WikiSysop: Created page with "== Citation == Su, B., Huang, K., Peng, Z., Amunts, A. and Yang, J. 2025. CryoAtom improves model building for cryo-EM. Nature Structural & Molecular Biology. (2025), 1–11. == Abstract == Constructing atomic models from cryogenic electron microscopy (cryo-EM) density maps is essential for interpreting molecular mechanisms. Here we present CryoAtom, an approach for de novo model building for cryo-EM maps, leveraging recent advancements in AlphaFold2 to improve the st..."

2025-11-21T11:14:35Z

Created page with "== Citation == Su, B., Huang, K., Peng, Z., Amunts, A. and Yang, J. 2025. CryoAtom improves model building for cryo-EM. Nature Structural & Molecular Biology. (2025), 1–11. == Abstract == Constructing atomic models from cryogenic electron microscopy (cryo-EM) density maps is essential for interpreting molecular mechanisms. Here we present CryoAtom, an approach for de novo model building for cryo-EM maps, leveraging recent advancements in AlphaFold2 to improve the st..."

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== Citation ==

Su, B., Huang, K., Peng, Z., Amunts, A. and Yang, J. 2025. CryoAtom improves model building for cryo-EM. Nature Structural & Molecular Biology. (2025), 1–11.

== Abstract ==

Constructing atomic models from cryogenic electron microscopy (cryo-EM)
density maps is essential for interpreting molecular mechanisms. Here we
present CryoAtom, an approach for de novo model building for cryo-EM
maps, leveraging recent advancements in AlphaFold2 to improve the
state-of-the-art method ModelAngelo. To accommodate the cryo-EM
map information, CryoAtom replaces the global attention mechanism
in AlphaFold2 with local attention, which is further enhanced by a novel
three-dimensional rotary position embedding. CryoAtom produces more
complete models, reduces the resolution requirement and accelerates the
modeling. The application of CryoAtom to three large maps demonstrates
its ability to detect previously uncharacterized proteins with unknown
functions, improve the modeling of conformational changes and
compartmentalize the map to isolate nonprotein components. A particular
case includes a 104-protein complex that was modeled within a few hours
and a minor conformational change of a single protein domain was detected
at the periphery when models from two different maps were compared.
CryoAtom stands as an accurate method currently available for model
building of proteins in cryo-EM structure determination. The source code
and model parameters are available from GitHub (https://github.com/
YangLab-SDU/CryoAtom).

== Keywords ==

== Links ==

https://www.nature.com/articles/s41594-025-01713-3

== Related software ==

== Related methods ==

== Comments ==

2025Su CryoAtom - Revision history