1. Structural Biology and Molecular Biophysics
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Automated cryo-EM structure refinement using correlation-driven molecular dynamics

  1. Maxim Igaev  Is a corresponding author
  2. Carsten Kutzner
  3. Lars V Bock
  4. Andrea C Vaiana  Is a corresponding author
  5. Helmut Grubmüller  Is a corresponding author
  1. Max Planck Institute for Biophysical Chemistry, Germany
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Cite this article as: eLife 2019;8:e43542 doi: 10.7554/eLife.43542

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.

Article and author information

Author details

  1. 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.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8781-1604
  2. 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.
  3. 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.
  4. 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.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8865-0651
  5. 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.
    ORCID icon "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

  1. Axel T Brunger, Stanford University, United States

Publication history

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

Copyright

© 2019, Igaev et al.

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.

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