Proteomic analysis and prediction of human phosphorylation sites in subcellular level reveal subcellular specificity

Bioinformatics. 2015 Jan 15;31(2):194-200. doi: 10.1093/bioinformatics/btu598. Epub 2014 Sep 17.


Motivation: Protein phosphorylation is the most common post-translational modification (PTM) regulating major cellular processes through highly dynamic and complex signaling pathways. Large-scale comparative phosphoproteomic studies have frequently been done on whole cells or organs by conventional bottom-up mass spectrometry approaches, i.e at the phosphopeptide level. Using this approach, there is no way to know from where the phosphopeptide signal originated. Also, as a consequence of the scale of these studies, important information on the localization of phosphorylation sites in subcellular compartments (SCs) is not surveyed.

Results: Here, we present a first account of the emerging field of subcellular phosphoproteomics where a support vector machine (SVM) approach was combined with a novel algorithm of discrete wavelet transform (DWT) to facilitate the identification of compartment-specific phosphorylation sites and to unravel the intricate regulation of protein phosphorylation. Our data reveal that the subcellular phosphorylation distribution is compartment type dependent and that the phosphorylation displays site-specific sequence motifs that diverge between SCs.

Availability and implementation: The method and database both are available as a web server at:

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Humans
  • Mass Spectrometry
  • Phosphopeptides / analysis*
  • Phosphorylation
  • Protein Processing, Post-Translational
  • Proteome / analysis*
  • Proteomics / methods*
  • Software*
  • Subcellular Fractions
  • Support Vector Machine


  • Phosphopeptides
  • Proteome