Computational identification of protein kinases and kinase-specific substrates in plants

Methods Mol Biol. 2015:1306:195-205. doi: 10.1007/978-1-4939-2648-0_15.


The protein phosphorylation catalyzed by protein kinases (PKs) plays an essential role in almost all biological progresses in plants. Thus, the identification of PKs and kinase-specific substrates is fundamental for understanding the regulatory mechanisms of protein phosphorylation especially in controlling plant growth and development. In this chapter, we describe the computational methods and protocols for the identification of PKs and kinase-specific substrates in plants, by using Vitis vinifera as an example. First, the proteome sequences and experimentally identified phosphorylation sites (p-sites) in Vitis vinifera were downloaded. The potential PKs were computationally identified based on preconstructed Hidden Markov Model (HMM) profiles and ortholog searches, whereas the kinase-specific p-sites, or site-specific kinase-substrate relations (ssKSRs) were initially predicted by the software package of Group-based Prediction System (GPS) and further processed by the iGPS algorithm (in vivo GPS) to filter potentially false positive hits. All primary data sets and prediction results of Vitis vinifera are available at:

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Databases, Protein
  • Markov Chains
  • Phosphorylation
  • Plant Proteins / analysis*
  • Plant Proteins / isolation & purification
  • Protein Kinases / analysis
  • Protein Kinases / isolation & purification*
  • Software
  • Substrate Specificity
  • Vitis / metabolism*


  • Plant Proteins
  • Protein Kinases