臺灣博碩士論文加值系統

泛素結合作用是真核生物中相當重要的基礎機轉，主要與蛋白酶體降解相關。像是，透過該作用能夠調控細胞中多種的生物機制。近年來，有大量研究與泛素化作用發生位置相關；然而，大多數的計算方法及預測工具皆基於小規模資料來發展。由於泛素化作用位置之實驗資料數量與日俱增。在此契機下，有機會透過生物資訊技術來分析大規模泛素化作用實驗驗證資料，發展泛素化作用位置之預測模型。因此，我們提出利用疊代統計方法來辨認泛素化作用發生位置，探索該位置周圍是否具有序列特徵。除此之外，為了提供對於泛素化蛋白質體學有興趣的研究人員，更具生物意義上的協助，該方法同時於線上實現自動化分析「UbiSite」，免費提供服務http://csb.cse.yzu.edu.tw/UbiSite/。
另外，E3連接酶（E3Ligases）具有辨認特定泛素化受質之特性，以及催化泛素連接至受質之特定位置上。於是，調查E3連接酶與泛素化受質間的網路，逐漸成為一個熱門的研究題目。截至目前，尚缺乏旨在探索E3連接酶與泛素化蛋白間調控網路的方法及工具。因此，本研究將基於機器學習學與圖論學，提出一個整合實驗驗證泛素化蛋白、E3連接酶及蛋白質相互作用等資料之方法，來嘗試解決上述問題。「UbiNet」一個全面性的線上資源，將有效地探索蛋白質泛素化調控網路和提供相關泛素化蛋白質體資訊。目前UbiNet收錄：499個實驗驗證E3轉移酶、43948個實驗驗證泛素化位置，來自14692個人類泛素化蛋白質和41889筆蛋白質交互作用等資料，以及其他相關資訊用以建構泛素化調控網路，該服務已免費提供於http://csb.cse.yzu.edu.tw/UbiNet/.

In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. The recent advancements in proteomics technology have stimulated an increasing amount of interest in identifying ubiquitin-conjugation sites. However, at the moment, most methods and computational prediction tools for ubiquitin-conjugation sites are focused on small-scale data. As more and more experimental data on ubiquitin conjugatation sites become available, it becomes possible to develop prediction models that can be scaled to big data. Therefore, we propose an approach that exploits an iteratively statistical method to identify ubiquitin conjugation sites with substrate site specificities. Moreover, in order to provide meaningful assistance to researchers interested in large-scale proteome data, the proposed models have been implemented into a web-based system (UbiSite), which is freely available at http://csb.cse.yzu.edu.tw/UbiSite/.
In addition, due to the very important roles of E3 ligases by recognizing specific protein substrate and catalyzing the attachment of ubiquitin to the target protein, the investigation of the networks of E3 ligases and ubiquitinated substrate proteins is emerging as a hot topic. However, there is a lack of methods proposed and tools designed to explore the regulatory networks of E3 ligases for ubiquitinated proteins. Therefore, in this work, we propose a method which applies support vector machine, graph theory and integrates all available ubiquitinome datasets, experimentally verified E3 ligases, and protein-protein interactions. Besides, UbiNet, a comprehensive web-resource is implemented to efficiently explore and provide a full investigation of protein ubiquitination networks. The current database of UbiNet contains: 499 experimentally verified E3 ligases, 43948 experimentally verified ubiquitination sites from 14692 ubiquitinated proteins of humans, and 41889 protein-protein interactions, and various relative information supporting for the exploring ubiquitination networks. The UbiNet is now freely accessible via http://csb.cse.yzu.edu.tw/UbiNet/.

