RELION: implementation of a Bayesian approach to cryo-EM structure determination

Area of Science:

• Structural biology
• Biophysics
• Computational biology

Background:

• Single-particle analysis in electron cryo-microscopy (cryo-EM) is crucial for determining macromolecular structures.
• Existing methods often require extensive user expertise for parameter tuning.
• Refinement of cryo-EM data is computationally intensive.

Purpose of the Study:

• To describe developments in RELION (REgularized LIkelihood OptimizatioN) for efficient macromolecular structure refinement.
• To introduce statistical insights into particle orientation determination accuracy.
• To present a gold-standard Fourier shell correlation (FSC) procedure for preventing overfitting.

Main Methods:

• Utilizing a Bayesian approach for parameter inference from data.
• Optimizing the maximum a posteriori (MAP) algorithm to reduce computational costs.
• Implementing a gold-standard Fourier shell correlation (FSC) procedure.

Main Results:

• Reduced computational costs for cryo-EM data refinement.
• Enhanced accuracy in determining relative orientations of individual particles.
• High-quality structural reconstructions and reliable resolution estimates.
• Minimized user intervention required for analysis.

Conclusions:

• RELION provides an efficient and accurate method for macromolecular structure refinement using cryo-EM data.
• The developed methods offer reliable resolution estimates and reduce the risk of overfitting.
• The software enables high-quality reconstructions with minimal user input and acceptable computational expense.