Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge
Category
Published on
Type
journal-article
Author
Catherine L. Lawson and Andriy Kryshtafovych and Paul D. Adams and Pavel V. Afonine and Matthew L. Baker and Benjamin A. Barad and Paul Bond and Tom Burnley and Renzhi Cao and Jianlin Cheng and Grzegorz Chojnowski and Kevin Cowtan and Ken A. Dill and Frank DiMaio and Daniel P. Farrell and James S. Fraser and Mark A. Herzik and Soon Wen Hoh and Jie Hou and Li-Wei Hung and Maxim Igaev and Agnel P. Joseph and Daisuke Kihara and Dilip Kumar and Sumit Mittal and Bohdan Monastyrskyy and Mateusz Olek and Colin M. Palmer and Ardan Patwardhan and Alberto Perez and Jonas Pfab and Grigore D. Pintilie and Jane S. Richardson and Peter B. Rosenthal and Daipayan Sarkar and Luisa U. Schäfer and Michael F. Schmid and Gunnar F. Schröder and Mrinal Shekhar and Dong Si and Abishek Singharoy and Genki Terashi and Thomas C. Terwilliger and Andrea Vaiana and Liguo Wang and Zhe Wang and Stephanie A. Wankowicz and Christopher J. Williams and Martyn Winn and Tianqi Wu and Xiaodi Yu and Kaiming Zhang and Helen M. Berman and Wah Chiu
Citation
Lawson, C.L. et al., 2021. Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge. Nature Methods, 18(2), pp.156–164. Available at: http://dx.doi.org/10.1038/s41592-020-01051-w.
Abstract
AbstractThis 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.
