Table of Contents Author Guidelines Submit a Manuscript
Journal of Biomedicine and Biotechnology
Volume 2010, Article ID 690925, 7 pages
http://dx.doi.org/10.1155/2010/690925
Research Article

Reconstruction of Protein-Protein Interaction Network of Insulin Signaling in Homo Sapiens

Department of Chemical Engineering, Boğaziçi University, 34342 Bebek-İstanbul, Turkey

Received 21 April 2010; Revised 22 July 2010; Accepted 27 October 2010

Academic Editor: Sorin Draghici

Copyright © 2010 Saliha Durmuş Tekir 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. H. Ruffner, A. Bauer, and T. Bouwmeester, “Human protein-protein interaction networks and the value for drug discovery,” Drug Discovery Today, vol. 12, no. 17-18, pp. 709–716, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  2. K. Oda and H. Kitano, “A comprehensive map of the toll-like receptor signaling network,” Molecular Systems Biology, vol. 2, Article ID 2006.0015, 2006. View at Publisher · View at Google Scholar · View at PubMed
  3. K. Oda, Y. Matsuoka, A. Funahashi, and H. Kitano, “A comprehensive pathway map of epidermal growth factor receptor signaling,” Molecular Systems Biology, vol. 1, Article ID 2005.0010, 2005. View at Publisher · View at Google Scholar · View at PubMed
  4. J. A. Papin and B. O. Palsson, “The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis,” Biophysical Journal, vol. 87, no. 1, pp. 37–46, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  5. D. E. Moller, “New drug targets for type 2 diabetes and the metabolic syndrome,” Nature, vol. 414, no. 6865, pp. 821–827, 2001. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  6. B. Cheatham and C. R. Kahn, “Insulin action and the insulin signaling network,” Endocrine Reviews, vol. 16, no. 2, pp. 117–142, 1995. View at Google Scholar · View at Scopus
  7. C. M. Taniguchi, B. Emanuelli, and C. R. Kahn, “Critical nodes in signalling pathways: insights into insulin action,” Nature Reviews, vol. 7, no. 2, pp. 85–96, 2006. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  8. J. Avruch, “Insulin signal transduction through protein kinase cascades,” Molecular and Cellular Biochemistry, vol. 182, no. 1-2, pp. 31–48, 1998. View at Publisher · View at Google Scholar · View at Scopus
  9. A. Avogaro, S. V. de Kreutzenberg, and G. P. Fadini, “Oxidative stress and vascular disease in diabetes: is the dichotomization of insulin signaling still valid?” Free Radical Biology and Medicine, vol. 44, no. 6, pp. 1209–1215, 2008. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  10. Y. H. Chew, Y. L. Shia, C. T. Lee, F. A. A. Majid, L. S. Chua, M. R. Sarmidi, and R. A. Aziz, “Modeling of glucose regulation and insulin signaling pathways,” Molecular and Cellular Endocrinology, vol. 303, no. 1-2, pp. 13–24, 2009. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  11. K. Schmelzle, S. Kane, S. Gridley, G. E. Lienhard, and F. M. White, “Temporal dynamics of tyrosine phosphorylation in insulin signaling,” Diabetes, vol. 55, no. 8, pp. 2171–2179, 2006. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  12. A. R. Sedaghat, A. Sherman, and M. J. Quon, “A mathematical model of metabolic insulin signaling pathways,” American Journal of Physiology, vol. 283, no. 5, pp. E1084–E1101, 2002. View at Google Scholar · View at Scopus
  13. B. Cheatham, C. J. Vlahos, L. Cheatham, L. Wang, J. Blenis, and C. R. Kahn, “Phosphatidylinositol 3-kinase activation is required for insulin stimulation of pp70 S6 kinase, DNA synthesis, and glucose transporter translocation,” Molecular and Cellular Biology, vol. 14, no. 7, pp. 4902–4911, 1994. View at Google Scholar · View at Scopus
  14. C. Stark, B. J. Breitkreutz, T. Reguly, L. Boucher, A. Breitkreutz, and M. Tyers, “BioGRID: a general repository for interaction datasets,” Nucleic Acids Research, vol. 34, pp. D535–539, 2006. View at Google Scholar · View at Scopus
  15. M. Steffen, A. Petti, J. Aach, P. D'haeseleer, and G. Church, “Automated modelling of signal transduction networks,” BMC Bioinformatics, vol. 3, article 34, 2002. View at Publisher · View at Google Scholar
