[Post-translational modification (PTM) bioinformatics in China: progresses and perspectives].

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.

[1]  Shao-Ping Shi,et al.  Proteome-wide analysis of amino acid variations that influence protein lysine acetylation. , 2013, Journal of proteome research.

[2]  Yu-Dong Cai,et al.  Prediction and Analysis of Protein Hydroxyproline and Hydroxylysine , 2010, PloS one.

[3]  Wei-Guo Zhu,et al.  Characterization and Prediction of Lysine (K)-Acetyl-Transferase Specific Acetylation Sites* , 2011, Molecular & Cellular Proteomics.

[4]  Jianding Qiu,et al.  Systematic Analysis and Prediction of Pupylation Sites in Prokaryotic Proteins , 2013, PloS one.

[5]  Chaochun Wei,et al.  LAceP: Lysine Acetylation Site Prediction Using Logistic Regression Classifiers , 2014, PloS one.

[6]  Ming Lu,et al.  Systematic identification of Class I HDAC substrates , 2014, Briefings Bioinform..

[7]  Guoliang Chen,et al.  A genome‐wide analysis of sumoylation‐related biological processes and functions in human nucleus , 2005, FEBS letters.

[8]  Hong-Bin Shen,et al.  LabCaS: Labeling calpain substrate cleavage sites from amino acid sequence using conditional random fields , 2013, Proteins.

[9]  Yu Xue,et al.  A summary of computational resources for protein phosphorylation. , 2010, Current protein & peptide science.

[10]  D. Bredt,et al.  Protein palmitoylation: a regulator of neuronal development and function , 2002, Nature Reviews Neuroscience.

[11]  Tingting Li,et al.  Identifying Human Kinase-Specific Protein Phosphorylation Sites by Integrating Heterogeneous Information from Various Sources , 2010, PloS one.

[12]  Yu Xue,et al.  Computational Prediction of Post-Translational Modification Sites in Proteins , 2011 .

[13]  Boshu Liu,et al.  Predicting Protein N-glycosylation by Combining Functional Domain and Secretion Information , 2007, Journal of biomolecular structure & dynamics.

[14]  Geoffrey I. Webb,et al.  Accurate in silico identification of species-specific acetylation sites by integrating protein sequence-derived and functional features , 2014, Scientific Reports.

[15]  R. Spiro Protein glycosylation: nature, distribution, enzymatic formation, and disease implications of glycopeptide bonds. , 2002, Glycobiology.

[16]  贾佳 SysPTM 2.0: an updated systematic resource for post-translational modification , 2016 .

[17]  J. Workman,et al.  Introducing the acetylome , 2009, Nature Biotechnology.

[18]  Shao-Ping Shi,et al.  PredSulSite: prediction of protein tyrosine sulfation sites with multiple features and analysis. , 2012, Analytical biochemistry.

[19]  Nikolaj Blom,et al.  PhosphoBase: a database of phosphorylation sites , 1998, Nucleic Acids Res..

[20]  Zexian Liu,et al.  Systematic analysis of the in situ crosstalk of tyrosine modifications reveals no additional natural selection on multiply modified residues , 2014, Scientific Reports.

[21]  Yu Xue,et al.  EKPD: a hierarchical database of eukaryotic protein kinases and protein phosphatases , 2013, Nucleic Acids Res..

[22]  Jiangning Song,et al.  Structural Propensities of Human Ubiquitination Sites: Accessibility, Centrality and Local Conformation , 2013, PloS one.

[23]  Ziding Zhang,et al.  Prediction of mucin-type O-glycosylation sites in mammalian proteins using the composition of k-spaced amino acid pairs , 2008, BMC Bioinformatics.

[24]  Ling-Yun Wu,et al.  Prediction of palmitoylation sites using the composition of k-spaced amino acid pairs. , 2009, Protein engineering, design & selection : PEDS.

[25]  N. Blom,et al.  Statistical analysis of protein kinase specificity determinants , 1998, FEBS letters.

[26]  Yi Shen,et al.  PKIS: computational identification of protein kinases for experimentally discovered protein phosphorylation sites , 2013, BMC Bioinformatics.

[27]  Tao Huang,et al.  Prediction of tyrosine sulfation with mRMR feature selection and analysis. , 2010, Journal of proteome research.

[28]  Yu Xue,et al.  MeMo: a web tool for prediction of protein methylation modifications , 2006, Nucleic Acids Res..

[29]  Yu-Dong Cai,et al.  Prediction and Analysis of Post-Translational Pyruvoyl Residue Modification Sites from Internal Serines in Proteins , 2013, PloS one.

[30]  Shao-Ping Shi,et al.  PLMLA: prediction of lysine methylation and lysine acetylation by combining multiple features. , 2012, Molecular bioSystems.

[31]  Yu Xue,et al.  CPLM: a database of protein lysine modifications , 2013, Nucleic Acids Res..

