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Updated: Jun 22, 2026
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Oligopeptide Competition Assay for Phosphorylation Site Determination
Published on: May 18, 2017
Evaluation of protein phosphorylation site predictors
Shufu Que1, Yongfei Wang, Peixiang Chen
1Key Laboratory of Ministry of Education for Genetic, Breeding and Multiple Utilization of Crops, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Protein and Peptide Letters
|June 11, 2009
Summary
Current phosphorylation site prediction tools show limited effectiveness for practical applications. Improvements are needed, especially for plant phosphoproteins, highlighting the need for plant-specific or meta-server approaches in proteomics research.
Area of Science:
- Biochemistry
- Bioinformatics
- Proteomics
Background:
- Phosphorylation site prediction methods accelerate experimental characterization of phosphoproteins.
- Several computational tools have been developed for predicting phosphorylation sites.
Purpose of the Study:
- To evaluate the performance of six recently published phosphorylation site prediction methods.
- To understand the overall effectiveness of current predictors on mammalian, Arabidopsis, and rice proteins.
Main Methods:
- Compiled three testing datasets of experimentally verified phosphorylation sites.
- Assessed the prediction performance of DISPHOS, NetPhosK, PPSP, KinasePhos, Scansite, and PredPhospho.
- Focused on understanding overall predictor performance rather than quantitative ranking.
Main Results:
- Current phosphorylation site predictors demonstrate limited effectiveness for practical use.
- Predictors perform poorly on plant phosphoproteins, indicating a need for plant-specific tools.
- Tested predictors show some complementarity, suggesting a meta-server approach.
Conclusions:
- Substantial improvement is required in phosphorylation site prediction accuracy.
- A rice-specific predictor is necessary for confident computational annotation in rice proteomics.
- A meta-server combining multiple predictors may enhance prediction systems.
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