WikiSysop: Created page with "== Citation == Li, Tao / He, Jiahua / Cao, Hong / Zhang, Yi / Chen, Ji / Xiao, Yi / Huang, Sheng-You. All-atom RNA structure determination from cryo-EM maps. 2024. Nature Biotechnology, p. 1-9 == Abstract == Many methods exist for determining protein structures from cryogenic electron microscopy maps, but this remains challenging for RNA structures. Here we developed EMRNA, a method for accurate, automated determination of full-length all-atom RNA structures from cryo..."

2024-08-05T06:26:57Z

Created page with "== Citation == Li, Tao / He, Jiahua / Cao, Hong / Zhang, Yi / Chen, Ji / Xiao, Yi / Huang, Sheng-You. All-atom RNA structure determination from cryo-EM maps. 2024. Nature Biotechnology, p. 1-9 == Abstract == Many methods exist for determining protein structures from cryogenic electron microscopy maps, but this remains challenging for RNA structures. Here we developed EMRNA, a method for accurate, automated determination of full-length all-atom RNA structures from cryo..."

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== Citation ==

Li, Tao / He, Jiahua / Cao, Hong / Zhang, Yi / Chen, Ji / Xiao, Yi / Huang, Sheng-You. All-atom RNA structure determination from cryo-EM maps. 2024. Nature Biotechnology, p. 1-9

== Abstract ==

Many methods exist for determining protein structures from cryogenic
electron microscopy maps, but this remains challenging for RNA
structures. Here we developed EMRNA, a method for accurate, automated
determination of full-length all-atom RNA structures from cryogenic
electron microscopy maps. EMRNA integrates deep learning-based
detection of nucleotides, three-dimensional backbone tracing and scoring
with consideration of sequence and secondary structure information,
and full-atom construction of the RNA structure. We validated EMRNA on
140 diverse RNA maps ranging from 37 to 423 nt at 2.0–6.0 Å resolutions,
and compared EMRNA with auto-DRRAFTER, phenix.map_to_model and
CryoREAD on a set of 71 cases. EMRNA achieves a median accuracy of
2.36 Å root mean square deviation and 0.86 TM-score for full-length RNA
structures, compared with 6.66 Å and 0.58 for auto-DRRAFTER. EMRNA also
obtains a high residue coverage and sequence match of 93.30% and 95.30%
in the built models, compared with 58.20% and 42.20% for phenix.map_to_
model and 56.45% and 52.3% for CryoREAD. EMRNA is fast and can build an
RNA structure of 100 nt within 3 min.

== Keywords ==

== Links ==

https://www.nature.com/articles/s41587-024-02149-8

== Related software ==

== Related methods ==

== Comments ==

2024Li EMRNA - Revision history