Last updated: June 12th, 2014
Introduction :
Protein phosphorylation is one of the extensively studied post-translational modifications. Phosphorylation was first discovered in rabbit skeletal muscle glycogen phosphorylase in the mid-1950s (KREBS and FISCHER, 1956). After 20 years later, phosphorylation was found in prokaryotes (Manaï and Cozzone, 1983). Impressive amount of data of prokaryotic phosphorylation has been reported in the last decade though the delay of studies in prokaryotes. All these indicated the importance of protein phosphorylation in the biological processes of microorganisms. What's more, phosphorylated proteins can be utilized for analysing pathways, biological mechanisms which might be of considerable clinical or industrial importance. Thus, the databases containing prokaryotic protein phosphorylation sites and substrates are collected below.
We apologized that the computational studies without any web links of databases will not be included in this compendium, since it's not easy for experimentalists to use studies directly. We are grateful for users feedback. Please inform Zhicheng Pan, Dr. Zexian Liu, Dr. Yu Xue or Dr. Jian Ren to add, remove or update one or multiple web links below.
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1. UniProt: The Universal Protein Resource (The UniProt Consortium et al., 2012).
2. PHOSIDA: comprises more than 80,000 phosphorylated sites from nine species obtained from high-resolution mass spectrometric data (Gnad et al., 2011).
3. PHOSPHORYLATION SITE DATABASE: contains the serine-, threonine-, and/or tyrosine-phosphorylatated proteins and sites in prokaryotic organisms (Wurgler-Murphy et al., 2004 ).
4. dbPTM 3.0: integrates experimentally verified PTMs from several databases, and to annotate the predicted PTMs on Swiss-Prot proteins (Cheng-Tsung Lu, et al., Nucleic Acids Res. 2013).
5. SysPTM 2.0: provides a systematic and sophisticated platform for proteomic PTM research, equipped not only with a knowledge base of manually curated multi-type modification data, but also with four fully developed, in-depth data mining tools. (Jing Li, et al., Database, 2014).