1
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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. Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge. Nat Methods 2024; 21:1340-1348. [PMID: 38918604 DOI: 10.1038/s41592-024-02321-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Accepted: 05/24/2024] [Indexed: 06/27/2024]
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.
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Affiliation(s)
- Catherine L Lawson
- RCSB Protein Data Bank and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
| | | | - Grigore D Pintilie
- Departments of Bioengineering and of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Stephen K Burley
- RCSB Protein Data Bank and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA
- RCSB Protein Data Bank and San Diego Supercomputer Center, University of California San Diego, La Jolla, CA, USA
| | - Jiří Černý
- Institute of Biotechnology, Czech Academy of Sciences, Vestec, Czech Republic
| | - Vincent B Chen
- Department of Biochemistry, Duke University, Durham, NC, USA
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Alberto Gobbi
- Discovery Chemistry, Genentech Inc., San Francisco, CA, USA
- , Berlin, Germany
| | - Andrzej Joachimiak
- Structural Biology Center, X-ray Science Division, Argonne National Laboratory, Argonne, IL, USA
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA
| | - Sigrid Noreng
- Structural Biology, Genentech Inc., South San Francisco, CA, USA
- Protein Science, Septerna, South San Francisco, CA, USA
| | | | - Randy J Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | | | - Alexis L Rohou
- Structural Biology, Genentech Inc., South San Francisco, CA, USA
| | - Bohdan Schneider
- Institute of Biotechnology, Czech Academy of Sciences, Vestec, Czech Republic
| | - Benjamin D Sellers
- Discovery Chemistry, Genentech Inc., San Francisco, CA, USA
- Computational Chemistry, Vilya, South San Francisco, CA, USA
| | - Chenghua Shao
- RCSB Protein Data Bank and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | | | | | | | - Ying Yang
- Structural Biology, Genentech Inc., South San Francisco, CA, USA
| | - Venkat Abbaraju
- RCSB Protein Data Bank and Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Pavel V Afonine
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Matthew L Baker
- Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Paul S Bond
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Tom L Blundell
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Tom Burnley
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Arthur Campbell
- Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Renzhi Cao
- Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA
| | - Jianlin Cheng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | | | - K D Cowtan
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Frank DiMaio
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Reza Esmaeeli
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Nabin Giri
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - Helmut Grubmüller
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Soon Wen Hoh
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Jie Hou
- Department of Computer Science, Saint Louis University, St. Louis, MO, USA
| | - Corey F Hryc
- Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Carola Hunte
- Institute of Biochemistry and Molecular Biology, ZBMZ, Faculty of Medicine and CIBSS-Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
| | - Maxim Igaev
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Agnel P Joseph
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Wei-Chun Kao
- Institute of Biochemistry and Molecular Biology, ZBMZ, Faculty of Medicine and CIBSS-Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
| | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Dilip Kumar
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA
- Trivedi School of Biosciences, Ashoka University, Sonipat, India
| | - Lijun Lang
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
- The Chinese University of Hong Kong, Hong Kong, China
| | - Sean Lin
- Division of Computing & Software Systems, University of Washington, Bothell, WA, USA
| | | | - Sumit Mittal
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
- School of Advanced Sciences and Languages, VIT Bhopal University, Bhopal, India
| | - Arup Mondal
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
- National Renewable Energy Laboratory (NREL), Golden, CO, USA
| | - Nigel W Moriarty
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Andrew Muenks
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, USA
| | | | - Robert A Nicholls
- MRC Laboratory of Molecular Biology, Cambridge, UK
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Mateusz Olek
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
- Electron Bio-Imaging Centre, Diamond Light Source, Harwell Science and Innovation Campus, Didcot, UK
| | - Colin M Palmer
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Alberto Perez
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Emmi Pohjolainen
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Karunakar R Pothula
- Institute of Biological Information Processing (IBI-7, Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
| | | | - Daipayan Sarkar
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
- MSU-DOE Plant Research Laboratory, East Lansing, MI, USA
- School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Luisa U Schäfer
- Institute of Biological Information Processing (IBI-7, Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
| | - Christopher J Schlicksup
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Gunnar F Schröder
- Institute of Biological Information Processing (IBI-7, Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
- Physics Department, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mrinal Shekhar
- Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Dong Si
- Division of Computing & Software Systems, University of Washington, Bothell, WA, USA
| | | | - Oleg V Sobolev
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Andrea C Vaiana
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Nature's Toolbox (NTx), Rio Rancho, NM, USA
| | | | - Jacob Verburgt
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Xiao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | | | - Martyn D Winn
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Simone Weyand
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | - Minglei Zhao
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA
| | - Michael F Schmid
- Division of Cryo-EM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Helen M Berman
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Wah Chiu
- Departments of Bioengineering and of Microbiology and Immunology, Stanford University, Stanford, CA, USA.
- Division of Cryo-EM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Menlo Park, CA, USA.
