RegPhos 2.0: An updated resource to explore protein kinase-substrate phosphorylation networks in mammals

Database

Volumn 2014, Issue , 2014, Pages

  Huang, Kai Yao ^a   Wu, Hsin Yi ^b   Chen, Yi Ju ^b   Lu, Cheng Tsung ^a   Su, Min Gang ^a   Hsieh, Yun Chung ^a   Tsai, Chih Ming ^c   Lin, Kuo I ^c   Huang, Hsien Da ^d   Lee, Tzong Yi ^a   Chen, Yu Ju ^b  

^a YUAN ZE UNIVERSITY   (Taiwan)

^b INSTITUTE OF CHEMISTRY   (Taiwan)

^c GENOMICS RESEARCH CENTER   (Taiwan)

^d NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

PHOSPHOPROTEIN; PROTEIN KINASE;

ARTICLE; CHEMISTRY; GENE EXPRESSION PROFILING; HUMAN; METABOLISM; METHODOLOGY; PHOSPHORYLATION; PROTEIN ANALYSIS; PROTEIN DATABASE; SIGNAL TRANSDUCTION;

DATABASES, PROTEIN; GENE EXPRESSION PROFILING; HUMANS; PHOSPHOPROTEINS; PHOSPHORYLATION; PROTEIN INTERACTION MAPPING; PROTEIN KINASES; SIGNAL TRANSDUCTION;

EID: 84908092742     PISSN: 17580463     EISSN: None     Source Type: Journal    
DOI: 10.1093/database/bau034     Document Type: Article

References (72)

