Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge

Lawson, Catherine L.; Kryshtafovych, Andriy; Adams, Paul D.; Afonine, Pavel V.; Baker, Matthew L.; Barad, Benjamin A.; Bond, Paul; Burnley, Tom; Cao, Renzhi; Cheng, Jianlin; Chojnowski, Grzegorz; Cowtan, Kevin; Dill, Ken A.; DiMaio, Frank; Farrell, Daniel P.; Fraser, James S.; Herzik, Jr., Mark A.; Hoh, Soon Wen; Hou, Jie; Hung, Li-Wei; Igaev, Maxim; Joseph, Agnel P.; Kihara, Daisuke; Kumar, Dilip; Mittal, Sumit; Monastyrskyy, Bohdan; Olek, Mateusz; Palmer, Colin M.; Patwardhan, Ardan; Perez, Alberto; Pfab, Jonas; Pintilie, Grigore D.; Richardson, Jane S.; Rosenthal, Peter B.; Sarkar, Daipayan; Schäfer, Luisa U.; Schmid, Michael F.; Schröder, Gunnar F.; Shekhar, Mrinal; Si, Dong; Singharoy, Abishek; Terashi, Genki; Terwilliger, Thomas C.; Vaiana, Andrea; Wang, Liguo; Wang, Zhe; Wankowicz, Stephanie A.; Williams, Christopher J.; Winn, Martyn; Wu, Tianqi; Yu, Xiaodi; Zhang, Kaiming; Berman, Helen M.; Chiu, Wah

doi:10.1038/s41592-020-01051-w

Title: Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge

Journal Article · Thu Feb 04 00:00:00 UTC 2021 · Nature Methods

DOI: https://doi.org/10.1038/s41592-020-01051-w · OSTI ID:1777461

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Rutgers Univ., Piscataway, NJ (United States)
Univ. of California, Davis, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
The University of Texas Health Science Center at Houston, TX (United States)
The Scripps Research Inst., La Jolla, CA (United States)
Univ. of York (United Kingdom)
UKRI Science and Technology Facilities Council, Didcot (United Kingdom)
Pacific Lutheran University, Tacoma, WA (United States)
Univ. of Missouri, Columbia, MO (United States)
Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). European Molecular Biology Laboratory
Stony Brook Univ., NY (United States)
Univ. of Washington, Seattle, WA (United States)
Univ. of California, San Francisco, CA (United States)
Univ. of California, San Diego, CA (United States)
Saint Louis University, MO (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Max Planck Institute for Biophysical Chemistry, Göttingen (Germany)
Purdue Univ., West Lafayette, IN (United States)
Baylor College of Medicine, Houston, TX (United States)
Arizona State Univ., Tempe, AZ (United States); VIT Bhopal University (India)
The European Bioinformatics Institute (EMBL-EBI), Hinxton (United States)
Univ. of Florida, Gainesville, FL (United States)
Univ. of Washington, Bothell, WA (United States)
Stanford Univ., CA (United States)
Duke Univ., Durham, NC (United States)
Francis Crick Institute, London (United Kingdom)
Purdue Univ., West Lafayette, IN (United States); Arizona State Univ., Tempe, AZ (United States)
Forschungszentrum Juelich (Germany)
SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL); Stanford Univ., CA (United States)
Forschungszentrum Juelich (Germany); Heinrich Heine University Düsseldorf (Germany)
Arizona State Univ., Tempe, AZ (United States); Broad Institute of MIT and Harvard, Cambridge, MA (United States)
Arizona State Univ., Tempe, AZ (United States)
New Mexico Consortium, Los Alamos, NM (United States)
Janssen Research and Development, Spring House, PA (United States)
Rutgers Univ., Piscataway, NJ (United States); Univ. of Southern California, Los Angeles, CA (United States)
Stanford Univ., CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL)

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)

Sponsoring Organization:: Biotechnology and Biological Sciences Research Council; Max Planck Society German Research Foundation; Medical Research Council; National Institute of General Medical Sciences (NIGMS); National Institutes of Health (NIH); National Science Foundation (NSF); Purdue Institute of Drug Discovery; USDOE Office of Science (SC), Basic Energy Sciences (BES); Welch Foundation; Wellcome Trust

Grant/Contract Number:: 89233218CNA000001; AC02-76SF00515; AC05-00OR22725

OSTI ID:: 1777461

Report Number(s):: LA-UR--20-25444

Journal Information:: Nature Methods, Journal Name: Nature Methods Journal Issue: 2 Vol. 18; ISSN 1548-7091

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Soil-Borne Bacterial Structure and Diversity Does Not Reflect Community Activity in Pampa Biome Lupatini, Manoeli; Suleiman, Afnan Khalil Ahmad; Jacques, Rodrigo Josemar Seminoti PLoS ONE, Vol. 8, Issue 10 https://doi.org/10.1371/journal.pone.0076465	journal	October 2013
In Silico Characterization of Meloidogyne Genus Nematode Cellulose Binding Proteins Menezes, Alana Manoela Fraga; Cavalcanti Junior, Edilton de Albuquerque; Martins, Luiza Suely Semen Brazilian Archives of Biology and Technology, Vol. 62 https://doi.org/10.1590/1678-4324-2019180120	journal	January 2019
ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps. Croll, Tristan Apollo - University of Cambridge Repository https://doi.org/10.17863/cam.24327	text	January 2018
Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Liebschner, Dorothee; Afonine, Pavel V.; Baker, Matthew L. Apollo - University of Cambridge Repository https://doi.org/10.17863/cam.43042	text	January 2019
Restructuring of Epibacterial Communities on Fucus vesiculosus forma mytili in Response to Elevated pCO2 and Increased Temperature Levels Mensch, Birte; Neulinger, Sven C.; Graiff, Angelika Frontiers in Microbiology, Vol. 7 https://doi.org/10.3389/fmicb.2016.00434	journal	March 2016
Mutations in ADAR1 cause Aicardi-Goutières syndrome associated with a type I interferon signature Rice, Gillian I.; Kasher, Paul R.; Forte, Gabriella M. A. Nature Publishing Group https://doi.org/10.5167/uzh-72421	text	January 2012
Hidden biosphere in an oxygen-deficient Atlantic open-ocean eddy: future implications of ocean deoxygenation on primary production in the eastern tropical North Atlantic Löscher, C. R.; Fischer, M. A.; Neulinger, S. C. Biogeosciences, Vol. 12, Issue 24 https://doi.org/10.5194/bg-12-7467-2015	journal	January 2015
Effect of different heterotrophic plate count methods on the estimation of the composition of the culturable microbial community Gensberger, Eva Theres; Gössl, Eva-Maria; Antonielli, Livio PeerJ, Vol. 3 https://doi.org/10.7717/peerj.862	journal	January 2015

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