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Using ensemble SVM to identify human GPCRs N-linked glycosylation sites based on the general form of Chou's PseAAC

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WOS被引频次:24
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成果类型:
期刊论文
作者:
Hua-Lin Xie;Liang Fu;Xi-Du Nie;Hua-Lin Xie;Liang Fu;Xi-Du Nie
通讯作者:
Xie, H.-L.(hualinxie@163.com)
作者机构:
[Hua-Lin Xie] School of Chemistry and Chemical Engineering, Yangtze Normal University, Fuling 408100, China
[Xi-Du Nie] College of Material and Chemical Engineering, Hunan Institute of Technology, Hengyang 421002, China
[Liang Fu; Hua-Lin Xie] School of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
通讯机构:
[Xie, HL] Cent S Univ, Sch Chem & Chem Engn, Changsha 410083, Peoples R China.
语种:
英文
关键词:
Biotechnology applications - Correlation coefficient - Experimental identification - G-protein coupled receptors - N-linked glycosylation - Post-translational modifications - Signal transduction pathways - Transmembrane receptors
期刊:
Protein engineering, design & selection : PEDS
ISSN:
1741-0126
年:
2013
卷:
26
期:
11
页码:
735-742
文献类别:
WOS:Article;EI:Journal article (JA)
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;Biotechnology & Applied Microbiology
入藏号:
WOS:000326382100002;EI:20135217118827;PMID:24048266
基金类别:
Educational Commission of Chongqing City of China [KJ121311, KJ131323]; Hunan Postdoctoral Scientific Program
机构署名:
本校为其他机构
院系归属:
材料与化学工程学院
摘要:
As the most frequent drug target, G-protein coupled receptors (GPCRs) are a large family of seven transmembrane receptors that sense molecules outside the cell and activate inside signal transduction pathways. Glycosylation is one of the most complex post-translational modifications (PTMs) of proteins in eukaryotic cells. It plays important roles in a variety of cellular functions, including protein folding, protein trafficking and localization, cell-cell interactions and epitope recognition. Therefore, investigating the exact position of glycosylation site in GPCR sequence can provide useful clues for drug design and other biotechnology applications. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is a significant interest in the development of computational methods for reliable prediction of glycosylation sites from amino acid sequences. In this article, we presented an effective method to recognize the sites of human GPCRs by combining amino acid hydrophobicity with ensemble support vector machine. The prediction accuracy, sensitivity, specificity, Matthews correlation coefficient and area under the curve values were 94.4, 89.7, 98.9%, 0.895 and 0.989, respectively. The establishment of such a fast and accurate prediction method will speed up the pace of identifying proper GPCRs functional sites to facilitate drug discovery. ©The Author 2013.
参考文献:
Abeel T, 2009, BIOINFORMATICS, V26, P392
Ahn H, 2007, COMPUT STAT DATA AN, V51, P6166, DOI 10.1016/j.csda.2006.12.043
Attwood TK, 2002, PROTEIN ENG, V15, P7, DOI 10.1093/protein/15.1.7
BALDWIN JM, 1994, CURR OPIN CELL BIOL, V6, P180, DOI 10.1016/0955-0674(94)90134-1
Betts MJ, 2003, BIOINFORMATICS GENET

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