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Protein phosphorylation database and prediction tools

Ming-Xiao Zhao1, Qiang Chen2, Fulai Li3

  • 1Department of Chemical Biology, Key Laboratory for Chemical Biology of Fujian Province, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005, China.

Briefings in Bioinformatics
|March 10, 2023
PubMed

Insights

This review summarizes protein phosphorylation databases and predictors, aiding researchers in selecting tools for phosphosite discovery. It highlights limitations to improve future in silico predictor development.

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Bioinformatics

Background:

  • Protein phosphorylation is a critical post-translational modification regulating cellular functions.
  • Dysregulation of protein phosphorylation is implicated in diseases like cancer.
  • Experimental phosphosite discovery is resource-intensive, necessitating computational tools.

Conclusions:

  • Effective selection of phosphorylation databases and predictors is crucial for research efficiency.
  • Understanding the limitations of current tools is essential for advancing in silico prediction methods.
  • This review serves as a valuable resource for researchers in the field of protein phosphorylation.
Keywords:
databasepost-translational modificationpredictorprotein phosphorylation

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