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Related Experiment Video

Updated: May 25, 2026

Modeling Ligands into Maps Derived from Electron Cryomicroscopy
09:30

Modeling Ligands into Maps Derived from Electron Cryomicroscopy

Published on: July 19, 2024

Ab initio protein modeling into CryoEM density maps using EM-Fold.

Steffen Lindert1, Tommy Hofmann, Nils Wötzel

  • 1Department of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, TN 37212, USA.

Biopolymers
|February 4, 2012
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Cryo-electron Microscopy01:28

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Lanthipeptide structure prediction and design with Rosetta.

Methods in enzymology·2026

EM-Fold successfully modeled protein structures from cryo-electron microscopy data by assembling secondary structure elements. Subsequent refinement with Rosetta improved accuracy, achieving low root-mean-square deviation values in this structural biology challenge.

Area of Science:

  • Structural biology
  • Computational biology
  • Biophysics

Background:

  • Cryo-electron microscopy (cryo-EM) provides low-resolution 3D density maps of biological macromolecules.
  • Accurate atomic model building into these maps is crucial for understanding protein function.
  • Ab initio modeling methods aim to build models without prior structural templates.

Purpose of the Study:

  • To evaluate the performance of EM-Fold for ab initio protein model building in cryo-EM density maps.
  • To assess the effectiveness of combining EM-Fold with Rosetta for refining protein models.

Main Methods:

  • EM-Fold was used to assemble predicted secondary structure elements (SSEs) into cryo-EM density maps of GroEL and ribosome.
  • A Monte Carlo algorithm guided the assembly, considering loop closure and density-SSE agreement.

Related Experiment Videos

Last Updated: May 25, 2026

Modeling Ligands into Maps Derived from Electron Cryomicroscopy
09:30

Modeling Ligands into Maps Derived from Electron Cryomicroscopy

Published on: July 19, 2024

  • Top models were refined by adjusting SSEs, followed by loop and side-chain modeling using Rosetta with a density-based force field.

    • Main Results:

    • EM-Fold generated models with backbone RMSD values ranging from 2.4 to 3.5 Å for six out of nine proteins.
    • Combined EM-Fold and Rosetta refinement achieved all-atom RMSDs as low as 3.4 Å.
    • Modeling challenges were observed for proteins with low secondary structure content, resulting in higher RMSDs.

    Conclusions:

    • EM-Fold is a viable tool for ab initio protein modeling in medium-to-high resolution cryo-EM maps.
    • Integrating Rosetta enhances model accuracy, particularly for loop and side-chain regions.
    • Further development is needed for proteins with complex loop structures and low secondary structure content.