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Bioinformatics Advance Access originally published online on January 24, 2006
Bioinformatics 2006 22(7):894-896; doi:10.1093/bioinformatics/btl013
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
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CSS-Palm: palmitoylation site prediction with a clustering and scoring strategy (CSS)

Fengfeng Zhou 1,{dagger}, Yu Xue 2,{dagger}, Xuebiao Yao 2,3,* and Ying Xu 1,*

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

*To whom correspondence should be addressed.

Summary: Palmitoylation is an important post-translational lipid modification of proteins. Unlike prenylation and myristoylation, palmitoylation is a reversible covalent modification, allowing for dynamic regulation of multiple complex cellular systems. However, in vivo or in vitro identification of palmitoylation sites is usually time-consuming and labor-intensive. So in silico predictions could help to narrow down the possible palmitoylation sites, which can be used to guide further experimental design. Previous studies suggested that there is no unique canonical motif for palmitoylation sites, so we hypothesize that the bona fide pattern might be compromised by heterogeneity of multiple structural determinants with different features. Based on this hypothesis, we partition the known palmitoylation sites into three clusters and score the similarity between the query peptide and the training ones based on BLOSUM62 matrix. We have implemented a computer program for palmitoylation site prediction, Clustering and Scoring Strategy for Palmitoylation Sites Prediction (CSS-Palm) system, and found that the program's prediction performance is encouraging with highly positive Jack-Knife validation results (sensitivity 82.16% and specificity 83.17% for cut-off score 2.6). Our analyses indicate that CSS-Palm could provide a powerful and effective tool to studies of palmitoylation sites.

Availability: CSS-Palm is implemented in PHP/PERL+MySQL and can be freely accessed at http://bioinformatics.lcd-ustc.org/css_palm/

Contact: yaoxb{at}ustc.edu.cn; xuyn{at}bmb.uga.edu

Supplementary information: Supplementary data are available at Bionformatics online.

Received on December 20, 2005; revised on January 19, 2006; accepted on January 20, 2006

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