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Cryo-electron Microscopy01:28

Cryo-electron Microscopy

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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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Related Experiment Video

Updated: Jun 24, 2025

A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion
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A Robust Single-Particle Cryo-Electron Microscopy cryo-EM Processing Workflow with cryoSPARC, RELION, and Scipion

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CLEAPA: a framework for exploring the conformational landscape of cryo-EM using energy-aware pathfinding algorithm.

Teng-Yu Lin1, Szu-Chi Chung1

  • 1Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung 804, Taiwan.

Bioinformatics (Oxford, England)
|June 5, 2024
PubMed
Summary
This summary is machine-generated.

This study presents a new framework for finding preferred pathways in complex, high-dimensional molecular landscapes. The method uses local density to estimate energy, enabling accurate identification of transition states in biomolecular conformational changes.

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Biophysics

Background:

  • Cryo-electron microscopy (cryo-EM) enables studying macromolecular conformational changes.
  • Representing complex biomolecular dynamics in 2D energy landscapes is challenging.
  • High-dimensional latent spaces from cryo-EM offer richer conformational information.

Purpose of the Study:

  • To develop a novel framework for identifying preferred transition pathways in high-dimensional conformational landscapes.
  • To address the challenge of searching for kinetically preferred sequences in complex biomolecular systems.

Main Methods:

  • Introduced a graph-based approach for minimum energy path searching.
  • Utilized local density estimation for determining edge weights in the conformational landscape graph.
  • Applied the method to both synthetic and real-world cryo-EM datasets.

Main Results:

  • Successfully identified accurate transition states in continuous conformational changes.
  • Demonstrated the framework's effectiveness on complex datasets.
  • The method facilitates exploration of high-dimensional conformational dynamics.

Conclusions:

  • The developed framework provides an effective means to navigate and analyze high-dimensional conformational landscapes.
  • This approach enhances the utility of cryo-EM data for understanding molecular mechanisms.
  • The CLEAPA package is available for broader application.