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Current and prospective computational approaches and challenges for developing COVID-19 vaccines
SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly pr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7871111/ https://www.ncbi.nlm.nih.gov/pubmed/33561453 http://dx.doi.org/10.1016/j.addr.2021.02.004 |
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author | Hwang, Woochang Lei, Winnie Katritsis, Nicholas M MacMahon, Méabh Chapman, Kathryn Han, Namshik |
author_facet | Hwang, Woochang Lei, Winnie Katritsis, Nicholas M MacMahon, Méabh Chapman, Kathryn Han, Namshik |
author_sort | Hwang, Woochang |
collection | PubMed |
description | SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses. |
format | Online Article Text |
id | pubmed-7871111 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78711112021-02-09 Current and prospective computational approaches and challenges for developing COVID-19 vaccines Hwang, Woochang Lei, Winnie Katritsis, Nicholas M MacMahon, Méabh Chapman, Kathryn Han, Namshik Adv Drug Deliv Rev Article SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses. Published by Elsevier B.V. 2021-05 2021-02-06 /pmc/articles/PMC7871111/ /pubmed/33561453 http://dx.doi.org/10.1016/j.addr.2021.02.004 Text en Crown Copyright © 2021 Published by Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Hwang, Woochang Lei, Winnie Katritsis, Nicholas M MacMahon, Méabh Chapman, Kathryn Han, Namshik Current and prospective computational approaches and challenges for developing COVID-19 vaccines |
title | Current and prospective computational approaches and challenges for developing COVID-19 vaccines |
title_full | Current and prospective computational approaches and challenges for developing COVID-19 vaccines |
title_fullStr | Current and prospective computational approaches and challenges for developing COVID-19 vaccines |
title_full_unstemmed | Current and prospective computational approaches and challenges for developing COVID-19 vaccines |
title_short | Current and prospective computational approaches and challenges for developing COVID-19 vaccines |
title_sort | current and prospective computational approaches and challenges for developing covid-19 vaccines |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7871111/ https://www.ncbi.nlm.nih.gov/pubmed/33561453 http://dx.doi.org/10.1016/j.addr.2021.02.004 |
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