Evidence map›Paper›PMID 36920996›Full record

ArticlePloS one2023

Exploring the structural basis to develop efficient multi-epitope vaccines displaying interaction with HLA and TAP and TLR3 molecules to prevent NIPAH infection, a global threat to human health.

Sukrit Srivastava, Sonia Verma, Mohit Kamthania, Ajay Kumar Saxena, Kailash C Pandey, Veena Pande, Michael Kolbe

Open access · goldFull text read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

12 citing papers in PubMed, 14 citations in OpenAlex.

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  11. Multi-epitope Based Peptide Vaccine Candidate AgainstBioinformatics and biology insights · 2024
    Article
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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 5 institutions in 2 countries.

Sukrit SrivastavaInfection Biology Group, Indian Foundation for Fundamental Research Trust, RaeBareli, India.ORCID 0000-0003-0295-0272
Sonia VermaProtein Biochemistry & Engineering Lab, Parasite-Host Biology Group, ICMR-National Institute of Malaria Research, New Delhi, India.
Mohit KamthaniaInfection Biology Group, Indian Foundation for Fundamental Research Trust, RaeBareli, India.
Ajay Kumar SaxenaMolecular Medicine Lab., School of Life Science, Jawaharlal Nehru University, New Delhi, India.
Kailash C PandeyProtein Biochemistry & Engineering Lab, Parasite-Host Biology Group, ICMR-National Institute of Malaria Research, New Delhi, India.
Veena PandeKumaun University, Bheemtal, Nainital, Uttarakhand, India.
Michael KolbeDepartment for Structural Infection Biology, Centre for Structural Systems Biology (CSSB) & Helmholtz-Centre for Infection Research, Hamburg, Germany.
National Institute of Malaria Research · INHelmholtz Centre for Infection Research · DEJawaharlal Nehru University · INKumaun University · INUniversität Hamburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nipah virus (NiV) is an emerging zoonotic virus that caused several serious outbreaks in the south asian region with high mortality rates ranging from 40 to 90% since 2001. NiV infection causes lethal encephalitis and respiratory disease with the symptom of endothelial cell-cell fusion. No specific and effective vaccine has yet been reported against NiV. To address the urgent need for a specific and effective vaccine against NiV infection, in the present study, we have designed two Multi-Epitope Vaccines (MEVs) composed of 33 Cytotoxic T lymphocyte (CTL) epitopes and 38 Helper T lymphocyte (HTL) epitopes. Out of those CTL and HTL combined 71 epitopes, 61 novel epitopes targeting nine different NiV proteins were not used before for vaccine design. Codon optimization for the cDNA of both the designed MEVs might ensure high expression potential in the human cell line as stable proteins. Both MEVs carry potential B cell linear epitope overlapping regions, B cell discontinuous epitopes as well as IFN-γ inducing epitopes. Additional criteria such as sequence consensus amongst CTL, HTL and B Cell epitopes was implemented for the design of final constructs constituting MEVs. Hence, the designed MEVs carry the potential to elicit cell-mediated as well as humoral immune response. Selected overlapping CTL and HTL epitopes were validated for their stable molecular interactions with HLA class I and II alleles and in case of CTL epitopes with human Transporter Associated with antigen Processing (TAP) cavity. The structure based epitope cross validation for interaction with TAP cavity was used as another criteria choosing final epitopes for NiV MEVs. Finally, human Beta-defensin 2 and Beta-defensin 3 were used as adjuvants to enhance the immune response of both the MEVs. Molecular dynamics simulation studies of MEVs-TLR3 ectodomain (Human Toll-Like Receptor 3) complex indicated the stable molecular interaction. We conclude that the MEVs designed and in silico validated here could be highly potential vaccine candidates to combat NiV infections, with great effectiveness, high specificity and large human population coverage worldwide.

Indexed as

beta-DefensinsHenipavirus InfectionsViral VaccinesComputational BiologyEpitopes, B-LymphocyteEpitopes, T-LymphocyteHLA AntigensHumansMolecular Docking SimulationNucleocytoplasmic Transport ProteinsRNA-Binding ProteinsToll-Like Receptor 3Vaccines, Subunitbeta-DefensinsEpitopes, B-LymphocyteEpitopes, T-LymphocyteHLA AntigensNucleocytoplasmic Transport ProteinsNXF1 protein, humanRNA-Binding ProteinsTLR3 protein, humanToll-Like Receptor 3Vaccines, SubunitViral Vaccines

Identifiers

PMID36920996
PMCPMC10016716
OpenAlexW4324309801

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read36
identifiers read8
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.