Table of Contents

List of Tables ii
List of Figures ii
Chapter 1 Introduction 2
1.1 Background 2
1.1.1 Protein Post-Translational Modifications (PTMs) 2
1.1.2 Ubiquitin and ubiquitination 2
1.1.3 Ubiquitin-proteasome system 2
1.1.4 Ubiquitin conjugation cascade 2
1.1.5 Families of E3 ubiquitin ligases 2
1.2 Motivation 2
1.3 Scope of the work 2
1.4 Organization of the dissertation 2
Chapter 2 Identification of protein ubiquitination sites 2
2.1 Characteristic and significance of protein ubiquitination sites identification 2
2.2 Material preparation and Approaches 2
2.2.1 Data collection and pre-processing 2
2.2.2 Feature extraction and coding 2
2.2.3 Maximal dependence decomposition 2
2.2.4 Model training and Evaluation 2
2.2.5 Web-tool implementation 2
2.3 Performance assessment and results 2
2.3.1 Single features in identifying Ubi-sites 2
2.3.2 Hybrid features in identifying Ubi-sites 2
2.3.3 Independent testing performance 2
2.3.4 Identification of substrate motifs by maximal dependence decomposition 2
2.3.5 Maximal dependence decomposition in improving performance 2
2.4 Web-based system for the prediction of protein ubiquitination sites 2
2.4.1 Functionalities and interface of the web-based system 2
2.4.2 Case study 2
2.5 Discussions 2
2.5.1 Characteristics 2
2.5.2 Benchmark dataset for protein ubiquitination sites prediction 2
2.5.3 Comparison of UbiSite-predictor with other prediction tools 2
2.5.4 Time complexity problem 2
Chapter 3 Functional roles and substrate specificities of E3 ligases 2
3.1 Preliminaries 2
3.2 HECT-type E3 ligase 2
3.3 RING-type E3 ligases 2
3.4 Investigation on functional roles and association of E3 ligases 2
3.4.1 E3 ligase in the regulation of p53 2
3.4.2 E3 ligase in angiogenesis 2
3.4.3 E3 ligase in the intrinsic apoptosis pathway 2
3.4.4 E3 ligase in the cell cycle 2
3.5 Domain analysis of E3 ligase 2
3. 6 Discovery of E3-substrate specificities motifs 2
Chapter 4 Discovery of protein ubiquitination regulatory networks 2
4.1 Significance and motivation of the work 2
4.2 Data construction and investigated methods 2
4.2.1 Data collection for E1 activating, E2 conjugating, and E3 ligating enzymes 2
4.2.2 Protein-protein and domain-domain interaction 2
4.2.3 E3-Associated functional categories 2
4.3 Analysis and Simulation results 2
4.3.1 Reconstruction of E3-substrate regulatory networks and Framework implementation of web-based system of UbiNet 2
4.3.2 Relationships of ubiquitinated proteins, E3 ubiquitin ligases, and Interacting proteins 2
4.3.3 Domain analysis of ubiquitinated proteins 2
4.3.4 Domain-domain interaction between E3 ligases and Ubi-substrate proteins 2
4.3.5 Functional investigation of E3 ligases through the E3-substrate regulatory networks 2
4.3.6 Web-based system of UbiNet 2
4.4 Discussions 2
4.4.1 Relationships between E3 ligases and ubiquitinated substrate proteins 2
4.4.2 Functional investigation of E3-ubiquitinated substrate proteins regulatory networks 2
Chapter 5 Conclusion 2
5.1 Contributions 2
5.1.1 Substrate specificity of ubiquitination sites 2
5.1.2 Protein ubiquitination sites prediction 2
5.1.3 Reconstruction of E3 ligase regulatory networks 2
5.2 Limitations 2
5.3 Future Directions 2
5.3.1 Toward more accurate prediction of ubiquitination sites on large-scale data and scalable to the big-data 2
5.3.2 Investigation of protein ubiquitination regulatory networks 2
References 2

1. Grotenbreg, G. and H. Ploegh, Chemical biology - Dressed-up proteins. Nature, 2007. 446(7139): p. 993-995.
2. Geiss-Friedlander, R. and F. Melchior, Concepts in sumoylation: a decade on. Nature Reviews Molecular Cell Biology, 2007. 8(12): p. 947-956.
3. Goldstein, G., et al., Isolation of a polypeptide that has lymphocyte-differentiating properties and is probably represented universally in living cells. Proc Natl Acad Sci U S A, 1975. 72(1): p. 11-5.
4. Wilkinson, K.D., The discovery of ubiquitin-dependent proteolysis. Proc Natl Acad Sci U S A, 2005. 102(43): p. 15280-2.
