Reconstructing protein structures from cryo-electron microscopy (cryo-EM) maps is essential for understanding macromolecular assemblies.
Although learning-based methods have improved protein reconstruction, information from hetero components remains underused.
Our analysis finds both false predictions and reference protein sites near hetero components; filtering nearby candidates can improve or impair chain construction.
CryoCue Framework Introduction
We introduce CryoCue, a framework that uses hetero information to guide protein reconstruction.
An anchor-supervised detector learns hetero representations across five component classes.
Multiscale hetero features guide backbone localization, while predicted hetero candidates condition structure refinement through their class, confidence, and frame-relative geometry.
Experiments and Results
Experiments show that CryoCue improves backbone localization near hetero components and achieves more accurate protein structure reconstruction.