Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12920-017-0301-2
Title: Analysis of viral diversity for vaccine target discovery
Authors: Khan A.M.
Hu Y. 
Miotto O.
Thevasagayam N.M. 
Sukumaran R. 
Abd Raman H.S.
Brusic V.
Tan T.W. 
Thomas August J.
Keywords: peptide
virus vaccine
viral protein
virus vaccine
Article
bioinformatics
conserved sequence
data analysis
data processing
Dengue virus
drug design
drug targeting
entropy
Human immunodeficiency virus 1
Influenza A virus
nonhuman
priority journal
sequence alignment
sequence homology
species comparison
species diversity
species identification
virus
virus strain
West Nile virus
amino acid sequence
biology
chemistry
genetic variation
genetics
immunology
procedures
species difference
Amino Acid Sequence
Computational Biology
Conserved Sequence
Genetic Variation
Species Specificity
Vaccinology
Viral Proteins
Viral Vaccines
Issue Date: 2017
Citation: Khan A.M., Hu Y., Miotto O., Thevasagayam N.M., Sukumaran R., Abd Raman H.S., Brusic V., Tan T.W., Thomas August J. (2017). Analysis of viral diversity for vaccine target discovery. BMC Medical Genomics 10 : 78. ScholarBank@NUS Repository. https://doi.org/10.1186/s12920-017-0301-2
Abstract: Background: 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. Results: 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. Conclusion: 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. © 2017 The Author(s).
Source Title: BMC Medical Genomics
URI: https://scholarbank.nus.edu.sg/handle/10635/173755
ISSN: 17558794
DOI: 10.1186/s12920-017-0301-2
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