5. Dye, B.T. and B.A. Schulman, Structural mechanisms underlying posttranslational modification by ubiquitin-like proteins. Annual Review of Biophysics and Biomolecular Structure, 2007. 36: p. 131-150.
6. Komander, D. and M. Rape, The Ubiquitin Code. Annual Review of Biochemistry, Vol 81, 2012. 81: p. 203-229.
7. Pickart, C.M. and M.J. Eddins, Ubiquitin: structures, functions, mechanisms. Biochimica Et Biophysica Acta-Molecular Cell Research, 2004. 1695(1-3): p. 55-72.
8. Welchman, R.L., C. Gordon, and R.J. Mayer, Ubiquitin and ubiquitin-like proteins as multifunctional signals. Nat Rev Mol Cell Biol, 2005. 6(8): p. 599-609.
9. Tokunaga, F., et al., Involvement of linear polyubiquitylation of NEMO in NF-kappaB activation. Nat Cell Biol, 2009. 11(2): p. 123-32.
10. Scaglione, K.M., et al., The ubiquitin-conjugating enzyme (E2) Ube2w ubiquitinates the N terminus of substrates. J Biol Chem, 2013. 288(26): p. 18784-8.
11. Tatham, M.H., et al., Ube2W conjugates ubiquitin to alpha-amino groups of protein N-termini. Biochem J, 2013. 453(1): p. 137-45.
12. Burger, A.M. and A.K. Seth, The ubiquitin-mediated protein degradation pathway in cancer: therapeutic implications. European Journal of Cancer, 2004. 40(15): p. 2217-2229.
13. Hershko, A. and A. Ciechanover, The ubiquitin system. Annual Review of Biochemistry, 1998. 67: p. 425-479.
14. Hurley, J.H., S. Lee, and G. Prag, Ubiquitin-binding domains. Biochemical Journal, 2006. 399: p. 361-372.
15. Hicke, L., H.L. Schubert, and C.P. Hill, Ubiquitin-binding domains. Nature Reviews Molecular Cell Biology, 2005. 6(8): p. 610-621.
16. Peng, J.M., et al., A proteomics approach to understanding protein ubiquitination. Nature Biotechnology, 2003. 21(8): p. 921-926.
17. Metzger, M.B., V.A. Hristova, and A.M. Weissman, HECT and RING finger families of E3 ubiquitin ligases at a glance. Journal of Cell Science, 2012. 125(3): p. 531-537.
18. Lee, T.Y., et al., Incorporating Distant Sequence Features and Radial Basis Function Networks to Identify Ubiquitin Conjugation Sites. Plos One, 2011. 6(3).
19. Gilon, T., O. Chomsky, and R.G. Kulka, Degradation signals for ubiquitin system proteolysis in Saccharomyces cerevisiae. EMBO J, 1998. 17(10): p. 2759-66.
20. Berndsen, C.E. and C. Wolberger, New insights into ubiquitin E3 ligase mechanism. Nature Structural &; Molecular Biology, 2014. 21(4): p. 301-307.
21. Robinson, P.A. and H.C. Ardley, Ubiquitin-protein ligases - Novel therapeutic targets? Current Protein &; Peptide Science, 2004. 5(3): p. 163-176.
22. Robinson, P.A. and H.C. Ardley, Ubiquitin-protein ligases. Journal of Cell Science, 2004. 117(22): p. 5191-5194.
23. Snoek, B.C., et al., Role of E3 ubiquitin ligases in lung cancer. World J Clin Oncol, 2013. 4(3): p. 58-69.
24. Downes, B.P., et al., The HECT ubiquitin-protein ligase (UPL) family in Arabidopsis: UPL3 has a specific role in trichome development. Plant Journal, 2003. 35(6): p. 729-742.
25. Bernassola, F., et al., The HECT family of E3 ubiquitin ligases: Multiple players in cancer development. Cancer Cell, 2008. 14(1): p. 10-21.
26. Scheffner, M. and O. Staub, HECT E3s and human disease. Bmc Biochemistry, 2007. 8.
27. Thrower, J.S., et al., Recognition of the polyubiquitin proteolytic signal. Embo Journal, 2000. 19(1): p. 94-102.
28. Tanaka, K., The proteasome: Overview of structure and functions. Proceedings of the Japan Academy Series B-Physical and Biological Sciences, 2009. 85(1): p. 12-36.
