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BioMed Research International
Volume 2014 (2014), Article ID 947416, 12 pages
Research Article

iMethyl-PseAAC: Identification of Protein Methylation Sites via a Pseudo Amino Acid Composition Approach

1Computer Department, Jingdezhen Ceramic Institute, Jingdezhen 333046, China
2Information School, ZheJiang Textile & Fashion College, Ningbo 315211, China
3Gordon Life Science Institute, Boston, MA 02478, USA
4Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 21589, Saudi Arabia

Received 15 February 2014; Revised 26 April 2014; Accepted 29 April 2014; Published 22 May 2014

Academic Editor: Liam McGuffin

Copyright © 2014 Wang-Ren Qiu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Before becoming the native proteins during the biosynthesis, their polypeptide chains created by ribosome’s translating mRNA will undergo a series of “product-forming” steps, such as cutting, folding, and posttranslational modification (PTM). Knowledge of PTMs in proteins is crucial for dynamic proteome analysis of various human diseases and epigenetic inheritance. One of the most important PTMs is the Arg- or Lys-methylation that occurs on arginine or lysine, respectively. Given a protein, which site of its Arg (or Lys) can be methylated, and which site cannot? This is the first important problem for understanding the methylation mechanism and drug development in depth. With the avalanche of protein sequences generated in the postgenomic age, its urgency has become self-evident. To address this problem, we proposed a new predictor, called iMethyl-PseAAC. In the prediction system, a peptide sample was formulated by a 346-dimensional vector, formed by incorporating its physicochemical, sequence evolution, biochemical, and structural disorder information into the general form of pseudo amino acid composition. It was observed by the rigorous jackknife test and independent dataset test that iMethyl-PseAAC was superior to any of the existing predictors in this area.