Evidence map›Paper›PMID 38051433›Full record

ArticleJournal, genetic engineering & biotechnology2023

Exploring structural antigens of yellow fever virus to design multi-epitope subunit vaccine candidate by utilizing an immuno-informatics approach.

Kiran Sura, Himanshi Rohilla, Dev Kumar, Ritu Jakhar, Vaishali Ahlawat, Deepshikha Kaushik, Mehak Dangi, Anil Kumar Chhillar

Open access · diamondAbstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2023. 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
0.2field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

8 authors at 1 institution in 1 country.

Kiran Sura *Centre for Bioinformatics, M.D. University, Rohtak, Haryana, India.
Himanshi Rohilla *Centre for Bioinformatics, M.D. University, Rohtak, Haryana, India.
Dev KumarCentre for Bioinformatics, M.D. University, Rohtak, Haryana, India.
Ritu JakharCentre for Bioinformatics, M.D. University, Rohtak, Haryana, India.
Vaishali AhlawatCentre for Bioinformatics, M.D. University, Rohtak, Haryana, India.
Deepshikha KaushikCentre for Bioinformatics, M.D. University, Rohtak, Haryana, India.
Mehak DangiCentre for Bioinformatics, M.D. University, Rohtak, Haryana, India. mehakdangi2007@gmail.com.
Anil Kumar ChhillarCentre for Biotechnology, M.D. University, Rohtak, Haryana, India. anil.chhillar@gmail.com.
Maharshi Dayanand University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundYellow fever is a mosquito-borne viral hemorrhagic disease transmitted by several species of virus-infected mosquitoes endemic to tropical regions of Central and South America and Africa. Earlier in the twentieth century, mass vaccination integrated with mosquito control was implemented to eradicate the yellow fever virus. However, regular outbreaks occur in these regions which pose a threat to travelers and residents of Africa and South America. There is no specific antiviral therapy, but there can be an effective peptide-based vaccine candidate to combat infection caused by the virus. Therefore, the study aims to design a multi-epitope-based subunit vaccine (MESV) construct against the yellow fever virus to reduce the time and cost using reverse vaccinology (RV) approach.

methodsYellow fever virus contains 10,233 nucleotides that encode for 10 proteins (C, prM, E, NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) including 3 structural and 7 non-structural proteins. Structural proteins-precursor membrane protein (prM) and envelope protein (E)-were taken as a target for B cell and T cell epitope screening. Further, various immunoinformatics approaches were employed to FASTA sequences of structural proteins to retrieve B cell and T cell epitopes. MESV was constructed from these epitopes based on allergenicity, antigenicity and immunogenicity, toxicity, conservancy, and population coverage followed by structure prediction. The efficacy of the MESV construct to bind with human TLR-3, TLR-4, and TLR-8 were evaluated using molecular docking and simulation studies. Finally, in-silico cloning of vaccine construct was performed withpBR322 Escherichia coli expression system using codon optimization.

resultsPredicted epitopes evaluated and selected for MESV construction were found stable, non-allergenic, highly antigenic, and global population coverage of 68.03% according to in-silico analysis. However, this can be further tested in in-vitro and in-vivo investigations. Epitopes were sequentially merged to construct a MESV consisting of 393 amino acids using adjuvant and linkers. Molecular docking and simulation studies revealed stable and high-affinity interactions. Furthermore, in-silico immune response graphs showed effective immune response generation. Finally, higher CAI value ensured high gene expression of vaccine in the host cell.

conclusionThe designed MESV construct in the present in-silico study can be effective in generating an immune response against the yellow fever virus. Therefore, to prevent yellow fever, it can be an effective vaccine candidate. However, further downstream, in-vitro study is required.

Indexed as

ImmunoinformaticsMESVMolecular dockingMolecular dynamics simulationVaccineYellow fever virus

Identifiers

PMID38051433
PMCPMC10697922
OpenAlexW4389339933

What OpenQuestion holds

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LicenceCC BY
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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.