29. Ventii, K.H. and K.D. Wilkinson, Protein partners of deubiquitinating enzymes. Biochem J, 2008. 414(2): p. 161-75.
30. Komander, D., M.J. Clague, and S. Urbe, Breaking the chains: structure and function of the deubiquitinases. Nature Reviews Molecular Cell Biology, 2009. 10(8): p. 550-563.
31. Morris, J.R. and E. Solomon, BRCA1 : BARD1 induces the formation of conjugated ubiquitin structures, dependent on K6 of ubiquitin, in cells during DNA replication and repair. Hum Mol Genet, 2004. 13(8): p. 807-17.
32. Leverson, J.D., et al., The APC11 RING-H2 finger mediates E2-dependent ubiquitination. Mol Biol Cell, 2000. 11(7): p. 2315-25.
33. Torii, K.U., et al., The RING finger motif of photomorphogenic repressor COP1 specifically interacts with the RING-H2 motif of a novel Arabidopsis protein. J Biol Chem, 1999. 274(39): p. 27674-81.
34. Xie, Q., et al., SINAT5 promotes ubiquitin-related degradation of NAC1 to attenuate auxin signals. Nature, 2002. 419(6903): p. 167-70.
35. Xu, G.Q., J.S. Paige, and S.R. Jaffrey, Global analysis of lysine ubiquitination by ubiquitin remnant immunoaffinity profiling. Nature Biotechnology, 2010. 28(8): p. 868-U154.
36. Li, W., et al., Genome-Wide and Functional Annotation of Human E3 Ubiquitin Ligases Identifies MULAN, a Mitochondrial E3 that Regulates the Organelle's Dynamics and Signaling. Plos One, 2008. 3(1).
37. Kraft, E., et al., Genome analysis and functional characterization of the E2 and RING-type E3 ligase ubiquitination enzymes of Arabidopsis. Plant Physiol, 2005. 139(4): p. 1597-611.
38. Smalle, J. and R.D. Vierstra, The ubiquitin 26S proteasome proteolytic pathway. Annual Review of Plant Biology, 2004. 55: p. 555-590.
39. Petroski, M.D., The ubiquitin system, disease, and drug discovery. Bmc Biochemistry, 2008. 9.
40. Ye, Y., et al., Ubiquitin chain conformation regulates recognition and activity of interacting proteins. Nature, 2012. 492(7428): p. 266-270.
41. Kim, W., et al., Systematic and Quantitative Assessment of the Ubiquitin-Modified Proteome. Molecular Cell, 2011. 44(2): p. 325-340.
42. Devoto, A., P.R. Muskett, and K. Shirasu, Role of ubiquitination in the regulation of plant defence against pathogens. Current Opinion in Plant Biology, 2003. 6(4): p. 307-311.
43. Gao, M. and M. Karin, Regulating the regulators: Control of protein ubiquitination and ubiquitin-like modifications by extracellular stimuli. Molecular Cell, 2005. 19(5): p. 581-593.
44. Wagner, S.A., et al., A proteome-wide, quantitative survey of in vivo ubiquitylation sites reveals widespread regulatory roles. Mol Cell Proteomics, 2011. 10(10): p. M111 013284.
45. Oshikawa, K., et al., Proteome-wide Identification of Ubiquitylation Sites by Conjugation of Engineered Lysine-less Ubiquitin. Journal of Proteome Research, 2012. 11(2): p. 796-807.
46. Hochstrasser, M., Origin and function of ubiquitin-like proteins. Nature, 2009. 458(7237): p. 422-429.
47. Cano, F. and P.J. Lehner, A novel post-transcriptional role for ubiquitin in the differential regulation of MHC class I allotypes. Molecular Immunology, 2013. 55(2): p. 135-138.
48. Kim, D.S. and Y. Hahn, Gains of ubiquitylation sites in highly conserved proteins in the human lineage. BMC Bioinformatics, 2012. 13: p. 306.
49. Chen, Z., et al., Towards more accurate prediction of ubiquitination sites: a comprehensive review of current methods, tools and features. Brief Bioinform, 2014.
