Abstract
Protein phosphorylation is an important type of post-translational modification that is involved in a variety of biological activities. Most phosphorylation events occur on serine, threonine and tyrosine residues in eukaryotes. In recent years, many phosphorylation sites have been identified as a result of advances in mass-spectrometric techniques. However, a large percentage of phosphorylation sites may be non-functional. Systematically prioritizing functional sites from a large number of phosphorylation sites will be increasingly important for the study of their biological roles. This study focused on exploring the intrinsic features of functional phosphorylation sites to predict whether a phosphosite is likely to be functional. We found significant differences in the distribution of evolutionary conservation, kinase association, disorder score, and secondary structure between known functional and background phosphorylation datasets. We built four different types of classifiers based on the most representative features and found that their performances were similar. We also prioritized 213,837 human phosphorylation sites from a variety of phosphorylation databases, which will be helpful for subsequent functional studies. All predicted results are available for query and download on our website (Predict Functional Phosphosites, PFP, http://pfp.biosino.org/).
Highlights
Conservation alone is not sufficient for measuring the function of a site, as some functional phosphosites are not conserved at specific positions[22,23]
Beltrao et al prioritized the functional relevance of post-translational modifications by predicting sites that were likely to be involved in cross-regulatory events, domain activity regulation, or protein-protein interactions[24]
The current study focused on evaluating the intrinsic characteristics of functional phosphosites and predicting whether a phosphosite is likely to be functional using multiple integrated characteristics
Summary
Conservation alone is not sufficient for measuring the function of a site, as some functional phosphosites are not conserved at specific positions[22,23]. Their study highlighted the importance of using multiple sources of information to characterize functional phosphosites. A systematic method of integrating and evaluating the features for functional phosphosite identification was not provided. The current study focused on evaluating the intrinsic characteristics of functional phosphosites and predicting whether a phosphosite is likely to be functional using multiple integrated characteristics. Kinase association and structure information were explored and compared in both known functional and background phosphosite datasets. We used the model to screen all human phosphosites collected from a variety of databases to provide the most likely candidates for further study
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