Immunoinformatics-Based Multi-Epitope Vaccine Design Against P. falciparum-Causing Malaria: A Computational Approach

基于免疫信息学的多表位疫苗设计:一种针对恶性疟原虫疟疾的计算方法

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Abstract

BACKGROUND AND AIM: Malaria is an infectious disease that affects people in Africa, and other parts of the world by the millions. Despite the effectiveness of artemisinin-based combination therapies against the disease, current findings on possible Plasmodium resistance to artemisinin warrants an exploration of new treatment options. This study aimed to design a multi-epitope vaccine against Plasmodium falciparum (P. falciparum) using immunoinformatics and computational techniques. METHODS: In this study, we employ immunoinformatics and computational techniques to design a multi-epitope vaccine against P. falciparum. B cell epitopes, cytotoxic T (Tc) cell and helper T (Th) cell epitopes were identified from five highly conserved P. falciparum antigens that play crucial roles in the pathogenicity of the infection. Predicted epitopes were selected based on set criteria and concatenated with appropriate adjuvants and linkers to construct a multi-epitope subunit vaccine. RESULTS: Collectively, the Tc cell and Th cell epitopes of the proposed vaccine cover an estimated 87.07% of the world's population, based on the HLA data set from the Allele Frequency Net Database. The vaccine construct was found to be soluble and have appropriate physicochemical properties. The docking, and molecular dynamics (MD) simulation studies carried out revealed strong and stable interactions between TLR4 and the vaccine construct. Immune simulation upon administration of the vaccine construct indicates the development of long-lasting memory B, and CD4+ T cells for antigen clearance. CONCLUSION: This computational study presents a promising multi-epitope subunit vaccine candidate against P. falciparum. The construct shows high population coverage, stability, and potential immunogenicity. These findings however require further experimental validations.

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