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2
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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 M, 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. Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge. RESEARCH SQUARE 2024:rs.3.rs-3864137. [PMID: 38343795 PMCID: PMC10854310 DOI: 10.21203/rs.3.rs-3864137/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/18/2024]
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: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) 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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Affiliation(s)
- Catherine L. Lawson
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | | | - Grigore D. Pintilie
- Departments of Bioengineering and of Microbiology and Immunology, Stanford University, Stanford, CA, USA
| | - Stephen K. Burley
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ USA
- San Diego Supercomputer Center, University of California San Diego, La Jolla, CA USA
| | - Jiří Černý
- Institute of Biotechnology, Czech Academy of Sciences, Vestec, CZ
| | | | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Alberto Gobbi
- Discovery Chemistry, Genentech Inc, South San Francisco, USA
| | - Andrzej Joachimiak
- Structural Biology Center, X-ray Science Division, Argonne National Laboratory, Argonne, IL, USA
| | - Sigrid Noreng
- Structural Biology, Genentech Inc, South San Francisco, USA
| | | | - Randy J. Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | | | | | - Bohdan Schneider
- Institute of Biotechnology, Czech Academy of Sciences, Vestec, CZ
| | | | - Chenghua Shao
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | | | | | | | - Ying Yang
- Structural Biology, Genentech Inc, South San Francisco, USA
| | - Venkat Abbaraju
- Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Pavel V. Afonine
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Matthew L. Baker
- Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Paul S. Bond
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Tom L. Blundell
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Tom Burnley
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Arthur Campbell
- Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Renzhi Cao
- Department of Computer Science, Pacific Lutheran University, Tacoma, WA, USA
| | - Jianlin Cheng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | | | - Kevin D. Cowtan
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Frank DiMaio
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Reza Esmaeeli
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Nabin Giri
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - Helmut Grubmüller
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Soon Wen Hoh
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Jie Hou
- Department of Computer Science, Saint Louis University, St. Louis, MO, USA
| | - Corey F. Hryc
- Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Carola Hunte
- Institute of Biochemistry and Molecular Biology, ZBMZ, Faculty of Medicine and CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, 79104 Freiburg, Germany
| | - Maxim Igaev
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Agnel P. Joseph
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Wei-Chun Kao
- Institute of Biochemistry and Molecular Biology, ZBMZ, Faculty of Medicine and CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, 79104 Freiburg, Germany
| | - Daisuke Kihara
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
- Department of Computer Science, Purdue University, West Lafayette, IN, USA
| | - Dilip Kumar
- Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Lijun Lang
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Sean Lin
- Division of Computing & Software Systems, University of Washington, Bothell, WA, USA
| | | | - Sumit Mittal
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
- School of Advanced Sciences and Languages, VIT Bhopal University, Bhopal, India
| | - Arup Mondal
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Nigel W. Moriarty
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Andrew Muenks
- Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, USA
| | | | | | - Mateusz Olek
- York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
- Electron Bio-Imaging Centre, Diamond Light Source, Harwell Science and Innovation Campus, Didcot, UK
| | - Colin M. Palmer
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Alberto Perez
- Department of Chemistry and Quantum Theory Project, University of Florida, Gainesville, FL, USA
| | - Emmi Pohjolainen
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
| | - Karunakar R. Pothula
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
| | | | - Daipayan Sarkar
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Luisa U. Schäfer
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
| | - Christopher J. Schlicksup
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Gunnar F. Schröder
- Institute of Biological Information Processing (IBI-7: Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
- Physics Department, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mrinal Shekhar
- Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Dong Si
- Division of Computing & Software Systems, University of Washington, Bothell, WA, USA
| | | | - Oleg V. Sobolev
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Andrea C. Vaiana
- Theoretical and Computational Biophysics Department, Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Nature’s Toolbox (NTx), Rio Rancho, NM, USA
| | | | - Jacob Verburgt
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Xiao Wang
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | | | - Martyn D. Winn
- Scientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Simone Weyand
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | - Minglei Zhao
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, USA
| | - Michael F. Schmid
- Division of Cryo-EM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
| | - Helen M. Berman
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Wah Chiu
- Departments of Bioengineering and of Microbiology and Immunology, Stanford University, Stanford, CA, USA
- Division of Cryo-EM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Menlo Park, CA, USA
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Cragnolini T, Kryshtafovych A, Topf M. Cryo-EM targets in CASP14. Proteins 2021; 89:1949-1958. [PMID: 34398978 PMCID: PMC8630773 DOI: 10.1002/prot.26216] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/27/2021] [Accepted: 08/06/2021] [Indexed: 11/22/2022]
Abstract
Structures of seven CASP14 targets were determined using cryo-electron microscopy (cryo-EM) technique with resolution between 2.1 and 3.8 Å. We provide an evaluation of the submitted models versus the experimental data (cryo-EM density maps) and experimental reference structures built into the maps. The accuracy of models is measured in terms of coordinate-to-density and coordinate-to-coordinate fit. A-posteriori refinement of the most accurate models in their corresponding cryo-EM density resulted in structures that are close to the reference structure, including some regions with better fit to the density. Regions that were found to be less "refineable" correlate well with regions of high diversity between the CASP models and low goodness-of-fit to density in the reference structure.
