Developmental toxicity prediction

Methods in Molecular Biology

Volumn 930, Issue , 2013, Pages 305-340

  Venkatapathy, Raghuraman ^a   Wang, Nina Ching Y ^b  

^a PEGASUS TECHNICAL SERVICES INC   (United States)

^b U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

Author keywords

Applicability domain; Developmental toxicity; Model development; Model validation; Modeling; QSAR; Quantitative structure activity relationships; Statistical methods; Structure activity relationships; Toxicity prediction

Indexed keywords

ANIMAL; ARTICLE; BIOASSAY; DATA BASE; GROWTH, DEVELOPMENT AND AGING; HUMAN; MAMMAL; METHODOLOGY; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICAL MODEL; STATISTICS; TOXICITY TESTING;

ANIMALS; DATABASES AS TOPIC; ENDPOINT DETERMINATION; GROWTH AND DEVELOPMENT; HUMANS; LINEAR MODELS; MAMMALS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; STATISTICS AS TOPIC; TOXICITY TESTS;

EID: 84870480741     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-62703-059-5_14     Document Type: Article

References (42)

1. Anderson ME, Al-Zoughool M, Croteau M et al (2010) The future of toxicity testing. J Toxicol Environ Health B Crit Rev 13(2-4):163-196
2. European Union Directive (2003) DIRECTIVE 2003/89/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 10 November 2003 amending Directive 2000/13/EC as regards indication of the ingredients present in foodstuffs. http://eurlex. europa.eu/LexUriServ/LexUriServ.do? uriOJ:L:2003:308:0015:0018:EN:PDF. Accessed 23 Oct 2010
3. Doull J, Borzelleca JF, Becker R et al (2007) Framework for use of toxicity screening tools in context-based decision-making. Food Chem Toxicol 45(5):759-796
4. Basak SC, Bertelsen S, Grunwald GD (1995) Use of graph theoretic parameters in risk assessment of chemicals. Toxicol Lett 79:239-250
5. Devillers J, Chezeau A, Thybaud E et al (2002) QSAR modeling of the adult and developmental toxicity of glycols, glycol ethers and xylenes to Hydra attenuata. SAR QSAR Environ Res 13(5):555-566
6. Devillers J, Chezeau A, Thybaud E (2002) PLS-QSAR of the adult and developmental toxicity of chemicals to Hydra attenuata. SAR QSAR Environ Res 13(7-8):705-712
7. Kavlock RJ (1990) Structure-activity relationships in the developmental toxicity of substituted phenols: In vivo effects. Teratology 41 (1):43-59
8. Richard AM, Hunter ES III (1996) Quantitative structure-activity relationships for the developmental toxicity of haloacetic acids in mammalian whole embryo culture. Teratology 53(6):352-360
9. Vedani A, McMasters DR, Dobler M (1991) Genetic algorithms in 3D-QSAR: Predicting the toxicity of dibenzodioxins, dibenzofurans and biphenyls. ALTEX 16(1):9-14
10. Matthews EJ, Kruhlak NL, Cimino MC et al (2006) 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(2):97-110
11. Matthews EJ, Kruhlak NL, Benz DR (2007) A comprehensive model for reproductive and developmental toxicity hazard identification: I. Development of a weight of evidence QSAR database. Regul Toxicol Pharmacol 47 (2):115-135
12. Matthews EJ, Kruhlak NL, Benz RD et al (2007) 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(2):136-155
13. Cassano A, Manganaro A, Martin T et al (2010) CAESAR models for developmental toxicity. Chem Cent J 4(Suppl 1):S4
14. Merlot C (2008) In silico methods for early toxicity assessment. Curr Opin Drug Discov Devel 11(1):80-85
15. Worth AP, Bassan A, de Brujin J et al (2007) The role of the European Chemicals Bureau in promoting the regulatory use of (Q)SAR methods. SAR QSAR Environ Res 18:111-125
16. Klopman G (1984) Artificial intelligence approach to structure-activity studies. Computer automated structure evaluation of biological activity of organic molecules. J Am Chem Soc 106:7315-7321
