
41. Matthews, E. J., Kruhlak, N. L., Cimino, M. C., Benz, R. D., and Contrera, J. F. 2006b. An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: II. Identification of genotoxicants, reprotoxicants, and carcinogens using in silico methods. Regul. Toxicol. Pharmacol. 44:97-110.
42. Matthews, E. J., Ursem, C. J., Kruhlak, N. L., Benz, R. D., Aragonés Sabaté, D., Prous, J. R., Yang, C., Klopman, G., and Contrera, J. F. 2008c. Identification of structure activity relationships for adverse effects of pharmaceuticals in humans: B: use of (Q)SAR systems for early detection of drug-induced urinary tract and hepatobiliary toxicities. Regul. Toxicol. Pharmacol. To be submitted.
43. McConnell, E. E., Solleveld, H. A., Swenberg, J. A., and Boorman, G. A. 1986. Guidelines for combining neoplasms for evaluation of rodent carcinogenesis studies. J. Natl. Canc. Inst. 76:283-289.
44. Molecular Operating Environment (MOE) 2006.07. Chemical Computing Group: http://www.chemcomp.com/. Accessed November 2007.
45. National Toxicology Program, NIEHS. http://ntp.niehs.nih.gov/index.cfm. Accessed November 2007.
46. Netzeva, T. I., Worth, A. P., Aldenber, T., Benigni, R., Cronin, M. T. D., Gramatica, P., Jaworska, J. S., Kahn, S., Klopman, G., Marchant, C. A., Myatt, G., Nikolova-Jeliazkova, N., Patlewicz, G. Y., Perkins, R., Roberts, D. W., Schultz, T. W., Stanton, D. T., van de Sandt, J. J. M., Tong, W., Veith, G., and Yang, C. 2005. Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop. Alternat. Lab. Anim. 33:155-173.
47. Office of Science Technology Policy (OSTP). 1985. Chemical carcinogens: a review of the science and its associated principles. Fed. Reg. 50:10371-10442.
48. Oncologic. An expert system software formerly distributed by Logichem and now available through the EPA. http://www.epa.gov/oppt/cahp/pubs/can.htm. Accessed November 2007.
49. Organisation for Economic Cooperation and Development (OECD) Quantitative Structure-Activity Relationships [(Q)SARs] Project. Guidance document on the validation of (quantitative) structure-activity relationship [(Q)SAR] models. http://www.oecd.org/dataoecd/55/35/38130292.pdf. Accessed November 2007.
50. Pearl, G. M., Livingston-Carr, S., and Durham, S. K. 2001. Integration of computational analysis as a sentinel tool in toxicological assessments. Curr. Topics Med. Chem. 1:247-255.
51. Pearson's Chi-square test. http://math.hws.edu/javamath/ryan/ChiSquare. html. Accessed November 2007.
52. Provost, F., and Fawcett, T. 2001. Robust classification for imprecise environments. Mach. Learn. J. 42:203-231.
53. Roberts, G., Myatt, G. J., Johnson, W. P., Cross, K. P., and Blower, P. E. 2000. LeadScope: software for exploring large sets of screening data. J. Chem. Inf. Comput. Sci. 40:1302-1314.
54. Tennant, R. W. 1993. Stratification of carcinogenicity bioassay results to reflect relative human hazard. Mut. Res. 286:111-118.
55. Tunkel, J., Mayo, K., Austin, C., Hickerson, A., and Howard, P. 2005. Practical considerations on the use of predictive models for regulatory purposes. Environ. Sci. Technol. 39:2188-2199.
56. Ursem, C. J., Matthews, E. J., Kruhlak, N. L., Contrera, J. F., and Benz, R. D. 2008. Identification of structure activity relationships for adverse effects of pharmaceuticals in humans IA: Use of FDA post market reports to create a database of hepatobiliary and urinary tract toxicities. Regul. Toxicol. Pharmacol. To be submitted.
57. Votano, J. R., Parham, M., Hall, L. H., Kier, L. B., Oloff, S., and Tropsha, A. 2004. Three new consensus QSAR models for the prediction of Ames genotoxicity. Mutagen. 19:365-377.
58. Yang, C., Cross, K., Myatt, G. J., Blower, P. E., and Rathman, J. F. 2004. Building predictive models for protein tyrosine phosphatase 1B inhibitors based on discriminating structural features by reassembling medicinal chemistry building blocks. J. Med. Chem. 47:5984-5994.
59. Yang, C., Richard, A. M., and Cross, K. P. 2006. The art of data mining the minefields of toxicity databases to link chemistry to biology. Curr. Comp. Aided Drug Design 2:135-150.