Abstract:
BACKGROUND:Cysteine S-sulfenylation is a major type of dynamic post-translational modification of the protein that plays an important role in regulating many biological processes in both of prokaryotic and eukaryotic species. To understand the function of S-sulfenylated proteins, identification of S-sulfenylation sites is an essential step. Due to numerous restrictions of experimental methods, computational prediction of the potential S-sulfenylation sites becomes popular. In this review, we discuss the recent development and challenges in protein S-sulfenylation site prediction from the available datasets, algorithms and accessible services. We also demonstrate the encountered limitation and future perspective of the computational prediction tools. CONCLUSION:The development of S-sulfenylation site prediction and their application is an emerging field of protein bioinformatics research. Accurate predictors are expected to identify general and species-specific S-sulfenylation sites when more experimental annotation data are available. Combining experimental and computational technologies will definitely accelerate an understanding of protein S-sulfenylation, discovering regulatory networks in living organisms.
journal_name
Protein Pept Lettjournal_title
Protein and peptide lettersauthors
Hasan MM,Khatun MS,Kurata Hdoi
10.2174/0929866525666180905110619subject
Has Abstractpub_date
2018-01-01 00:00:00pages
815-821issue
9eissn
0929-8665issn
1875-5305pii
PPL-EPUB-92829journal_volume
25pub_type
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journal_title:Protein and peptide letters
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journal_title:Protein and peptide letters
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journal_title:Protein and peptide letters
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journal_title:Protein and peptide letters
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journal_title:Protein and peptide letters
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journal_title:Protein and peptide letters
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journal_title:Protein and peptide letters
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