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Related Experiment Video

Updated: Jun 21, 2026

Single Particle Cryo-Electron Microscopy: From Sample to Structure
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Single Particle Cryo-Electron Microscopy: From Sample to Structure

Published on: May 29, 2021

Refinement of protein structures into low-resolution density maps using rosetta.

Frank DiMaio1, Michael D Tyka, Matthew L Baker

  • 1Department of Biochemistry, University of Washington, Seattle, 98195, USA. dimaio@u.washington.edu

Journal of Molecular Biology
|July 15, 2009
PubMed
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This study presents a new method using Rosetta refinement to build accurate, high-resolution protein models from cryo-EM density maps. The technique improves model quality and can achieve near-atomic resolution even with lower-resolution maps.

Area of Science:

  • Structural Biology
  • Biophysics
  • Computational Biology

Background:

  • Electron cryomicroscopy (cryo-EM) is a powerful technique for determining protein structures.
  • Generating accurate, high-resolution atomic models from cryo-EM density maps remains a challenge.

Purpose of the Study:

  • To develop and validate a method for generating high-resolution, all-atom protein models from cryo-EM density maps.
  • To improve the accuracy of protein models derived from cryo-EM data.

Main Methods:

  • Utilized Rosetta structure refinement software.
  • Employed a local measure of model-to-density fit to guide refinement.
  • Implemented targeted rebuilding of regions inconsistent with the density map.

Main Results:

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Last Updated: Jun 21, 2026

Single Particle Cryo-Electron Microscopy: From Sample to Structure
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Published on: May 29, 2021

Enhancing Density Maps by Removing the Majority of Particles in Single Particle Cryogenic Electron Microscopy Final Stacks
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  • Consistently improved the accuracy of starting models from comparative modeling or hand-tracing.
  • Demonstrated success across various test cases with simulated and experimental data.
  • Achieved near-atomic resolution from cryo-EM density maps at 4-6 Å resolution.

Conclusions:

  • The Rosetta-based refinement method effectively generates accurate, high-resolution protein models from cryo-EM data.
  • The approach is robust and applicable to diverse datasets, enhancing structural biology research.