Table of Contents Author Guidelines Submit a Manuscript
Table of Contents Alerts

To receive news and publication updates for BioMed Research International, enter your email address in the box below.

BioMed Research International
Volume 2015, Article ID 670949, 12 pages
http://dx.doi.org/10.1155/2015/670949
Research Article

Systematic Analysis of the Associations between Adverse Drug Reactions and Pathways

Xiaowen Chen, Yanqiu Wang, Pingping Wang, Baofeng Lian, Chunquan Li, Jing Wang, Xia Li, and Wei Jiang

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China

Received 6 February 2015; Revised 24 April 2015; Accepted 14 May 2015

Academic Editor: Md. Altaf-Ul-Amin

Copyright © 2015 Xiaowen Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Evans and A. Rees, “Effects of HMG-CoA reductase inhibitors on skeletal muscle: are all statins the same?” Drug Safety, vol. 25, no. 9, pp. 649–663, 2002. View at Publisher · View at Google Scholar · View at Scopus
  2. N. Atias and R. Sharan, “An algorithmic framework for predicting side effects of drugs,” Journal of Computational Biology, vol. 18, no. 3, pp. 207–218, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. D. C. Liebler and F. P. Guengerich, “Elucidating mechanisms of drug-induced toxicity,” Nature Reviews Drug Discovery, vol. 4, no. 5, pp. 410–420, 2005. View at Publisher · View at Google Scholar · View at Scopus
  4. J. Scheiber, B. Chen, M. Milik et al., “Gaining insight into off-target mediated effects of drug candidates with a comprehensive systems chemical biology analysis,” Journal of Chemical Information and Modeling, vol. 49, no. 2, pp. 308–317, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. L. Xie, J. Li, and P. E. Bourne, “Drug discovery using chemical systems biology: identification of the protein-ligand binding network to explain the side effects of CETP inhibitors,” PLoS Computational Biology, vol. 5, no. 5, Article ID e1000387, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. I. Wallach, N. Jaitly, and R. Lilien, “A structure-based approach for mapping adverse drug reactions to the perturbation of underlying biological pathways,” PLoS ONE, vol. 5, no. 8, Article ID e12063, 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. A. L. Hopkins, “Network pharmacology: the next paradigm in drug discovery,” Nature Chemical Biology, vol. 4, no. 11, pp. 682–690, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. G. Hu and P. Agarwal, “Human disease-drug network based on genomic expression profiles,” PLoS ONE, vol. 4, no. 8, Article ID e6536, 2009. View at Publisher · View at Google Scholar · View at Scopus
  9. K.-I. Goh, M. E. Cusick, D. Valle, B. Childs, M. Vidal, and A.-L. Barabási, “The human disease network,” Proceedings of the National Academy of Sciences of the United States of America, vol. 104, no. 21, pp. 8685–8690, 2007. View at Publisher · View at Google Scholar · View at Scopus
  10. M. A. Yildirim, K.-I. Goh, M. E. Cusick, A.-L. Barabási, and M. Vidal, “Drug-target network,” Nature Biotechnology, vol. 25, no. 10, pp. 1119–1126, 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. D. S. Wishart, C. Knox, A. C. Guo et al., “DrugBank: a knowledgebase for drugs, drug actions and drug targets,” Nucleic Acids Research, vol. 36, no. 1, pp. D901–D906, 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. B. L. Roth, E. Lopez, S. Patel, and W. K. Kroeze, “The multiplicity of serotonin receptors: uselessly diverse molecules or an embarrassment of riches?” The Neuroscientist, vol. 6, no. 4, pp. 252–262, 2000. View at Publisher · View at Google Scholar · View at Scopus
  13. S. Günther, M. Kuhn, M. Dunkel et al., “SuperTarget and Matador: resources for exploring drug-target relationships,” Nucleic Acids Research, vol. 36, no. 1, pp. D919–D922, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. X. Chen, Z. L. Ji, and Y. Z. Chen, “TTD: therapeutic target database,” Nucleic Acids Research, vol. 30, no. 1, pp. 412–415, 2002. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Campillos, M. Kuhn, A.-C. Gavin, L. J. Jensen, and P. Bork, “Drug target identification using side-effect similarity,” Science, vol. 321, no. 5886, pp. 263–266, 2008. View at Publisher · View at Google Scholar · View at Scopus
