tetano
Editor, Senior Moderator
BMC Med Genomics. 2017 Dec 21;10(Suppl 4):78. doi: 10.1186/s12920-017-0301-2.
[h=1]Analysis of viral diversity for vaccine target discovery.[/h] Khan AM[SUP]1,[/SUP][SUP]2[/SUP], Hu Y[SUP]3[/SUP], Miotto O[SUP]4,[/SUP][SUP]5[/SUP], Thevasagayam NM[SUP]3[/SUP], Sukumaran R[SUP]3[/SUP], Abd Raman HS[SUP]6[/SUP], Brusic V[SUP]7[/SUP], Tan TW[SUP]3[/SUP], Thomas August J[SUP]8[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] 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.
[h=4]RESULTS:[/h] 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.
[h=4]CONCLUSION:[/h] 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.
[h=4]KEYWORDS:[/h] Bioinformatics; Database; Reverse vaccinology; Target discovery; Tools; Vaccine design; Viral diversity
PMID: 29322922 DOI: 10.1186/s12920-017-0301-2
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[h=1]Analysis of viral diversity for vaccine target discovery.[/h] Khan AM[SUP]1,[/SUP][SUP]2[/SUP], Hu Y[SUP]3[/SUP], Miotto O[SUP]4,[/SUP][SUP]5[/SUP], Thevasagayam NM[SUP]3[/SUP], Sukumaran R[SUP]3[/SUP], Abd Raman HS[SUP]6[/SUP], Brusic V[SUP]7[/SUP], Tan TW[SUP]3[/SUP], Thomas August J[SUP]8[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]BACKGROUND:[/h] 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.
[h=4]RESULTS:[/h] 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.
[h=4]CONCLUSION:[/h] 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.
[h=4]KEYWORDS:[/h] Bioinformatics; Database; Reverse vaccinology; Target discovery; Tools; Vaccine design; Viral diversity
PMID: 29322922 DOI: 10.1186/s12920-017-0301-2
Free full text