17. Klopman G (1992) MULTICASE: A hierarchical computer automated structure evaluation program. Quant Struct Act Relat 11:176-184
18. KlopmanG,RosenkranzHS (1994)Approaches to SAR in carcinogenesis and mutagenesis. Prediction of carcinogenicity/mutagenicity using Multi-CASE.Mutat Res 305:33-46
19. Maslankiewicz L, Hulzebos EM, Vermeire TG et al (2005) Can chemical structure predict reproductive toxicity? RIVM, Bilthoven. www. rivm.nl/bibliotheek/rapporten/601200005. html. Accessed 24 Oct 2010
20. Accelrys (2001) TOPKAT 6.1: User Guide. Oxford Molecular Ltd, Burlington, MA
21. Gombar VK (1998) Quantitative structureactivity relationships in toxicology: From fundamentals to application. In: Reiss C, Parvez S, Labbe G et al (eds) Advances in molecular toxicology. VSP, Utrecht
22. Purcell WP, Bass GE, Clayton JM (1973) Strategy of drug design: A guide to biological activity. Wiley, New York
23. Moudgal CJ, Venkatapathy R, Choudhury H et al (2003) Application of QSTRs in the selection of a surrogate toxicity value for a chemical of concern. Environ Sci Technol 37:5228-5235
24. Gombar VK, Enslein K (1996) Assessment of n-octanol/water partition coefficient: When is the assessment reliable? J Chem Inf Comput Sci 36:1127-1134
25. Todeschini R, Consonni V (2000) Handbook of molecular descriptors, vol 11, Methods and principles in medicinal chemistry. Wiley-VCH Verlag GmbH, Weinheim
26. Ghose AK, Crippen GM (1987) Atomic physicochemical parameters for three-dimensionalstructure-directed quantitative structureactivity relationships. 2. Modeling dispersive and hydrophobic interactions. J Chem Inf Comput Sci 27(1):21-35
27. Kier LB (1986) Shape indexes of orders one and three from molecular graphs. Quant Struct Act Relat 5:1-7
28. Kier LB, Hall LH (1999) The Kappa indices for modeling molecular shape and flexibility. In: Devillers J, Balaban AT (eds) Topological indices and related descriptors in QSAR and QSPR. Gordon and Breach, Reading
29. Eriksson L, Johansson E, Kettaneh-Wold N et al (1999) Introduction to multi-and megavariate data analysis using projection methods (PCA & PLS). Umetrics, Inc., Kinnelon
30. Eriksson L, Jaworska JS,Worth AP et al (2003) Methods for reliability and uncertainty assessment and for applicability evaluations of classification-and regression-based QSARs. Environ Health Perspect 111:1361-1375
31. Gramatica P (2007) Principles of QSAR models validation: Internal and external. QSAR Comb Sci 26:694-701
32. Atkinson AC (1985) Plots, transformations and regression. Clarendon, Oxford
33. Wold S, Eriksson L (1995) Statistical validation of QSAR results. In: Van de Waterbeemd H (ed) Chemometric methods in molecular design. VCH, New York
34. Golbraikh A, Tropsha A (2002) Beware of q2! J Mol Graph Model 20(4):269-276
35. Kozak A, Kozak R (2003) Does cross validation provide additional information in the evaluation of regression models? Can J Forest Res 33(6):976-987
36. Reunanen J (2003) Overfitting in making comparisons between variable selection methods. J Mach Learn Res 3:1371-1382
37. Olsson I-M, Gottfries J, Wold S (2004) D-optimal onion designs in statistical molecular design. Chemometr Intell Lab Syst 73 (1):37-46
38. Mosier PD, Jurs PC (2002) QSAR/QSPR studies using probabilistic neural networks and generalized regression neural networks. J Chem Inf Comput Sci 42(6):1460-1470
39. Hawkins DM, Basak SC, Mills D (2004) Assessing model fit by cross-validation. J Chem Inf Comput Sci 43(2):579-586
40. Matthews BW (1975) Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta 405 (2):442-451
41. Obach RS, Baxter JG, Liston TE et al (1997) The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J Pharmacol Exp Ther 283 (1):46-58
42. Hawkins DM (2004) The problem of overfitting. J Chem Inf Comput Sci 44(1):1-12