Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models

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 a...

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Detalles Bibliográficos
Autores principales: Chen, Muyuan, Schmid, Michael F., Chiu, Wah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491338/
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author Chen, Muyuan
Schmid, Michael F.
Chiu, Wah
author_facet Chen, Muyuan
Schmid, Michael F.
Chiu, Wah
author_sort Chen, Muyuan
collection PubMed
description 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.
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spelling pubmed-104913382023-09-09 Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models Chen, Muyuan Schmid, Michael F. Chiu, Wah ArXiv Article 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. Cornell University 2023-08-29 /pmc/articles/PMC10491338/ Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Chen, Muyuan
Schmid, Michael F.
Chiu, Wah
Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models
title Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models
title_full Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models
title_fullStr Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models
title_full_unstemmed Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models
title_short Improving Resolution and Resolvability of Single Particle CryoEM Structures using Gaussian Mixture Models
title_sort improving resolution and resolvability of single particle cryoem structures using gaussian mixture models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10491338/
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AT schmidmichaelf improvingresolutionandresolvabilityofsingleparticlecryoemstructuresusinggaussianmixturemodels
AT chiuwah improvingresolutionandresolvabilityofsingleparticlecryoemstructuresusinggaussianmixturemodels

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