Hashim Omar, Dimier-Poisson Isabelle
Lovaltech, Tours, France.
Department of Pharmacology, University of Gezira, Wad Medany, Sudan.
Comput Struct Biotechnol J. 2025 Jun 4;27:2386-2393. doi: 10.1016/j.csbj.2025.06.011. eCollection 2025.
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.
原生动物寄生虫仍然是全球主要的健康和经济负担，尤其是在低收入和中等收入国家。化疗和病媒控制等传统策略由于耐药性、毒性和实施挑战而面临越来越多的限制。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工具来克服这些障碍，它将免疫信息学、反向疫苗学和人工智能相结合，以加速免疫原性表位的识别并简化疫苗设计。本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、针对特定人群的疫苗设计和数字孪生技术方面的进展。应用包括针对跨物种保守抗原的多价疫苗、基于宿主免疫遗传学的个性化制剂，以及原生动物载体在癌症免疫治疗中的新兴应用。尽管有这些有前景的途径，但重大挑战仍然存在，特别是需要强大的实验验证、改进短肽的递送系统，以及更广泛的科学界对计算机方法的更大接受度。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，将是开发针对原生动物感染的安全、有效且广泛可及的疫苗的关键。这种学科融合不仅有可能解决被忽视的热带病，还有可能在精准疫苗学和免疫治疗中建立新的范式。
