Evidence map›Paper›PMID 41917113›Full record

ArticleScientific reports2026

Integrative immunogenomic strategy for designing a multi-epitope vaccine against Zika and Dengue viruses.

Akmal Zubair, Majed Aldehri, Muhammad Yaqoob Shahani, Naila Afghan

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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

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. 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

4 authors.

Akmal ZubairDepartment of Biotechnology, Quaid-i-Azam University, Islamabad, Pakistan. akmalkhattak1994@gmail.com.
Majed AldehriDepartment of Anatomy, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Muhammad Yaqoob ShahaniDepartment of Anesthesia Technology and Operations, College of Applied Medical Sciences, King Khalid University, Muhayil Aseer, Saudi Arabia.
Naila AfghanDepartment of Biology, Kabul University, Kabul, Afghanistan. nailaafghan650@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two of the most prevalent illnesses spread by mosquitoes are the Dengue virus (DENV) and the Zika virus (ZIKV), both of which belong to the Flaviviridae family. Co-infection with ZIKV and DENV has been reported worldwide, sometimes with dire consequences. Developing a single vaccine capable of protecting against both pathogens would therefore be highly beneficial. In this research, an in-silico immunology strategy was employed to construct a multi-epitope, multi-pathogen vaccine targeting both viruses. Considering that DENV and ZIKV share the same mosquito vector, Aedes aegypti, and that its salivary proteins can facilitate viral infection, eleven CTL epitopes, five B-cell antigenic determinants, and twelve HTL epitopes were chosen for the final vaccine. Our DENV and ZIKV vaccine have 567 amino acids and molecular mass is 58603.84 amu. An in-silico 3D modelling process and a structural explanation of the model followed docking and dynamics simulations utilizing human TLR7 and TLR5 with docking scores of -392.81 and − 370.88, respectively. The immune reaction simulation suggests that the suggested vaccination may cause a significant immune response that can protect against both DENV and ZIKV.

Indexed as

DengueDengue VaccinesDengue VirusEpitopesViral VaccinesZika VirusZika Virus InfectionAedesAnimalsEpitopes, B-LymphocyteEpitopes, T-LymphocyteHumansImmunoinformaticsMolecular Docking SimulationProtein Subunit VaccinesVaccine DevelopmentDengue VaccinesEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteProtein Subunit VaccinesViral VaccinesDENVImmunoinformaticsTherapyVaccineZIKV

Identifiers

PMID41917113
PMCPMC13187040

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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.