[32]  Xing-Ming Zhao,et al.  Prediction of S-Glutathionylation Sites Based on Protein Sequences , 2013, PloS one.

[33]  Yu-Dong Cai,et al.  Prediction of Protein Cleavage Site with Feature Selection by Random Forest , 2012, PloS one.

[34]  N. Blom,et al.  Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. , 1999, Journal of molecular biology.

[35]  Yinglin Wang,et al.  Predicting the protein SUMO modification sites based on Properties Sequential Forward Selection (PSFS). , 2007, Biochemical and biophysical research communications.

[36]  F. Melchior,et al.  Concepts in sumoylation: a decade on , 2007, Nature Reviews Molecular Cell Biology.

[37]  Ao Li,et al.  Phosphorylation Site Prediction with A Modified k-Nearest Neighbor Algorithm and BLOSUM62 Matrix , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[38]  Yigong Shi,et al.  Molecular mechanisms of caspase regulation during apoptosis , 2004, Nature Reviews Molecular Cell Biology.

[39]  Jeffrey R. Whiteaker,et al.  Proteogenomic characterization of human colon and rectal cancer , 2014, Nature.

[40]  Yu Xue,et al.  PPSP: prediction of PK-specific phosphorylation site with Bayesian decision theory , 2006, BMC Bioinformatics.

[41]  W. Paik,et al.  Historical review: the field of protein methylation. , 2007, Trends in biochemical sciences.

[42]  Yong-Zi Chen,et al.  GANNPhos: a new phosphorylation site predictor based on a genetic algorithm integrated neural network. , 2007, Protein engineering, design & selection : PEDS.

[43]  Yu Xue,et al.  UUCD: a family-based database of ubiquitin and ubiquitin-like conjugation , 2012, Nucleic Acids Res..

[44]  Rui Jiang,et al.  Systematic Characterization and Prediction of Post-Translational Modification Cross-Talk* , 2015, Molecular & Cellular Proteomics.

[45]  Jiangning Song,et al.  Towards more accurate prediction of ubiquitination sites: a comprehensive review of current methods, tools and features , 2015, Briefings Bioinform..

[46]  Yu Xue,et al.  CPLA 1.0: an integrated database of protein lysine acetylation , 2010, Nucleic Acids Res..

[47]  Bin Zhang,et al.  PhosphoSitePlus, 2014: mutations, PTMs and recalibrations , 2014, Nucleic Acids Res..

[48]  Ying Xu,et al.  A general user interface for prediction servers of proteins' post-translational modification sites , 2006, Nature Protocols.

[49]  Rong Zeng,et al.  Predicting O-glycosylation sites in mammalian proteins by using SVMs , 2006, Comput. Biol. Chem..

[50]  Yu Xue,et al.  Systematic Analysis of the Phosphoproteome and Kinase-substrate Networks in the Mouse Testis* , 2014, Molecular & Cellular Proteomics.

[51]  Jiangning Song,et al.  hCKSAAP_UbSite: improved prediction of human ubiquitination sites by exploiting amino acid pattern and properties. , 2013, Biochimica et biophysica acta.

[52]  Zineng Yuan,et al.  PhosSNP for Systematic Analysis of Genetic Polymorphisms That Influence Protein Phosphorylation* , 2009, Molecular & Cellular Proteomics.

[53]  Changjiang Jin,et al.  CSS-Palm 2.0: an updated software for palmitoylation sites prediction. , 2008, Protein engineering, design & selection : PEDS.

[54]  Zexian Liu,et al.  GPS-YNO2: computational prediction of tyrosine nitration sites in proteins. , 2011, Molecular bioSystems.

[55]  Ming Lu,et al.  ASEB: a web server for KAT-specific acetylation site prediction , 2012, Nucleic Acids Res..

[56]  Xing-Ming Zhao,et al.  Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets , 2014, Bioinform..

[57]  Tao Zhou,et al.  mUbiSiDa: A Comprehensive Database for Protein Ubiquitination Sites in Mammals , 2014, PloS one.

[58]  Christopher T. Walsh,et al.  Protein Posttranslational Modifications: The Chemistry of Proteome Diversifications , 2006 .

[59]  Yu Xue,et al.  GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy *S , 2008, Molecular & Cellular Proteomics.

[60]  Yu Xue,et al.  NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm , 2006, BMC Bioinformatics.

[61]  Dongdong Sun,et al.  Literature mining of protein phosphorylation using dependency parse trees. , 2014, Methods.

[62]  Yi Shen,et al.  Prediction of protein kinase-specific phosphorylation sites in hierarchical structure using functional information and random forest , 2014, Amino Acids.

[63]  Shu-Yun Huang,et al.  PMeS: Prediction of Methylation Sites Based on Enhanced Feature Encoding Scheme , 2012, PloS one.

