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Nucleic Acids Research 2006 34(Web Server issue):W254-W257; doi:10.1093/nar/gkl207
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© The Author 2006. Published by Oxford University Press. All rights reserved
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Article

SUMOsp: a web server for sumoylation site prediction

Yu Xue1, Fengfeng Zhou2, Chuanhai Fu1,3, Ying Xu2,* and Xuebiao Yao1,3,*

1 Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China Hefei, China 230027 2 Computational Systems Biology Laboratory, Department of Biochemical and Molecular Biology, and Institute of Bioinformatics, University of Georgia Athens, GA 30602, USA 3 Department of Physiology and Cancer Research Program, Morehouse School of Medicine Atlanta, GA 30310, USA

*To whom correspondence should be addressed. Tel: +86 551 3606304; Fax: 001 404 752 1045; Email: yaoxb{at}ustc.edu.cn

*Correspondence may also be addressed to Ying Xu. Tel: +001 706 542 9779; Fax: +001 706 542 9751; Email: xyn{at}bmb.uga.edu

Received January 27, 2006. Revised March 13, 2006. Accepted March 22, 2006.

Systematic dissection of the sumoylation proteome is emerging as an appealing but challenging research topic because of the significant roles sumoylation plays in cellular dynamics and plasticity. Although several proteome-scale analyzes have been performed to delineate potential sumoylatable proteins, the bona fide sumoylation sites still remain to be identified. Previously, we carried out a genome-wide analysis of the SUMO substrates in human nucleus using the putative motif {psi}-K-X-E and evolutionary conservation. However, a highly specific predictor for in silico prediction of sumoylation sites in any individual organism is still urgently needed to guide experimental design. In this work, we present a computational system SUMOsp—SUMOylation Sites Prediction, based on a manually curated dataset, integrating the results of two methods, GPS and MotifX, which were originally designed for phosphorylation site prediction. SUMOsp offers at least as good prediction performance as the only available method, SUMOplot, on a very large test set. We expect that the prediction results of SUMOsp combined with experimental verifications will propel our understanding of sumoylation mechanisms to a new level. SUMOsp has been implemented on a freely accessible web server at: http://bioinformatics.lcd-ustc.org/sumosp/.

The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors


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