Application of protein grey incidence degree measure to predict protein quaternary structural types

被引:29
作者
Xiao, Xuan [1 ]
Lin, Wei-Zhong [1 ]
机构
[1] Jing De Zhen Ceram Inst, Dept Comp, Jing De Zhen 333001, Peoples R China
基金
中国国家自然科学基金;
关键词
Protein sequence distance measure; Grey system; Grey incidence degree; Protein quaternary structural type; Nearest neighbor algorithm; AMINO-ACID-COMPOSITION; SUBCELLULAR LOCATION PREDICTION; FUNCTIONAL DOMAIN COMPOSITION; SUPPORT VECTOR MACHINE; STATE ENZYME-KINETICS; COMPLEXITY MEASURE FACTOR; INFLUENZA-A VIRUS; WEB-SERVER; ENSEMBLE CLASSIFIER; DRUG DESIGN;
D O I
10.1007/s00726-008-0212-9
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Many proteins are composed of two or more subunits, each associated with different polypeptide chains. The number and arrangement of subunits forming a protein are referred to as quaternary structure. It has been known for long that the functions of proteins are closely related to their quaternary structure. In this paper the grey incidence degree is introduced that can calculate the numerical relation between various components, expressed the similar or different degree between these components. We have demonstrated that introduction of the grey incidence degree can remarkably enhance the success rates in predicting the protein quaternary structural class. It is anticipated that the grey incidence degree can be also used to predict many other protein attributes, such as subcellular localization, membrane protein type, enzyme functional class, GPCR type, protease type, among many others.
引用
收藏
页码:741 / 749
页数:9
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