Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge

Catherine L. Lawson; Andriy Kryshtafovych; Grigore D. Pintilie; Stephen K. Burley; Jiří Černý; Vincent B. Chen; Paul Emsley; Alberto Gobbi; Andrzej Joachimiak; Sigrid Noreng; Michael G. Prisant; Randy J. Read; Jane S. Richardson; Alexis L. Rohou; Bohdan Schneider; Benjamin D. Sellers; Chenghua Shao; Elizabeth Sourial; Chris I. Williams; Christopher J. Williams; Ying Yang; Venkat Abbaraju; Pavel V. Afonine; Matthew L. Baker; Paul S. Bond; Tom L. Blundell; Tom Burnley; Arthur Campbell; Renzhi Cao; Jianlin Cheng; Grzegorz Chojnowski; K. D. Cowtan; Frank DiMaio; Reza Esmaeeli; Nabin Giri; Helmut Grubmüller; Soon Wen Hoh; Jie Hou; Corey F. Hryc; Carola Hunte; Maxim Igaev; Agnel P. Joseph; Wei Chun Kao; Daisuke Kihara; Dilip Kumar; Lijun Lang; Sean Lin; Sai R. Maddhuri Venkata Subramaniya; Sumit Mittal; Arup Mondal; Nigel W. Moriarty; Andrew Muenks; Garib N. Murshudov; Robert A. Nicholls; Mateusz Olek; Colin M. Palmer; Alberto Perez; Emmi Pohjolainen; Karunakar R. Pothula; Christopher N. Rowley; Daipayan Sarkar; Luisa U. Schäfer; Christopher J. Schlicksup; Gunnar F. Schröder; Mrinal Shekhar; Dong Si; Abhishek Singharoy; Oleg V. Sobolev; Genki Terashi; Andrea C. Vaiana; Sundeep C. Vedithi; Jacob Verburgt; Xiao Wang; Rangana Warshamanage; Martyn D. Winn; Simone Weyand; Keitaro Yamashita; Minglei Zhao; Michael F. Schmid; Helen M. Berman; Wah Chiu

doi:10.1038/s41592-024-02321-7

Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge

Catherine L. Lawson^*, Andriy Kryshtafovych, Grigore D. Pintilie, Stephen K. Burley, Jiří Černý, Vincent B. Chen, Paul Emsley, Alberto Gobbi, Andrzej Joachimiak, Sigrid Noreng, Michael G. Prisant, Randy J. Read, Jane S. Richardson, Alexis L. Rohou, Bohdan Schneider, Benjamin D. Sellers, Chenghua Shao, Elizabeth Sourial, Chris I. Williams, Christopher J. WilliamsYing Yang, Venkat Abbaraju, Pavel V. Afonine, Matthew L. Baker, Paul S. Bond, Tom L. Blundell, Tom Burnley, Arthur Campbell, Renzhi Cao, Jianlin Cheng, Grzegorz Chojnowski, K. D. Cowtan, Frank DiMaio, Reza Esmaeeli, Nabin Giri, Helmut Grubmüller, Soon Wen Hoh, Jie Hou, Corey F. Hryc, Carola Hunte, Maxim Igaev, Agnel P. Joseph, Wei Chun Kao, Daisuke Kihara, Dilip Kumar, Lijun Lang, Sean Lin, Sai R. Maddhuri Venkata Subramaniya, Sumit Mittal, Arup Mondal, Nigel W. Moriarty, Andrew Muenks, Garib N. Murshudov, Robert A. Nicholls, Mateusz Olek, Colin M. Palmer, Alberto Perez, Emmi Pohjolainen, Karunakar R. Pothula, Christopher N. Rowley, Daipayan Sarkar, Luisa U. Schäfer, Christopher J. Schlicksup, Gunnar F. Schröder, Mrinal Shekhar, Dong Si, Abhishek Singharoy, Oleg V. Sobolev, Genki Terashi, Andrea C. Vaiana, Sundeep C. Vedithi, Jacob Verburgt, Xiao Wang, Rangana Warshamanage, Martyn D. Winn, Simone Weyand, Keitaro Yamashita, Minglei Zhao, Michael F. Schmid, Helen M. Berman, Wah Chiu^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Original language	English
Pages (from-to)	1340-1348
Number of pages	9
Journal	Nature Methods
Volume	21
Issue number	7
Early online date	25 Jun 2024
DOIs	https://doi.org/10.1038/s41592-024-02321-7
Publication status	Published - 1 Jul 2024

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer Nature America, Inc. 2024.

