Evidence map›Paper›PMID 39146295›Full record

ArticlePloS one2024

Engineering receptor-binding domain and heptad repeat domains towards the development of multi-epitopes oral vaccines against SARS-CoV-2 variants.

Nur Farhanah Arshad, Fariza Juliana Nordin, Lian Chee Foong, Lionel Lian Aun In, Michelle Yee Mun Teo

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nur Farhanah ArshadDepartment of Biotechnology, Faculty of Applied Sciences, UCSI University, Kuala Lumpur, Malaysia.
Fariza Juliana NordinDepartment of Biological Sciences and Biotechnology, Faculty of Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Lian Chee FoongState Key Laboratory of Systems Medicine for Cancer, Renji-Med X Clinical Stem Cell Research Center, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Lionel Lian Aun InDepartment of Biotechnology, Faculty of Applied Sciences, UCSI University, Kuala Lumpur, Malaysia.
Michelle Yee Mun TeoDepartment of Biotechnology, Faculty of Applied Sciences, UCSI University, Kuala Lumpur, Malaysia.ORCID 0009-0004-0506-0165

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The inability of existing vaccines to cope with the mutation rate has highlighted the need for effective preventative strategies for COVID-19. Through the secretion of immunoglobulin A, mucosal delivery of vaccines can effectively stimulate mucosal immunity for better protection against SARS-CoV-2 infection. In this study, various immunoinformatic tools were used to design a multi-epitope oral vaccine against SARS-CoV-2 based on its receptor-binding domain (RBD) and heptad repeat (HR) domains. T and B lymphocyte epitopes were initially predicted from the RBD and HR domains of SARS-CoV-2, and potential antigenic, immunogenic, non-allergenic, and non-toxic epitopes were identified. Epitopes that are highly conserved and have no significant similarity to human proteome were selected. The epitopes were joined with appropriate linkers, and an adjuvant was added to enhance the vaccine efficacy. The vaccine 3D structure constructs were docked with toll-like receptor 4 (TLR-4) and TLR1-TLR2, and the binding affinity was calculated. The designed multi-epitope vaccine construct (MEVC) consisted of 33 antigenic T and B lymphocyte epitopes. The results of molecular dockings and free binding energies confirmed that the MEVC effectively binds to TLR molecules, and the complexes were stable. The results suggested that the designed MEVC is a potentially safe and effective oral vaccine against SARS-CoV-2. This in silico study presents a novel approach for creating an oral multi-epitope vaccine against the rapidly evolving SARS-CoV-2 variants. These findings offer valuable insights for developing an effective strategy to combat COVID-19. Further preclinical and clinical studies are required to confirm the efficacy of the MEVC vaccine.

Indexed as

COVID-19COVID-19 VaccinesEpitopes, B-LymphocyteEpitopes, T-LymphocyteSARS-CoV-2Spike Glycoprotein, CoronavirusAdministration, OralHumansMolecular Docking SimulationProtein BindingProtein DomainsToll-Like Receptor 4COVID-19 VaccinesEpitopes, B-LymphocyteEpitopes, T-LymphocyteSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Toll-Like Receptor 4

Identifiers

PMID39146295
PMCPMC11326571

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.