Evidence map›Paper›PMID 32461973›Full record

ArticleBioMed research international2020

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach.

Miyssa I Abdelmageed, Abdelrahman H Abdelmoneim, Mujahed I Mustafa, Nafisa M Elfadol, Naseem S Murshed, Shaza W Shantier, Abdelrafie M Makhawi

Abstract read
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed, 2 pooled it
–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

118 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Computational design of a novel chimeric multi-epitope vaccine against chlamydia trachomatis serovar a to prevent trachoma.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026
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58 more citing papers are in PubMed but not listed here.

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

7 authors.

Miyssa I AbdelmageedFaculty of Pharmacy, University of Khartoum, Khartoum, Sudan.
Abdelrahman H AbdelmoneimFaculty of Medicine, Alneelain University, Khartoum, Sudan.ORCID https://orcid.org/0000-0002-5037-8488
Mujahed I MustafaDepartment of Biotechnology, University of Bahri, Khartoum, Sudan.ORCID https://orcid.org/0000-0001-6893-0536
Nafisa M ElfadolDepartment of Molecular Biology, National University Biomedical Research Institute, National University, Khartoum, Sudan.
Naseem S MurshedDepartment of Microbiology, International University of Africa, Khartoum, Sudan.
Shaza W ShantierDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Khartoum, Khartoum, Sudan.
Abdelrafie M MakhawiDepartment of Biotechnology, University of Bahri, Khartoum, Sudan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA new endemic disease has spread across Wuhan City, China, in December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a "public-health emergency of international concern" due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus, the objective of this study is to design a multiepitope peptide vaccine against COVID-19 using an immunoinformatics approach.

methodSeveral techniques facilitating the combination of the immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T-cell epitope-based peptide vaccine using the envelope protein of 2019-nCoV as a target.

resultsExtensive mutations, insertion, and deletion were discovered with comparative sequencing in the COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively.

conclusionThe T-cell epitope-based peptide vaccine was designed for COVID-19 using the envelope protein as an immunogenic target. Nevertheless, the proposed vaccine rapidly needs to be validated clinically in order to ensure its safety and immunogenic profile to help stop this epidemic before it leads to devastating global outbreaks.

Indexed as

Amino Acid SequenceBetacoronavirusComputational BiologyCoronavirus InfectionsCOVID-19COVID-19 VaccinesEpitopesEpitopes, T-LymphocyteEvolution, MolecularHLA AntigensHumansModels, MolecularPandemicsPneumonia, ViralSARS-CoV-2SoftwareCOVID-19 VaccinesEpitopesEpitopes, T-LymphocyteHLA AntigensVaccines, SubunitViral ProteinsViral Vaccines

Identifiers

PMID32461973
PMCPMC7212276

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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.