Literature DB >> 21720494

Identification of Novel Phosphorylation Motifs Through an Integrative Computational and Experimental Analysis of the Human Phosphoproteome.

Ramars Amanchy1, Kumaran Kandasamy, Suresh Mathivanan, Balamurugan Periaswamy, Raghunath Reddy, Wan-Hee Yoon, Jos Joore, Michael A Beer, Leslie Cope, Akhilesh Pandey.   

Abstract

Protein phosphorylation occurs in certain sequence/structural contexts that are still incompletely understood. The amino acids surrounding the phosphorylated residues are important in determining the binding of the kinase to the protein sequence. Upon phosphorylation these sequences also determine the binding of certain domains that specifically bind to phosphorylated sequences. Thus far, such 'motifs' have been identified through alignment of a limited number of well identified kinase substrates.
RESULTS: Experimentally determined phosphorylation sites from Human Protein Reference Database were used to identify 1,167 novel serine/threonine or tyrosine phosphorylation motifs using a computational approach. We were able to statistically validate a number of these novel motifs based on their enrichment in known phosphopeptides datasets over phosphoserine/threonine/tyrosine peptides in the human proteome. There were 299 novel serine/threonine or tyrosine phosphorylation motifs that were found to be statistically significant. Several of the novel motifs that we identified computationally have subsequently appeared in large datasets of experimentally determined phosphorylation sites since we initiated our analysis. Using a peptide microarray platform, we have experimentally evaluated the ability of casein kinase I to phosphorylate a subset of the novel motifs discovered in this study. Our results demonstrate that it is feasible to identify novel phosphorylation motifs through large phosphorylation datasets. Our study also establishes peptide microarrays as a novel platform for high throughput kinase assays and for the validation of consensus motifs. Finally, this extended catalog of phosphorylation motifs should assist in a systematic study of phosphorylation networks in signal transduction pathways.

Entities:  

Year:  2011        PMID: 21720494      PMCID: PMC3124146          DOI: 10.4172/jpb.1000163

Source DB:  PubMed          Journal:  J Proteomics Bioinform        ISSN: 0974-276X


  45 in total

1.  Sequence and structure-based prediction of eukaryotic protein phosphorylation sites.

Authors:  N Blom; S Gammeltoft; S Brunak
Journal:  J Mol Biol       Date:  1999-12-17       Impact factor: 5.469

Review 2.  14-3-3 proteins; bringing new definitions to scaffolding.

Authors:  G Tzivion; Y H Shen; J Zhu
Journal:  Oncogene       Date:  2001-10-01       Impact factor: 9.867

3.  Phosphoproteome analysis of HeLa cells using stable isotope labeling with amino acids in cell culture (SILAC).

Authors:  Ramars Amanchy; Dario E Kalume; Akiko Iwahori; Jun Zhong; Akhilesh Pandey
Journal:  J Proteome Res       Date:  2005 Sep-Oct       Impact factor: 4.466

4.  A curated compendium of phosphorylation motifs.

Authors:  Ramars Amanchy; Balamurugan Periaswamy; Suresh Mathivanan; Raghunath Reddy; Sudhir Gopal Tattikota; Akhilesh Pandey
Journal:  Nat Biotechnol       Date:  2007-03       Impact factor: 54.908

5.  Predicting protein post-translational modifications using meta-analysis of proteome scale data sets.

Authors:  Daniel Schwartz; Michael F Chou; George M Church
Journal:  Mol Cell Proteomics       Date:  2008-10-28       Impact factor: 5.911

Review 6.  Protein kinase phosphorylation site sequences and consensus specificity motifs: tabulations.

Authors:  R B Pearson; B E Kemp
Journal:  Methods Enzymol       Date:  1991       Impact factor: 1.600

Review 7.  Phosphoserine/threonine-binding domains.

Authors:  M B Yaffe; A E Elia
Journal:  Curr Opin Cell Biol       Date:  2001-04       Impact factor: 8.382

8.  Global phosphoproteome of HT-29 human colon adenocarcinoma cells.

Authors:  Ji-Eun Kim; Steven R Tannenbaum; Forest M White
Journal:  J Proteome Res       Date:  2005 Jul-Aug       Impact factor: 4.466

9.  Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules.

Authors:  Yi Zhang; Alejandro Wolf-Yadlin; Phillip L Ross; Darryl J Pappin; John Rush; Douglas A Lauffenburger; Forest M White
Journal:  Mol Cell Proteomics       Date:  2005-06-11       Impact factor: 5.911

10.  A noncanonical sequence phosphorylated by casein kinase 1 in beta-catenin may play a role in casein kinase 1 targeting of important signaling proteins.

