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DOI 10.1038/s41592-020-01051-w

Медицинская библиотека · Nature methods · 2021

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 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

СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАПоддержка правительства СШАВалидационное исследованиеПеревод в очереди

Аннотация

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.

Для цитирования: 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 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. Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge.. Nature methods. 2021. DOI: 10.1038/s41592-020-01051-w.

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