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肠道病毒 30 与其受体复合物的结构为合理预测肠道病毒受体的使用提供了信息。

Structures of Echovirus 30 in complex with its receptors inform a rational prediction for enterovirus receptor usage.

机构信息

CAS Key Laboratory of Infection and Immunity, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.

NHC Key Laboratories of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.

出版信息

Nat Commun. 2020 Sep 4;11(1):4421. doi: 10.1038/s41467-020-18251-9.

DOI:10.1038/s41467-020-18251-9
PMID:32887891
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7474057/
Abstract

Receptor usage that determines cell tropism and drives viral classification closely correlates with the virus structure. Enterovirus B (EV-B) consists of several subgroups according to receptor usage, among which echovirus 30 (E30), a leading causative agent for human aseptic meningitis, utilizes FcRn as an uncoating receptor. However, receptors for many EVs remain unknown. Here we analyzed the atomic structures of E30 mature virion, empty- and A-particles, which reveals serotype-specific epitopes and striking conformational differences between the subgroups within EV-Bs. Of these, the VP1 BC loop markedly distinguishes E30 from other EV-Bs, indicative of a role as a structural marker for EV-B. By obtaining cryo-electron microscopy structures of E30 in complex with its receptor FcRn and CD55 and comparing its homologs, we deciphered the underlying molecular basis for receptor recognition. Together with experimentally derived viral receptor identifications, we developed a structure-based in silico algorithm to inform a rational prediction for EV receptor usage.

摘要

受体使用决定了细胞嗜性,并推动了病毒分类,这与病毒结构密切相关。肠道病毒 B(EV-B)根据受体使用情况分为几个亚群,其中柯萨奇病毒 30(E30)是引起人类无菌性脑膜炎的主要病原体,利用 FcRn 作为脱壳受体。然而,许多 EV 的受体仍然未知。在这里,我们分析了 E30 成熟病毒体、空病毒和 A 病毒粒子的原子结构,揭示了血清型特异性表位和 EV-B 内亚群之间惊人的构象差异。其中,VP1 BC 环明显将 E30 与其他 EV-B 区分开来,表明它是 EV-B 的结构标志物。通过获得 E30 与其受体 FcRn 和 CD55 复合物的冷冻电镜结构,并比较其同源物,我们揭示了受体识别的潜在分子基础。结合实验获得的病毒受体鉴定结果,我们开发了一种基于结构的计算算法,以合理预测 EV 受体的使用情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/33c1c829b649/41467_2020_18251_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/93f7d261a58f/41467_2020_18251_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/a5453f985d19/41467_2020_18251_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/33c1c829b649/41467_2020_18251_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/93f7d261a58f/41467_2020_18251_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/a5453f985d19/41467_2020_18251_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9abd/7474057/33c1c829b649/41467_2020_18251_Fig4_HTML.jpg

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