Evidence map›Paper›PMID 39840071›Full record

ArticleFrontiers in immunology2024

Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach.

Tajul Islam Mamun, Md Ahad Ali, Md Nazmul Hosen, Jillur Rahman, Md Anwarul Islam, Md Golam Akib, Kamruz Zaman, Md Masudur Rahman, Ferdaus Mohd Altaf Hossain, Samir Ibenmoussa and 2 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. The rhinovirus puzzle: Linking virus and host factors to childhood asthma.The Journal of allergy and clinical immunology · 2026
    Review
  3. Article
  4. Vitamin D-Induced Antimicrobial Peptides in Combating Viral Infections.Advances in experimental medicine and biology · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. 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

12 authors.

Tajul Islam MamunDepartment of Epidemiology and Public Health, Sylhet Agricultural University, Sylhet, Bangladesh.
Md Ahad AliDepartment Of Chemistry, University of Rajshahi, Rajshahi, Bangladesh.
Md Nazmul HosenDepartment of Pharmacology and Toxicology, Sylhet Agricultural University, Sylhet, Bangladesh.
Jillur RahmanFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.
Md Anwarul IslamFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.
Md Golam AkibFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.
Kamruz ZamanFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.
Md Masudur RahmanFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.
Ferdaus Mohd Altaf HossainFaculty of Veterinary, Animal and Biomedical Sciences, Sylhet Agricultural University, Sylhet, Bangladesh.
Samir IbenmoussaLaboratory of Therapeutic and Organic Chemistry, Faculty of Pharmacy, University of Montpellier, Montpellier, France.
Mohammed BourhiaDepartment of Chemistry and Biochemistry, Faculty of Medicine and Pharmacy, Ibn Zohr University, Laayoune, Morocco.
Turki M DawoudDepartment of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C. The sequences of the chosen structural proteins VP1 and VP2, along with the non-structural protein 2C of HRV-C, were downloaded in FASTA format from the NCBI server for further analysis. Through an exhaustive analysis of HRV-C genomic sequences, we identified highly conserved immunogenic regions capable of eliciting a protective immune response. Leveraging advanced immunoinformatics tools, we predicted epitopes for B-cells, Cytotoxic T lymphocytes, and Helper T lymphocytes, ensuring broad coverage across different HRV-C strains. The vaccine candidate was constructed by integrating selected antigens with immunogenic epitopes and adjuvants, employing optimal linkers. Three vaccine constructs were developed, with V2 being the most promising, consisting of 480 amino acids residues. V2 exhibited strong antigenicity, non-allergenicity, and solubility, with a solubility score greater than 0.550, and demonstrated excellent structural stability, with 91.9% of residues in the most favorable regions of the Ramachandran plot. Molecular dynamics and simulation studies revealed a stable Vaccine-TLR8 complex, with a binding energy of -296.15 and consistent RMSD values. Furthermore, in silico cloning and sequence optimization ensured efficient expression in

Indexed as

EnterovirusEpitopesEpitopes, T-LymphocytePicornaviridae InfectionsRhinovirusViral VaccinesComputational BiologyEpitopes, B-LymphocyteHumansImmunogenicity, VaccineImmunoinformaticsVaccine DevelopmentEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteViral Vaccinesepitope predictionhuman rhinovirus Cimmunoinformaticsmulti-epitope vaccinereverse vaccinology

Identifiers

PMID39840071
PMCPMC11747413

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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.