Evidence map›Paper›PMID 33257716›Full record

ArticleScientific reports2020

Immunoinformatic design of a COVID-19 subunit vaccine using entire structural immunogenic epitopes of SARS-CoV-2.

Esmaeil Behmard, Bijan Soleymani, Ali Najafi, Ebrahim Barzegari

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

46 citing papers in PubMed.

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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

4 authors.

Esmaeil BehmardMedical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Zakariya Razi Blvd., Kermanshah, Iran.
Bijan SoleymaniMedical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Zakariya Razi Blvd., Kermanshah, Iran.
Ali NajafiMolecular Biology Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran. najafi74@bmsu.ac.ir.
Ebrahim BarzegariMedical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Zakariya Razi Blvd., Kermanshah, Iran. e.barzegari@kums.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) is an acute pneumonic disease, with no prophylactic or specific therapeutical solution. Effective and rapid countermeasure against the spread of the disease's associated virus, SARS-CoV-2, requires to incorporate the computational approach. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Potential non-toxic and non-allergenic T-cell and B-cell binding and cytokine inducing epitopes were then identified through a priori prediction. Selected epitopes were bound to each other with appropriate linkers, followed by appending a suitable adjuvant to increase the immunogenicity of the vaccine polypeptide. Molecular modelling of the 3D structure of the vaccine construct, docking, molecular dynamics simulations and free energy calculations confirmed that the vaccine peptide had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. As our vaccine polypeptide design captures the advantages of structural epitopes and simultaneously integrates precautions to avoid relevant side effects, it is suggested to be promising for elicitation of an effective and safe immune response against SARS-CoV-2 in vivo.

Indexed as

Computational BiologyCOVID-19COVID-19 VaccinesEpitopes, B-LymphocyteEpitopes, T-LymphocyteHumansImmunogenicity, VaccineModels, MolecularMolecular Docking SimulationMolecular Dynamics SimulationSARS-CoV-2Toll-Like Receptor 3Vaccines, SubunitViral Structural ProteinsCOVID-19 VaccinesEpitopes, B-LymphocyteEpitopes, T-LymphocyteTLR3 protein, humanToll-Like Receptor 3Vaccines, SubunitViral Structural Proteins

Identifiers

PMID33257716
PMCPMC7704662

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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.