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PMeS: prediction of methylation sites based on enhanced feature encoding scheme.

Shi SP, Qiu JD, Sun XY, Suo SB, Huang SY, Liang RP - PLoS ONE (2012)

Bottom Line: Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction.Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases.The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry, Nanchang University, Nanchang, People's Republic of China.

ABSTRACT
Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction. Given their important involvement in gene expression, protein methylation and their regulatory enzymes are implicated in a variety of human disease states such as cancer, coronary heart disease and neurodegenerative disorders. Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases. In this study, we developed a method called PMeS to improve the prediction of protein methylation sites based on an enhanced feature encoding scheme and support vector machine. The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area. The PMeS achieved a promising performance with a sensitivity of 92.45%, a specificity of 93.18%, an accuracy of 92.82% and a Matthew's correlation coefficient of 85.69% for arginine as well as a sensitivity of 84.38%, a specificity of 93.94%, an accuracy of 89.16% and a Matthew's correlation coefficient of 78.68% for lysine in 10-fold cross validation. Compared with other existing methods, the PMeS provides better predictive performance and greater robustness. It can be anticipated that the PMeS might be useful to guide future experiments needed to identify potential methylation sites in proteins of interest. The online service is available at http://bioinfo.ncu.edu.cn/inquiries_PMeS.aspx.

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Related in: MedlinePlus

Sequence logo plots of methylation sites and non-methylation sites represent normalized amino acid frequencies for ±7 amino acids.
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pone-0038772-g004: Sequence logo plots of methylation sites and non-methylation sites represent normalized amino acid frequencies for ±7 amino acids.

Mentions: PWAA feature reflects the position information of residues surrounding methylation sites and non-methylation sites. In order to analyze position specific properties, we adopted WebLogo [42] to generate the graphical sequence logo for the relative frequency of the corresponding amino acid at each position around methylation and non-methylation sites. As we can see from Figure 4, the methylated arginines (R) are enriched in arginine-glycine (R–G) regions which are much different from non-methylated arginines. Indeed, motif analysis reveals many arginine methylation are associated with RGG/RXG/RGX [43] or GXXR [20] motifs. The conserved residues at specific sequence sites are under strong selective pressure and therefore are always functional relevant. The type I PRMTs is known to methylate a number of proteins that contain an RGG-motif [44]. The repeated RGG-motif is known as a RNA-binding motif [45], and this also supports the role of arginine methylation in the regulation of mRNA binding [46]. In contrast, no amino acids surrounding methylated lysines (K) are obviously conserved in the current available data (Fig. 4). Therefore, sequence profiles of the flanking regions of methylarginine are more conservative with higher specificity than those of methyllysine.


PMeS: prediction of methylation sites based on enhanced feature encoding scheme.

Shi SP, Qiu JD, Sun XY, Suo SB, Huang SY, Liang RP - PLoS ONE (2012)

Sequence logo plots of methylation sites and non-methylation sites represent normalized amino acid frequencies for ±7 amino acids.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3376144&req=5

pone-0038772-g004: Sequence logo plots of methylation sites and non-methylation sites represent normalized amino acid frequencies for ±7 amino acids.
Mentions: PWAA feature reflects the position information of residues surrounding methylation sites and non-methylation sites. In order to analyze position specific properties, we adopted WebLogo [42] to generate the graphical sequence logo for the relative frequency of the corresponding amino acid at each position around methylation and non-methylation sites. As we can see from Figure 4, the methylated arginines (R) are enriched in arginine-glycine (R–G) regions which are much different from non-methylated arginines. Indeed, motif analysis reveals many arginine methylation are associated with RGG/RXG/RGX [43] or GXXR [20] motifs. The conserved residues at specific sequence sites are under strong selective pressure and therefore are always functional relevant. The type I PRMTs is known to methylate a number of proteins that contain an RGG-motif [44]. The repeated RGG-motif is known as a RNA-binding motif [45], and this also supports the role of arginine methylation in the regulation of mRNA binding [46]. In contrast, no amino acids surrounding methylated lysines (K) are obviously conserved in the current available data (Fig. 4). Therefore, sequence profiles of the flanking regions of methylarginine are more conservative with higher specificity than those of methyllysine.

Bottom Line: Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction.Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases.The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry, Nanchang University, Nanchang, People's Republic of China.

ABSTRACT
Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction. Given their important involvement in gene expression, protein methylation and their regulatory enzymes are implicated in a variety of human disease states such as cancer, coronary heart disease and neurodegenerative disorders. Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases. In this study, we developed a method called PMeS to improve the prediction of protein methylation sites based on an enhanced feature encoding scheme and support vector machine. The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area. The PMeS achieved a promising performance with a sensitivity of 92.45%, a specificity of 93.18%, an accuracy of 92.82% and a Matthew's correlation coefficient of 85.69% for arginine as well as a sensitivity of 84.38%, a specificity of 93.94%, an accuracy of 89.16% and a Matthew's correlation coefficient of 78.68% for lysine in 10-fold cross validation. Compared with other existing methods, the PMeS provides better predictive performance and greater robustness. It can be anticipated that the PMeS might be useful to guide future experiments needed to identify potential methylation sites in proteins of interest. The online service is available at http://bioinfo.ncu.edu.cn/inquiries_PMeS.aspx.

Show MeSH
Related in: MedlinePlus