1. Fischer, E.H. (1997) Cellular regulation by protein phosphorylation: a historical overview. Biofactors, 6, 367-374.
2. Marshall, C.J. (1994) Signal transduction. Hot lips and phosphorylation of protein kinases. Nature, 367, 686.
3. Steffen, M., Petti, A., Aach, J. et al. (2002) Automated modelling of signal transduction networks. BMC Bioinformatics, 3, 34.
4. Hubbard, M.J. and Cohen, P. (1993) On target with a new mechanism for the regulation of protein phosphorylation. Trends Biochem. Sci., 18, 172-177.
5. Diella, F., Cameron, S., Gemund, C. et al. (2004) Phospho.ELM: a database of experimentally verified phosphorylation sites in eukaryotic proteins. BMC Bioinformatics, 5, 79.
6. Hornbeck, P.V., Kornhauser, J.M., Tkachev, S. et al. (2012) PhosphoSitePlus: a comprehensive resource for investigating the structure and function of experimentally determined post-translational modifications in man and mouse. Nucleic Acids Res., 40, D261-D270.
7. Wurgler-Murphy, S.M., King, D.M. and Kennelly, P.J. (2004) The Phosphorylation Site Database: a guide to the serine-, threonine-, and/or tyrosine-phosphorylated proteins in prokaryotic organisms. Proteomics, 4, 1562-1570.
8. Gnad, F., Ren, S., Cox, J. et al. (2007) PHOSIDA (phosphorylation site database): management, structural and evolutionary investigation, and prediction of phosphosites. Genome Biol., 8, R250.
9. Heazlewood, J.L., Durek, P., Hummel, J. et al. (2008) PhosPhAt: a database of phosphorylation sites in Arabidopsis thaliana and a plant-specific phosphorylation site predictor. Nucleic Acids Res., 36, D1015-D1021.
10. Stark, C., Su, T.C., Breitkreutz, A. et al. (2010) PhosphoGRID: a database of experimentally verified in vivo protein phosphorylation sites from the budding yeast Saccharomyces cerevisiae. Database (Oxford), 2010, bap026.
11. Zanzoni, A., Carbajo, D., Diella, F. et al. (2011) Phospho3D 2.0: an enhanced database of three-dimensional structures of phosphorylation sites. Nucleic Acids Res., 39, D268-D271.
12. Yang, C.Y., Chang, C.H., Yu, Y.L. et al. (2008) PhosphoPOINT: a comprehensive human kinase interactome and phospho-protein database. Bioinformatics, 24, i14-i20.
13. Zhou, F., Xue, Y., Yao, X. et al. (2006) A general user interface for prediction servers of proteins' post-translational modification sites. Nat. Protoc., 1, 1318-1321.
14. Su, M.G. and Lee, T.Y. (2013) Incorporating substrate sequence motifs and spatial amino acid composition to identify kinase-specific phosphorylation sites on protein three-dimensional structures. BMC Bioinformatics, 14, S2.
15. Bretana, N.A., Lu, C.T., Chiang, C.Y. et al. (2012) Identifying protein phosphorylation sites with kinase substrate specificity on human viruses. PLoS One, 7, e40694.
16. Lee, T.Y., Bretana, A. and Lu, C.T. (2011) PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity. BMC Bioinformatics, 12, 261.
17. Wong, Y.H., Lee, T.Y., Liang, H.K. et al. (2007) KinasePhos 2.0: a web server for identifying protein kinase-specific phosphorylation sites based on sequences and coupling patterns. Nucleic Acids Res., 35, W588-W594.
18. Huang, H.D., Lee, T.Y., Tzeng, S.W. et al. (2005) Incorporating hidden Markov models for identifying protein kinase-specific phosphorylation sites. J. Comput. Chem., 26, 1032-1041.
19. Huang, H.D., Lee, T.Y., Tzeng, S.W. et al. (2005) KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites. Nucleic Acids Res., 33, W226-W229.
20. Manning, G., Whyte, D.B., Martinez, R. et al. (2002) The protein kinase complement of the human genome. Science, 298, 1912-1934.
21. Neves, S.R. and Iyengar, R. (2002) Modeling of signaling networks. Bioessays, 24, 1110-1117.
22. Choi, C., Crass, T., Kel, A. et al. (2004) Consistent re-modeling of signaling pathways and its implementation in the TRANSPATH database. Genome Inform., 15, 244-254.
23. Sachs, K., Perez, O., Pe'er, D. et al. (2005) Causal protein-signaling networks derived from multiparameter single-cell data. Science, 308, 523-529.
24. Bebek, G. and Yang, J. (2007) PathFinder: mining signal transduction pathway segments from protein-protein interaction networks. BMC Bioinformatics, 8, 335.
