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Prediction of protein secondary structure content by using the concept of Chou's pseudo amino acid composition and support vector machine.

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WOS被引频次:206
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成果类型:
期刊论文
作者:
Chen, Chao*;Chen, Lixuan;Zou, Xiaoyong;Cai, Peixiang
通讯作者:
Chen, Chao
作者机构:
[Chen, Lixuan] Guangzhou Inst Standardizat, Guangzhou 510170, Guangdong, Peoples R China.
[Zou, Xiaoyong; Cai, Peixiang] Sun Yat Sen Univ, Sch Chem & Chem Engn, Guangzhou 510275, Guangdong, Peoples R China.
[Chen, Chao] Guangdong Pharmaceut Univ, Sch Tradit Chinese Med, Guangzhou 510006, Guangdong, Peoples R China.
通讯机构:
[Chen, C] Guangdong Pharmaceut Univ, Sch Tradit Chinese Med, Guangzhou 510006, Guangdong, Peoples R China.
语种:
英文
关键词:
Pseudo Amino acid composition;support vector machine;protein secondary structure content;prediction
期刊:
Protein and peptide letters
ISSN:
0929-8665
年:
2009
卷:
16
期:
1
页码:
27-31
文献类别:
WOS:Article
所属学科:
ESI学科类别:生物学与生物化学;WOS学科类别:Biochemistry & Molecular Biology
入藏号:
WOS:000263980100004;PMID:19149669
基金类别:
Scientific Research Foundation for Doctoral Program of Guangdong Pharmaceutical University [2007ZYX05]; National Natural Science Foundation of China [20475068, 20575082]; Natural Science Foundation of Guangdong Province [7003714]; Scientific Technology Project of Guangdong Province [2005B30101003]
机构署名:
本校为第一且通讯机构
院系归属:
中药学院
摘要:
Protein secondary structure carries information about local structural arrangements. Significant majority of successful methods for predicting the secondary structure is based on multiple sequence alignment. However, the multiple alignment fails to achieve accurate results when a protein sequence is characterized by low homology. To this end, we propose a novel method for prediction of secondary structure content through comprehensive sequence representation. The method is featured by employing a support vector machine (SVM) regressing system and adopting a different pseudo amino acid composition (PseAAC), which can partially take into account the sequence-order effects to represent protein samples. It was shown by both the self-consistency test and the independent-dataset test that the trained SVM has remarkable power in grasping the relationship between the PseAAC and the content of protein secondary structural elements, including alpha-helix, 3(10)-helix, pi-helix, beta-strand, beta-bridge, turn, bend and the rest random coil. Results prior to or competitive with the popular methods have been obtained, which indicate that the present method may at least serve as an alternative to the existing predictors in this area.
参考文献:
Chou KC, 2001, PROTEINS, V43, P246, DOI 10.1002/prot.1035
Du QS, 2003, PEPTIDES, V24, P1863, DOI 10.1016/j.peptides.2003.10.012
Chou KC, 2007, BIOCHEM BIOPH RES CO, V357, P633, DOI 10.1016/j.bbrc.2007.03.162
Chen C, 2006, ANAL BIOCHEM, V357, P116, DOI 10.1016/j.ab.2006.07.022
Jones DT, 1999, J MOL BIOL, V292, P195, DOI 10.1006/jmbi.1999.3091

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