Likelihood-based interactive local docking into cryo-EM maps in ChimeraX.

Area of Science:

• Structural biology
• Biophysics
• Computational biology

Background:

• Cryo-electron microscopy (cryo-EM) map interpretation often involves docking known or predicted component structures.
• This process is crucial for low-resolution maps (worse than 4 Å) but can be computationally intensive for large maps.
• Prior knowledge of component location can significantly accelerate docking.

Purpose of the Study:

• To develop a faster and more sensitive method for docking components into cryo-EM maps.
• To implement a local search strategy for component placement within specific map subvolumes.
• To leverage existing software (em_placement) for a novel local search approach.

Main Methods:

• Implemented a Fourier-space likelihood-based local search algorithm in the emplace_local program.
• Utilized a smaller search volume (subvolume) for component docking to improve efficiency.
• Integrated an interactive graphical interface within ChimeraX for defining search regions and evaluating results.

Main Results:

• The emplace_local program demonstrates enhanced computational speed compared to whole-map searches.
• Local search significantly improves the sensitivity of component detection and placement.
• The ChimeraX interface facilitates convenient setup and assessment of local docking calculations.

Conclusions:

• Local search strategies are highly effective for accelerating and improving the accuracy of component docking in cryo-EM map interpretation.
• The emplace_local program offers a valuable tool for structural biologists working with low-resolution cryo-EM data.
• Interactive visualization tools enhance the usability and efficiency of computational structure determination in cryo-EM.