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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.
  • Hwang W; Milner Therapeutics Institute, University of Cambridge, Cambridge, UK.
  • Lei W; Milner Therapeutics Institute, University of Cambridge, Cambridge, UK; Department of Surgery, University of Cambridge, Cambridge, UK.
  • Katritsis NM; Milner Therapeutics Institute, University of Cambridge, Cambridge, UK; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.
  • MacMahon M; Milner Therapeutics Institute, University of Cambridge, Cambridge, UK; Centre for Therapeutics Discovery, LifeArc, Stevenage, UK.
  • Chapman K; Milner Therapeutics Institute, University of Cambridge, Cambridge, UK.
  • Han N; Milner Therapeutics Institute, University of Cambridge, Cambridge, UK. Electronic address: n.han@milner.cam.ac.uk.
Adv Drug Deliv Rev ; 172: 249-274, 2021 05.
Article in English | MEDLINE | ID: covidwho-1064699
Semantic information from SemMedBD (by NLM)
1. 2019 novel coronavirus CAUSES COVID-19
Subject
2019 novel coronavirus
Predicate
CAUSES
Object
COVID-19
2. 2019 novel coronavirus PROCESS_OF Homo sapiens
Subject
2019 novel coronavirus
Predicate
PROCESS_OF
Object
Homo sapiens
3. 2019 novel coronavirus CAUSES COVID-19
Subject
2019 novel coronavirus
Predicate
CAUSES
Object
COVID-19
4. 2019 novel coronavirus PROCESS_OF Homo sapiens
Subject
2019 novel coronavirus
Predicate
PROCESS_OF
Object
Homo sapiens
ABSTRACT
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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Computational Biology / Drug Development / COVID-19 Vaccines / SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Animals / Humans Language: English Journal: Adv Drug Deliv Rev Journal subject: Pharmacology / Drug Therapy Year: 2021 Document Type: Article Affiliation country: J.addr.2021.02.004

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computational Biology / Drug Development / COVID-19 Vaccines / SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Animals / Humans Language: English Journal: Adv Drug Deliv Rev Journal subject: Pharmacology / Drug Therapy Year: 2021 Document Type: Article Affiliation country: J.addr.2021.02.004