Evidence map›Paper›PMID 33422682›Full record

ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2021

Identification of SARS-CoV-2 CTL epitopes for development of a multivalent subunit vaccine for COVID-19.

Clayton Fernando Rencilin, Joseph Christina Rosy, Manikandan Mohan, Richard Coico, Krishnan Sundar

Open access · greenAbstract read
In one paragraph

Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Biotechnologia · 2025
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  5. Article
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  8. Article
  9. Article
  10. Article
  11. Multivalent Vaccine Strategies in Battling the Emergence of COVID-19 Variants.Methods in molecular biology (Clifton, N.J.) · 2022
    Review
  12. Article
  13. Article
  14. Article
  15. Lessons Learned from Cutting-Edge Immunoinformatics on Next-Generation COVID-19 Vaccine Research.International journal of peptide research and therapeutics · 2021
    Article
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 at 3 institutions in 2 countries.

Clayton Fernando RencilinDepartment of Biotechnology, School of Bio and Chemical Engineering, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamil Nadu, India.
Joseph Christina RosyDepartment of Biotechnology, School of Bio and Chemical Engineering, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamil Nadu, India.
Manikandan MohanCollege of Pharmacy, University of Georgia, Athens, GA, USA.
Richard CoicoSUNY Downstate Health Sciences University, College of Medicine, Brooklyn, NY, USA.
Krishnan SundarDepartment of Biotechnology, School of Bio and Chemical Engineering, Kalasalingam Academy of Research and Education, Krishnankoil 626126, Tamil Nadu, India. Electronic address: sundarkr@klu.ac.in.
Kalasalingam Academy of Research and Education · INSUNY Downstate Health Sciences University · USUniversity of Georgia · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An immunoinformatics-based approach was used to identify potential multivalent subunit CTL vaccine candidates for SARS-CoV-2. Criteria for computational screening included antigen processing, antigenicity, allergenicity, and toxicity. A total of 2604 epitopes were found to be strong binders to MHC class I molecules when analyzed using IEDB tools. Further testing for antigen processing yielded 826 peptides of which 451 were 9-mers that were analyzed for potential antigenicity. Antigenic properties were predicted for 102 of the 451 peptides. Further assessment for potential allergenicity and toxicity narrowed the number of candidate CTL epitopes to 50 peptide sequences, 45 of which were present in all strains of SARS-CoV-2 that were tested. The predicted CTL epitopes were then tested to eliminate those with MHC class II binding potential, a property that could induce hyperinflammatory responses mediated by T

Indexed as

Amino Acid SequenceCOVID-19COVID-19 VaccinesEpitopes, T-LymphocyteHistocompatibility Antigens Class IHistocompatibility Antigens Class IIHumansImmunogenicity, VaccineMolecular Docking SimulationProteomicsT-Lymphocytes, CytotoxicVaccines, CombinedVaccines, SubunitCOVID-19 VaccinesEpitopes, T-LymphocyteHistocompatibility Antigens Class IHistocompatibility Antigens Class IIVaccines, CombinedVaccines, SubunitCTL epitopesEpitope mappingSARS-CoV-2

Identifiers

PMID33422682
PMCPMC7836868
OpenAlexW3119129280

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.