Cargando…

Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination

Three-dimensional reconstruction of the electron-scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularization approach that is based on the prior assum...

Descripción completa

Detalles Bibliográficos
Autores principales: Kimanius, Dari, Zickert, Gustav, Nakane, Takanori, Adler, Jonas, Lunz, Sebastian, Schönlieb, Carola-Bibiane, Öktem, Ozan, Scheres, Sjors H. W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793004/
https://www.ncbi.nlm.nih.gov/pubmed/33520243
http://dx.doi.org/10.1107/S2052252520014384
_version_ 1783633900222808064
author Kimanius, Dari
Zickert, Gustav
Nakane, Takanori
Adler, Jonas
Lunz, Sebastian
Schönlieb, Carola-Bibiane
Öktem, Ozan
Scheres, Sjors H. W.
author_facet Kimanius, Dari
Zickert, Gustav
Nakane, Takanori
Adler, Jonas
Lunz, Sebastian
Schönlieb, Carola-Bibiane
Öktem, Ozan
Scheres, Sjors H. W.
author_sort Kimanius, Dari
collection PubMed
description Three-dimensional reconstruction of the electron-scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularization approach that is based on the prior assumption that the scattering potential varies smoothly over three-dimensional space. Although this approach has been hugely successful in recent years, the amount of prior knowledge that it exploits compares unfavorably with the knowledge about biological structures that has been accumulated over decades of research in structural biology. Here, a regularization framework for cryo-EM structure determination is presented that exploits prior knowledge about biological structures through a convolutional neural network that is trained on known macromolecular structures. This neural network is inserted into the iterative cryo-EM structure-determination process through an approach that is inspired by regularization by denoising. It is shown that the new regularization approach yields better reconstructions than the current state of the art for simulated data, and options to extend this work for application to experimental cryo-EM data are discussed.
format Online
Article
Text
id pubmed-7793004
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher International Union of Crystallography
record_format MEDLINE/PubMed
spelling pubmed-77930042021-01-29 Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination Kimanius, Dari Zickert, Gustav Nakane, Takanori Adler, Jonas Lunz, Sebastian Schönlieb, Carola-Bibiane Öktem, Ozan Scheres, Sjors H. W. IUCrJ Research Papers Three-dimensional reconstruction of the electron-scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularization approach that is based on the prior assumption that the scattering potential varies smoothly over three-dimensional space. Although this approach has been hugely successful in recent years, the amount of prior knowledge that it exploits compares unfavorably with the knowledge about biological structures that has been accumulated over decades of research in structural biology. Here, a regularization framework for cryo-EM structure determination is presented that exploits prior knowledge about biological structures through a convolutional neural network that is trained on known macromolecular structures. This neural network is inserted into the iterative cryo-EM structure-determination process through an approach that is inspired by regularization by denoising. It is shown that the new regularization approach yields better reconstructions than the current state of the art for simulated data, and options to extend this work for application to experimental cryo-EM data are discussed. International Union of Crystallography 2021-01-01 /pmc/articles/PMC7793004/ /pubmed/33520243 http://dx.doi.org/10.1107/S2052252520014384 Text en © Dari Kimanius et al. 2021 http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited.http://creativecommons.org/licenses/by/4.0/
spellingShingle Research Papers
Kimanius, Dari
Zickert, Gustav
Nakane, Takanori
Adler, Jonas
Lunz, Sebastian
Schönlieb, Carola-Bibiane
Öktem, Ozan
Scheres, Sjors H. W.
Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
title Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
title_full Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
title_fullStr Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
title_full_unstemmed Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
title_short Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination
title_sort exploiting prior knowledge about biological macromolecules in cryo-em structure determination
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793004/
https://www.ncbi.nlm.nih.gov/pubmed/33520243
http://dx.doi.org/10.1107/S2052252520014384
work_keys_str_mv AT kimaniusdari exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT zickertgustav exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT nakanetakanori exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT adlerjonas exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT lunzsebastian exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT schonliebcarolabibiane exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT oktemozan exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination
AT scheressjorshw exploitingpriorknowledgeaboutbiologicalmacromoleculesincryoemstructuredetermination