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Immunoinformatics Approaches in Designing Vaccines Against COVID-19.
Chakraborty, Ankita; Bayry, Jagadeesh; Mukherjee, Suprabhat.
  • Chakraborty A; Integrative Biochemistry and Immunology Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol, West Bengal, India.
  • Bayry J; Department of Biological Sciences & Engineering, Indian Institute of Technology Palakkad, Palakkad, Kerala, India. bayry@iitpkd.ac.in.
  • Mukherjee S; Integrative Biochemistry and Immunology Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol, West Bengal, India. suprabhat.mukherjee@knu.ac.in.
Methods Mol Biol ; 2673: 431-452, 2023.
Article in English | MEDLINE | ID: covidwho-20233939
ABSTRACT
Since the onset of the COVID-19 pandemic, a number of approaches have been adopted by the scientific communities for developing efficient vaccine candidate against SARS-CoV-2. Conventional approaches of developing a vaccine require a long time and a series of trials and errors which indeed limit the feasibility of such approaches for developing a dependable vaccine in an emergency situation like the COVID-19 pandemic. Hitherto, most of the available vaccines have been developed against a particular antigen of SARS-CoV, spike protein in most of the cases, and intriguingly, these vaccines are not effective against all the pathogenic coronaviruses. In this context, immunoinformatics-based reverse vaccinology approaches enable a robust design of efficacious peptide-based vaccines against all the infectious strains of coronaviruses within a short frame of time. In this chapter, we enumerate the methodological trajectory of developing a universal anti-SARS-CoV-2 vaccine, namely, "AbhiSCoVac," through advanced computational biology-based immunoinformatics approach and its in-silico validation using molecular dynamics simulations.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Vaccines / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2023 Document Type: Article Affiliation country: 978-1-0716-3239-0_29

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Viral Vaccines / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: Methods Mol Biol Journal subject: Molecular Biology Year: 2023 Document Type: Article Affiliation country: 978-1-0716-3239-0_29