  16. S. Durmuş Tekir, K. Yalçin Arga, and K. O. Ülgen, “Drug targets for tumorigenesis: insights from structural analysis of EGFR signaling network,” Journal of Biomedical Informatics, vol. 42, no. 2, pp. 228–236, 2009. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  17. N. Pržulj, D. A. Wigle, and I. Jurisica, “Functional topology in a network of protein interactions,” Bioinformatics, vol. 20, no. 3, pp. 340–348, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  18. A.-L. Barabási and Z. N. Oltvai, “Network biology: understanding the cell's functional organization,” Nature Reviews Genetics, vol. 5, no. 2, pp. 101–113, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  19. R. Albert, “Scale-free networks in cell biology,” Journal of Cell Science, vol. 118, no. 21, pp. 4947–4957, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  20. C. M. Deane, L. Salwiński, I. Xenarios, and D. Eisenberg, “Protein interactions: two methods for assessment of the reliability of high throughput observations,” Molecular & Cellular Proteomics, vol. 1, no. 5, pp. 349–356, 2002. View at Google Scholar · View at Scopus
  21. E. Sprinzak, S. Sattath, and H. Margalit, “How reliable are experimental protein-protein interaction data?” Journal of Molecular Biology, vol. 327, no. 5, pp. 919–923, 2003. View at Publisher · View at Google Scholar · View at Scopus
  22. C. Von Mering, R. Krause, B. Snel, M. Cornell, S. G. Oliver, S. Fields, and P. Bork, “Comparative assessment of large-scale data sets of protein-protein interactions,” Nature, vol. 417, no. 6887, pp. 399–403, 2002. View at Google Scholar · View at Scopus
  23. K. Y. Arga, Z. I. Önsan, B. Kirdar, K. Ö. Ülgen, and J. Nielsen, “Understanding signaling in yeast: insights from network analysis,” Biotechnology and Bioengineering, vol. 97, no. 5, pp. 1246–1258, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  24. L. J. Lu, Y. Xia, A. Paccanaro, H. Yu, and M. Gerstein, “Assessing the limits of genomic data integration for predicting protein networks,” Genome Research, vol. 15, no. 7, pp. 945–953, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  25. A. Patil and H. Nakamura, “Filtering high-throughput protein-protein interaction data using a combination of genomic features,” BMC Bioinformatics, vol. 6, p. 100, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  26. J. S. Bader, A. Chaudhuri, J. M. Rothberg, and J. Chant, “Gaining confidence in high-throughput protein interaction networks,” Nature Biotechnology, vol. 22, no. 1, pp. 78–85, 2004. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  27. R. Jansen, H. Yu, and H. Yu, “A bayesian networks approach for predicting protein-protein interactions from genomic data,” Science, vol. 302, no. 5644, pp. 449–453, 2003. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  28. A. C. Haugen, R. Kelley, and R. Kelley, “Integrating phenotypic and expression profiles to map arsenic-response networks,” Genome Biology, vol. 5, no. 12, p. R95, 2004. View at Google Scholar · View at Scopus
  29. Y. Liu and H. Zhao, “A computational approach for ordering signal transduction pathway components from genomics and proteomics data,” BMC Bioinformatics, vol. 5, pp. 158–163, 2004. View at Google Scholar
  30. T. J. Begley, A. S. Rosenbach, T. Ideker, and L. D. Samson, “Damage recovery pathways in Saccharomyces cerevisiae revealed by genomic phenotyping and interactome mapping,” Molecular Cancer Research, vol. 1, no. 2, pp. 103–112, 2002. View at Google Scholar · View at Scopus
  31. G. Lomberk and R. Urrutia, “Primers on molecular pathways—the insulin pathway,” Pancreatology, vol. 9, no. 3, pp. 203–205, 2009. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  32. H. K. R. Karlsson and J. R. Zierath, “Insulin signaling and glucose transport in insulin resistant human skeletal muscle,” Cell Biochemistry and Biophysics, vol. 48, no. 2-3, pp. 103–113, 2007. View at Publisher · View at Google Scholar · View at Scopus
  33. J. M. Lizcano and D. R. Alessi, “The insulin signalling pathway,” Current Biology, vol. 12, no. 7, pp. R236–R238, 2002. View at Publisher · View at Google Scholar · View at Scopus
