原生动物计算疫苗的研制。

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-06-04 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.06.011
Omar Hashim, Isabelle Dimier-Poisson
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引用次数: 0

摘要

原生动物寄生虫仍然是一个主要的全球健康和经济负担,特别是在低收入和中等收入国家。由于耐药性、毒性和实施方面的挑战,化疗和病媒控制等传统策略面临越来越大的限制。疫苗接种是一种可持续的解决方案,但原生动物生命周期的复杂性和抗原多样性阻碍了疫苗的开发。计算疫苗学提供了创新的工具来克服这些障碍,结合免疫信息学、反向疫苗学和人工智能来加速免疫原性表位的识别和简化疫苗设计。这篇综述探讨了针对原生动物的计算疫苗开发的现状,重点介绍了表位预测、人群特异性疫苗设计和数字孪生技术方面的进展。应用包括针对物种间保守抗原的多价疫苗,基于宿主免疫遗传学的个性化配方,以及原生动物载体在癌症免疫治疗中的新应用。尽管有这些有希望的途径,重大的挑战仍然存在,特别是需要强大的实验验证,改进短肽的输送系统,以及更广泛的科学界对计算机方法的更大接受。我们认为,将计算工具与实验免疫学、高通量基因组学和转化研究相结合,将是开发安全、有效和广泛可及的针对原生动物感染的疫苗的关键。这种学科的融合不仅有可能解决被忽视的热带病,而且有可能在精确疫苗学和免疫治疗方面建立新的范例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computational vaccine development against protozoa.

Protozoan parasites remain a major global health and economic burden, particularly in low- and middle-income countries. Conventional strategies such as chemotherapy and vector control face growing limitations due to resistance, toxicity, and implementation challenges. Vaccination represents a sustainable solution, but the complexity of protozoan life cycles and antigenic diversity has hindered vaccine development. Computational vaccinology offers innovative tools to overcome these barriers, combining immuno-informatics, reverse vaccinology, and artificial intelligence to accelerate the identification of immunogenic epitopes and streamline vaccine design. This review explores the current landscape of computational vaccine development against protozoa, highlighting advances in epitope prediction, population-specific vaccine design, and digital twin technologies. Applications include multivalent vaccines targeting conserved antigens across species, personalized formulations based on host immunogenetics, and the emerging use of protozoan vectors in cancer immunotherapy. Despite these promising avenues, significant challenges remain, particularly the need for robust experimental validation, improved delivery systems for short peptides, and greater acceptance of in silico methods by the broader scientific community. We argue that integrating computational tools with experimental immunology, high-throughput genomics, and translational research will be the key to developing safe, effective, and broadly accessible vaccines against protozoan infections. This convergence of disciplines has the potential to not only address neglected tropical diseases but also to establish new paradigms in precision vaccinology and immunotherapy.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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