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Subtomogram averaging for biophysical analysis and supramolecular context
Recent advances in hardware, software and computing power have led to increasingly ambitious applications of cryo-electron tomography and subtomogram averaging. It is now possible to reveal both structures and biophysical relationships like protein binding partners and small molecule occupancy in th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596874/ https://www.ncbi.nlm.nih.gov/pubmed/36311290 http://dx.doi.org/10.1016/j.yjsbx.2022.100076 |
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author | Metskas, Lauren Ann Wilfong, Rosalie Jensen, Grant J. |
author_facet | Metskas, Lauren Ann Wilfong, Rosalie Jensen, Grant J. |
author_sort | Metskas, Lauren Ann |
collection | PubMed |
description | Recent advances in hardware, software and computing power have led to increasingly ambitious applications of cryo-electron tomography and subtomogram averaging. It is now possible to reveal both structures and biophysical relationships like protein binding partners and small molecule occupancy in these experiments. However, some data processing choices require the user to prioritize structure or biophysical context. Here, we present a modified subtomogram averaging approach that preserves both capabilities. By increasing the accuracy of particle-picking, performing alignment and averaging on all subtomograms, and decreasing reliance on symmetry and tight masks, the usability of tomography and subtomogram averaging data for biophysical analyses is greatly increased without negatively impacting structural refinements. |
format | Online Article Text |
id | pubmed-9596874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-95968742022-10-27 Subtomogram averaging for biophysical analysis and supramolecular context Metskas, Lauren Ann Wilfong, Rosalie Jensen, Grant J. J Struct Biol X Research Article Recent advances in hardware, software and computing power have led to increasingly ambitious applications of cryo-electron tomography and subtomogram averaging. It is now possible to reveal both structures and biophysical relationships like protein binding partners and small molecule occupancy in these experiments. However, some data processing choices require the user to prioritize structure or biophysical context. Here, we present a modified subtomogram averaging approach that preserves both capabilities. By increasing the accuracy of particle-picking, performing alignment and averaging on all subtomograms, and decreasing reliance on symmetry and tight masks, the usability of tomography and subtomogram averaging data for biophysical analyses is greatly increased without negatively impacting structural refinements. Elsevier 2022-10-18 /pmc/articles/PMC9596874/ /pubmed/36311290 http://dx.doi.org/10.1016/j.yjsbx.2022.100076 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Metskas, Lauren Ann Wilfong, Rosalie Jensen, Grant J. Subtomogram averaging for biophysical analysis and supramolecular context |
title | Subtomogram averaging for biophysical analysis and supramolecular context |
title_full | Subtomogram averaging for biophysical analysis and supramolecular context |
title_fullStr | Subtomogram averaging for biophysical analysis and supramolecular context |
title_full_unstemmed | Subtomogram averaging for biophysical analysis and supramolecular context |
title_short | Subtomogram averaging for biophysical analysis and supramolecular context |
title_sort | subtomogram averaging for biophysical analysis and supramolecular context |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596874/ https://www.ncbi.nlm.nih.gov/pubmed/36311290 http://dx.doi.org/10.1016/j.yjsbx.2022.100076 |
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