Infectious disease mRNA vaccines and a review on epitope prediction for vaccine design

Cai, X; Li, JJ; Liu, T; Brian, O; Li, J

Infectious disease mRNA vaccines and a review on epitope prediction for vaccine design

Cai, X Li, JJ Liu, T Brian, O Li, J

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Publisher:: Oxford University Press (OUP)
Publication Type:: Journal Article
Citation:: Briefings in Functional Genomics, 2021, pp. elab027-
Issue Date:: 2021-06-04

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Field	Value	Language
dc.contributor.author	Cai, X
dc.contributor.author	Li, JJ
dc.contributor.author	Liu, T
dc.contributor.author	Brian, O
dc.contributor.author	Li, J https://orcid.org/0000-0002-3584-6765
dc.date.accessioned	2021-07-27T09:00:09Z
dc.date.available	2021-03-12
dc.date.available	2021-07-27T09:00:09Z
dc.date.issued	2021-06-04
dc.identifier.citation	Briefings in Functional Genomics, 2021, pp. elab027-
dc.identifier.issn	2041-2649
dc.identifier.issn	2041-2657
dc.identifier.uri	http://hdl.handle.net/10453/149949
dc.description.abstract	Messenger RNA (mRNA) vaccines have recently emerged as a new type of vaccine technology, showing strong potential to combat the COVID-19 pandemic. In addition to SARS-CoV-2 which caused the pandemic, mRNA vaccines have been developed and tested to prevent infectious diseases caused by other viruses such as Zika virus, the dengue virus, the respiratory syncytial virus, influenza H7N9 and Flavivirus. Interestingly, mRNA vaccines may also be useful for preventing non-infectious diseases such as diabetes and cancer. This review summarises the current progresses of mRNA vaccines designed for a range of diseases including COVID-19. As epitope study is a primary component in the in silico design of mRNA vaccines, we also survey on advanced bioinformatics and machine learning algorithms which have been used for epitope prediction, and review on user-friendly software tools available for this purpose. Finally, we discuss some of the unanswered concerns about mRNA vaccines, such as unknown long-term side effects, and present with our perspectives on future developments in this exciting area.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Oxford University Press (OUP)
dc.relation	http://purl.org/au-research/grants/nhmrc/1120249
dc.relation.ispartof	Briefings in Functional Genomics
dc.relation.isbasedon	10.1093/bfgp/elab027
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0604 Genetics
dc.title	Infectious disease mRNA vaccines and a review on epitope prediction for vaccine design
dc.type	Journal Article
utslib.location.activity	England
utslib.for	0604 Genetics
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2021-07-27T09:00:04Z
pubs.publication-status	Published

Abstract:

Messenger RNA (mRNA) vaccines have recently emerged as a new type of vaccine technology, showing strong potential to combat the COVID-19 pandemic. In addition to SARS-CoV-2 which caused the pandemic, mRNA vaccines have been developed and tested to prevent infectious diseases caused by other viruses such as Zika virus, the dengue virus, the respiratory syncytial virus, influenza H7N9 and Flavivirus. Interestingly, mRNA vaccines may also be useful for preventing non-infectious diseases such as diabetes and cancer. This review summarises the current progresses of mRNA vaccines designed for a range of diseases including COVID-19. As epitope study is a primary component in the in silico design of mRNA vaccines, we also survey on advanced bioinformatics and machine learning algorithms which have been used for epitope prediction, and review on user-friendly software tools available for this purpose. Finally, we discuss some of the unanswered concerns about mRNA vaccines, such as unknown long-term side effects, and present with our perspectives on future developments in this exciting area.

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http://hdl.handle.net/10453/149949