Single particle cryo-EM map and model validation: It's not crystal clear.

Area of Science:

• Structural Biology
• Biophysics
• Biochemistry

Background:

• Single particle cryogenic electron microscopy (cryo-EM) is revolutionizing biological structure determination.
• Significant algorithmic advancements have improved resolution and model building in cryo-EM.
• However, validation metrics for cryo-EM maps and models have not kept pace with these developments.

Purpose of the Study:

• To review persistent issues in single particle cryo-EM structure validation.
• To highlight currently accepted validation metrics within the scientific community.
• To emphasize the need for improved validation criteria and explore the role of machine learning.

Main Methods:

• Literature review of current practices and challenges in cryo-EM structure validation.
• Discussion of established and emerging validation metrics.
• Exploration of potential machine learning applications for quality assessment.

Main Results:

• Identified key challenges in validating cryo-EM maps and models.
• Summarized widely adopted validation metrics.
• Highlighted the gap between resolution enhancement and validation rigor.

Conclusions:

• There is a critical need for enhanced validation metrics in single particle cryo-EM.
• Machine learning holds promise for improving the confidence in cryo-EM structure quality assessment.
• Further development in validation methodologies is essential for reliable structural biology insights.