50. Tung, C.W. and S.Y. Ho, Computational identification of ubiquitylation sites from protein sequences. BMC Bioinformatics, 2008. 9: p. 310.
51. Radivojac, P., et al., Identification, analysis, and prediction of protein ubiquitination sites. Proteins, 2010. 78(2): p. 365-80.
52. Zhao, X.W., et al., Prediction of Lysine Ubiquitylation with Ensemble Classifier and Feature Selection. International Journal of Molecular Sciences, 2011. 12(12): p. 8347-8361.
53. Cai, Y.D., et al., Prediction of lysine ubiquitination with mRMR feature selection and analysis. Amino Acids, 2012. 42(4): p. 1387-1395.
54. Feng, K.Y., et al., Using WPNNA Classifier in Ubiquitination Site Prediction Based on Hybrid Features. Protein and Peptide Letters, 2013. 20(3): p. 318-323.
55. Chen, Z., et al., Prediction of Ubiquitination Sites by Using the Composition of k-Spaced Amino Acid Pairs. Plos One, 2011. 6(7).
56. Chen, X., et al., Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites. Bioinformatics, 2013. 29(13): p. 1614-1622.
57. Chen, Z., et al., hCKSAAP_UbSite: Improved prediction of human ubiquitination sites by exploiting amino acid pattern and properties. Biochimica Et Biophysica Acta-Proteins and Proteomics, 2013. 1834(8): p. 1461-1467.
58. Lu, C.T., et al., dbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications. Nucleic Acids Research, 2013. 41(D1): p. D295-D305.
59. Boeckmann, B., et al., The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Research, 2003. 31(1): p. 365-370.
60. Chen, T., et al., mUbiSiDa: A Comprehensive Database for Protein Ubiquitination Sites in Mammals. Plos One, 2014. 9(1).
61. Huang, Y., et al., CD-HIT Suite: a web server for clustering and comparing biological sequences. Bioinformatics, 2010. 26(5): p. 680-682.
62. Crooks, G.E., et al., WebLogo: A sequence logo generator. Genome Research, 2004. 14(6): p. 1188-1190.
63. Burge, C. and S. Karlin, Prediction of complete gene structures in human genomic DNA. Journal of Molecular Biology, 1997. 268(1): p. 78-94.
64. Lee, T.Y., et al., SNOSite: Exploiting Maximal Dependence Decomposition to Identify Cysteine S-Nitrosylation with Substrate Site Specificity. Plos One, 2011. 6(7).
65. Lee, T.Y., et al., Exploiting maximal dependence decomposition to identify conserved motifs from a group of aligned signal sequences. Bioinformatics, 2011. 27(13): p. 1780-1787.
66. Chang, C.C. and C.J. Lin, LIBSVM: A Library for Support Vector Machines. Acm Transactions on Intelligent Systems and Technology, 2011. 2(3).
67. Vacic, V., L.M. Iakoucheva, and P. Radivojac, Two Sample Logo: a graphical representation of the differences between two sets of sequence alignments. Bioinformatics, 2006. 22(12): p. 1536-1537.
68. Hsu, J.B.K., et al., Incorporating Evolutionary Information and Functional Domains for Identifying RNA Splicing Factors in Humans. Plos One, 2011. 6(11).
69. Maor, R., et al., Multidimensional protein identification technology (MudPIT) analysis of ubiquitinated proteins in plants. Mol Cell Proteomics, 2007. 6(4): p. 601-10.
70. Quevillon, E., et al., InterProScan: protein domains identifier. Nucleic Acids Res, 2005. 33(Web Server issue): p. W116-20.
71. Rotin, D. and S. Kumar, Physiological functions of the HECT family of ubiquitin ligases. Nat Rev Mol Cell Biol, 2009. 10(6): p. 398-409.
72. Huang, L., et al., Structure of an E6AP-UbcH7 complex: Insights into ubiquitination by the E2-E3 enzyme cascade. Science, 1999. 286(5443): p. 1321-1326.
