Evidence map›Paper›PMID 41274916›Full record

ArticleScientific reports2025

Multi-epitope vaccine design against human metapneumovirus via reverse vaccinology and molecular modelling.

Khulud Bukhari

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

1 author.

Khulud BukhariDepartment of Microbiology and Parasitology, College of Veterinary Medicine, King Faisal University, 36362, Hofuf, Al-Ahsa, Saudi Arabia. kbukh@kfu.edu.sa.

Funding

King Faisal University 00000
6 · The paper itself

Abstract

Human metapneumovirus (HMPV) is a respiratory viral pathogen classified within the Paramyxoviridae family and is a significant cause of acute respiratory tract infections. The vaccine construct maintains stable binding affinity with targeted receptors anaffects young children, the elderly, and immunocompromised individuals. HMPV was recognized initially in 2001. HMPV exhibits characteristics similar to respiratory syncytial virus (RSV) and generally causes symptoms ranging from mild, cold-like signs to more severe issues such as pneumonia and bronchiolitis. This study employs reverse vaccinology and bioinformatics approaches to screen potential vaccine targets and design epitope vaccine constructs. Following immunoinformatics analysis, six proteins, including >YP_009513265.1 nucleoprotein, >YP_009513266.1 phosphoprotein, >YP_009513268.1 fusion protein, >YP_009513269.1 matrix protein 2-1, >YP_009513272.1 attachment glycoprotein, and >YP_009513273.1 RNA-dependent RNA polymerase, were selected for further analysis. These proteins underwent B-cell epitope prediction, and the identified B-cell epitopes were used in T cell epitope prediction. Both MHC-I and MHC-II epitopes were predicted, with lower percentile scores prioritized. The selected epitopes- SLGKIKNNK, IPQNQRPSA, IPSEPKLAW, FPEDQNVAL, KLKNKNRLR, ELSSIKTRR, and QEKKLVPVY- were further screened through immunoinformatics analysis. These epitopes were connected with a GPGPG linker to form a linear sequence, and an EAAAK linker was used to attach the adjuvant to this sequence, which was then processed for structural modeling. Effective vaccines must bind to receptors on immune cells to activate the immune system. The vaccine-TLR-4 docked complex, predicted using Cluspro 2. 2.0 web server, showed that cluster 4 had the lowest binding energy score of - 1175. 3, indicating potential effectiveness in eliciting an immune response via TLR-4 activation. Similarly, for the vaccine- MHC-I complex, cluster 2 exhibited the lowest energy score of - 1087. 4 kcal/mol, suggesting a stable binding interaction. For the vaccine-MHC-II complex, cluster 2 showed the most stable binding with a lowest energy score of - 1189. 1 kcal/mol. To validate these docking results, molecular dynamics simulations analyze the stability of the complexes. The RMSD from the simulations indicated that the vaccine- MHC-I complex stabilized around 10 to 12 (Å). The vaccine-MHC-II complex stabilized after 60 ns, while the vaccine-TLR-4 complex initially showed a lower RMSD of approximately 5 (Å), which gradually increased to 12-15 (Å), reflecting conformational stability and binding affinity. In addition, in silico immune simulations suggested activation of both humoral and cellular immunity, indicating that the vaccine construct could effectively induce immune responses against HMPV.

Indexed as

EpitopesMetapneumovirusParamyxoviridae InfectionsViral VaccinesComputational BiologyEpitopes, B-LymphocyteEpitopes, T-LymphocyteHumansModels, MolecularVaccinologyViral ProteinsEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteViral ProteinsViral VaccinesClusPro 2.0Human metapneumovirusImmunoinformatics analysisProtein–protein docking

Identifiers

PMID41274916
PMCPMC12749620

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