Cysteine S-sulfenylation is an important post-translational modification (PTM) in proteins, and provides redox regulation of protein functions. Bioinformatics and structural analyses indicated that S-sulfenylation could impact many biological and functional categories and had distinct structural features. However, major limitations for identifying cysteine S-sulfenylation were expensive and low-throughout. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor iSulf-Cys which incorporated 14 kinds of physicochemical properties of amino acids was proposed. With the 10-fold cross-validation, the value of area under the curve (AUC) was 0.7155 ± 0.0085, MCC 0.3122 ± 0.0144 on the training dataset for 20 times. iSulf-Cys also showed satisfying performance in the independent testing dataset with AUC 0.7343 and MCC 0.3315. Features which were constructed from physicochemical properties and position were carefully analyzed. Meanwhile, a user-friendly webserver for iSulf-Cys is accessible at http://app.aporc.org/iSulf-Cys/.
CITATION STYLE
Xu, Y., Ding, J., & Wu, L. Y. (2016). iSulf-Cys: Prediction of S-Sulfenylation sites in proteins with physicochemical properties of amino acids. PLoS ONE, 11(4). https://doi.org/10.1371/journal.pone.0154237
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