[64]  H. E. Marshall,et al.  Protein S-nitrosylation: purview and parameters , 2005, Nature Reviews Molecular Cell Biology.

[65]  Yu Xue,et al.  GPS: a novel group-based phosphorylation predicting and scoring method. , 2004, Biochemical and biophysical research communications.

[66]  Yu Xue,et al.  CSS-Palm: palmitoylation site prediction with a clustering and scoring strategy (CSS) , 2006, Bioinform..

[67]  Xiang Chen,et al.  Proteomic analysis and prediction of human phosphorylation sites in subcellular level reveal subcellular specificity , 2015, Bioinform..

[68]  M. Mann,et al.  In vivo SILAC-based proteomics reveals phosphoproteome changes during mouse skin carcinogenesis. , 2013, Cell reports.

[69]  Yong-Zi Chen,et al.  Prediction of Ubiquitination Sites by Using the Composition of k-Spaced Amino Acid Pairs , 2011, PloS one.

[70]  Xuegong Zhang,et al.  Prediction of kinase‐specific phosphorylation sites with sequence features by a log‐odds ratio approach , 2007, Proteins.

[71]  C. Bertozzi,et al.  Tyrosine sulfation: a modulator of extracellular protein-protein interactions. , 2000, Chemistry & biology.

[72]  B. Freeman,et al.  NO-dependent protein nitration: a cell signaling event or an oxidative inflammatory response? , 2003, Trends in biochemical sciences.

[73]  Xiang Chen,et al.  Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites , 2013, Bioinform..

[74]  Yu Xue,et al.  SUMOsp: a web server for sumoylation site prediction , 2006, Nucleic Acids Res..

[75]  Zexian Liu,et al.  GPS-CCD: A Novel Computational Program for the Prediction of Calpain Cleavage Sites , 2011, PloS one.

[76]  Ning Zhang,et al.  Prediction of protein amidation sites by feature selection and analysis , 2013, Molecular Genetics and Genomics.

[77]  Yixue Li,et al.  SysPTM: A Systematic Resource for Proteomic Research on Post-translational Modifications* , 2009, Molecular & Cellular Proteomics.

[78]  Avram Hershko,et al.  The Ubiquitin System for Protein Degradation and Some of Its Roles in the Control of the Cell‐Division Cycle Nobel Lecture , 2006 .

[79]  Qi Zhao,et al.  GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs , 2014, Nucleic Acids Res..

[80]  Bermseok Oh,et al.  Prediction of phosphorylation sites using SVMs , 2004, Bioinform..

[81]  Ming Lu,et al.  Prediction of substrate sites for protein phosphatases 1B, SHP-1, and SHP-2 based on sequence features , 2014, Amino Acids.

[82]  Ming Lu,et al.  hUbiquitome: a database of experimentally verified ubiquitination cascades in humans , 2011, Database J. Biol. Databases Curation.

[83]  Yu Shyr,et al.  Improved prediction of lysine acetylation by support vector machines. , 2009, Protein and peptide letters.

[84]  M. Yaffe,et al.  A motif-based profile scanning approach for genome-wide prediction of signaling pathways , 2001, Nature Biotechnology.

[85]  Shao-Ping Shi,et al.  The prediction of palmitoylation site locations using a multiple feature extraction method. , 2013, Journal of molecular graphics & modelling.

[86]  Changjiang Jin,et al.  Prediction of Nepsilon-acetylation on internal lysines implemented in Bayesian Discriminant Method. , 2006, Biochemical and biophysical research communications.

[87]  Hongyang Wang,et al.  Systematic Analysis of Protein Phosphorylation Networks From Phosphoproteomic Data* , 2012, Molecular & Cellular Proteomics.

[88]  Yu Xue,et al.  GPS-PUP: computational prediction of pupylation sites in prokaryotic proteins. , 2011, Molecular Biosystems.

[89]  Yu Xue,et al.  GPS: a comprehensive www server for phosphorylation sites prediction , 2005, Nucleic Acids Res..

[90]  Klaus Ersfeld,et al.  The calpains: modular designs and functional diversity , 2007, Genome Biology.

[91]  Shao-Ping Shi,et al.  PSEA: Kinase-specific prediction and analysis of human phosphorylation substrates , 2014, Scientific Reports.

[92]  Yu Xue,et al.  Systematic analysis of the Plk-mediated phosphoregulation in eukaryotes , 2013, Briefings Bioinform..

[93]  Yu-Dong Cai,et al.  Predicting N-terminal acetylation based on feature selection method. , 2008, Biochemical and biophysical research communications.

[94]  James E. Ferrell,et al.  Mechanisms of specificity in protein phosphorylation , 2007, Nature Reviews Molecular Cell Biology.

[95]  C. Landry,et al.  Weak functional constraints on phosphoproteomes. , 2009, Trends in genetics : TIG.