Chiu Wah, Baker Matthew L, Jiang Wen, Dougherty Matthew, Schmid Michael F
National Center for Macromolecular Imaging, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas 77030, USA.
Structure. 2005 Mar;13(3):363-72. doi: 10.1016/j.str.2004.12.016.
Advances in electron cryomicroscopy (cryo-EM) have made possible the structural determination of large biological machines in the resolution range of 6-9 angstroms. Rice dwarf virus and the acrosomal bundle represent two distinct types of machines amenable to cryo-EM investigations at subnanometer resolutions. However, calculating the density map is only the first step, and much analysis remains to extract structural insights and the mechanism of action in these machines. This paper will review the computational and visualization methodologies necessary for analysis (structure mining) of the computed cryo-EM maps of these machines. These steps include component segmentation, averaging based on local symmetry among components, density connectivity trace, incorporation of bioinformatics analysis, and fitting of high-resolution component data, if available. The consequences of these analyses can not only identify accurately some of the secondary structure elements of the molecular components in machines but also suggest structural mechanisms related to their biological functions.
电子冷冻显微镜技术(cryo-EM)的进步使得在6-9埃分辨率范围内确定大型生物机器的结构成为可能。水稻矮缩病毒和顶体束代表了两种不同类型的机器,适合在亚纳米分辨率下进行冷冻电镜研究。然而,计算密度图只是第一步,还需要进行大量分析才能提取这些机器的结构见解和作用机制。本文将回顾分析这些机器的计算冷冻电镜图(结构挖掘)所需的计算和可视化方法。这些步骤包括组件分割、基于组件间局部对称性的平均、密度连通性追踪、纳入生物信息学分析,以及如果有高分辨率组件数据则进行拟合。这些分析的结果不仅可以准确识别机器中分子组件的一些二级结构元素,还可以揭示与其生物学功能相关的结构机制。