Predicting Chemical Toxicity Effects Based on Chemical-Chemical Interactions

PLoS ONE

Volumn 8, Issue 2, 2013, Pages

  Chen, Lei ^b   Lu, Jing ^c   Zhang, Jian ^d   Feng, Kai Rui ^e   Zheng, Ming Yue ^c   Cai, Yu Dong ^a  

^a SHANGHAI UNIVERSITY   (China)

^b SHANGHAI MARITIME UNIVERSITY   (China)

^c SHANGHAI INSTITUTE OF MATERIA MEDICA   (China)

^d SHANGHAI FIRST PEOPLE S HOSPITAL   (China)

^e CERTARA UK LIMITED   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

1,2,3,4,6,7,8 HEPTACHLORODIBENZODIOXIN; 2,2',5,5' TETRACHLOROBENZIDINE; 2,3,7,8 TETRABROMODIBENZO 4 DIOXIN; 4 BROMOPHENOL; 4 CHLOROTHIOPHENOL; 4 HYDROXY 2',4',6' TRICHLOROBIPHENYL; PHENYLTHIOHYDANTOIN; POLYCYCLIC AROMATIC HYDROCARBON; RUBEANIC ACID; TASOSARTAN; UNCLASSIFIED DRUG;

ACCURACY; ARTICLE; CARCINOGENICITY; CHEMICAL CHEMICAL INTERACTION; CHEMICAL INTERACTION; CHEMICAL REACTION; CHEMICAL STRUCTURE; CHEMICAL TOXICITY; EYE IRRITATION; JACKKNIFE TEST; MULTI DOSE EFFECT; MUTAGENICITY; PREDICTION; REPRODUCTIVE TOXICITY; SKIN IRRITATION; TOXICITY; TOXICITY TESTING;

DRUG DISCOVERY; DRUG INTERACTIONS; ENDPOINT DETERMINATION; INFORMATICS; STRUCTURE-ACTIVITY RELATIONSHIP; TOXICOLOGY;

EID: 84874060259     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0056517     Document Type: Article

References (42)

