Computational Identification of Protein Kinases and Kinase-Specific Substrates in Plants

  • Han Cheng
  • Yongbo Wang
  • Zexian Liu
  • Yu XueEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1306)


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:

Key words

Protein kinase Phosphorylation Kinase-specific substrate Hidden Markov Model GPS Site-specific kinase–substrate relation 



This work was supported by grants from the National Basic Research Program (973 project) (2013CB933900 and 2012CB910101), Natural Science Foundation of China (31171263, and 81272578), and International Science & Technology Cooperation Program of China (2014DFB30020).


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Biomedical Engineering, College of Life Science and TechnologyHuazhong University of Science and TechnologyWuhanChina

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