About SUMOhydro

SUMOhydro has been developed to predict sumoylation lysine (K) sites in proteins by introduction of hydrophobicity to binary encoding. With the assistance of Support Vector Machine (SVM)(, the predictor was trained and tested in a new and stringent sumoylation sites dataset.

The proposed SUMOhydro has been proved to be more powerful than the traditional methods which constructed the prediction model based on all the sumoylation sites.  when compared with two existing predictors, it can serve as a competitive method in predicting sumoylation sites.


The input is a single-letter AA code sequence in FASTA format without the FASTA header, the email address is required since the result will be sent to it. A session ID will be generated when you submit a sequence, and you can query the result through this ID when the processing is ready. The result page consists of position, residue name, prediction score and glycosylation annotations (yes or no). A higher absolute value of prediction score implies a more confident prediction. Additionally, graph output is also given in the result page to show all the positions of serine and threonine of a query protein and the corresponding prediction score.

The output consists of 5 columns: position, residue, prediction score,  sumoylation annotation (yes for positive result). The predictions are made on all lysine residues of a query sequence. Only residues with the score >0 are considered to be sumoylated. A high score implies a more confident positive prediction. Graphical output shows directly the prediction result. The red line represents the threshold of prediction(which is zero), and the green line indicates the prediction score. If it is larger than zero it is predicted as sumoylated, otherwise it is predicted as non-sumoylation site.

Datasets and source code

Available under request from Yong-Zi CHEN.


Ziding Zhang's Laboratory of Protein Bioinformatics

ZhenSu's Lab

CAU Bioinfo Center


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