Evidence map›Paper›PMID 41484553›Full record

ArticleBMC immunology2026

TZ1391: a computationally designed circular mRNA multi-epitope vaccine candidate against Mycobacterium tuberculosis via TLR3 immunomodulation.

Awais Ali, Abdulaziz Alamri, Vipin Kumar Mishra, Aigul Utegenova, Gulsum Askarova, Aliya Baiduissenova, Aigul Dusmagambetova

Abstract read
In one paragraph

Article in BMC immunology, 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. Antigen 85B ofVaccines · 2026
    Review
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.

Awais AliImmunology, Diagnostics & Research Discovery Lab (IDRDL), Department of Biochemistry, Abdul Wali Khan University Mardan (AWKUM), Mardan, 23200, Pakistan. awaisalibio@gmail.com.ORCID 0000-0002-4514-9509
Abdulaziz AlamriDepartment of Biochemistry, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia. abalamri@ksu.edu.sa.
Vipin Kumar MishraChemistry Division, School of Advance Sciences and Languages, VIT Bhopal University, Sehore, Bhopal- Kothri Kalan, India.
Aigul UtegenovaDepartment of Microbiology and Virology, Astana Medical University, Astana, Kazakhstan. utegenova.a@amu.kz.ORCID 0000-0002-5777-3747
Gulsum AskarovaDepartment of Dermatovenereology, Head of the Department, Faculty of Medicine and Public Health, Al- Farabi Kazakh National University, Almaty, Kazakhstan.ORCID 0000-0001-5019-8957
Aliya BaiduissenovaDepartment of Microbiology and Virology, Astana Medical University, Astana, Kazakhstan.ORCID 0000-0003-4967-2804
Aigul DusmagambetovaLaboratory Department of City Polyclinic №5 of the Akimat of Astana, Astana Medical University, Astana, Kazakhstan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health burden due to latent infection, multidrug resistance, and the limited efficacy of the BCG vaccine. To address this challenge, we computationally designed and evaluated a circular mRNA-based multi-epitope vaccine candidate, TZ1391. Five experimentally validated M. tuberculosis antigens (ESAT-6, CFP-10, Ag85B, PPE18, and HspX) were used to predict immunodominant cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B-cell epitopes. Three vaccine constructs (MTB-C1, MTB-C2, and MTB-C3) were assembled by integrating 20 CTL, 20 HTL, and 20 B-cell epitopes with appropriate linkers, PADRE sequence, and innate immune adjuvants. Structural modeling using AlphaFold2 and GalaxyRefine confirmed stable, native-like conformations for all constructs, with MTB-C3 showing the highest structural quality (GDT-HA = 0.8782; RMSD = 0.646 Å) and the greatest number of stabilizing disulfide bonds. Molecular docking against TLR3, TLR4, and TLR8 identified two top-performing candidates. MTB-C3 exhibited the strongest interaction with TLR3, achieving the lowest HDock score (− 480.53) and highest confidence score (0.9987), while MTB-C2 showed optimal binding to TLR4 (ClusPro score − 1488.6; confidence 0.9700). Despite favorable TLR4 engagement by MTB-C2, MTB-C3 was prioritized as the lead candidate (TZ1391) due to its superior structural stability, reduced conformational fluctuations during molecular dynamics simulations, and stronger TLR3 binding free energy (ΔG_bind = − 173.25 ± 7.9 kcal/mol). Immune simulations further predicted that TZ1391 elicits a robust Th1-biased response, characterized by sustained IgG production, strong IFN-γ and IL-2 induction, and durable immune memory. Overall, the strong TLR3-mediated interaction, combined with enhanced structural stability and favorable immunogenic profiles, establishes TZ1391 as a promising multi-epitope vaccine candidate for further experimental validation against tuberculosis.

Indexed as

EpitopesMycobacterium tuberculosisToll-Like Receptor 3TuberculosisTuberculosis VaccinesAnimalsAntigens, BacterialEpitopes, B-LymphocyteEpitopes, T-LymphocyteHumansImmunoinformaticsMolecular Docking SimulationRNA, MessengerT-Lymphocytes, CytotoxicAntigens, BacterialEpitopesEpitopes, B-LymphocyteEpitopes, T-LymphocyteRNA, MessengerToll-Like Receptor 3Tuberculosis VaccinesCircular mRNA vaccineImmune simulationsMolecular dynamics simulationsMulti-epitope vaccineMycobacterium tuberculosis (MTB)

Identifiers

PMID41484553
PMCPMC12930736

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LicenceCC BY-NC-ND
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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.