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<p><i>Chlamydia trachomatis</i> serovar A is a re-emerging worldwide health problem that causes the ocular trachoma, the leading cause of avoidable blindness. The disease continues to spread due to reinfection and failure to develop long-lasting immunity. This study aimed to develop an in silico novel multi-epitope that can induce long-term immune protection against <i>C. trachomatis</i> serovar A. Researchers harvested the protein sequences of serovar A and queried for virulence-related factors. The predictions of epitopes for CTLs, HTLs, and B cells using immunoinformatics tools, and tested for its ability to induce an immune response without evoking allergic or toxic reactions. Shortlisted epitopes were then combined in a multi-epitope construct with appropriate adjuvants and linkers. Researchers tested the vaccine through physicochemical characterization, solubility, structural modeling, molecular docking with TLR2 and TLR4, and stability tests. Immune simulations, codon optimization, and in silico cloning helped assess immunogenicity and established the potential of expression. Fourteen CTL, four HTL, and ten B-cell epitopes were identified from nine virulence proteins, which all expressed high antigenicity and did not contain allergenic or toxic properties. The final construct was well-stable and exhibited strong predicted binding with TLR2 and TLR4. Immune simulations suggested extended B and T cell responses, increased antibody titers, and increased cytokine release upon repeated antigen encounter. HLA population coverage was greater than 95% globally, indicating significant potential for safeguarding. In silico analysis indicates that the multi-epitope vaccine construct exhibits stability, immunogenicity, and broad HLA coverage, and thus it might be a viable approach for further investigation in vaccine development against <i>C. trachomatis</i> serovar A.</p>

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Computational design of a novel chimeric multi-epitope vaccine against chlamydia trachomatis serovar a to prevent trachoma

  • 期刊论文

  • 发表日期：

    2026年5月29日

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  • Muhammad Irsyad Amien,
  • Bimanda Rizki Nurhidayat,
  • Siti Ulfatur Rizqa,
  • Siti Zahra Arfiani,
  • Latiefah Noer Widiastuti,
  • Galuh Prasasti Isbach

摘要

Chlamydia trachomatis serovar A is a re-emerging worldwide health problem that causes the ocular trachoma, the leading cause of avoidable blindness. The disease continues to spread due to reinfection and failure to develop long-lasting immunity. This study aimed to develop an in silico novel multi-epitope that can induce long-term immune protection against C. trachomatis serovar A. Researchers harvested the protein sequences of serovar A and queried for virulence-related factors. The predictions of epitopes for CTLs, HTLs, and B cells using immunoinformatics tools, and tested for its ability to induce an immune response without evoking allergic or toxic reactions. Shortlisted epitopes were then combined in a multi-epitope construct with appropriate adjuvants and linkers. Researchers tested the vaccine through physicochemical characterization, solubility, structural modeling, molecular docking with TLR2 and TLR4, and stability tests. Immune simulations, codon optimization, and in silico cloning helped assess immunogenicity and established the potential of expression. Fourteen CTL, four HTL, and ten B-cell epitopes were identified from nine virulence proteins, which all expressed high antigenicity and did not contain allergenic or toxic properties. The final construct was well-stable and exhibited strong predicted binding with TLR2 and TLR4. Immune simulations suggested extended B and T cell responses, increased antibody titers, and increased cytokine release upon repeated antigen encounter. HLA population coverage was greater than 95% globally, indicating significant potential for safeguarding. In silico analysis indicates that the multi-epitope vaccine construct exhibits stability, immunogenicity, and broad HLA coverage, and thus it might be a viable approach for further investigation in vaccine development against C. trachomatis serovar A.