Molecular dynamics-based model refinement and validation for sub-5 Å cryo-electron microscopy maps

  1. Abhishek Singharoy  Is a corresponding author
  2. Ivan Teo
  3. Ryan McGreevy
  4. John E Stone
  5. Jianhua Zhao
  6. Klaus Schulten  Is a corresponding author
  1. University of Illinois at Urbana Champaign, United States
  2. University of Illinois at Urbana-Champaign, United States
  3. University of California, San Francisco, United States

Abstract

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5-Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a convergence radius of ~25Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2Å and 3.4Å resolution. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the respective macromolecules studied, captured employing local root mean square fluctuations. The MDFF tools are made available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

Data availability

The following previously published data sets were used

Article and author information

Author details

  1. Abhishek Singharoy

    Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign, Urbana, United States
    For correspondence
    singharo@illinois.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Ivan Teo

    Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Ryan McGreevy

    Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. John E Stone

    Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Jianhua Zhao

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Klaus Schulten

    Department of Physics, University of Illinois at Urbana-Champaign, Urbana, United States
    For correspondence
    kschulte@ks.uiuc.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7192-9632

Reviewing Editor

  1. Axel T Brunger, Howard Hughes Medical Institute, Stanford University, United States

Version history

  1. Received: March 16, 2016
  2. Accepted: July 6, 2016
  3. Accepted Manuscript published: July 7, 2016 (version 1)
  4. Accepted Manuscript updated: July 8, 2016 (version 2)
  5. Version of Record published: August 18, 2016 (version 3)
  6. Version of Record updated: October 7, 2016 (version 4)

Copyright

© 2016, singharoy 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.

Metrics

  • 5,641
    views
  • 1,086
    downloads
  • 133
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Abhishek Singharoy
  2. Ivan Teo
  3. Ryan McGreevy
  4. John E Stone
  5. Jianhua Zhao
  6. Klaus Schulten
(2016)
Molecular dynamics-based model refinement and validation for sub-5 Å cryo-electron microscopy maps
eLife 5:e16105.
https://doi.org/10.7554/eLife.16105

Share this article

https://doi.org/10.7554/eLife.16105

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Damien M Rasmussen, Manny M Semonis ... Nicholas M Levinson
    Research Article

    The type II class of RAF inhibitors currently in clinical trials paradoxically activate BRAF at subsaturating concentrations. Activation is mediated by induction of BRAF dimers, but why activation rather than inhibition occurs remains unclear. Using biophysical methods tracking BRAF dimerization and conformation, we built an allosteric model of inhibitor-induced dimerization that resolves the allosteric contributions of inhibitor binding to the two active sites of the dimer, revealing key differences between type I and type II RAF inhibitors. For type II inhibitors the allosteric coupling between inhibitor binding and BRAF dimerization is distributed asymmetrically across the two dimer binding sites, with binding to the first site dominating the allostery. This asymmetry results in efficient and selective induction of dimers with one inhibited and one catalytically active subunit. Our allosteric models quantitatively account for paradoxical activation data measured for 11 RAF inhibitors. Unlike type II inhibitors, type I inhibitors lack allosteric asymmetry and do not activate BRAF homodimers. Finally, NMR data reveal that BRAF homodimers are dynamically asymmetric with only one of the subunits locked in the active αC-in state. This provides a structural mechanism for how binding of only a single αC-in inhibitor molecule can induce potent BRAF dimerization and activation.

    1. Structural Biology and Molecular Biophysics
    Nicholas James Ose, Paul Campitelli ... Sefika Banu Ozkan
    Research Article

    We integrate evolutionary predictions based on the neutral theory of molecular evolution with protein dynamics to generate mechanistic insight into the molecular adaptations of the SARS-COV-2 spike (S) protein. With this approach, we first identified candidate adaptive polymorphisms (CAPs) of the SARS-CoV-2 S protein and assessed the impact of these CAPs through dynamics analysis. Not only have we found that CAPs frequently overlap with well-known functional sites, but also, using several different dynamics-based metrics, we reveal the critical allosteric interplay between SARS-CoV-2 CAPs and the S protein binding sites with the human ACE2 (hACE2) protein. CAPs interact far differently with the hACE2 binding site residues in the open conformation of the S protein compared to the closed form. In particular, the CAP sites control the dynamics of binding residues in the open state, suggesting an allosteric control of hACE2 binding. We also explored the characteristic mutations of different SARS-CoV-2 strains to find dynamic hallmarks and potential effects of future mutations. Our analyses reveal that Delta strain-specific variants have non-additive (i.e., epistatic) interactions with CAP sites, whereas the less pathogenic Omicron strains have mostly additive mutations. Finally, our dynamics-based analysis suggests that the novel mutations observed in the Omicron strain epistatically interact with the CAP sites to help escape antibody binding.