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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

The mean value of normalized van der Waals volume (VDWV) of residues around methylation sites and non-methylation sites.
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pone-0038772-g003: The mean value of normalized van der Waals volume (VDWV) of residues around methylation sites and non-methylation sites.

Mentions: Figure 3 gives the mean values of normalized van der Waals volume (VDWV) of residues around methylation sites and non-methylation sites based on training data. From −7 to +7 positions, the mean values of VDWV of residues surrounding methylarginine were lower than those of non-methylarginine, especially for the -1 and +1 position. Most of P-values were less than 0.05 (see Table S7), indicating that there was significant difference between the VDWV surrounding methylarginine and that surrounding non-methylarginine. From −7 to −1 positions, there was obvious difference between the VDWV surrounding methyllysine and that surrounding non-methyllysine (P≤1.24e-05). This reveals that the upstream residues may have a significant influence on 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)

The mean value of normalized van der Waals volume (VDWV) of residues around methylation sites and non-methylation sites.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0038772-g003: The mean value of normalized van der Waals volume (VDWV) of residues around methylation sites and non-methylation sites.
Mentions: Figure 3 gives the mean values of normalized van der Waals volume (VDWV) of residues around methylation sites and non-methylation sites based on training data. From −7 to +7 positions, the mean values of VDWV of residues surrounding methylarginine were lower than those of non-methylarginine, especially for the -1 and +1 position. Most of P-values were less than 0.05 (see Table S7), indicating that there was significant difference between the VDWV surrounding methylarginine and that surrounding non-methylarginine. From −7 to −1 positions, there was obvious difference between the VDWV surrounding methyllysine and that surrounding non-methyllysine (P≤1.24e-05). This reveals that the upstream residues may have a significant influence on 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