A structural feature-based computational approach for toxicology predictions

Expert Opinion on Drug Metabolism and Toxicology

Volumn 6, Issue 4, 2010, Pages 505-518

  Valerio Jr , Luis G ^a   Yang, Chihae ^a   Arvidson, Kirk B ^a   Kruhlak, Naomi L ^a  

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

Author keywords

Computational toxicology; Preclinical toxicity; QSAR; Safety assessment; SAR

Indexed keywords

ALGORITHM; CARCINOGENICITY; CLINICAL EVALUATION; COMPUTER PROGRAM; FOOD AND DRUG ADMINISTRATION; GENETIC TOXICOLOGY; HYDROPHILICITY; LEADSCOPE MODEL APPLIER; LIPOPHILICITY; LOGISTIC REGRESSION ANALYSIS; PHENOTYPE; PREDICTION; PRODUCT DEVELOPMENT; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; RISK ASSESSMENT; SAFETY; SENSITIVITY AND SPECIFICITY; STRUCTURE ANALYSIS; VALIDATION PROCESS;

ANIMALS; COMPUTATIONAL BIOLOGY; HUMANS; PHARMACEUTICAL PREPARATIONS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SOFTWARE;

EID: 77949889455     PISSN: 17425255     EISSN: None     Source Type: Journal    
DOI: 10.1517/17425250903499286     Document Type: Review

References (27)

1. FDA. Challenge and opportunity on the critical path to new medical products. Available from URL: http://www.fda.gov/ ScienceResearch/SpecialTopics/ CriticalPathInitiative/ CriticalPathOpportunitiesReports/ ucm077262.htm 10 August 2009. 2004 [cited 2009; Available from: http://www. fda.gov/oc/ initiatives/criticalpath/ whitepaper.html
2. Valerio LG Jr, Arvidson KB, Chanderbhan RF, Contrera JF. Prediction of rodent carcinogenic potential of naturally occurring chemicals in the human diet using high-throughput QSAR predictive modeling. Toxicol Appl Pharmacol 2007;222(1):1-16
3. Kruhlak NL, Choi SS, Contrera JF, et al. Development of a phospholipidosis database and predictive quantitative structure-activity relationship (QSAR) models. Toxicol Mech Methods 2008;18(2):217-227
4. Bailey AB, Chanderbhan R, Collazo-Braier N, et al. The use of structure-activity relationship analysis in the food contact notification program. Regul Toxicol Pharmacol 2005;42(2):225-235
5. Mayer J, Cheeseman MA, Twaroski ML. Structure-activity relationship analysis tools: validation and applicability in predicting carcinogens. Regul Toxicol Pharmacol 2008;50(1):50-58
6. Tong W, Welsh WJ, Shi L, et al. Structure-activity relationship approaches and applications. Environ Toxicol Chem 2003;22(8):1680-1695
7. Beger RD, Harris S, Xie Q. Models of steroid binding based on the minimum deviation of structurally assigned 13C NMR spectra analysis (MiDSASA). J Chem Inf Comput Sci 2004;44(4):1489-1496
8. Yu H, Adedoyin A. ADME-Tox in drug discovery: integration of experimental and computational technologies. Drug Discov Today 2003;8(18):852-861
9. Segall MD, Beresford AP, Gola JMR, et al. Focus on success: using a probabilistic approach to achieve an optimal balance of compound properties in drug discovery. Expert Opin Drug Metab Toxicol 2006;2(2):325-337
10. Dearden JC. In silico prediction of ADMET properties: how far have we come? Expert Opin Drug Metab Toxicol 2007;3(5):635-639
11. Yang C, Cross K, Myatt GJ, et al. Building predictive models for protein tyrosine phosphatase 1B inhibitors based on discriminating structural features by reassembling medicinal chemistry building blocks. J Med Chem 2004;47(24):5984-5994
12. Matthews EJ, Kruhlak NL, Benz RD, et al. 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. Toxicol Mech Methods 2008;18(2):189-206
13. Ursem CJ, Kruhlak NL, Contrera JF, et al. Identification of structure activity relationships for adverse effects of pharmaceuticals in humans: A. Use of FDA post-market reports to create a database of hepatobiliary and urinary tract toxicities. Regul Toxicol Pharmacol 2009;54(1):1-22
14. Roberts G, Myatt GJ, Johnson WP, et al. LeadScope: software for exploring large sets of screening data. J Chem Inf Comput Sci 2000;40(6):1302-1314
15. Cross KP, Myatt G, Yang C, et al. Finding discriminating structural features by reassembling common building blocks. J Med Chem 2003;46(22):4770- 4775
16. Geladi P, Kowalski BR. Partial least-squares regression: a tutorial. Anal Chim Acta 1986;185:1-17
17. Nguyen DV, Rocke DM. Tumor classification by partial least squares using microarray gene expression data. Bioinformatics 2002;18(1):39-50
18. Wold S. Chemometrics: mathematics and statistics in chemistry. Reidel, Dordrecht; 1984
19. Wold S. Food research and data analysis. Applied Science Publications, London; 1983
20. Hanley JA. Receiver operating characteristic (ROC) methodology: the state of the art. Crit Rev Diagn Imaging 1989;29(3):307-335
21. Contrera JF, Maclaughlin P, Hall LH, Kier LB. QSAR modeling of carcinogenic risk using discriminant analysis and topological molecular descriptors. Curr Drug Discov Technol 2005 2005;2(2):55-67
22. Matthews EJ, Contrera JF. A new highly specific method for predicting the carcinogenic potential of pharmaceuticals in rodents using enhanced MCASE QSAR-ES software. Regul Toxicol Pharmacol 1998;28(3):242-264
23. Valerio LG Jr, Arvidson KB, Busta E, et al. Testing computational toxicology models with phytochemicals. Mol Nutr Food Res 2009. In press
24. Matthews EJ, Kruhlak NL, Benz RD, Contrera JF. A comprehensive model for reproductive and developmental toxicity hazard identification: I. Development of a weight of evidence QSAR database. Regul Toxicol Pharmacol 2007;47(2):115-135
25. Contrera JF, Matthews EJ, Kruhlak NL, Benz RD. In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL QSAR software. Regul Toxicol Pharmacol 2005;43(3):313-323
26. Matthews EJ, Kruhlak NL, Benz RD, et al. Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans: part C: use of QSAR and an expert system for the estimation of the mechanism of action of drug-induced hepatobiliary and urinary tract toxicities. Regul Toxicol Pharmacol 2009;54(1):43-65
27. Matthews EJ, Ursem CJ, Kruhlak NL, et al. Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans: B. Use of (Q) SAR systems for early detection of drug-induced hepatobiliary and urinary tract toxicities. Regul Toxicol Pharmacol 2009;54(1):23-42