Abstract

This paper describes outcomes of the 2019 Cryo-EM Map-based Model Metrics Challenge sponsored by EMDataResource (www.emdataresource.org). The goals of this challenge were (1) to assess the quality of models that can be produced using current modeling software, (2) to check the reproducibility of modeling results from different software developers and users, and (3) compare the performance of current metrics used for evaluation of models. The focus was on near-atomic resolution maps with an innovative twist: three of four target maps formed a resolution series (1.8 to 3.1 Angstrom) from the same specimen and imaging experiment. Tools developed in previous challenges were expanded for managing, visualizing and analyzing the 63 submitted coordinate models, and several novel metrics were introduced. The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual laboratory experiments and holdings of structure data archives such as the Protein Data Bank. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived from these benchmark maps by 13 participating teams, representing both widely used and novel modeling approaches. We also evaluate the pros and cons of the commonly used metrics to assess model quality and recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed density in the cryo-EM map.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* https://model-compare.emdataresource.org/

* https://challenges.emdataresource.org/

Details

Title
Outcomes of the 2019 EMDataResource model challenge: validation of cryo-EM models at near-atomic resolution
Author
Lawson, Catherine L; Kryshtafovych, Andriy; Adams, Paul D; Afonine, Pavel; 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; Fraser, James S; Herzik, Mark A, Jr; Soon Wen Hoh; Hou, Jie; Li-Wei, Hung; Igaev, Maxim; Joseph, Agnel P; Kihara, Daisuke; Kumar, Dilip; Mittal, Sumit; Monastyrskyy, Bohdan; Olek, Mateusz; Palmer, Colin; Patwardhan, Ardan; Perez, Alberto; Pfab, Jonas; Pintilie, Grigore D; Richardson, Jane S; Rosenthal, Peter B; Sarkar, Daipayan; Schaefer, Luisa U; Schmid, Michael F; Schroeder, Gunnar F; Shekhar, Mrinal; Dong Si; Singharoy, Abhishek; 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
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2020
Publication date
Jun 15, 2020
Publisher
Cold Spring Harbor Laboratory Press
Source type
Working Paper
Language of publication
English
ProQuest document ID
2413254858
Copyright
© 2020. This article is published under http://creativecommons.org/licenses/by-nd/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.