4.8 Article

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

Journal

NATURE METHODS
Volume 18, Issue 2, Pages 156-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41592-020-01051-w

Keywords

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Funding

  1. US National Institutes of Health (NIH)/National Institute of General Medical Science [R01GM079429]
  2. Office of Science at the Department of Energy [DE-AC05-00OR22725]
  3. National Science Foundation [(NSF)/MCB-1942763, NIH/R01GM095583, NIH/R01GM123055, NIH/R01GM133840, NSF/DMS1614777, NSF/CMMI1825941, NSF/MCB1925643, NSF/DBI2003635, NIH/R01GM123159]
  4. Max Planck Society German Research Foundation [IG 109/1-1, FOR-1805]
  5. Welch Foundation [Q1279]
  6. Medical Research Council [MR/N009614/1]
  7. Wellcome Trust [208398/Z/17/Z]
  8. Biotechnology and Biological Sciences Research Council [BB/P000517/1, BB/P000975/1]
  9. [NIH/R35GM131883]
  10. [NIH/P01GM063210]
  11. [NIH/R37AI36040]
  12. [NSF/DBI2030381]
  13. Wellcome Trust [208398/Z/17/Z] Funding Source: Wellcome Trust
  14. BBSRC [1792631, BB/P000517/1, BB/P000975/1, BB/T012935/1, BB/L006383/1, BB/S005099/1] Funding Source: UKRI
  15. MRC [MR/N009614/1] Funding Source: UKRI

Ask authors/readers for more resources

The 2019 Cryo-EM Model Challenge evaluated the quality of models produced from cryo-EM maps, reproducibility of modeling results, and performance of metrics used for model validation. The study found relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, with recommendations for validating near-atomic cryo-EM structures.
A multi-laboratory study in the form of a community challenge assesses the quality of models that can be produced from cryo-EM maps using different software tools, the reproducibility of models generated by different users and the performance of metrics used for model validation. 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 angstrom). 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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