Abstract：
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.
摘要：
COVID-19疫情突出了大流行防备对预防未来健康危机的重要性。一个具有高流行潜力的病毒家族是Arenavirus，几乎在全世界都被发现，特别是在非洲和美洲。这些病毒研究不足，关于其结构的许多问题，复制和向性仍然没有答案，使设计一种有效和分子定义的疫苗具有挑战性。我们建议结构驱动的计算疫苗设计将有助于克服这些挑战。在过去的几十年中，特别是在COVID-19大流行期间，稳定病毒糖蛋白或表位集中的计算方法取得了进展，并已被证明对合理的疫苗设计和建立新的诊断工具有用。在这次审查中,我们总结了我们对Arenavirus分子生物学理解的差距，强调疫苗设计中的挑战，并讨论结构驱动和计算知情的策略将如何帮助克服这些障碍。