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10.1038/s41592-024-02321-7

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Lawson, C. L., Kryshtafovych, A., Pintilie, G. D., Burley, S. K., Černý, J., Chen, V. B., Emsley, P., Gobbi, A., Joachimiak, A., Noreng, S., Prisant, M. G., Read, R. J., Richardson, J. S., Rohou, A. L., Schneider, B., Sellers, B. D., Shao, C., Sourial, E., Williams, C. I., ... Chiu, W. (2024). Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge. Nature Methods, 21(7), 1340-1348. https://doi.org/10.1038/s41592-024-02321-7

@article{2225963aaa574862a45368bf356c931c,

title = "Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge",

abstract = "The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 {\AA}) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.",

author = "Lawson, {Catherine L.} and Andriy Kryshtafovych and Pintilie, {Grigore D.} and Burley, {Stephen K.} and Ji{\v r}{\'i} {\v C}ern{\'y} and Chen, {Vincent B.} and Paul Emsley and Alberto Gobbi and Andrzej Joachimiak and Sigrid Noreng and Prisant, {Michael G.} and Read, {Randy J.} and Richardson, {Jane S.} and Rohou, {Alexis L.} and Bohdan Schneider and Sellers, {Benjamin D.} and Chenghua Shao and Elizabeth Sourial and Williams, {Chris I.} and Williams, {Christopher J.} and Ying Yang and Venkat Abbaraju and Afonine, {Pavel V.} and Baker, {Matthew L.} and Bond, {Paul S.} and Blundell, {Tom L.} and Tom Burnley and Arthur Campbell and Renzhi Cao and Jianlin Cheng and Grzegorz Chojnowski and Cowtan, {K. D.} and Frank DiMaio and Reza Esmaeeli and Nabin Giri and Helmut Grubm{\"u}ller and Hoh, {Soon Wen} and Jie Hou and Hryc, {Corey F.} and Carola Hunte and Maxim Igaev and Joseph, {Agnel P.} and Kao, {Wei Chun} and Daisuke Kihara and Dilip Kumar and Lijun Lang and Sean Lin and {Maddhuri Venkata Subramaniya}, {Sai R.} and Sumit Mittal and Arup Mondal and Moriarty, {Nigel W.} and Andrew Muenks and Murshudov, {Garib N.} and Nicholls, {Robert A.} and Mateusz Olek and Palmer, {Colin M.} and Alberto Perez and Emmi Pohjolainen and Pothula, {Karunakar R.} and Rowley, {Christopher N.} and Daipayan Sarkar and Sch{\"a}fer, {Luisa U.} and Schlicksup, {Christopher J.} and Schr{\"o}der, {Gunnar F.} and Mrinal Shekhar and Dong Si and Abhishek Singharoy and Sobolev, {Oleg V.} and Genki Terashi and Vaiana, {Andrea C.} and Vedithi, {Sundeep C.} and Jacob Verburgt and Xiao Wang and Rangana Warshamanage and Winn, {Martyn D.} and Simone Weyand and Keitaro Yamashita and Minglei Zhao and Schmid, {Michael F.} and Berman, {Helen M.} and Wah Chiu",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive licence to Springer Nature America, Inc. 2024.",