73. Lin, D.Y., J. Diao, and J. Chen, Crystal structures of two bacterial HECT-like E3 ligases in complex with a human E2 reveal atomic details of pathogen-host interactions. Proc Natl Acad Sci U S A, 2012. 109(6): p. 1925-30.
74. Huibregtse, J.M., et al., A family of proteins structurally and functionally related to the E6-AP ubiquitin-protein ligase. Proc Natl Acad Sci U S A, 1995. 92(11): p. 5249.
75. Li, W., et al., Genome-wide and functional annotation of human E3 ubiquitin ligases identifies MULAN, a mitochondrial E3 that regulates the organelle's dynamics and signaling. PLoS One, 2008. 3(1): p. e1487.
76. Zheng, N., et al., Structure of a c-Cbl-UbcH7 complex: RING domain function in ubiquitin-protein ligases. Cell, 2000. 102(4): p. 533-9.
77. Petroski, M.D. and R.J. Deshaies, Function and regulation of cullin-RING ubiquitin ligases. Nat Rev Mol Cell Biol, 2005. 6(1): p. 9-20.
78. Hua, Z. and R.D. Vierstra, The cullin-RING ubiquitin-protein ligases. Annu Rev Plant Biol, 2011. 62: p. 299-334.
79. Wade, M., Y.V. Wang, and G.M. Wahl, The p53 orchestra: Mdm2 and Mdmx set the tone. Trends Cell Biol, 2010. 20(5): p. 299-309.
80. Lee, J.T. and W. Gu, The multiple levels of regulation by p53 ubiquitination. Cell Death Differ, 2010. 17(1): p. 86-92.
81. Haupt, Y., et al., Mdm2 promotes the rapid degradation of p53. Nature, 1997. 387(6630): p. 296-9.
82. Kubbutat, M.H.G., S.N. Jones, and K.H. Vousden, Regulation of p53 stability by Mdm2. Nature, 1997. 387(6630): p. 299-303.
83. Honda, R., H. Tanaka, and H. Yasuda, Oncoprotein MDM2 is a ubiquitin ligase E3 for tumor suppressor p53. Febs Letters, 1997. 420(1): p. 25-27.
84. Fang, S.Y., et al., Mdm2 is a RING finger-dependent ubiquitin protein ligase for itself and p53. Journal of Biological Chemistry, 2000. 275(12): p. 8945-8951.
85. Honda, R. and H. Yasuda, Activity of MDM2, a ubiquitin Ligase, toward p53 or itself is dependent on the RING finger domain of the ligase. Oncogene, 2000. 19(11): p. 1473-1476.
86. Hanahan, D. and R.A. Weinberg, Hallmarks of cancer: the next generation. Cell, 2011. 144(5): p. 646-74.
87. Benita, Y., et al., An integrative genomics approach identifies Hypoxia Inducible Factor-1 (HIF-1)-target genes that form the core response to hypoxia. Nucleic Acids Res, 2009. 37(14): p. 4587-602.
88. Nakayama, K., et al., Siah2 regulates stability of prolyl-hydroxylases, controls HIF1alpha abundance, and modulates physiological responses to hypoxia. Cell, 2004. 117(7): p. 941-52.
89. Bailey, T.L., et al., MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res, 2009. 37(Web Server issue): p. W202-8.
90. Lee, K.A., et al., Ubiquitin Ligase Substrate Identification through Quantitative Proteomics at Both the Protein and Peptide Levels. Journal of Biological Chemistry, 2011. 286(48): p. 41530-41538.
91. Nguyen, V.N., et al., Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities. BMC Bioinformatics, 2015. 16(Suppl 1): p. S1.
92. Han, Y., et al., E3Net: A System for Exploring E3-mediated Regulatory Networks of Cellular Functions. Molecular &; Cellular Proteomics, 2012. 11(4).
93. Zhang, J., et al., Functional characterization of Anaphase Promoting Complex/Cyclosome (APC/C) E3 ubiquitin ligases in tumorigenesis. Biochim Biophys Acta, 2014. 1845(2): p. 277-93.
94. Manchado, E., M. Eguren, and M. Malumbres, The anaphase-promoting complex/cyclosome (APC/C): cell-cycle-dependent and -independent functions. Biochem Soc Trans, 2010. 38(Pt 1): p. 65-71.
