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Created page with "== Citation == Terashi, Genki / Wang, Xiao / Maddhuri Venkata Subramaniya, Sai Raghavendra / Tesmer, John J. G. / Kihara, Daisuke Residue-wise local quality estimation for p..."

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== Citation ==

Terashi, Genki / Wang, Xiao / Maddhuri Venkata Subramaniya, Sai Raghavendra / Tesmer, John J. G. / Kihara, Daisuke
Residue-wise local quality estimation for protein models from cryo-EM maps. 2022. Nature Methods, Vol. 19, No. 9, p. 1116-1125

== Abstract ==

An increasing number of protein structures are being determined by cryogenic electron microscopy (cryo-EM). Although the
resolution of determined cryo-EM density maps is improving in general, there are still many cases where amino acids of a protein
are assigned with different levels of confidence. Here we developed a method that identifies potential misassignment of
residues in the map, including residue shifts along an otherwise correct main-chain trace. The score, named DAQ, computes
the likelihood that the local density corresponds to different amino acids, atoms, and secondary structures, estimated via deep
learning, and assesses the consistency of the amino acid assignment in the protein structure model with that likelihood. When
DAQ was applied to different versions of model structures in the Protein Data Bank that were derived from the same density
maps, a clear improvement in the DAQ score was observed in the newer versions of the models. DAQ also found potential misassignment
errors in a substantial number of deposited protein structure models built into cryo-EM maps.

== Keywords ==

== Links ==

https://www.nature.com/articles/s41592-022-01574-4

== Related software ==

== Related methods ==

== Comments ==

2022Terashi DAQ - Revision history

WikiSysop: Created page with "== Citation == Terashi, Genki / Wang, Xiao / Maddhuri Venkata Subramaniya, Sai Raghavendra / Tesmer, John J. G. / Kihara, Daisuke Residue-wise local quality estimation for p..."