TY - JOUR
T1 - Identification and characterization of lysine-methylated sites on histones and non-histone proteins
AU - Lee, Tzong Yi
AU - Chang, Cheng Wei
AU - Lu, Cheng Tzung
AU - Cheng, Tzu Hsiu
AU - Chang, Tzu Hao
N1 - Funding Information:
The authors would like to thank the National Science Council of the Republic of China for financially supporting this research under Contract Nos. NSC 101-2628-E-155-002-MY2 and NSC 102-2221-E-266-005- . This work was supported in part by Taipei Medical University under grant TMU101-AE1-B44 .
Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014/6
Y1 - 2014/6
N2 - Protein methylation is a kind of post-translational modification (PTM), and typically takes place on lysine and arginine amino acid residues. Protein methylation is involved in many important biological processes, and most recent studies focused on lysine methylation of histones due to its critical roles in regulating transcriptional repression and activation. Histones possess highly conserved sequences and are homologous in most species. However, there is much less sequence conservation among non-histone proteins. Therefore, mechanisms for identifying lysine-methylated sites may greatly differ between histones and non-histone proteins. Nevertheless, this point of view was not considered in previous studies. Here we constructed two support vector machine (SVM) models by using lysine-methylated data from histones and non-histone proteins for predictions of lysine-methylated sites. Numerous features, such as the amino acid composition (AAC) and accessible surface area (ASA), were used in the SVM models, and the predictive performance was evaluated using five-fold cross-validations. For histones, the predictive sensitivity was 85.62% and specificity was 80.32%. For non-histone proteins, the predictive sensitivity was 69.1% and specificity was 88.72%. Results showed that our model significantly improved the predictive accuracy of histones compared to previous approaches. In addition, features of the flanking region of lysine-methylated sites on histones and non-histone proteins were also characterized and are discussed. A gene ontology functional analysis of lysine-methylated proteins and correlations of lysine-methylated sites with other PTMs in histones were also analyzed in detail. Finally, a web server, MethyK, was constructed to identify lysine-methylated sites.
AB - Protein methylation is a kind of post-translational modification (PTM), and typically takes place on lysine and arginine amino acid residues. Protein methylation is involved in many important biological processes, and most recent studies focused on lysine methylation of histones due to its critical roles in regulating transcriptional repression and activation. Histones possess highly conserved sequences and are homologous in most species. However, there is much less sequence conservation among non-histone proteins. Therefore, mechanisms for identifying lysine-methylated sites may greatly differ between histones and non-histone proteins. Nevertheless, this point of view was not considered in previous studies. Here we constructed two support vector machine (SVM) models by using lysine-methylated data from histones and non-histone proteins for predictions of lysine-methylated sites. Numerous features, such as the amino acid composition (AAC) and accessible surface area (ASA), were used in the SVM models, and the predictive performance was evaluated using five-fold cross-validations. For histones, the predictive sensitivity was 85.62% and specificity was 80.32%. For non-histone proteins, the predictive sensitivity was 69.1% and specificity was 88.72%. Results showed that our model significantly improved the predictive accuracy of histones compared to previous approaches. In addition, features of the flanking region of lysine-methylated sites on histones and non-histone proteins were also characterized and are discussed. A gene ontology functional analysis of lysine-methylated proteins and correlations of lysine-methylated sites with other PTMs in histones were also analyzed in detail. Finally, a web server, MethyK, was constructed to identify lysine-methylated sites.
KW - Histone
KW - Lysine
KW - Methylation
KW - Non-histone
KW - PTM
KW - Post-translational modification
KW - SVM
KW - Support vector machine
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U2 - 10.1016/j.compbiolchem.2014.01.009
DO - 10.1016/j.compbiolchem.2014.01.009
M3 - Article
C2 - 24560580
AN - SCOPUS:84902242497
SN - 1476-9271
VL - 50
SP - 11
EP - 18
JO - Computational Biology and Chemistry
JF - Computational Biology and Chemistry
ER -