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. 2014 Jul;42(Web Server issue):W325-30.
doi: 10.1093/nar/gku383. Epub 2014 May 31.

GPS-SUMO: A Tool for the Prediction of Sumoylation Sites and SUMO-interaction Motifs

Free PMC article

GPS-SUMO: A Tool for the Prediction of Sumoylation Sites and SUMO-interaction Motifs

Qi Zhao et al. Nucleic Acids Res. .
Free PMC article


Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP+JavaScript and freely available at


Figure 1.
Figure 1.
Performance evaluation of GPS-SUMO. (A) The performance evaluation for the prediction of sumoylation sites. The Self, LOO and n-fold validations were carried out. (B) The performance evaluation for the prediction of SIM. (C) A performance comparison among GPS-SUMO, SUMOsp 2.0 and seeSUMO. The algorithms of SVMs and RF in seeSUMO were separately validated and compared. The LOO validation was carried out in this comparison. (D) A further evaluation of the sumoylation prediction. An additional test data set was applied to perform this evaluation.
Figure 2.
Figure 2.
A snapshot of the GPS-SUMO web server. (A) As an example, the sequences of DNA replication complex GINS protein SLD5 (GINS4) and E3 ubiquitin-protein ligase Arkadia (RNF111) were inputted into GPS-SUMO. The sumoylation sites and SIMs were predicted using the medium threshold. (B) The prediction result of these two protein sequences. The information on the FASTA title, modified position, modified peptide, predicted score, prediction cutoff and regulation type are presented.

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