TY - JOUR
AU - Lawson, Catherine L.
AU - Kryshtafovych, Andriy
AU - Pintilie, Grigore D.
AU - Burley, Stephen K.
AU - Černý, Jiří
AU - Chen, Vincent B.
AU - Emsley, Paul
AU - Gobbi, Alberto
AU - Joachimiak, Andrzej
AU - Noreng, Sigrid
AU - Prisant, Michael G.
AU - Read, Randy J.
AU - Richardson, Jane S.
AU - Rohou, Alexis L.
AU - Schneider, Bohdan
AU - Sellers, Benjamin D.
AU - Shao, Chenghua
AU - Sourial, Elizabeth
AU - Williams, Chris I.
AU - Williams, Christopher J.
AU - Yang, Ying
AU - Abbaraju, Venkat
AU - Afonine, Pavel V.
AU - Baker, Matthew L.
AU - Bond, Paul S.
AU - Blundell, Tom L.
AU - Burnley, Tom
AU - Campbell, Arthur
AU - Cao, Renzhi
AU - Cheng, Jianlin
AU - Chojnowski, Grzegorz
AU - Cowtan, K. D.
AU - DiMaio, Frank
AU - Esmaeeli, Reza
AU - Giri, Nabin
AU - Grubmüller, Helmut
AU - Hoh, Soon Wen
AU - Hou, Jie
AU - Hryc, Corey F.
AU - Hunte, Carola
AU - Igaev, Maxim
AU - Joseph, Agnel P.
AU - Kao, Wei Chun
AU - Kihara, Daisuke
AU - Kumar, Dilip
AU - Lang, Lijun
AU - Lin, Sean
AU - Maddhuri Venkata Subramaniya, Sai R.
AU - Mittal, Sumit
AU - Mondal, Arup
AU - Moriarty, Nigel W.
AU - Muenks, Andrew
AU - Murshudov, Garib N.
AU - Nicholls, Robert A.
AU - Olek, Mateusz
AU - Palmer, Colin M.
AU - Oteo Perez, Alberto
AU - Pohjolainen, Emmi
AU - Pothula, Karunakar R.
AU - Rowley, Christopher N.
AU - Sarkar, Daipayan
AU - Schäfer, Luisa U.
AU - Schlicksup, Christopher J.
AU - Schröder, Gunnar F.
AU - Shekhar, Mrinal
AU - Si, Dong
AU - Singharoy, Abhishek
AU - Sobolev, Oleg V.
AU - Terashi, Genki
AU - Vaiana, Andrea C.
AU - Vedithi, Sundeep C.
AU - Verburgt, Jacob
AU - Wang, Xiao
AU - Warshamanage, Rangana
AU - Winn, Martyn D.
AU - Weyand, Simone
AU - Yamashita, Keitaro
AU - Zhao, Minglei
AU - Schmid, Michael F.
AU - Berman, Helen M.
AU - Chiu, Wah
PY - 2024
DA - June
TI - Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge
JO - Nature Methods
EP - 1348
VL - 21
DO - https://doi.org/10.1038/s41592-024-02321-7
AB - The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.
PB - Springer Nature
UR - https://discovery.dundee.ac.uk/en/publications/96d7ee46-f562-4e6b-bef7-cf75296e3ec3
KW - Coronavirus (COVID-19)
ER