Predicting homo-oligomers and hetero-oligomers by pseudo-amino acid composition: An approach from discrete wavelet transformation

被引:12
作者
Qiu, Jian-Ding [1 ,2 ]
Sun, Xing-Yu [1 ]
Suo, Sheng-Bao [1 ]
Shi, Shao-Ping [1 ]
Huang, Shu-Yun [1 ]
Liang, Ru-Ping [1 ]
Zhang, Li [1 ]
机构
[1] Nanchang Univ, Dept Chem, Nanchang 330031, Jiangxi, Peoples R China
[2] Pingxiang Coll, Dept Chem Engn, Pingxiang 337055, Peoples R China
基金
中国国家自然科学基金;
关键词
Protein quaternary structures; Discrete wavelet transform; Support vector machine; Jackknife test; SUPPORT VECTOR MACHINES; PROTEIN QUATERNARY STRUCTURE; FUNCTIONAL DOMAIN COMPOSITION; STRUCTURAL CLASS PREDICTION; SUBCELLULAR LOCATION; BIOLOGICAL FUNCTIONS; CLEAVAGE SITES; TURN TYPES; CLASSIFICATION; SEQUENCES;
D O I
10.1016/j.biochi.2011.03.010
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 exist in vivo as oligomers with different quaternary structural attributes rather than as individual chains. These proteins are the structural components of various biological functions, including cooperative effects, allosteric mechanisms and ion-channel gating. With the dramatic increase in the number of protein sequences submitted to the public databank, it is important for both basic research and drug discovery research to acquire the knowledge about possible quaternary structural attributes of their interested proteins in a timely manner. A high-throughput method (DWT_SVM), fusing discrete wavelet transform (DWT) and support vector machine (SVM) classifier algorithm with various physicochemical features, has been developed to predict protein quaternary structure. The accuracy in distinguishing candidate proteins as homo-oligomer or hetero-oligomer using the dataset R-2720 was 85.95% and 85.49% respectively by jackknife, showing that DWT_SVM is guide promising in predicting protein quaternary structures. The online service is available at http://bioinfo.ncu.edu.cn/Services.aspx. Protein sequences in FASTA format can be directly fed to the system OligoPred. The processed results will be presented in a diagram that includes the information of feature extraction and the classification error rate. (C) 2011 Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:1132 / 1138
页数:7
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