Qiu Wang-Ren, Xiao Xuan, Lin Wei-Zhong, Chou Kuo-Chen
Computer Department, Jingdezhen Ceramic Institute, Jingdezhen 333046, China.
Computer Department, Jingdezhen Ceramic Institute, Jingdezhen 333046, China ; Information School, ZheJiang Textile & Fashion College, Ningbo 315211, China ; Gordon Life Science Institute, Boston, MA 02478, USA.
Biomed Res Int. 2014;2014:947416. doi: 10.1155/2014/947416. Epub 2014 May 22.
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.
在生物合成过程中成为天然蛋白质之前,核糖体翻译mRNA产生的多肽链会经历一系列“产物形成”步骤,如切割、折叠和翻译后修饰(PTM)。了解蛋白质中的PTM对于各种人类疾病的动态蛋白质组分析和表观遗传遗传至关重要。最重要的PTM之一是分别发生在精氨酸或赖氨酸上的精氨酸或赖氨酸甲基化。对于一种蛋白质,其精氨酸(或赖氨酸)的哪个位点可以被甲基化,哪个位点不能?这是深入理解甲基化机制和药物开发的第一个重要问题。随着后基因组时代产生的蛋白质序列雪崩式增长,其紧迫性已不言而喻。为了解决这个问题,我们提出了一种新的预测器,称为iMethyl-PseAAC。在预测系统中,一个肽样本由一个346维向量表示,该向量通过将其物理化学、序列进化、生化和结构无序信息纳入伪氨基酸组成的一般形式而形成。通过严格的留一法测试和独立数据集测试发现,iMethyl-PseAAC在该领域优于任何现有的预测器。