Application of function domain and pseudo amino acid composition to predict hetero-oligomer protein structural types
With the avalanche of protein sequences generated in the post-genomic age, it is highly desirable to develop an automated method by which crystallographic scientists can rapidly and effectively identify which quaternary attribute a particular protein chain has according to its sequence information. Given most of the previous studies are limited to homo-oligomers, in this paper, we will try to identify the quaternary attribute of hetero-oligomer proteins. For a hetero-oligomer, its type will be identified among the following six categories: (1) heterodimer, (2) heterotrimer, (3) heterotetramer, (4) heteropentamer, (5) heterohexamer, (6) heterooctamer. Using machine learning approach, the Fuzzy Nearest Neighbor Algorithm (FKNN), we developed a prediction system for protein quaternary structural type in which we incorporated functional domain composition (FunD) and pseudo-amino acid composition (PseAA). The overall accuracy achieved by this system is more than 80% in the Jack-knife test. Such a technique should improve the success rate of structural biology projects.
Xuan Xiao Pu Wang
School of Mechanical & Electronic Engineering ,Jing-De-Zhen Ceramic Institute,Jing-De-Zhen 333000, C School of Mechanical & Electronic Engineering,Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333000, C
国际会议
成都
英文
1-4
2010-06-18（万方平台首次上网日期，不代表论文的发表时间）