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Updated: Jan 8, 2026

Cryo-EM and Single-Particle Analysis with Scipion
Published on: May 29, 2021
Cryo-EM Analysis in CASP16
Thomas Mulvaney1,2, Andriy Kryshtafovych3, Maya Topf1,2,4
1Research Department of Integrative Virology, Leibniz Institute of Virology (LIV), Hamburg, Germany.
Cryo-electron microscopy (cryo-EM) data reveals local resolution correlates with protein flexibility in predictions. This finding aids in assessing atomic models and identifying discrepancies between predictions and experimental data.
Area of Science:
- Structural Biology
- Computational Biology
- Biophysics
Background:
- Experimentalists are encouraged to submit cryo-electron microscopy (cryo-EM) data and atomic models for assessment in CASP.
- CASP16 saw 38 cryo-EM datasets submitted, representing most targets, often with a single atomic structure provided.
Purpose of the Study:
- To investigate the relationship between local resolution in cryo-EM reconstructions and the flexibility of predicted protein structures.
- To evaluate the accuracy of CASP predictions by comparing them with experimental cryo-EM data and local resolution information.
Main Methods:
- Analysis of 38 cryo-EM datasets from CASP16.
- Correlation analysis between local resolution in cryo-EM maps and root-mean-square fluctuations (RMSF) of residues in CASP predictions.
- Assessment of sidechain details using a variant of SMOC with local fragment alignment.
Main Results:
- Local resolution in cryo-EM reconstructions shows a good correlation with the root-mean-square fluctuations (RMSF) of residues in accurate CASP predictions.
- The correlation between local resolution and pLDDT was less clear, particularly with mobile domains.
- Assessment of sidechains revealed areas for improvement in high-quality predictions and identified modeling discrepancies in some targets.
Conclusions:
- Local resolution in cryo-EM data serves as a valuable indicator of structural flexibility in predicted models.
- Experimental cryo-EM data is crucial for model-free assessment, enabling unique analyses like comparison to local resolution.
- Discrepancies between predictions and experimental density highlight areas where modeling needs refinement.
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