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使用高斯混合模型提高单颗粒 cryoEM 结构的分辨率和可分辨性。

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models.

机构信息

Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA, USA.

Department of Bioengineering, and of Microbiology and Immunology, Stanford University, Stanford, CA, USA.

出版信息

Nat Methods. 2024 Jan;21(1):37-40. doi: 10.1038/s41592-023-02082-9. Epub 2023 Nov 16.

DOI:10.1038/s41592-023-02082-9
PMID:37973972
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10860619/
Abstract

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.

摘要

低温电子显微镜在结构生物学中被广泛应用,但它的分辨率通常受到大分子动力学的限制。在这里,我们开发了一种基于高斯混合模型的精修方案,该方案集成了粒子取向和构象估计,并改进了蛋白质结构柔性域的对准。我们在多个数据集上验证了该方案,通过视觉和定量测量,在局部和全局范围内提高了分辨率和可分辨性。

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