Institute for Drug Discovery, Leipzig University, Faculty of Medicine, Leipzig, Germany.
Institute for Drug Discovery, Leipzig University, Faculty of Medicine, Leipzig, Germany; Center for Scalable Data Analytics and Artificial Intelligence ScaDS.AI, Dresden/Leipzig, Germany.
Infect Genet Evol. 2024 Sep;123:105626. doi: 10.1016/j.meegid.2024.105626. Epub 2024 Jun 20.
The COVID-19 outbreak has highlighted the importance of pandemic preparedness for the prevention of future health crises. One virus family with high pandemic potential are Arenaviruses, which have been detected almost worldwide, particularly in Africa and the Americas. These viruses are highly understudied and many questions regarding their structure, replication and tropism remain unanswered, making the design of an efficacious and molecularly-defined vaccine challenging. We propose that structure-driven computational vaccine design will contribute to overcome these challenges. Computational methods for stabilization of viral glycoproteins or epitope focusing have made progress during the last decades and particularly during the COVID-19 pandemic, and have proven useful for rational vaccine design and the establishment of novel diagnostic tools. In this review, we summarize gaps in our understanding of Arenavirus molecular biology, highlight challenges in vaccine design and discuss how structure-driven and computationally informed strategies will aid in overcoming these obstacles.
新型冠状病毒疫情凸显了预防未来卫生危机的大流行防范的重要性。具有高大流行潜力的病毒家族之一是沙粒病毒科,几乎在全世界都有检测到,特别是在非洲和美洲。这些病毒的研究还很不充分,关于它们的结构、复制和嗜性的许多问题仍未得到解答,这使得设计一种有效和分子定义明确的疫苗具有挑战性。我们提出,基于结构的计算疫苗设计将有助于克服这些挑战。在过去几十年中,特别是在新型冠状病毒疫情期间,用于稳定病毒糖蛋白或表位聚焦的计算方法取得了进展,并且已被证明对合理的疫苗设计和新型诊断工具的建立有用。在这篇综述中,我们总结了我们对沙粒病毒科分子生物学理解的差距,强调了疫苗设计的挑战,并讨论了基于结构的和计算信息丰富的策略如何帮助克服这些障碍。