  16. M. Kuhn, M. Campillos, I. Letunic, L. J. Jensen, and P. Bork, “A side effect resource to capture phenotypic effects of drugs,” Molecular Systems Biology, vol. 6, article 343, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. M. Kanehisa, S. Goto, M. Furumichi, M. Tanabe, and M. Hirakawa, “KEGG for representation and analysis of molecular networks involving diseases and drugs,” Nucleic Acids Research, vol. 38, supplement 1, pp. D355–D360, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. C. Li, X. Li, Y. Miao et al., “SubpathwayMiner: a software package for flexible identification of pathways,” Nucleic Acids Research, vol. 37, no. 19, article e131, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. J. Wang, S. Zhang, Y. Wang, L. Chen, and X.-S. Zhang, “Disease-aging network reveals significant roles of aging genes in connecting genetic diseases,” PLoS Computational Biology, vol. 5, no. 9, Article ID e1000521, 12 pages, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. B. Adamcsek, G. Palla, I. J. Farkas, I. Derényi, and T. Vicsek, “CFinder: locating cliques and overlapping modules in biological networks,” Bioinformatics, vol. 22, no. 8, pp. 1021–1023, 2006. View at Publisher · View at Google Scholar · View at Scopus
  21. A. M. Sadowska, P. Specenier, P. Germonpre, and M. Peeters, “Antineoplastic therapy-induced pulmonary toxicity,” Expert Review of Anticancer Therapy, vol. 13, no. 8, pp. 997–1006, 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. A. Colombo, C. A. Meroni, C. M. Cipolla, and D. Cardinale, “Managing cardiotoxicity of chemotherapy,” Current Treatment Options in Cardiovascular Medicine, vol. 15, no. 4, pp. 410–424, 2013. View at Publisher · View at Google Scholar · View at Scopus
  23. Z. Ji, J. Su, C. Liu et al., “Integrating genomics and proteomics data to predict drug effects using binary linear programming,” PLoS ONE, vol. 9, no. 7, Article ID e102798, 2014. View at Publisher · View at Google Scholar
  24. C. Wu, J. Schwartz, and G. Nenadic, “PathNER: a tool for systematic identification of biological pathway mentions in the literature,” BMC Systems Biology, vol. 7, supplement 3, p. S2, 2013. View at Publisher · View at Google Scholar
  25. T. Toyofuku, M. Yabuki, K. Otsu, T. Kuzuya, M. Tada, and M. Hori, “Functional role of c-Src in Gap junctions of the cardiomyopathic heart,” Circulation Research, vol. 85, no. 8, pp. 672–681, 1999. View at Publisher · View at Google Scholar · View at Scopus
  26. T. Seaborn, O. Masmoudi-Kouli, A. Fournier, H. Vaudry, and D. Vaudry, “Protective effects of pituitary adenylate cyclase-activating polypeptide (PACAP) against apoptosis,” Current Pharmaceutical Design, vol. 17, no. 3, pp. 204–214, 2011. View at Publisher · View at Google Scholar · View at Scopus
  27. N. Itoh and H. Ohta, “Pathophysiological roles of FGF signaling in the heart,” Frontiers in Physiology, vol. 4, article 247, 2013. View at Publisher · View at Google Scholar · View at Scopus
  28. P. H. Sugden and A. Clerk, “‘Stress-responsive’ mitogen-activated protein kinases (c-Jun N-terminal kinases and p38 mitogen-activated protein kinases) in the myocardium,” Circulation Research, vol. 83, no. 4, pp. 345–352, 1998. View at Publisher · View at Google Scholar · View at Scopus
  29. M. C. Michel, Y. Li, and G. Heusch, “Mitogen-activated protein kinases in the heart,” Naunyn-Schmiedeberg's Archives of Pharmacology, vol. 363, no. 3, pp. 245–266, 2001. View at Publisher · View at Google Scholar · View at Scopus
  30. B. J. Warn-Cramer, P. D. Lampe, W. E. Kurata et al., “Characterization of the mitogen-activated protein kinase phosphorylation sites on the connexin-43 gap junction protein,” The Journal of Biological Chemistry, vol. 271, no. 7, pp. 3779–3786, 1996. View at Publisher · View at Google Scholar · View at Scopus
  31. A. R. Marks, “Intracellular calcium-release channels: regulators of cell life and death,” American Journal of Physiology: Heart and Circulatory Physiology, vol. 272, no. 2, pp. H597–H605, 1997. View at Google Scholar · View at Scopus
  32. E. G. Brown, “Methods and pitfalls in searching drug safety databases utilising the medical dictionary for regulatory activities (MedDRA),” Drug Safety, vol. 26, no. 3, pp. 145–158, 2003. View at Publisher · View at Google Scholar · View at Scopus
  33. J. Scheiber, J. L. Jenkins, S. C. K. Sukuru et al., “Mapping adverse drug reactions in chemical space,” Journal of Medicinal Chemistry, vol. 52, no. 9, pp. 3103–3107, 2009. View at Publisher · View at Google Scholar · View at Scopus
  34. D. E. Yocum, D. E. Furst, W. G. Bensen et al., “Safety of tacrolimus in patients with rheumatoid arthritis: long-term experience,” Rheumatology, vol. 43, no. 8, pp. 992–999, 2004. View at Publisher · View at Google Scholar
  35. K. S. Song, M. J. Kim, C. S. Jang et al., “Clinical features of acute viral hepatitis A complicated with acute renal failure,” Korean Journal of Hepatology, vol. 13, no. 2, pp. 166–173, 2007. View at Google Scholar · View at Scopus