Liu Jianying, Quan Yixin, Tong Hua, Zhu Yibin, Shi Xiaolu, Liu Yang, Cheng Gong
New Cornerstone Science Laboratory, Tsinghua University-Peking University Joint Center for Life Sciences, School of Basic Medical Sciences, Tsinghua University, Beijing, 100084, China.
Institute of Infectious Diseases, Shenzhen Bay Laboratory, Shenzhen, 518000, China.
Cell Insight. 2024 Aug 24;3(6):100196. doi: 10.1016/j.cellin.2024.100196. eCollection 2024 Dec.
The increasing global prevalence of mosquito-borne viruses has emerged as a significant threat to human health and life. Identifying receptors for these viruses is crucial for improving our knowledge of viral pathogenesis and developing effective antiviral strategies. The widespread application of CRISPR-Cas9 screening have led to the discovery of many mosquito-borne virus receptors. The revealed structures of virus-receptor complexes also provide important information for understanding their interaction mechanisms. This review provides a comprehensive summary of both conventional and novel approaches for identifying new viral receptors and the putative entry factors of the most prevalent mosquito-borne viruses within the , , and . At the same time, we emphasize the common receptors utilized by these viruses for entry into both vertebrate hosts and mosquito vectors. We discuss promising avenues for developing anti-mosquito-borne viral strategies that target these receptors. Notably, targeting universal receptors of specific mosquito-borne viruses in both vertebrates and mosquitoes offers dual benefits for disease prevention. Additionally, the widespread use of AI-based machine learning and protein structure prediction will accelerate the identification of new viral receptors and provide new avenues for antiviral drug discovery.
全球蚊媒病毒流行率的上升已成为对人类健康和生命的重大威胁。识别这些病毒的受体对于增进我们对病毒发病机制的了解以及制定有效的抗病毒策略至关重要。CRISPR-Cas9筛选的广泛应用已导致发现了许多蚊媒病毒受体。所揭示的病毒-受体复合物结构也为理解它们的相互作用机制提供了重要信息。本综述全面总结了用于识别新病毒受体以及最常见的、、和蚊媒病毒推定进入因子的传统方法和新方法。同时,我们强调了这些病毒用于进入脊椎动物宿主和蚊媒的共同受体。我们讨论了针对这些受体开发抗蚊媒病毒策略的有前景的途径。值得注意的是,针对脊椎动物和蚊子中特定蚊媒病毒的通用受体进行靶向,对疾病预防具有双重益处。此外,基于人工智能的机器学习和蛋白质结构预测的广泛应用将加速新病毒受体的识别,并为抗病毒药物发现提供新途径。