Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge
Year: 2024
Type: article
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. The EMDataResource Ligand Model Challenge aimed at assessing the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryo-EM maps determined at near-atomic resolution. This analysis presents the results and recommends best practices for assessing cryo-EM structures of liganded macromolecules.
Source: Nature Methods
Authors: 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
Institutions: Rutgers, The State University of New Jersey, Worldwide Protein Data Bank, University of California, Davis, Stanford University, San Diego Supercomputer Center, University of California San Diego, Rutgers Cancer Institute, Czech Academy of Sciences, Czech Academy of Sciences, Institute of Biotechnology, Duke University, MRC Laboratory of Molecular Biology, Genentech, Argonne National Laboratory, University of Chicago, University of Cambridge, Vilya, Lawrence Berkeley National Laboratory, The University of Texas Health Science Center at Houston, University of York, Science and Technology Facilities Council, Research Complex at Harwell, Broad Institute, Pacific Lutheran University, University of Missouri, European Molecular Biology Laboratory, European Molecular Biology Laboratory, University of Washington, University of Florida, Max Planck Institute for Multidisciplinary Sciences, Saint Louis University, University of Freiburg, Purdue University West Lafayette, Baylor College of Medicine, Ashoka University, Chinese University of Hong Kong, University of Washington Bothell, VIT Bhopal University, Arizona State University, National Laboratory of the Rockies, Diamond Light Source, Forschungszentrum Jülich, Carleton University, Michigan State University, Heinrich Heine University Düsseldorf, Rancho BioSciences (United States), Rio Tinto (United States), Forestry Agency, SLAC National Accelerator Laboratory, Stanford Synchrotron Radiation Lightsource, University of Southern California
Language: English
Subfield: Structural Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $12,290
Funders: National Science Foundation, U.S. Department of Energy, U.S. Department of Health and Human Services, Wellcome Trust, American Leprosy Missions, Deutsche Forschungsgemeinschaft, Akademie Věd České Republiky, National Institutes of Health, Directorate for Biological Sciences, Medical Research Council, Biotechnology and Biological Sciences Research Council, Science and Engineering Research Board, Department of Biochemistry, University of Cambridge, National Institute of General Medical Sciences, Division of Chemistry
Awards: Phenix: Integrated algorithms for high quality models from crystallographic and cryo-EM data, Validation Tools for Cryo-EM, G1276303444, G1286236842, G131485024, G1478526422, G1863003419, Extending MolProbity Diagnosis & Healing Methods to Empower Better CryoEM & Xray Models at 2.5-4A Resolution, plus Versioned, Redeposited "GEMS" for Important Individual Structures, CCP4 Advanced integrated approaches to macromolecular structure determination, G2539837713, G259924242, PDB MANAGEMENT BY THE RESEARCH COLLABORATORY FOR STRUCTURAL BIOINFORMATICS, CAREER: Enhanced Sampling Methods to Characterize Nucleic Acid Structure, Recognition Mechanisms and Function, G3083819904, G339059223, G3408399831, Unified Data Resource for 3DEM, CCP4 Advanced integrated approaches to macromolecular structure determination, G362302541, G3685081974, G382641700, G4206649126, G42916606, G4292987561, Graduate Research Fellowship Program (GRFP), EXC 2189: CIBSS Centre for Integrative Biological Signalling Studies, G4950536974, G5094606986, G546177184, Computational Tools for Neutron Protein Crystallography, G5527199202, G5572387977, G577202574, G5986892838, G6224570086, Flexible-body refinement for Cryogenic Electron Microscopy Applications, G632094257, Development of likelihood-based methods in structural biology, G6671297155, G6887602689, G7392202181, Distance-based ab initio protein structure prediction, G8214903687, Building protein structure models for intermediate resolution cryo-electron microscopy maps, MolProbity Validation & Corrections: for Crystallography, PDB & Biomedicine, G8375967886, G842756989, G8513669286, Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM): 2021 - 2026, G8892198465, Phenix: providing high quality software to the research community for crystallography and cryo-EM, Deep learning methods for automated and accurate reconstruction of protein structures from cryo-EM image data, Structural and Functional Studies of Molecular Machines Involved in Chemical Modifications of Macromolecules, Protein structure determination from low-resolution experimental data, PDB Management by the Research Collaboratory for Structural Bioinformatics, G969889393
OpenAlex ID: W4400007706