MeMo: a web tool for prediction of protein methylation modifications

被引:122
作者
Chen, Hu
Xue, Yu
Huang, Ni
Yao, Xuebiao
Sun, Zhirong [1 ]
机构
[1] Tsinghua Univ, Inst Bioinformat & Syst Biol, MOE Key Lab Bioinformat,Dept Biol Sci & Biotechno, State Key Lab Biomembrane & Membrane Biotechnol, Beijing 100084, Peoples R China
[2] Hefei Natl Lab Phys Sci, Lab Cellular Dynam, Hefei 230027, Peoples R China
[3] Univ Sci & Technol China, Hefei 230027, Peoples R China
关键词
D O I
10.1093/nar/gkl233
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Protein methylation is an important and reversible post-translational modification of proteins (PTMs), which governs cellular dynamics and plasticity. Experimental identification of the methylation site is labor-intensive and often limited by the availability of reagents, such as methyl-specific antibodies and optimization of enzymatic reaction. Computational analysis may facilitate the identification of potential methylation sites with ease and provide insight for further experimentation. Here we present a novel protein methylation prediction web server named MeMo, protein methylation modification prediction, implemented in Support Vector Machines (SVMs). Our present analysis is primarily focused on methylation on lysine and arginine, two major protein methylation sites. However, our computational platform can be easily extended into the analyses of other amino acids. The accuracies for prediction of protein methylation on lysine and arginine have reached 67.1 and 86.7%, respectively. Thus, the MeMo system is a novel tool for predicting protein methylation and may prove useful in the study of protein methylation function and dynamics. The MeMo web server is available at: http://www.bioinfo.tsinghua.edu.cn/similar to tigerchen/memo.html.
引用
收藏
页码:W249 / W253
页数:5
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