95. Acquaviva, C. and J. Pines, The anaphase-promoting complex/cyclosome: APC/C. J Cell Sci, 2006. 119(Pt 12): p. 2401-4.
96. Spratt, D.E., H. Walden, and G.S. Shaw, RBR E3 ubiquitin ligases: new structures, new insights, new questions. Biochem J, 2014. 458(3): p. 421-37.
97. Paul, I. and M.K. Ghosh, The E3 Ligase CHIP: Insights into Its Structure and Regulation. Biomed Research International, 2014.
98. Duplan, V. and S. Rivas, E3 ubiquitin-ligases and their target proteins during the regulation of plant innate immunity. Frontiers in Plant Science, 2014. 5.
99. Plechanovova, A., et al., Structure of a RING E3 ligase and ubiquitin-loaded E2 primed for catalysis. Nature, 2012. 489(7414): p. 115-20.
100. Mazzucotelli, E., et al., The E3 ubiquitin ligase gene family in plants: Regulation by degradation. Current Genomics, 2006. 7(8): p. 509-522.
101. Sun, Y., Targeting E3 ubiquitin ligases for cancer therapy. Cancer Biology &; Therapy, 2003. 2(6): p. 623-629.
102. Sakiyama, T., et al., The Construction of a Database for Ubiquitin Signaling Cascade. Genome Informatics, 2003. 14: p. 653–654.
103. Lee, H., G.S. Yi, and J.C. Park, E3Miner: a text mining tool for ubiquitin-protein ligases. Nucleic Acids Res, 2008. 36(Web Server issue): p. W416-22.
104. Hutchins, A.P., et al., The repertoires of ubiquitinating and deubiquitinating enzymes in eukaryotic genomes. Mol Biol Evol, 2013. 30(5): p. 1172-87.
105. Gao, T., et al., UUCD: a family-based database of ubiquitin and ubiquitin-like conjugation. Nucleic Acids Res, 2013. 41(Database issue): p. D445-51.
106. Kohl, M., S. Wiese, and B. Warscheid, Cytoscape: software for visualization and analysis of biological networks. Methods Mol Biol, 2011. 696: p. 291-303.
107. Ng, S.K., Z. Zhang, and S.H. Tan, Integrative approach for computationally inferring protein domain interactions. Bioinformatics, 2003. 19(8): p. 923-929.
108. Nguyen, T.P. and T.B. Ho, Discovering signal transduction networks using signaling domain-domain interactions. Genome Inform, 2006. 17(2): p. 35-45.
109. Ng, K.L., et al., Applications of domain-domain interactions in pathway study. Comput Biol Chem, 2008. 32(2): p. 81-7.
110. Rose, P.W., et al., The RCSB Protein Data Bank: redesigned web site and web services. Nucleic Acids Res, 2011. 39(Database issue): p. D392-401.
111. Kanehisa, M., et al., KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res, 2012. 40(Database issue): p. D109-14.
112. Manfredi, J.J., The Mdm2-p53 relationship evolves: Mdm2 swings both ways as an oncogene and a tumor suppressor. Genes Dev, 2010. 24(15): p. 1580-9.
113. Chou, C.C., et al., AMPK reverses the mesenchymal phenotype of cancer cells by targeting the Akt-MDM2-Foxo3a signaling axis. Cancer Res, 2014. 74(17): p. 4783-95.
114. Strelow, A., C. Kollewe, and H. Wesche, Characterization of Pellino2, a substrate of IRAK1 and IRAK4. FEBS Lett, 2003. 547(1-3): p. 157-61.
115. Oberst, A., et al., The Nedd4-binding partner 1 (N4BP1) protein is an inhibitor of the E3 ligase Itch. Proc Natl Acad Sci U S A, 2007. 104(27): p. 11280-5.
116. Vazquez, A., J.F. Rual, and K. Venkatesan, Quality control methodology for high-throughput protein-protein interaction screening. Methods Mol Biol, 2011. 781: p. 279-94.
117. Huang, J.N., et al., High-throughput screening for inhibitors of the E3 ubiquitin ligase APC. Ubiquitin and Protein Degradation, Pt B, 2005. 399: p. 740-754.