Evidence map›Paper›PMID 39677846›Full record

ArticleVirusdisease2024

Exploring immunogenic CD8 + T-cell epitopes for peptide-based vaccine development against evolving SARS-CoV-2 variants: An immunoinformatics approach.

Mohd Sultan Khan, Madhvi Shakya, Chandan Kumar Verma

Abstract read
In one paragraph

Article in Virusdisease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Mohd Sultan KhanDepartment of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh 462003 India.ORCID 0000-0002-8998-7416
Madhvi ShakyaDepartment of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh 462003 India.
Chandan Kumar VermaDepartment of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh 462003 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic originated in Wuhan in 2019 due to a novel SARS-COV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) responsible for the massive number of deaths across the globe. So far, several vaccines have been developed using highly antigenic Spike protein and authorized for emergency use, reducing the severity of the infection. Nonetheless, the virus continues to evolve through multiple mutations, resulting in numerous variants with enhanced transmission that evade the vaccine-induced immune response. Given the persistently mutating nature of the SARS-COV-2 virus, peptide-based vaccines with highly conserved epitopes may offer lasting protection against evolving variants. This study presents an immunoinformatics-based identification of potentially immunogenic CD8 + T-cell epitopes (CTLs) of Spike (S), Membrane (M), Nucleocapsid (N) and Envelope (E) proteins of SARS-COV-2. By utilizing the immunoinformatic approach, 21 epitopes have successfully been evaluated, where 15, 3, 2, and 1 epitopes are respectively from Spike, Membrane, Envelope and Nucleocapsid proteins. Out of these, 20 are found to be identical with experimentally verified immunogenic epitopes, except for the novel NTQEVFAQV epitope from spike protein. These epitopes show a high degree of conservation in both former variants of concerns (VOCs), variants of interest (VOIs) and current variants under monitoring (VUMs), are non-toxic, non-homologous to humans and have a wide range of global population coverage. Furthermore, utilizing molecular docking analysis followed by molecular dynamics simulation, these epitopes have been verified as having stable interactions with their respective HLA molecules. The described framework and projected immunogenic epitopes could significantly impact the development of SARS-COV-2 vaccines based on peptides. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-024-00894-7.

Indexed as

ImmunogenicityImmunoinformaticsMolecular dockingMolecular dynamics simulationPeptide-based vaccineSARS-COV-2

Identifiers

PMID39677846
PMCPMC11635080

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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.