Using the scan‐x Web Site to Predict Protein Post‐Translational Modifications

Michael F. Chou1, Daniel Schwartz2

1 Department of Genetics, Harvard Medical School, Boston, Massachusetts, 2 Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 13.16
DOI:  10.1002/0471250953.bi1316s36
Online Posting Date:  December, 2011
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Abstract

The recent plethora of proteomic mass spectrometry data is providing evidence that almost every protein in the cell undergoes some form of post‐translational modification. We describe a protocol to use the scan‐x Web site to view predicted acetylation sites in the human proteome and predicted phosphorylation sites in the human, mouse, fly, and yeast proteomes with high specificity. This tool is accessible from virtually any computer with a Web browser. The only requirement is a means of searching for a protein of interest in one of the represented organisms. Curr. Protoc. Bioinform. 36:13.16.1‐13.16.8. © 2011 by John Wiley & Sons, Inc.

Keywords: acetylation; phosphorylation; post‐translational modification (PTM); scan‐x; motif‐x; mass spectrometry; proteomics

     
 
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Table of Contents

  • Introduction
  • Basic Protocol 1: Using the scan‐x Web Server to View Predicted Post‐Translational Modification Sites on a Protein of Interest
  • Guidelines for Understanding Results
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

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Figures

Videos

Literature Cited

   Bodenmiller, B., Malmstrom, J., Gerrits, B., Campbell, D., Lam, H., Schmidt, A., Rinner, O., Mueller, L.N., Shannon, P.T., Pedrioli, P.G., Panse, C., Lee, H.K., Schlapbach, R., and Aebersold, R. 2007. PhosphoPep—a phosphoproteome resource for systems biology research in Drosophila Kc167 cells. Mol. Syst. Biol. 3:139.
   Gnad, F., Gunawardena, J., and Mann, M. 2011. PHOSIDA 2011: The posttranslational modification database. Nucleic Acids Res. 39:D253‐D260.
   Hornbeck, P.V., Chabra, I., Kornhauser, J.M., Skrzypek, E., and Zhang, B. 2004. PhosphoSite: A bioinformatics resource dedicated to physiological protein phosphorylation. Proteomics 4:1551‐1561.
   Ingrell, C.R., Miller, M.L., Jensen, O.N., and Blom, N. 2007. NetPhosYeast: Prediction of protein phosphorylation sites in yeast. Bioinformatics 23:895‐897.
   Obenauer, J.C., Cantley, L.C., and Yaffe, M.B. 2003. Scansite 2.0: Proteome‐wide prediction of cell signaling interactions using short sequence motifs. Nucleic Acids Res. 31:3635‐3641
   Schwartz, D. and Gygi, S.P. 2005. An iterative statistical approach to the identification of protein phosphorylation motifs from large‐scale data sets. Nat. Biotechnol. 23:1391‐1398.
   Schwartz, D., Chou, M.F., and Church, G.M. 2009. Predicting protein post‐translational modifications using meta‐analysis of proteome scale data sets. Mol. Cell Proteomics 8:365‐379.
Key Reference
  Schwartz et al., 2009. See above.
  Original description of the scan‐x algorithm.
Internet Resources
  http://scan‐x.med.harvard.edu
  Home page for the scan‐x version 1.1 Web tool.
   http://phosphosite.org
  A large database of experimentally determined post‐translational modification sites.
  http://phospho.elm.eu.org
  A large database of experimentally determined phosphorylation sites.
  http://scansite.mit.edu
  An alternative, widely used Web tool for kinase‐specific phosphorylation prediction.
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