Analysis of viral diversity for vaccine target discovery.
Analysis of viral diversity for vaccine target discovery.
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DOI：
10.1186/s12920-017-0301-2
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发表时间：
2017-12-21
影响因子：
2.7
通讯作者：
Thomas August J
中科院分区：
文献类型：
--
作者：
Khan AM;Hu Y;Miotto O;Thevasagayam NM;Sukumaran R;Abd Raman HS;Brusic V;Tan TW;Thomas August J
Viral vaccine target discovery requires understanding the diversity of both the virus and the human immune system. The readily available and rapidly growing pool of viral sequence data in the public domain enable the identification and characterization of immune targets relevant to adaptive immunity. A systematic bioinformatics approach is necessary to facilitate the analysis of such large datasets for selection of potential candidate vaccine targets. This work describes a computational methodology to achieve this analysis, with data of dengue, West Nile, hepatitis A, HIV-1, and influenza A viruses as examples. Our methodology has been implemented as an analytical pipeline that brings significant advancement to the field of reverse vaccinology, enabling systematic screening of known sequence data in nature for identification of vaccine targets. This includes key steps (i) comprehensive and extensive collection of sequence data of viral proteomes (the virome), (ii) data cleaning, (iii) large-scale sequence alignments, (iv) peptide entropy analysis, (v) intra- and inter-species variation analysis of conserved sequences, including human homology analysis, and (vi) functional and immunological relevance analysis. These steps are combined into the pipeline ensuring that a more refined process, as compared to a simple evolutionary conservation analysis, will facilitate a better selection of vaccine targets and their prioritization for subsequent experimental validation. The online version of this article (10.1186/s12920-017-0301-2) contains supplementary material, which is available to authorized users.
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影响因子：
3.7
作者：
Hu YF;Lee KT;Wang HH;Ueng KC;Yeh HI;Chao TF;Liao JN;Lin YJ;Chang SL;Lo LW;Tuan TC;Li CH;Chung FP;Hsu CP;Chang HH;Huang CH;Chen SA
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Chen SA
影响因子：
82.9
作者：
Fischer, Will;Perkins, Simon;Korber, Bette T.
通讯作者：
Korber, Bette T.
影响因子：
4.8
作者：
Brusic, V;Bajic, VB;Petrovsky, N
通讯作者：
Petrovsky, N
影响因子：
5.9
作者：
Garcia-Sastre, Adolfo;Mena, Ignacio
通讯作者：
Mena, Ignacio
影响因子：
3
作者：
Camacho C;Coulouris G;Avagyan V;Ma N;Papadopoulos J;Bealer K;Madden TL
通讯作者：
Madden TL