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Title: Density modification of cryo-EM maps

Abstract

Density modification uses expectations about features of a map such as a flat solvent and expected distributions of density in the region of the macromolecule to improve individual Fourier terms representing the map. This process transfers information from one part of a map to another and can improve the accuracy of a map. Here, the assumptions behind density modification for maps from electron cryomicroscopy are examined and a procedure is presented that allows the incorporation of model-based information. Density modification works best in cases where unfiltered, unmasked maps with clear boundaries between the macromolecule and solvent are visible, and where there is substantial noise in the map, both in the region of the macromolecule and the solvent. It also is most effective if the characteristics of the map are relatively constant within regions of the macromolecule and the solvent. Model-based information can be used to improve density modification, but model bias can in principle occur. Here, model bias is reduced by using ensemble models that allow an estimation of model uncertainty. A test of model bias is presented that suggests that even if the expected density in a region of a map is specified incorrectly by using an incorrect model,more » the incorrect expectations do not strongly affect the final map.« less

Authors:
ORCiD logo; ORCiD logo; ORCiD logo; ORCiD logo; ORCiD logo
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC); National Institutes of Health (NIH); Wellcome Trust
OSTI Identifier:
1664563
Alternate Identifier(s):
OSTI ID: 1713273; OSTI ID: 1739996
Report Number(s):
LA-UR-20-23439
Journal ID: ISSN 2059-7983; ACSDAD; PII: S205979832001061X
Grant/Contract Number:  
AC02-05CH11231; P01GM063210; 209407/Z/17/Z; 89233218CNA000001
Resource Type:
Published Article
Journal Name:
Acta Crystallographica. Section D. Structural Biology
Additional Journal Information:
Journal Name: Acta Crystallographica. Section D. Structural Biology Journal Volume: 76 Journal Issue: 10; Journal ID: ISSN 2059-7983
Publisher:
IUCr
Country of Publication:
United Kingdom
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; electron cryomicroscopy; structural biology; map improvement; density modification

Citation Formats

Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., Adams, Paul D., and Read, Randy J. Density modification of cryo-EM maps. United Kingdom: N. p., 2020. Web. https://doi.org/10.1107/S205979832001061X.
Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., Adams, Paul D., & Read, Randy J. Density modification of cryo-EM maps. United Kingdom. https://doi.org/10.1107/S205979832001061X
Terwilliger, Thomas C., Sobolev, Oleg V., Afonine, Pavel V., Adams, Paul D., and Read, Randy J. Tue . "Density modification of cryo-EM maps". United Kingdom. https://doi.org/10.1107/S205979832001061X.
@article{osti_1664563,
title = {Density modification of cryo-EM maps},
author = {Terwilliger, Thomas C. and Sobolev, Oleg V. and Afonine, Pavel V. and Adams, Paul D. and Read, Randy J.},
abstractNote = {Density modification uses expectations about features of a map such as a flat solvent and expected distributions of density in the region of the macromolecule to improve individual Fourier terms representing the map. This process transfers information from one part of a map to another and can improve the accuracy of a map. Here, the assumptions behind density modification for maps from electron cryomicroscopy are examined and a procedure is presented that allows the incorporation of model-based information. Density modification works best in cases where unfiltered, unmasked maps with clear boundaries between the macromolecule and solvent are visible, and where there is substantial noise in the map, both in the region of the macromolecule and the solvent. It also is most effective if the characteristics of the map are relatively constant within regions of the macromolecule and the solvent. Model-based information can be used to improve density modification, but model bias can in principle occur. Here, model bias is reduced by using ensemble models that allow an estimation of model uncertainty. A test of model bias is presented that suggests that even if the expected density in a region of a map is specified incorrectly by using an incorrect model, the incorrect expectations do not strongly affect the final map.},
doi = {10.1107/S205979832001061X},
journal = {Acta Crystallographica. Section D. Structural Biology},
number = 10,
volume = 76,
place = {United Kingdom},
year = {2020},
month = {9}
}

Journal Article:
Free Publicly Available Full Text
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https://doi.org/10.1107/S205979832001061X

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