Automated cryo-EM structure refinement using correlation-driven molecular dynamics

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Cite this article as: eLife 2019;8:e43542 doi: 10.7554/eLife.43542

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Abstract

We present a correlation-driven molecular dynamics (CDMD) method for automated refinement of atomistic models into cryo-electron microscopy (cryo-EM) maps at resolutions ranging from near-atomic to subnanometer. It utilizes a chemically accurate force field and thermodynamic sampling to improve the real-space correlation between the modeled structure and the cryo-EM map. Our framework employs a gradual increase in resolution and map-model agreement as well as simulated annealing, and allows fully automated refinement without manual intervention or any additional rotamer- and backbone-specific restraints. Using multiple challenging systems covering a wide range of map resolutions, system sizes, starting model geometries and distances from the target state, we assess the quality of generated models in terms of both model accuracy and potential of overfitting. To provide an objective comparison, we apply several well-established methods across all examples and demonstrate that CDMD performs best in most cases.

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Author details

Maxim Igaev

Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

For correspondence
migaev@mpibpc.mpg.de

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-8781-1604
Carsten Kutzner

Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

Competing interests
The authors declare that no competing interests exist.
Lars V Bock

Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

Competing interests
The authors declare that no competing interests exist.
Andrea C Vaiana

Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

For correspondence
Andrea.Vaiana@mpibpc.mpg.de

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-8865-0651
Helmut Grubmüller

Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

For correspondence
hgrubmu@gwdg.de

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-3270-3144

Funding

Max-Planck-Gesellschaft (Open-access funding)

Maxim Igaev
Carsten Kutzner
Lars V Bock
Andrea C Vaiana
Helmut Grubmüller

Deutsche Forschungsgemeinschaft (Open-access funding)

Maxim Igaev
Andrea C Vaiana

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

Reviewing Editor

Axel T Brunger, Stanford University, United States

Publication history

Received: November 9, 2018
Accepted: March 3, 2019
Accepted Manuscript published: March 4, 2019 (version 1)
Version of Record published: March 19, 2019 (version 2)

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.