Castón J R, Belnap D M, Steven A C, Trus B L
Laboratory of Structural Biology Research, National Institute of Arthritis, Musculoskeletal and Skin Diseases, Bethesda, Maryland 20892-5624, USA.
J Struct Biol. 1999 Apr-May;125(2-3):209-15. doi: 10.1006/jsbi.1999.4085.
Cryo-electron microscopy and three-dimensional image reconstruction are powerful tools for analyzing icosahedral virus capsids at resolutions that now extend below 1 nm. However, the validity of such density maps depends critically on correct identification of the viewing geometry of each particle in the data set. In some cases-for example, round capsids with low surface relief-it is difficult to identify orientations by conventional application of the two most widely used approaches-"common lines" and model-based iterative refinement. We describe here a strategy for determining the orientations of such refractory specimens. The key step is to determine reliable orientations for a base set of particles. For each particle, a list of candidate orientations is generated by common lines: correct orientations are then identified by computing a single-particle reconstruction for each candidate and then systematically matching their reprojections with the original images by visual criteria and cross-correlation analysis. This base set yields a first-generation reconstruction that is fed into the model-based procedure. This strategy has led to the structural determination of two viruses that, in our hands, resisted solution by other means.
冷冻电子显微镜和三维图像重建是用于分析二十面体病毒衣壳的强大工具,其分辨率目前已降至1nm以下。然而,这种密度图的有效性关键取决于数据集中每个粒子观察几何结构的正确识别。在某些情况下,例如表面起伏较小的圆形衣壳,通过常规应用两种最广泛使用的方法——“共线”和基于模型的迭代精修——来识别方向是困难的。我们在此描述一种确定此类难处理标本方向的策略。关键步骤是为一组基础粒子确定可靠的方向。对于每个粒子,通过共线生成候选方向列表:然后通过为每个候选方向计算单粒子重建,再通过视觉标准和互相关分析系统地将其重投影与原始图像匹配,来识别正确的方向。这个基础集产生第一代重建结果,将其输入基于模型的程序中。在我们手中,这种策略已导致两种病毒的结构确定,而其他方法未能解决这两种病毒的结构问题。