25. Eungdamrong, N.J. and Iyengar, R. (2004) Modeling cell signaling networks. Biol. Cell, 96, 355-362.
26. Janes, K.A. and Yaffe, M.B. (2006) Data-driven modelling of signal-transduction networks. Nat. Rev. Mol. Cell. Biol., 7, 820-828.
27. Wang, L., Hou, L., Qian, M. et al. (2012) Integrating phosphorylation network with transcriptional network reveals novel functional relationships. PLoS One, 7, e33160.
28. Newman, R.H., Hu, J., Rho, H.S. et al. (2013) Construction of human activity-based phosphorylation networks. Mol. Syst. Biol., 9, 655.
29. Aebersold, R. and Mann, M. (2003) Mass spectrometry-based proteomics. Nature, 422, 198-207.
30. Lee, T.Y., Bo-Kai Hsu, J., Chang, W.C. et al. (2011) RegPhos: a system to explore the protein kinase-substrate phosphorylation network in humans. Nucleic Acids Res., 39, D777-D787.
31. de Castro, R.O. (2011) Regulation and function of syk tyrosine kinase in mast cell signaling and beyond. J. Signal Transduct, 2011, 507291.
32. Kurosaki, T., Shinohara, H. and Baba, Y. (2010) B cell signaling and fate decision. Annu. Rev. Immunol., 28, 21-55.
33. Lee, T.Y., Huang, H.D., Hung, J.H. et al. (2006) dbPTM: an information repository of protein post-translational modification. Nucleic Acids Res., 34, D622-D627.
34. Lu, C.T., Huang, K.Y., Su, M.G. et al. (2013) DbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications. Nucleic Acids Res., 41, D295-D305.
35. Gnad, F., Gunawardena, J. and Mann, M. (2011) PHOSIDA 2011: the posttranslational modification database. Nucleic Acids Res., 39, D253-D260.
36. Li, H., Xing, X., Ding, G. et al. (2009) SysPTM: a systematic resource for proteomic research on post-translational modifications. Mol. Cell Proteomics, 8, 1839-1849.
37. Mishra, G.R., Suresh, M., Kumaran, K. et al. (2006) Human protein reference database - 2006 update. Nucleic Acids Res., 34, D411-D414.
38. Farriol-Mathis, N., Garavelli, J.S., Boeckmann, B. et al. (2004) Annotation of post-translational modifications in the Swiss-Prot knowledge base. Proteomics, 4, 1537-1550.
39. Hu, Z.Z., Narayanaswamy, M., Ravikumar, K.E. et al. (2005) Literature mining and database annotation of protein phosphorylation using a rule-based system. Bioinformatics, 21, 2759-2765.
40. Caenepeel, S., Charydczak, G., Sudarsanam, S. et al. (2004) The mouse kinome: discovery and comparative genomics of all mouse protein kinases. Proc. Natl Acad. Sci. USA, 101, 11707-11712.
41. Kohl, M., Wiese, S. and Warscheid, B. (2010) Cytoscape: software for visualization and analysis of biological networks. Methods Mol. Biol., 696, 291-303.
42. Ogata, H., Goto, S., Sato, K. et al. (1999) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res., 27, 29-34.
43. von Mering, C., Huynen, M., Jaeggi, D. et al. (2003) STRING: a database of predicted functional associations between proteins. Nucleic Acids Res., 31, 258-261.
44. Olsen, J.V., Blagoev, B., Gnad, F. et al. (2006) Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. Cell, 127, 635-648.
45. Cao, L., Yu, K., Banh, C. et al. (2007) Quantitative time-resolved phosphoproteomic analysis of mast cell signaling. J. Immunol., 179, 5864-5876.
46. Nguyen, V., Cao, L., Lin, J.T. et al. (2009) A new approach for quantitative phosphoproteomic dissection of signaling pathways applied to T cell receptor activation. Mol. Cell Proteomics, 8, 2418-2431.
47. Kampen, K.R. (2011) Membrane proteins: the key players of a cancer cell. J. Membr. Biol., 242, 69-74.
48. Kanehisa, M., Goto, S., Furumichi, M. et al. (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res., 38, D355-D360.
49. Huang, W.C., Lin, F.M., Chang, T.H. et al. (2012) Identifying cancer highly-expressed membrane receptors for targeted drug delivery. Int. J. Bioinform. Res. Appl., 8, 192-209.
50. Barrett, T., Troup, D.B., Wilhite, S.E. et al. (2007) NCBI GEO: mining tens of millions of expression profiles-database and tools update. Nucleic Acids Res., 35, D760-D765.
51. Hochreiter, S., Clevert, D.A. and Obermayer, K. (2006) A new summarization method for Affymetrix probe level data. Bioinformatics, 22, 943-949.
