Model-based local density sharpening of cryo-EM maps

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Abstract

Atomic models based on high-resolution density maps are the ultimate result of the cryo-EM structure determination process. Here, we introduce a general procedure for local sharpening of cryo-EM density maps based on prior knowledge of an atomic reference structure. The procedure optimizes contrast of cryo-EM densities by amplitude scaling against the radially averaged local falloff estimated from a windowed reference model. By testing the procedure using six cryo-EM structures of TRPV1, β-galactosidase, γ-secretase, ribosome-EF-Tu complex, 20S proteasome and RNA polymerase III, we illustrate how local sharpening can increase interpretability of density maps in particular in cases of resolution variation and facilitates model building and atomic model refinement.

Data availability

The following previously published data sets were used

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Article and author information

Author details

Arjen J Jakobi

Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-7761-2027
Matthias Wilmanns

European Molecular Biology Laboratory, Hamburg, Germany

Competing interests
The authors declare that no competing interests exist.
Carsten Sachse

Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

For correspondence
carsten.sachse@embl.de

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-1168-5143

Funding

Marie Curie Actions (PCOFUND-GA-2008-229597)

Arjen J Jakobi

Marie-Sklodowska-Curie (PIEF-GA-2012-331285)

Arjen J Jakobi

Deutsche Forschungsgemeinschaft (Hamburg Center for Ultrafast Imaging (CUI))

Arjen J Jakobi

Joachim Herz Stiftung

Arjen J Jakobi

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.