Independent Test
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Tyrosine sulfation is a post-translational modification occurring on many secreted and membrane-bound proteins. Previous studies have implicated tyrosine sulfation as a determinant of protein-protein interactions involved in leukocyte adhesion, hemostasis and chemokine signalling. Furthermore, sulfation typically facilitates excretion of metabolites by making the compounds more water soluble. However, the intrinsic feature of sulfated protein is still elusive and remains to be delineated. In this investigation, we present SulfoSite, a computational method based on support vector machine (SVM) for prediction of sulfotyrosine sites with proteins. The method was developed to consider the structural information such as secondary structure and solvent accessibility surrounding the tyrosine sulfation sites. 162 experimentally verified tyrosine sulfation sites were extracted from UniProtKB/SwissProt release 53.0, then removed the homologous sequences with a given window size. Following the evaluation of 5-fold cross-validation, the results indicate that the value of solvent accessibility surrounding the sulfotyrosine sites can improve the prediction accuracy. The SVM classifier was able to accomplish an accuracy of 84 % in the independent test. This method significantly outperforms previous attempts of tyrosine sulfation sites predictions. The effective SulfoSite is freely accessible from http://SulfoSite.mbc.nctu.edu.tw.

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Data Statistics

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The ExPASy (Expert Protein Analysis System) proteomics server of the Swiss Institute of Bioinformatics (SIB) is dedicated to the analysis of protein sequences and structures as well as 2-D PAGE
A curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domains structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases
An information repository of protein post-translational modification
The Sulfinator predicts tyrosine sulfation sites in protein sequences

Bid Lab, Institute of Bioinformatics, National Chiao Tung University , Taiwan.
Contact us:bryan@mail.nctu.edu.tw with questions or comments.