Evidence map›Paper›PMID 39325755›Full record

ArticlePloS one2024

Advancing one health vaccination: In silico design and evaluation of a multi-epitope subunit vaccine against Nipah virus for cross-species immunization using immunoinformatics and molecular modeling.

Edward Coralde Banico, Ella Mae Joy Sinco Sira, Lauren Emily Fajardo, Albert Neil Gura Dulay, Nyzar Mabeth Obenio Odchimar, Alea Maurice Simbulan, Fredmoore Legaspi Orosco

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Edward Coralde BanicoDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.ORCID 0009-0009-9839-9315
Ella Mae Joy Sinco SiraDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.
Lauren Emily FajardoDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.
Albert Neil Gura DulayDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.ORCID 0009-0000-4708-4625
Nyzar Mabeth Obenio OdchimarDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.ORCID 0000-0003-1979-5571
Alea Maurice SimbulanDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.
Fredmoore Legaspi OroscoDepartment of Science and Technology, Virology and Vaccine Research Program, Industrial Development Technology Institute, Taguig City, Metro Manila, Philippines.ORCID 0000-0002-8861-7923

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The resurgence of the Nipah virus (NiV) in 2023 has raised concerns for another potentially severe pandemic, given its history of high mortality from previous outbreaks. Unfortunately, no therapeutics and vaccines have been available for the virus. This study used immunoinformatics and molecular modeling to design and evaluate a multi-epitope subunit vaccine targeting NiV. The designed vaccine construct aims to stimulate immune responses in humans and two other intermediate animal hosts of the virus-swine and equine. Using several epitope prediction tools, ten peptides that induced B-lymphocyte responses, 17 peptides that induced cytotoxic T-lymphocyte (CTL) responses, and 12 peptides that induced helper T-lymphocyte (HTL) responses were mapped from nine NiV protein sequences. However, the CTL and HTL-inducing peptides were reduced to ten and eight, respectively, following molecular docking and dynamics. These screened peptides exhibited stability with 30 common major histocompatibility complex (MHC) receptors found in humans, swine, and equine. All peptides were linked using peptide linkers to form the multi-epitope construct and various adjuvants were tested to enhance its immunogenicity. The vaccine construct with resuscitation-promoting factor E (RpfE) adjuvant was selected as the final design based on its favorable physicochemical properties and superior immune response profile. Molecular docking was used to visualize the interaction of the vaccine to toll-like receptor 4 (TLR4), while molecular dynamics confirmed the structural stability of this interaction. Physicochemical property evaluation and computational simulations showed that the designed vaccine construct exhibited favorable properties and elicited higher antibody titers than the six multi-epitope NiV vaccine designs available in the literature. Further in vivo and in vitro experiments are necessary to validate the immunogenicity conferred by the designed vaccine construct and its epitope components. This study demonstrates the capability of computational methodologies in rational vaccine design and highlights the potential of cross-species vaccination strategies for mitigating potential NiV threats.

Indexed as

Computational BiologyHenipavirus InfectionsNipah VirusVaccines, SubunitViral VaccinesAnimalsComputer SimulationEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteHorsesHumansImmunoinformaticsMiceModels, MolecularMolecular Docking SimulationEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteToll-Like Receptor 4Vaccines, SubunitViral Vaccines

Identifiers

PMID39325755
PMCPMC11426463

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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.