Gly-PseAAC: Identifying protein lysine glycation through sequences

doi:10.1016/j.gene.2016.11.021

	Gly-PseAAC: Identifying protein lysine glycation through sequences
	Xu, Yan 1; Li, Li 1; Ding, Jun 1; Wu, Ling-Yun 2; Mai, Guoqin 3; Zhou, Fengfeng 4,5
刊名	GENE
	2017-02-20
卷号	602 页码:1-7
关键词	Glycation Amino acid propensity Support Vector Machine
ISSN号	0378-1119
DOI	10.1016/j.gene.2016.11.021
英文摘要	Background: Similar to the regular enzymatic glycosylation, glycation also attaches a sugar molecule to a peptide, but does not need the help of an enzyme. Glycation may occur both inside and outside the host body, and will compete with the glycosylation procedure for functional regulation of mature protein products. The glycated residues do not show significant patterns, which make both in silico sequence-level predictors and wet-lab validations a major challenge. This study hypothesizes that a better feature set formulated from the glycated flanking peptides may lead to a good glycation prediction program. Results: We explored the application of sequence order information and position specific amino acid propensity (PSAAP) in the glycation residue prediction problem. The PSAAP demonstrated its ability to discriminate the glycated residues from the background control peptides. A Support Vector Machine (SVM) model was constructed from the training dataset and achieved 68.91% in the overall accuracy. The model also achieves 0.7258 and 0.3198 in the Area under the ROC and Matthew's Correlation Coefficient, respectively. The user-friendly online version of the proposed algorithm may be found on the web server Gly-PseAAC at http://app.aporc.org/Gly-PseAAC/. Conclusion: The feature set PSAAP was calculated and led to a useful classification of glycation residues. (C) 2016 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[11301024] ; National Natural Science Foundation of China[11671032] ; National Natural Science Foundation of China[11371365] ; National Natural Science Foundation of China[11131009] ; Fundamental Research Funds for the Central Universities[FRF-BR-15-075A] ; Chinese Academy of Sciences[XDB13040400] ; Shenzhen Peacock Plan[KQCX20130628112914301] ; Shenzhen Peacock Plan[KQCX20130628112914291] ; Shenzhen Research Grants[ZDSY20120617113021359] ; Shenzhen Research Grants[CXB201104220026A] ; Shenzhen Research Grants[JCYJ20130401170306884]
WOS研究方向	Genetics & Heredity
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000393016300001
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/24644]
专题	中国科学院数学与系统科学研究院
通讯作者	Mai, Guoqin; Zhou, Fengfeng
作者单位	1.Univ Sci & Technol Beijing, Dept Informat & Comp Sci, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Shenzhen Inst Adv Technol, Ctr Synthet Biol Engn Res, Shenzhen 518055, Guangdong, Peoples R China 4.Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China 5.Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Jilin, Peoples R China
推荐引用方式 GB/T 7714	Xu, Yan,Li, Li,Ding, Jun,et al. Gly-PseAAC: Identifying protein lysine glycation through sequences[J]. GENE,2017,602:1-7.
APA	Xu, Yan,Li, Li,Ding, Jun,Wu, Ling-Yun,Mai, Guoqin,&Zhou, Fengfeng.(2017).Gly-PseAAC: Identifying protein lysine glycation through sequences.GENE,602,1-7.
MLA	Xu, Yan,et al."Gly-PseAAC: Identifying protein lysine glycation through sequences".GENE 602(2017):1-7.