GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy

Mol Cell Proteomics. 2008 Sep;7(9):1598-608. doi: 10.1074/mcp.M700574-MCP200. Epub 2008 May 6.

Abstract

Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been addressed. In this work, we adopted a well established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily, and single PK. In addition, we developed a simple approach to estimate the theoretically maximal false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large scale prediction of more than 13,000 mammalian phosphorylation sites by GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic prediction of Aurora-B-specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases and is freely available on line.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Amino Acid Sequence
  • Aurora Kinase B
  • Aurora Kinases
  • Cyclic AMP-Dependent Protein Kinases / metabolism*
  • Humans
  • Molecular Sequence Data
  • Phosphorylation
  • Protein Processing, Post-Translational*
  • Protein-Serine-Threonine Kinases / metabolism
  • Proteome / metabolism*
  • Software Design*
  • Software Validation*

Substances

  • Proteome
  • AURKB protein, human
  • Aurora Kinase B
  • Aurora Kinases
  • Protein-Serine-Threonine Kinases
  • Cyclic AMP-Dependent Protein Kinases