Authors:  Oriano Marin; Victor H Bustos; Luca Cesaro; Flavio Meggio; Mario A Pagano; Marcelo Antonelli; Catherine C Allende; Lorenzo A Pinna; Jorge E Allende
Journal:  Proc Natl Acad Sci U S A       Date:  2003-08-18       Impact factor: 11.205

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  18 in total

1.  Posttranslational modifications of the retinoblastoma tumor suppressor protein as determinants of function.

Authors:  James I Macdonald; Frederick A Dick
Journal:  Genes Cancer       Date:  2012-11

2.  Large conductance voltage- and Ca2+-gated potassium (BK) channel β4 subunit influences sensitivity and tolerance to alcohol by altering its response to kinases.

Authors:  Cristina Velázquez-Marrero; Garrett E Seale; Steven N Treistman; Gilles E Martin
Journal:  J Biol Chem       Date:  2014-09-04       Impact factor: 5.157

3.  Phosphoproteomics Analysis Identifies Novel Candidate Substrates of the Nonreceptor Tyrosine Kinase, Src-related Kinase Lacking C-terminal Regulatory Tyrosine and N-terminal Myristoylation Sites (SRMS).

Authors:  Raghuveera Kumar Goel; Marta Paczkowska; Jüri Reimand; Scott Napper; Kiven Erique Lukong
Journal:  Mol Cell Proteomics       Date:  2018-03-01       Impact factor: 5.911

4.  Comparative genomic and proteomic analysis of cytoskeletal changes in dexamethasone-treated trabecular meshwork cells.

Authors:  Ross Clark; Amanda Nosie; Teresa Walker; Jennifer A Faralli; Mark S Filla; Gregory Barrett-Wilt; Donna M Peters
Journal:  Mol Cell Proteomics       Date:  2012-10-28       Impact factor: 5.911

Review 5.  Coupling enrichment methods with proteomics for understanding and treating disease.

Authors:  Amit Kumar; Deniz Baycin-Hizal; Joseph Shiloach; Michael A Bowen; Michael J Betenbaugh
Journal:  Proteomics Clin Appl       Date:  2015-01-19       Impact factor: 3.603

6.  The Escherichia coli phosphotyrosine proteome relates to core pathways and virulence.

Authors:  Anne-Marie Hansen; Raghothama Chaerkady; Jyoti Sharma; J Javier Díaz-Mejía; Nidhi Tyagi; Santosh Renuse; Harrys K C Jacob; Sneha M Pinto; Nandini A Sahasrabuddhe; Min-Sik Kim; Bernard Delanghe; Narayanaswamy Srinivasan; Andrew Emili; James B Kaper; Akhilesh Pandey
Journal:  PLoS Pathog       Date:  2013-06-13       Impact factor: 6.823

7.  Metabotropic glutamate receptor 1 expression and its polymorphic variants associate with breast cancer phenotypes.

Authors:  Madhura S Mehta; Sonia C Dolfi; Roman Bronfenbrener; Erhan Bilal; Chunxia Chen; Dirk Moore; Yong Lin; Hussein Rahim; Seena Aisner; Romona D Kersellius; Jessica Teh; Suzie Chen; Deborah L Toppmeyer; Dan J Medina; Shridar Ganesan; Alexei Vazquez; Kim M Hirshfield
Journal:  PLoS One       Date:  2013-07-26       Impact factor: 3.240

8.  CK1δ kinase activity is modulated by Chk1-mediated phosphorylation.

Authors:  Joachim Bischof; Sven-Jannis Randoll; Nadine Süßner; Doris Henne-Bruns; Lorenzo A Pinna; Uwe Knippschild
Journal:  PLoS One       Date:  2013-07-04       Impact factor: 3.240

9.  Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures.

Authors:  Ghim Siong Ow; Anna V Ivshina; Gloria Fuentes; Vladimir A Kuznetsov
Journal:  Cell Cycle       Date:  2014-05-30       Impact factor: 4.534

10.  Enhanced regulatory sequence prediction using gapped k-mer features.

Authors:  Mahmoud Ghandi; Dongwon Lee; Morteza Mohammad-Noori; Michael A Beer
Journal:  PLoS Comput Biol       Date:  2014-07-17       Impact factor: 4.475

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