Evidence map›Paper›PMID 40341420›Full record

ArticleScientific reports2025

Designing a multi-epitope vaccine against African swine fever virus using immunoinformatics approach.

Dhithya Venkateswaran, Anwesha Prakash, Quynh Anh Nguyen, Roypim Suntisukwattana, Waranya Atthaapa, Angkana Tantituvanont, Dachrit Nilubol

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 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.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. 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

7 authors.

Dhithya VenkateswaranSwine Viral Evolution and Vaccine Development Research Unit, Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Anwesha PrakashSwine Viral Evolution and Vaccine Development Research Unit, Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Quynh Anh NguyenSwine Viral Evolution and Vaccine Development Research Unit, Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Roypim SuntisukwattanaSwine Viral Evolution and Vaccine Development Research Unit, Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Waranya AtthaapaSwine Viral Evolution and Vaccine Development Research Unit, Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand.
Angkana TantituvanontDepartment of Pharmaceutic and Industrial Pharmacies, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.
Dachrit NilubolSwine Viral Evolution and Vaccine Development Research Unit, Department of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, 10330, Thailand. dachrit@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

African swine fever (ASF) is a highly contagious and fatal haemorrhagic disease affecting domestic and wild pigs, with no effective vaccine currently available. The lack of an effective vaccine has hindered global ASF control efforts, leading to devastating economic losses in the swine industry. Traditional vaccine development approaches have faced challenges due to ASFV's genetic complexity and immune evasion strategies. Therefore, this study aims to leverage immunoinformatic approaches to facilitate acceleration of the early stages of vaccine development, optimizing resource utilization and time efficiency while providing a rational design for a potent multi-epitope vaccine against ASFV. In this study, a multi-epitope vaccine against ASFV was designed using an in-silico approach incorporating epitopes from conserved ASFV genes - B646L (p72), CP204L (p30), E183L (p54) and EP402R (CD2v). Promising epitopes that were antigenic and non-allergenic were used for the vaccine construct along with suitable adjuvant and linkers. Further analyses of the construct interpreted the physico-chemical properties, secondary and tertiary structure prediction and validation. The docking and molecular dynamics analysis of the docked complex (vaccine construct and SLA-1 0401) were performed. The docking analysis demonstrated that the vaccine construct binds well with SLA-1 0401 and the molecular dynamics analysis confirmed its strong binding affinity. The vaccine construct was confirmed as stable through normal mode analysis (NMA). Immune simulations demonstrated that this multi-epitope vaccine construct generates a strong adaptive immune response including both humoral and cell-mediated immunity. The sequence of the vaccine construct was further codon optimized with better CAI and GC content, for enhanced expression in the host Sus scrofa. Finally, the optimized sequence of vaccine construct was cloned into the plasmid pVAX1-eGFP. These in-silico results prove that the designed multi-epitope vaccine is potentially effective and warrants for further in vitro and in vivo studies to confirm the efficiency of the vaccine against ASFV.

Indexed as

African Swine FeverAfrican Swine Fever VirusComputational BiologyEpitopesViral VaccinesAnimalsImmunoinformaticsMolecular Docking SimulationMolecular Dynamics SimulationSwineVaccine DevelopmentEpitopesViral VaccinesAfrican swine fever virusEfficacyIn-silico approachMulti-epitopeVaccine

Identifiers

PMID40341420
PMCPMC12062365

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.