year = "2024",

month = jul,

day = "1",

doi = "10.1038/s41592-024-02321-7",

language = "English",

volume = "21",

pages = "1340--1348",

journal = "Nature Methods",

issn = "1548-7091",

publisher = "Nature Publishing Group",

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Lawson, CL, Kryshtafovych, A, Pintilie, GD, Burley, SK, Černý, J, Chen, VB, Emsley, P, Gobbi, A, Joachimiak, A, Noreng, S, Prisant, MG, Read, RJ, Richardson, JS, Rohou, AL, Schneider, B, Sellers, BD, Shao, C, Sourial, E, Williams, CI, Williams, CJ, Yang, Y, Abbaraju, V, Afonine, PV, Baker, ML, Bond, PS, Blundell, TL, Burnley, T, Campbell, A, Cao, R, Cheng, J, Chojnowski, G, Cowtan, KD, DiMaio, F, Esmaeeli, R, Giri, N, Grubmüller, H, Hoh, SW, Hou, J, Hryc, CF, Hunte, C, Igaev, M, Joseph, AP, Kao, WC, Kihara, D, Kumar, D, Lang, L, Lin, S, Maddhuri Venkata Subramaniya, SR, Mittal, S, Mondal, A, Moriarty, NW, Muenks, A, Murshudov, GN, Nicholls, RA, Olek, M, Palmer, CM, Perez, A, Pohjolainen, E, Pothula, KR, Rowley, CN, Sarkar, D, Schäfer, LU, Schlicksup, CJ, Schröder, GF, Shekhar, M, Si, D, Singharoy, A, Sobolev, OV, Terashi, G, Vaiana, AC, Vedithi, SC, Verburgt, J, Wang, X, Warshamanage, R, Winn, MD, Weyand, S, Yamashita, K, Zhao, M, Schmid, MF, Berman, HM & Chiu, W 2024, 'Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge', Nature Methods, vol. 21, no. 7, pp. 1340-1348. https://doi.org/10.1038/s41592-024-02321-7

TY - JOUR

T1 - Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge

AU - Lawson, Catherine L.

AU - Kryshtafovych, Andriy

AU - Pintilie, Grigore D.

AU - Burley, Stephen K.

AU - Černý, Jiří

AU - Chen, Vincent B.

AU - Emsley, Paul

AU - Gobbi, Alberto

AU - Joachimiak, Andrzej

AU - Noreng, Sigrid

AU - Prisant, Michael G.

AU - Read, Randy J.

AU - Richardson, Jane S.

AU - Rohou, Alexis L.

AU - Schneider, Bohdan

AU - Sellers, Benjamin D.

AU - Shao, Chenghua

AU - Sourial, Elizabeth

AU - Williams, Chris I.

AU - Williams, Christopher J.

AU - Yang, Ying

AU - Abbaraju, Venkat

AU - Afonine, Pavel V.

AU - Baker, Matthew L.

AU - Bond, Paul S.

AU - Blundell, Tom L.

AU - Burnley, Tom

AU - Campbell, Arthur

AU - Cao, Renzhi

AU - Cheng, Jianlin

AU - Chojnowski, Grzegorz

AU - Cowtan, K. D.

AU - DiMaio, Frank

AU - Esmaeeli, Reza

AU - Giri, Nabin

AU - Grubmüller, Helmut

AU - Hoh, Soon Wen

AU - Hou, Jie

AU - Hryc, Corey F.

AU - Hunte, Carola

AU - Igaev, Maxim

AU - Joseph, Agnel P.

AU - Kao, Wei Chun

AU - Kihara, Daisuke

AU - Kumar, Dilip

AU - Lang, Lijun

AU - Lin, Sean

AU - Maddhuri Venkata Subramaniya, Sai R.

AU - Mittal, Sumit

AU - Mondal, Arup

AU - Moriarty, Nigel W.

AU - Muenks, Andrew

AU - Murshudov, Garib N.

AU - Nicholls, Robert A.

AU - Olek, Mateusz

AU - Palmer, Colin M.

AU - Perez, Alberto

AU - Pohjolainen, Emmi

AU - Pothula, Karunakar R.

AU - Rowley, Christopher N.

AU - Sarkar, Daipayan

AU - Schäfer, Luisa U.

AU - Schlicksup, Christopher J.

AU - Schröder, Gunnar F.

AU - Shekhar, Mrinal

AU - Si, Dong

AU - Singharoy, Abhishek

AU - Sobolev, Oleg V.

AU - Terashi, Genki

AU - Vaiana, Andrea C.

AU - Vedithi, Sundeep C.

AU - Verburgt, Jacob

AU - Wang, Xiao

AU - Warshamanage, Rangana

AU - Winn, Martyn D.

AU - Weyand, Simone

AU - Yamashita, Keitaro

AU - Zhao, Minglei

AU - Schmid, Michael F.

AU - Berman, Helen M.

AU - Chiu, Wah

PY - 2024/7/1

Y1 - 2024/7/1

N2 - The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

AB - The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

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DO - 10.1038/s41592-024-02321-7

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AN - SCOPUS:85196858277

SN - 1548-7091

VL - 21

SP - 1340

EP - 1348

JO - Nature Methods

JF - Nature Methods

IS - 7

ER -

Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge

Abstract

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