52. Pierleoni, A., Martelli, P.L., Fariselli, P. et al. (2006) BaCelLo: a balanced subcellular localization predictor. Bioinformatics, 22, e408-e416.
53. Kasahara, K., Nakayama, Y., Ikeda, K. et al. (2004) Trafficking of Lyn through the Golgi caveolin involves the charged residues on alphaE and alphaI helices in the kinase domain. J. Cell. Biol., 165, 641-652.
54. Miyazaki, T., Neff, L., Tanaka, S. et al. (2003) Regulation of cytochrome c oxidase activity by c-Src in osteoclasts. J. Cell. Biol., 160, 709-718.
55. Guil, S., de La Iglesia, N., Fernandez-Larrea, J. et al. (2003) Alternative splicing of the human proto-oncogene c-H-ras renders a new Ras family protein that trafficks to cytoplasm and nucleus. Cancer Res., 63, 5178-5187.
56. Zhou, F., Hu, J., Ma, H. et al. (2006) Nucleocytoplasmic trafficking of the Syk protein tyrosine kinase. Mol. Cell. Biol., 26, 3478-3491.
57. Wu, X., Carr, H.S., Dan, I. et al. (2008) p21 activated kinase 5 activates Raf-1 and targets it to mitochondria. J. Cell. Biochem., 105, 167-175.
58. Byrd, D.A., Sweet, D.J., Pante, N. et al. (1994) Tpr, a large coiled coil protein whose amino terminus is involved in activation of oncogenic kinases, is localized to the cytoplasmic surface of the nuclear pore complex. J. Cell. Biol., 127, 1515-1526.
59. Portal, M.M., Ferrero, G.O. and Caputto, B.L. (2007) N-Terminal c-Fos tyrosine phosphorylation regulates c-Fos/ER association and c-Fos-dependent phospholipid synthesis activation. Oncogene, 26, 3551-3558.
60. Melander, F., Andersson, T. and Dib, K. (2003) Fgr but not Syk tyrosine kinase is a target for beta 2 integrin-induced c-Cbl-mediated ubiquitination in adherent human neutrophils. Biochem. J., 370, 687-694.
61. Xue, L., Wang, W.H., Iliuk, A. et al. (2012) Sensitive kinase assay linked with phosphoproteomics for identifying direct kinase substrates. Proc. Natl Acad. Sci. USA, 109, 5615-5620.
62. Cheung, R., Malik, M., Ravyn, V. et al. (2009) An arrestin-dependent multi-kinase signaling complex mediates MIP-1beta/CCL4 signaling and chemotaxis of primary human macrophages. J. Leukoc. Biol., 86, 833-845.
63. Titz, B., Low, T., Komisopoulou, E. et al. (2010) The proximal signaling network of the BCR-ABL1 oncogene shows a modular organization. Oncogene, 29, 5895-5910.
64. Sattler, M., Salgia, R., Shrikhande, G. et al. (1997) The phosphatidylinositol polyphosphate 5-phosphatase SHIP and the protein tyrosine phosphatase SHP-2 form a complex in hematopoietic cells which can be regulated by BCR/ABL and growth factors. Oncogene, 15, 2379-2384.
65. Marshall, A.J., Niiro, H., Lerner, C.G. et al. (2000) A novel B lymphocyte-associated adaptor protein, Bam32, regulates antigen receptor signaling downstream of phosphatidylinositol 3-kinase. J. Exp. Med., 191, 1319-1332.
66. Yang, T.T., Xiong, Q., Enslen, H. et al. (2002) Phosphorylation of NFATc4 by p38 mitogen-activated protein kinases. Mol. Cell. Biol., 22, 3892-3904.
67. Hinohara, K., Kobayashi, S., Kanauchi, H. et al. (2012) ErbB receptor tyrosine kinase/NF-kappaB signaling controls mammosphere formation in human breast cancer. Proc. Natl Acad. Sci. USA, 109, 6584-6589.
68. Booy, E.P., Henson, E.S. and Gibson, S.B. (2011) Epidermal growth factor regulates Mcl-1 expression through the MAPK-Elk-1 signalling pathway contributing to cell survival in breast cancer. Oncogene, 30, 2367-2378.
69. Jost, M., Huggett, T.M., Kari, C. et al. (2001) Matrix-independent survival of human keratinocytes through an EGF receptor/MAPK-kinase-dependent pathway. Mol. Biol. Cell, 12, 1519-1527.
70. Shawarby, M.A., Al-Tamimi, D.M. and Ahmed, A. (2011) Very low prevalence of epidermal growth factor receptor (EGFR) protein expression and gene amplification in Saudi breast cancer patients. Diagn. Pathol., 6, 57.
71. Liu, D., He, J., Yuan, Z. et al. (2011) EGFR expression correlates with decreased disease-free survival in triple-negative breast cancer: a retrospective analysis based on a tissue microarray. Med. Oncol., 29, 401-405.
72. Durek, P., Schudoma, C., Weckwerth, W. et al. (2009) Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins. BMC Bioinformatics, 10, 117.