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用于评估最佳像素大小以提高单颗粒冷冻电子显微镜图谱准确性的计算方案。

Computational Protocol for Assessing the Optimal Pixel Size to Improve the Accuracy of Single-particle Cryo-electron Microscopy Maps.

机构信息

Computational Structural Biology Division, RIKEN Center for Computational Science, Kobe, Hyogo Prefecture 650-0047, Japan.

Department of Chemistry, University of Michigan-Ann Arbor, Ann Arbor, Michigan 48109-1382, United States.

出版信息

J Chem Inf Model. 2020 May 26;60(5):2570-2580. doi: 10.1021/acs.jcim.9b01107. Epub 2020 Feb 14.

DOI:10.1021/acs.jcim.9b01107
PMID:32003995
Abstract

Cryo-electron microscopy (cryo-EM) single-particle analysis has come a long way in achieving atomic-level resolution when imaging biomolecules. To obtain the best possible three-dimensional (3D) structure in cryo-EM, many parameters have to be carefully considered. Here we address the often-overlooked parameter of the pixel size, which describes the magnification of the image produced by the experiment. While efforts are made to refine and validate this parameter in the analysis of cryo-EM experimental data, there is no systematic protocol in place. Since the pixel size parameter can have an impact on the resolution and accuracy of a cryo-EM map, and the atomic resolution 3D structure models derived from it, we propose a computational protocol to estimate the appropriate pixel size parameter. In our protocol, we fit and refine atomic structures against cryo-EM maps at multiple pixel sizes. The resulting fitted and refined structures are evaluated using the GOAP (generalized orientation-dependent, all-atom statistical potential) score, which we found to perform better than other commonly used functions, such as Molprobity and the correlation coefficient from refinement. Finally, we describe the efficacy of this protocol in retrieving appropriate pixel sizes for several examples; simulated data based on yeast elongation factor 2 and experimental data from Gro-EL chaperone, beta-galactosidase, and the TRPV1 ion channel.

摘要

低温电子显微镜(cryo-EM)单颗粒分析在对生物分子进行成像时,已经取得了很大的进展,可以达到原子级分辨率。为了在 cryo-EM 中获得最佳的三维(3D)结构,必须仔细考虑许多参数。在这里,我们讨论了经常被忽视的像素大小参数,它描述了实验产生的图像的放大倍数。虽然在分析 cryo-EM 实验数据时,人们努力细化和验证这个参数,但目前还没有系统的方案。由于像素大小参数会影响 cryo-EM 图谱的分辨率和准确性,以及从中得出的原子分辨率 3D 结构模型,我们提出了一种计算方案来估计合适的像素大小参数。在我们的方案中,我们在多个像素大小下拟合和细化原子结构对 cryo-EM 图谱。使用我们发现比其他常用函数(如 Molprobity 和来自细化的相关系数)表现更好的 GOAP(广义取向依赖,全原子统计势)评分来评估得到的拟合和细化结构。最后,我们描述了该方案在检索几个示例的适当像素大小方面的效果;基于酵母延伸因子 2 的模拟数据和 Gro-EL 伴侣、β-半乳糖苷酶和 TRPV1 离子通道的实验数据。

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引用本文的文献

1
Automated simulation-based membrane protein refinement into cryo-EM data.基于自动化模拟的膜蛋白低温电镜数据重构。
Biophys J. 2023 Jul 11;122(13):2773-2781. doi: 10.1016/j.bpj.2023.05.033. Epub 2023 Jun 5.
2
Faces of Contemporary CryoEM Information and Modeling.当代冷冻电镜信息与建模的面貌。
J Chem Inf Model. 2020 May 26;60(5):2407-2409. doi: 10.1021/acs.jcim.0c00481.