Current approaches for the fitting and refinement of atomic models into cryo-EM maps using CCP-EM

Area of Science:

• Structural Biology
• Biophysics
• Computational Biology

Background:

• Cryo-electron microscopy (cryo-EM) is increasingly preferred for determining the 3D structures of large macromolecular complexes.
• Advances in instrumentation and software have accelerated cryo-EM adoption.
• CCP-EM provides a suite of tools for structural biology research.

Purpose of the Study:

• To review macromolecular structure refinement tools available in CCP-EM for cryo-EM reconstructions.
• To highlight the adaptation of X-ray crystallography refinement tools for cryo-EM.
• To discuss challenges and solutions for refining models into cryo-EM maps.

Main Methods:

• Review of REFMAC5 and related tools within CCP-EM.
• Discussion of principles applicable to both X-ray and cryo-EM refinement.
• Exploration of phase importance and amplitude correction strategies.
• Analysis of map blurring/sharpening techniques and Fourier shell correlation (FSC).
• Introduction of the Divide and Conquer pipeline for efficient parallel refinement.
• Summary of recent Coot developments for model building and fitting.
• Introduction of ProSHADE for symmetry identification.

Main Results:

• REFMAC5 and other X-ray-based tools are effectively repurposed for cryo-EM refinement.
• Strategies for handling cryo-EM specific data, such as phase information and map quality, are presented.
• Computational efficiency is improved through methods like the Divide and Conquer pipeline.
• New tools expedite atomic model building, fitting, and refinement in cryo-EM.
• ProSHADE facilitates symmetry identification for deposition and visualization.

Conclusions:

• CCP-EM offers a comprehensive toolkit for cryo-EM structure refinement.
• Adaptation of existing tools and development of new ones significantly improve the process.
• Accurate refinement leads to higher resolution and more reliable macromolecular structures.
• Efficient computational strategies are crucial for handling large complexes.