  34. M. Holgado-Madruga, D. R. Emlet, D. K. Moscatello, A. K. Godwin, and A. J. Wong, “A Grb2-associated docking protein in EGF- and insulin-receptor signalling,” Nature, vol. 379, no. 6565, pp. 560–564, 1996. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  35. M. G. Myers Jr. and M. F. White, “The new elements of insulin signaling: insulin receptor substrate-1 and proteins with SH2 domains,” Diabetes, vol. 42, no. 5, pp. 643–650, 1993. View at Google Scholar · View at Scopus
  36. M. Langeveld and J. M. F. G. Aerts, “Glycosphingolipids and insulin resistance,” Progress in Lipid Research, vol. 48, no. 3-4, pp. 196–205, 2009. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  37. J. A. Papin, T. Hunter, B. O. Palsson, and S. Subramaniam, “Reconstruction of cellular signalling networks and analysis of their properties,” Nature Reviews Molecular Cell Biology, vol. 6, no. 2, pp. 99–111, 2005. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  38. H. Yu, P. M. Kim, E. Sprecher, V. Trifonov, and M. Gerstein, “The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics,” PLoS Computational Biology, vol. 3, no. 4, pp. 713–720, 2007. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  39. X. R. Wu, Y. Zhu, and Y. Li, “Analyzing protein interaction networks via random graph model,” International Journal of Information Technology, vol. 11, no. 2, pp. 125–132, 2005. View at Google Scholar
  40. S. H. Yook, Z. N. Oltvai, and A. L. Barabasi, “Functional and topological characterization of protein interaction networks,” Proteomics, vol. 4, pp. 928–942, 2004. View at Google Scholar
  41. V. S. Lalioti, S. Vergarajauregui, D. Pulido, and I. V. Sandoval, “The insulin-sensitive glucose transporter, GLUT4, interacts physically with Daxx. Two proteins with capacity to bind Ubc9 and conjugated to SUMO1,” Journal of Biological Chemistry, vol. 277, no. 22, pp. 19783–19791, 2002. View at Publisher · View at Google Scholar · View at PubMed
  42. V. S. Lalioti, S. Vergarajauregui, Y. Tsuchiya, S. Hernandez-Tiedra, and I. V. Sandoval, “Daxx functions as a scaffold of a protein assembly constituted by GLUT4, JNK1 and KIF5B,” Journal of Cellular Physiology, vol. 218, no. 2, pp. 416–426, 2009. View at Publisher · View at Google Scholar · View at PubMed
  43. S. Maslov and K. Sneppen, “Specificity and stability in topology of protein networks,” Science, vol. 296, no. 5569, pp. 910–913, 2002. View at Publisher · View at Google Scholar · View at PubMed
  44. H. Jeong, S. P. Mason, A.-L. Barabási, and Z. N. Oltvai, “Lethality and centrality in protein networks,” Nature, vol. 411, no. 6833, pp. 41–42, 2001. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  45. A. Wagner and D. A. Fell, “The small world inside large metabolic networks,” Proceedings of the Royal Society B, vol. 268, no. 1478, pp. 1803–1810, 2001. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  46. H. Jeong, B. Tombor, R. Albert, Z. N. Oltval, and A.-L. Barabásl, “The large-scale organization of metabolic networks,” Nature, vol. 407, no. 6804, pp. 651–654, 2000. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  47. D. J. Watts and S. H. Strogatz, “Collective dynamics of ‘small-world’ networks,” Nature, vol. 393, no. 6684, pp. 440–442, 1998. View at Google Scholar · View at Scopus
  48. S. L. McGee, B. J. W. Van Denderen, K. F. Howlett, J. Mollica, J. D. Schertzer, B. E. Kemp, and M. Hargreaves, “AMP-activated protein kinase regulates GLUT4 transcription by phosphorylating histone deacetylase 5,” Diabetes, vol. 57, no. 4, pp. 860–867, 2008. View at Publisher · View at Google Scholar · View at PubMed · View at Scopus
  49. F. Schwartzenberg-Bar-Yoseph, M. Armoni, and E. Karnieli, “The tumor suppressor p53 down-regulates glucose transporters GLUT1 and GLUT4 gene expression,” Cancer Research, vol. 64, no. 7, pp. 2627–2633, 2004. View at Publisher · View at Google Scholar · View at Scopus
  50. C. A. Heinlein and C. Chang, “The roles of androgen receptors and androgen-binding proteins in nongenomic androgen actions,” Molecular Endocrinology, vol. 16, no. 10, pp. 2181–2187, 2002. View at Publisher · View at Google Scholar · View at Scopus