Title
Incorporating structural characteristics for identification of protein methylation sites.
Abstract
Studies over the last few years have identified protein methylation on histones and other proteins that are involved in the regulation of gene transcription. Several works have developed approaches to identify computationally the potential methylation sites on lysine and arginine. Studies of protein tertiary structure have demonstrated that the sites of protein methylation are preferentially in regions that are easily accessible. However, previous studies have not taken into account the solvent-accessible surface area (ASA) that surrounds the methylation sites. This work presents a method named MASA that combines the support vector machine with the sequence and structural characteristics of proteins to identify methylation sites on lysine, arginine, glutamate, and asparagine. Since most experimental methylation sites are not associated with corresponding protein tertiary structures in the Protein Data Bank, the effective solvent-accessible prediction tools have been adopted to determine the potential ASA values of amino acids in proteins. Evaluation of predictive performance by cross-validation indicates that the ASA values around the methylation sites can improve the accuracy of prediction. Additionally, an independent test reveals that the prediction accuracies for methylated lysine and arginine are 80.8 and 85.0%, respectively. Finally, the proposed method is implemented as an effective system for identifying protein methylation sites. The developed web server is freely available at http:/IMASA.mbc.nctu.edu.tw/. (C) 2009 Wiley Periodicals, Inc. J Comput Chem 30: 1532-1543, 2009
Year
DOI
Venue
2009
10.1002/jcc.21232
JOURNAL OF COMPUTATIONAL CHEMISTRY
Keywords
Field
DocType
protein methylation,solvent accessible surface area (ASA),support vector machine (SVM)
Protein methylation,Protein tertiary structure,Histone,Biochemistry,Histone methylation,Chemistry,Methylation,Lysine,Protein Data Bank,Protein structure
Journal
Volume
Issue
ISSN
30
9
0192-8651
Citations 
PageRank 
References 
24
1.00
8
Authors
8
Name
Order
Citations
PageRank
Dray-Ming Shien1573.09
Tzong-Yi Lee261737.18
Wen-Chi Chang31488.92
Justin Bo-Kai Hsu41086.69
Jorng-Tzong Horng554167.78
Po-Chiang Hsu6673.48
Ting-Yuan Wang724020.37
Hsien-Da Huang883563.83