Post-translational modifications (PTMs) are essential for regulating conformational changes, activities and functions of proteins, and are involved in almost all cellular pathways and processes. Identification of protein PTMs is the basis for understanding cellular and molecular mechanisms. In contrast with labor-intensive and time-consuming experiments, the PTM prediction using various bioinformatics approaches can provide accurate, convenient, and efficient strategies and generate valuable information for further experimental consideration. In this review, we summarize the current progresses made by Chineses bioinformaticians in the field of PTM Bioinformatics, including the design and improvement of computational algorithms for predicting PTM substrates and sites, design and maintenance of online and offline tools, establishment of PTM-related databases and resources, and bioinformatics analysis of PTM proteomics data. Through comparing similar studies in China and other countries, we demonstrate both advantages and limitations of current PTM bioinformatics as well as perspectives for future studies in China.
Zexian Liu, Yudong Cai, Xuejiang Guo, Ao Li, Tingting Li, Jianding Qiu, Jian Ren, Shaoping Shi, Jiangning Song, Minghui Wang, Lu Xie, Yu Xue, Ziding Zhang, Xingming Zhao
. Post-translational modification (PTM) bioinformatics in China: progresses and perspectives[J]. Hereditas(Beijing), 2015
, 37(7)
: 621
-634
.
DOI: 10.16288/j.yczz.15-003
[1] Xue Y, Liu ZX, Cao J, Ren J. Computational prediction of post-translational modification sites in proteins. Systems and Computational Biology-Molecular and Cellular Experimental Systems , 2011, 5772(6): 18559.
[2] Ubersax JA, Ferrell JE Jr. Mechanisms of specificity in protein phosphorylation. Nat Rev Mol Cell Biol , 2007, 8(7): 530-541.
[3] Hershko A. The ubiquitin system for protein degradation and some of its roles in the control of the cell-division cycle (Nobel lecture). Angew Chem Int Ed , 2005, 44(37): 5932- 5943.
[4] Smith KT, Workman JL. Introducing the acetylome. Nat Biotechnol , 2009, 27(10): 917-919.
[5] Riedl SJ, Shi Y. Molecular mechanisms of caspase regulation during apoptosis. Nat Rev Mol Cell Biol , 2004, 5(11): 897-907.
[6] Croall DE, Ersfeld K. The calpains: modular designs and functional diversity. Genome Biol , 2007, 8(6): 218.
[7] Wang YB, Liu ZX, Cheng H, Gao TS, Pan ZC, Yang Q, Guo AY, Xue Y. EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases. Nucleic Acids Res , 2014, 42(Database issue): D496-D502.
[8] Gao TS, Liu ZX, Wang YB, Cheng H, Yang Q, Guo AY, Ren J, Xue Y. UUCD: a family-based database of ubiquitin and ubiquitin-like conjugation. Nucleic Acids Res , 2013, 41(Database issue): D445-D451.
[9] Liu ZX, Cao J, Gao XJ, Zhou YH, Wen LP, Yang XJ, Yao X, Ren J, Xue Y. CPLA 1.0: an integrated database of protein lysine acetylation. Nucleic Acids Res , 2011, 39(Database issue): D1029-D1034.
[10] Walsh CT, Garneau-Tsodikova S, Gatto GJ Jr. Protein posttranslational modifications: the chemistry of proteome diversifications. Angew Chem Int Ed , 2005, 44(45): 7342- 7372.
[11] Spiro RG. Protein glycosylation: nature, distribution, enzymatic formation, and disease implications of glycopeptide bonds. Glycobiology , 2002, 12(4): 43R-56R.
[12] Schopfer FJ, Baker PRS, Freeman BA. NO-dependent protein nitration: a cell signaling event or an oxidative inflammatory response? Trends Biochem Sci , 2003, 28(12): 646-654.
[13] Geiss-Friedlander R, Melchior F. Concepts in sumoylation: a decade on. Nat Rev Mol Cell Biol , 2007, 8(12): 947-956.
[14] El-Husseini AED, Bredt DS. Protein palmitoylation: a regulator of neuronal development and function. Nat Rev Neurosci , 2002, 3(10): 791-802.
[15] Paik WK, Paik DC, Kim S. Historical review: the field of protein methylation. Trends Biochem Sci , 2007, 32(3): 146-152.
[16] Kehoe JW, Bertozzi CR. Tyrosine sulfation: a modulator of extracellular protein-protein interactions. Chem Biol , 2000, 7(3): R57-61.
[17] Hess DT, Matsumoto A, Kim SO, Marshall HE, Stamler JS. Protein S -nitrosylation: purview and parameters. Nat Rev Mol Cell Biol , 2005, 6(2): 150-166.
[18] Ren J, Gao XJ, Liu XZ, Cao J, Ma Q, Xue Y. Computational analysis of phosphoproteomics: progresses and perspectives. Curr Protein Pept Sci , 2011, 12(7): 591-601.
[19] Xue Y, Gao X, Cao J, Liu Z, Jin C, Wen L, Yao X, Ren J. A summary of computational resources for protein phosphorylation. Curr Protein Pept Sci , 2010, 11(6): 485-496.
[20] Liu ZX, Wang YB, Xue Y. Phosphoproteomics-based network medicine. FEBS J , 2013, 280(22): 5696-5704.
[21] Blom N, Kreegipuu A, Brunak S. PhosphoBase: a database of phosphorylation sites. Nucleic Acids Res , 1998, 26(1): 382-386.
[22] Kreegipuu A, Blom N, Brunak S, Jarv J. Statistical analysis of protein kinase specificity determinants. FEBS Lett , 1998, 430(1-2): 45-50.
[23] Blom N, Gammeltoft S, Brunak S. Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol , 1999, 294(5): 1351-1362.
[24] Zhou FF, Xue Y, Lu HL, Chen GL, Yao XB. A genome-wide analysis of sumoylation-related biological processes and functions in human nucleus. FEBS Lett , 2005, 579(16): 3369-3375.
[25] Zhou FF, Xue Y, Yao XB, Xu Y. CSS-Palm: palmitoylation site prediction with a clustering and scoring strategy (CSS). Bioinformatics , 2006, 22(7): 894
