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Frontiers in cellular and infection microbiology · 2026

In Silico design and evaluation of a multi-epitope vaccine candidate against Toxoplasma gondii for humans.

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Yi Chenchen, Shen Yu, Luo Ye, Wang Qin, Tong Xiaomei

Аннотация

INTRODUCTION: Toxoplasma gondii is a significant zoonotic pathogen responsible for severe disease in immunocompromised individuals, adverse pregnancy outcomes, and substantial economic losses in the livestock industry. Given the limitations of current therapeutic strategies and vaccines, this study utilized immunoinformatics and reverse vaccinology approaches to design a multi-epitope candidate vaccine.

METHODS: A total of 49 T. gondii proteins from the SAG, GRA, MIC, and ROP families were screened. Epitopes were selected based on antigenicity, immunogenicity, cytokine-inducing potential, toxicity, and allergenicity. The selected epitopes were assembled using AAY, GPGPG, and KK linkers, with the 50S ribosomal protein L7/L12 as an adjuvant. Physicochemical properties, molecular docking, molecular dynamics simulations, immune simulations, and codon optimization were subsequently evaluated.

RESULTS: We identified 9 cytotoxic T lymphocyte (CTL), 6 helper T lymphocyte (HTL), and 11 B-cell epitopes. The finalized 556-amino-acid construct (61.13 kDa) demonstrated favorable antigenicity (VaxiJen score: 0.6843), stability (instability index: 39.05), solubility (0.663), and hydrophilicity (GRAVY: -0.502), while maintaining safety profiles. Molecular docking and dynamics simulations confirmed robust and stable binding to TLR2 (-32.8 kcal/mol) and TLR4 (-72.37 kcal/mol). Furthermore, immune simulations predicted a strong, memory-forming humoral and cellular immune response. Codon optimization (CAI: 0.93, GC content: 56.43%) suggested high expression efficiency in Escherichia coli.

DISCUSSION: The rationally designed multi-epitope vaccine demonstrates robust theoretical potential to elicit comprehensive, long-lasting immunity in humans, although its safety and effectiveness require additional experimental validation.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты