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Cryo-electron Microscopy

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Updated: Jul 27, 2025

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

基于自动模拟的膜蛋白精制成冷EM数据.

Linnea Yvonnesdotter¹, Urška Rovšnik¹, Christian Blau²

¹Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden.

Biophysical journal

|June 6, 2023

概括

这项研究引入了一种使用密度引导分子动力学模拟的自动化协议,用于将膜蛋白模型改进为冷电子显微镜 (cryo-EM) 地图. 这种方法简化了模型的合适性,并提高了药物标发现的准确性.

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Cryo-EM and Single-Particle Analysis with Scipion

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

相关实验视频

Last Updated: Jul 27, 2025

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

Cryo-EM and Single-Particle Analysis with Scipion

Cryo-EM and Single-Particle Analysis with Scipion

Published on: May 29, 2021

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

Published on: January 31, 2022

科学领域:

结构生物学结构生物学
计算生物学计算生物学
生物物理学的生物物理.

背景情况:

单粒子冷电子显微镜 (cryo-EM) 的进步允许对复杂的生物系统进行高分辨率成像.
膜蛋白是关键的药物标,但在结构上有挑战性研究.
将精确的原子模型精细化成冷EM地图对于理解蛋白质功能至关重要.

研究的目的:

开发和验证一种自动化的协议,用于将原子模型精制成膜蛋白冷EM密度图.
为了证明密度导向分子动力学模拟对这个过程的实用性.
建立选择最适合模型的标准,平衡结构完整性和地图相关性.

主要方法:

在GROMACS包中利用了适应力密度引导的分子动力学模拟.
实现了一个自动化工作流程,用于在没有手动参数调整的情况下进行模型改进.
制定了选择标准,以优化模型的合适性,考虑立体化学和合适质量.
应用该协议来完善马尔托波林的模型,在脂质双层和洗剂微粒内的冷EM密度.
使用密度指导的配合与一般化取决于方向的全原子潜力来纠正冷-EM地图像素大小.

主要成果:

自动化协议成功地将原子模型改进为膜蛋白冷EM图.
无论蛋白质是在脂质双层,洗剂微粒或溶液中,精炼结果都是可比的.
装配的结构符合标准模型质量指标,并增强了与实验冷电磁数据的相关性.
该方法提高了现有的X射线结构的质量.
实现了对冷EM图的精确像素大小估计.

结论:

本协议提供了一种简单而自动化的方法,用于将膜蛋白模型安装到冷EM密度中.
这种计算方法可以在各种条件和联结状态中快速改进模型.
这种方法对于研究重要的膜蛋白超级家族特别有价值,加速了药物发现工作.