ArticleJournal, genetic engineering & biotechnology2025
Targeting Streptococcus pyogenes atpF protein for multi-epitope vaccine development: a genomics-driven immunoinformatics strategy.
Article in Journal, genetic engineering & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Computational systems immunology and multi-scale modeling for the design of a Multi-Epitope Vaccine (MEV) against emerging multidrug-resistant Klebsiella michiganensis.International microbiology : the official journal of the Spanish Society for Microbiology · 2026Article
- Rational selection of antigenic targets for Group A Streptococcus vaccine: updates, challenges and opportunities.NPJ vaccines · 2026Review
- A multi-epitope pan-betacoronavirus vaccine construct predicted to induce broad-spectrum and durable immune responses: an immunoinformatics approach.Frontiers in bioinformatics · 2026Article
- Molecular Characterization ofMicroorganisms · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Streptococcus pyogenes, a medium-priority pathogen on the WHO's 2024 Bacterial Pathogen Priority List, is a major cause of infectious disease-related mortality. The increasing prevalence of antibiotic resistance, coupled with the absence of a licensed vaccine due to the pathogen's genetic diversity and autoimmune concerns, underscores the need for novel therapeutic strategies. This study employs reverse vaccinology and subtractive proteomics to design a multi-epitope vaccine targeting atpF, a conserved extracellular protein essential for ATP synthesis. The atpF protein was identified based on its high antigenicity and functional importance in S. pyogenes. Three vaccine constructs (SM1, SM2, and SM3) were designed by integrating antigenic B-cell and T-cell epitopes with immune-modulating adjuvants and linkers. Physicochemical and immunological assessments confirmed their stability, solubility, and antigenicity. Molecular modeling identified SM1 as the most promising candidate, demonstrating superior immune receptor binding affinity and flexible epitope interactions, facilitating effective antibody recognition. In silico immune simulations further demonstrated SM1's potential to elicit strong humoral and cellular immune responses, while codon optimization confirmed efficient expression in E. coli. These findings introduce atpF as a promising vaccine target and highlight SM1's potential as a viable vaccine candidate. However, experimental validation is essential to confirm its efficacy, safety, and immunogenicity in vivo. This study underscores the role of computational modeling in accelerating vaccine development, providing a strategic alternative to traditional approaches.
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