Evidence map›Paper›PMID 33285567›Full record

ArticleBriefings in bioinformatics2021

Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach.

Aftab Alam, Arbaaz Khan, Nikhat Imam, Mohd Faizan Siddiqui, Mohd Waseem, Md Zubbair Malik, Romana Ishrat

Open access · bronzeAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.9field-weighted citation impact, top 8% of its field
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

30 citing papers in PubMed, 54 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Peptide-Based Vaccines and Therapeutics for COVID-19.International journal of peptide research and therapeutics · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. Review
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 at 3 institutions in 2 countries.

Aftab AlamCentre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia University, New Delhi 110025, India.
Arbaaz KhanDepartment of computer science, Jamia Millia Islamia University, New Delhi, India.
Nikhat ImamCentre for Interdisciplinary Research in Basic Science, Jamia Millia Islamia University, New Delhi, India.
Mohd Faizan SiddiquiInternational Medical Faculty, Osh State University, Kyrgyz Republic.
Mohd WaseemSchool of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
Md Zubbair MalikSchool of Computational & Integrative Sciences, Jawaharlal Nehru University, New Delhi, India.
Romana IshratCentre for Interdisciplinary Research in Basic Science, Jamia Millia Islamia University, New Delhi, India.
Jamia Millia Islamia · INJawaharlal Nehru University · INOsh State University · KG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recurrent and recent global outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has turned into a global concern which has infected more than 42 million people all over the globe, and this number is increasing in hours. Unfortunately, no vaccine or specific treatment is available, which makes it more deadly. A vaccine-informatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides [including thymus cells (T-cells) and bone marrow or bursa-derived cells] in the surface glycoprotein (SG) of SARS-CoV-2 which is nontoxic and nonallergenic in nature, nonallergenic, highly antigenic and non-mutated in other SARS-CoV-2 virus strains. The population coverage analysis has found that cluster of differentiation 4 (CD4+) T-cell peptides showed higher cumulative population coverage over cluster of differentiation 8 (CD8+) peptides in the 16 different geographical regions of the world. We identified 12 peptides ((LTDEMIAQY, WTAGAAAYY, WMESEFRVY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQI, YGFQPTNGVGYQ, LPDPSKPSKR, QTQTNSPRRARS and VITPGTNTSN) that are $80\hbox{--} 90\%$ identical with experimentally determined epitopes of SARS-CoV, and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that the identified peptides are tightly bound in the groove of human leukocyte antigen molecules which can induce the T-cell response. Overall, this study allows us to determine potent peptide antigen targets in the SG on intuitive grounds, which opens up a new horizon in the coronavirus disease (COVID-19) research. However, this study needs experimental validation by in vitro and in vivo.

Indexed as

Amino Acid SequenceComputational BiologyCOVID-19Epitopes, B-LymphocyteEpitopes, T-LymphocyteHLA AntigensHumansMolecular Docking SimulationSARS-CoV-2Vaccines, SubunitEpitopes, B-LymphocyteEpitopes, T-LymphocyteHLA AntigensVaccines, SubunitallergenicityCOVID-19epitope predictionimmunogenicitymolecular dockingpopulation coverageT- and B-cellvaccinomics

Identifiers

PMID33285567
PMCPMC7799329
OpenAlexW3113260825

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.