Enhancing Cryo-EM Density Map Segmentation in Phenix for Improved Atomic Model Building

arXiv:2605.0525945.7
Predicted impact top 54% in BM · last 90 daysOriginality Incremental advance
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For structural biologists, this addresses the bottleneck of noisy cryo-EM data in automated model building, offering a more accurate and efficient pipeline.

PhenixCraft automates atomic model building from cryo-EM density maps by integrating AlphaFold predictions to improve map segmentation, achieving superior TM-scores and sequence accuracy over traditional Phenix methods.

We introduce PhenixCraft, a fully automated pipeline for building atomic models from cryo-EM density maps. By integrating AlphaFold predictions, we enhance the map-segmentation step in Phenix during model building, addressing challenges posed by noise and artifacts that traditionally hinder this step. Our results demonstrate PhenixCraft's superior performance in TM-scores and sequence accuracy, significantly improving upon the limitations and inefficiencies of traditional model building using Phenix.

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