Towards better structural models from cryo-electron microscopy data with physics-based methods.

Area of Science:

• Structural biology
• Biophysics

Background:

• Cryo-electron microscopy (cryo-EM) routinely achieves atomic resolution for biological systems.
• The utility of cryo-EM structures depends on the quality of the atomic model built into the density map.
• Model quality is crucial for interpreting experimental data and understanding biological mechanisms.

Purpose of the Study:

• To survey hybrid approaches combining traditional and physics-based methods for cryo-EM model building.
• To highlight the benefits of these hybrid methods for various cryo-EM datasets and molecule types.
• To advocate for the integration of hybrid methods into standard cryo-EM workflows.

Main Methods:

• Review of existing literature on hybrid model-building techniques.
• Discussion of physics-based methods including docking, simulation, and modern force fields.
• Analysis of the application of these methods to different resolution ranges and molecule sizes.

Main Results:

• Hybrid approaches demonstrably improve the quality of atomic models built into cryo-EM density maps.
• These methods are particularly effective for medium- and low-resolution cryo-EM datasets.
• Hybrid methods show utility in refining structures of small molecules within larger biological assemblies.

Conclusions:

• Integrating physics-based methods with traditional tools enhances cryo-EM structure quality.
• Hybrid approaches offer significant advantages for challenging datasets and small molecule structures.
• Widespread adoption of these hybrid workflows will benefit the structural biology community.