1. Dubach UC, Rosner B, Sturmer T, (1991) An epidemiologic study of abuse of analgesic drugs. Effects of phenacetin and salicylate on mortality and cardiovascular morbidity (1968 to 1987). N Engl J Med 324: 155-160.
2. "AstraZeneca Decides to Withdraw Exanta" (2006) Available: http://www.astrazeneca.com/Media/Press-releases/Article/20060214-AstraZeneca-Decides-to-Withdraw-Exanta.Accessed 2012 Sep 2.
3. Wang WB, Zhao YP, Cong L, Jing H, Liao Q, et al. (2011) Clinical characters of gastrointestinal lesions in intestinal Behcet's disease. Chin Med Sci J 26: 168-171.
4. Zheng M, Liu Z, Xue C, Zhu W, Chen K, et al. (2006) Mutagenic probability estimation of chemical compounds by a novel molecular electrophilicity vector and support vector machine. Bioinformatics 22: 2099-2106.
5. Wang Y, Lu J, Wang F, Shen Q, Zheng M, et al. (2012) Estimation of carcinogenicity using molecular fragments tree. J Chem Inf Model 52: 1994-2003.
6. Crammer K, Singer Y, (2001) On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research 2: 265-292.
7. Dietterich TG, Bakiri G, (1995) Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research 2: 263-286.
8. Sharan R, Ulitsky I, Shamir R, (2007) Network-based prediction of protein function. Mol Syst Biol 3: 88.
9. Bogdanov P, Singh AK, (2010) Molecular function prediction using neighborhood features. IEEE/ACM Trans Comput Biol Bioinform 7: 208-217.
10. Kourmpetis YA, van Dijk AD, Bink MC, van Ham RC, ter Braak CJ, (2010) Bayesian Markov Random Field analysis for protein function prediction based on network data. PLoS One 5: e9293.
11. Ng KL, Ciou JS, Huang CH, (2010) Prediction of protein functions based on function-function correlation relations. Comput Biol Med 40: 300-305.
12. Hu L, Huang T, Liu XJ, Cai YD, (2011) Predicting protein phenotypes based on protein-protein interaction network. PLoS One 6: e17668.
13. Hu L, Huang T, Shi X, Lu WC, Cai YD, et al. (2011) Predicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid properties. PLoS One 6: e14556.
14. Gao P, Wang QP, Chen L, Huang T, (2012) Prediction of Human Genes Regulatory Functions Based on Proteinprotein Interaction Network. Protein and Peptide Letters 19: 910-916.
15. Hu LL, Chen C, Huang T, Cai YD, Chou KC, (2011) Predicting Biological Functions of Compounds Based on Chemical-Chemical Interactions. PLoS ONE 6: e29491.
16. Chen L, Zeng WM, Cai YD, Feng KY, Chou KC, (2012) Predicting Anatomical Therapeutic Chemical (ATC) Classification of Drugs by Integrating Chemical-Chemical Interactions and Similarities. PLoS ONE 7: e35254.
17. Kuhn M, von Mering C, Campillos M, Jensen LJ, Bork P, (2008) STITCH: interaction networks of chemicals and proteins. Nucleic Acids Res 36: D684-688.
18. Kuhn M, Szklarczyk D, Franceschini A, Campillos M, von Mering C, et al. (2010) STITCH 2: an interaction network database for small molecules and proteins. Nucleic Acids Res 38: D552-556.
19. Accelrys Toxicity Database 2011.4. Accelrys Software Inc.: San Diego, CA.
20. DrugBank. Available: http://www.drugbank.ca/downloads. Accessed 2012 Sep 2.
21. HMDB. Available: http://www.hmdb.ca/downloads. Accessed 2012 Sep 2.
22. Du P, Li T, Wang X, (2011) Recent progress in predicting protein sub-subcellular locations. Expert Review of Proteomics 8: 391-404.
23. Cai YD, Lu L, Chen L, He JF, (2010) Predicting subcellular location of proteins using integrated-algorithm method. Molecular Diversity 14: 551-558.
24. Shao X, Tian Y, Wu L, Wang Y, Jing L, et al. (2009) Predicting DNA-and RNA-binding proteins from sequences with kernel methods. Journal of Theoretical Biology 258: 289-293.
25. Zeng Y, Guo Y, Xiao R, Yang L, Yu L, et al. (2009) Using the augmented Chou's pseudo amino acid composition for predicting protein submitochondria locations based on auto covariance approach. Journal of Theoretical Biology 259: 366-372.
26. Chen L, Cai YD, Shi XH, Huang T, (2012) Analysis of Metabolic Pathway Using Hybrid Properties. Protein and Peptide Letters 19: 99-107.
27. Esmaeili M, Mohabatkar H, Mohsenzadeh S, (2010) Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses. Journal of theoretical biology 263: 203-209.
28. Georgiou D, Karakasidis T, Nieto J, Torres A, (2009) Use of fuzzy clustering technique and matrices to classify amino acids and its impact to Chou's pseudo amino acid composition. Journal of theoretical biology 257: 17-26.
29. Li BQ, Hu LL, Chen L, Feng KY, Cai YD, et al. (2012) Prediction of Protein Domain with mRMR Feature Selection and Analysis. PLoS ONE 7: e39308.
30. Jin L, Fang W, Tang H, (2003) Prediction of protein structural classes by a new measure of information discrepancy. Computational Biology and Chemistry 27: 373-380.
31. Ivanciuc O, (2008) Weka machine learning for predicting the phospholipidosis inducing potential. Current Topics in Medicinal Chemistry 8: 1691-1709.
32. Ravetti MG, Moscato P, (2008) Identification of a 5-protein biomarker molecular signature for predicting Alzheimer's disease. PLoS ONE 3: e3111.
33. Sun XD, Huang RB, (2006) Prediction of protein structural classes using support vector machines. Amino acids 30: 469-475.
34. Yuan JM, Koh WP, Murphy SE, Fan Y, Wang R, et al. (2009) Urinary levels of tobacco-specific nitrosamine metabolites in relation to lung cancer development in two prospective cohorts of cigarette smokers. Cancer Res 69: 2990-2995.
35. Kitiporn P, Jan-Phillip M, Marcus O, Fabian S, Victor S, et al. (2008) Machine learning based analyses on metabolic networks supports high-throughput knockout screens. BMC Systems Biology 2: 67.
36. Church TR, Anderson KE, Caporaso NE, Geisser MS, Le CT, et al. (2009) A prospectively measured serum biomarker for a tobacco-specific carcinogen and lung cancer in smokers. Cancer Epidemiol Biomarkers Prev 18: 260-266.
37. Benigni R, Bossa C, (2011) Mechanisms of chemical carcinogenicity and mutagenicity: a review with implications for predictive toxicology. Chem Rev 111: 2507-2536.
38. Benigni R, Bossa C, (2008) Structure alerts for carcinogenicity, and the Salmonella assay system: a novel insight through the chemical relational databases technology. Mutat Res 659: 248-261.
39. Arcos JC, Argus MF, editors (1995) Multifactor interaction network of carcinogenesis- a "tour guide". Boston: Birkhauser. 1-20 p.
40. DrugBank. Available: http://www.drugbank.ca/drugs/DB01349. Accessed 2012 Sep 12.
41. Patlewicz GY, Wright ZM, Basketter DA, Pease CK, Lepoittevin JP, et al. (2002) Structure-activity relationships for selected fragrance allergens. Contact Dermatitis 47: 219-226.
42. Woo YT (2003) Mechanisms of action of chemical carcinogens, and their role in structure-activity relationships (SAR) analysis and risk assessment. In: Benigni R, editor. Quantitative Structure-Activity Relationship (QSAR) Models of Mutagens and Carcinogens. Boca Raton: CRC Press. 41-80.