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Affiliation(s)
- Tristan Cragnolini
- Institute of Structural and Molecular Biology, Birkbeck, University College London, London, UK
| | | | - Maya Topf
- Center for Structural Systems Biology, Leibniz-Institut für Experimentelle Virologie and Universitätsklinikum Hamburg-Eppendorf (UKE), Hamburg, Germany
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4
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Chiu W, Schmid MF, Pintilie GD, Lawson CL. Evolution of standardization and dissemination of cryo-EM structures and data jointly by the community, PDB, and EMDB. J Biol Chem 2021; 296:100560. [PMID: 33744287 PMCID: PMC8050867 DOI: 10.1016/j.jbc.2021.100560] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 02/08/2021] [Accepted: 03/16/2021] [Indexed: 01/04/2023] Open
Abstract
Cryogenic electron microscopy (cryo-EM) methods began to be used in the mid-1970s to study thin and periodic arrays of proteins. Following a half-century of development in cryo-specimen preparation, instrumentation, data collection, data processing, and modeling software, cryo-EM has become a routine method for solving structures from large biological assemblies to small biomolecules at near to true atomic resolution. This review explores the critical roles played by the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in partnership with the community to develop the necessary infrastructure to archive cryo-EM maps and associated models. Public access to cryo-EM structure data has in turn facilitated better understanding of structure–function relationships and advancement of image processing and modeling tool development. The partnership between the global cryo-EM community and PDB and EMDB leadership has synergistically shaped the standards for metadata, one-stop deposition of maps and models, and validation metrics to assess the quality of cryo-EM structures. The advent of cryo-electron tomography (cryo-ET) for in situ molecular cell structures at a broad resolution range and their correlations with other imaging data introduce new data archival challenges in terms of data size and complexity in the years to come.
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Affiliation(s)
- Wah Chiu
- Department of Bioengineering, Stanford University, Stanford, California, USA; Division of CryoEM and Bioimaging, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, California, USA.
| | - Michael F Schmid
- Division of CryoEM and Bioimaging, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, California, USA
| | - Grigore D Pintilie
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Catherine L Lawson
- Institute for Quantitative Biomedicine and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA
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5
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Lawson CL, Kryshtafovych A, Adams PD, Afonine PV, Baker ML, Barad BA, Bond P, Burnley T, Cao R, Cheng J, Chojnowski G, Cowtan K, Dill KA, DiMaio F, Farrell DP, Fraser JS, Herzik MA, Hoh SW, Hou J, Hung LW, Igaev M, Joseph AP, Kihara D, Kumar D, Mittal S, Monastyrskyy B, Olek M, Palmer CM, Patwardhan A, Perez A, Pfab J, Pintilie GD, Richardson JS, Rosenthal PB, Sarkar D, Schäfer LU, Schmid MF, Schröder GF, Shekhar M, Si D, Singharoy A, Terashi G, Terwilliger TC, Vaiana A, Wang L, Wang Z, Wankowicz SA, Williams CJ, Winn M, Wu T, Yu X, Zhang K, Berman HM, Chiu W. Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge. Nat Methods 2021; 18:156-164. [PMID: 33542514 PMCID: PMC7864804 DOI: 10.1038/s41592-020-01051-w] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 12/21/2020] [Indexed: 01/30/2023]
Abstract
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.
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Affiliation(s)
- Catherine L. Lawson
- grid.430387.b0000 0004 1936 8796Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ USA
| | - Andriy Kryshtafovych
- grid.27860.3b0000 0004 1936 9684Genome Center, University of California, Davis, CA USA
| | - Paul D. Adams
- grid.184769.50000 0001 2231 4551Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA ,grid.47840.3f0000 0001 2181 7878Department of Bioengineering, University of California Berkeley, Berkeley, CA USA
| | - Pavel V. Afonine
- grid.184769.50000 0001 2231 4551Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA USA
| | - Matthew L. Baker
- grid.267308.80000 0000 9206 2401Department of Biochemistry and Molecular Biology, The University of Texas Health Science Center at Houston, Houston, TX USA
| | - Benjamin A. Barad
- grid.214007.00000000122199231Department of Integrated Computational Structural Biology, The Scripps Research Institute, La Jolla, CA USA
| | - Paul Bond
- grid.5685.e0000 0004 1936 9668York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Tom Burnley
- grid.465239.fScientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Renzhi Cao
- grid.261584.c0000 0001 0492 9915Department of Computer Science, Pacific Lutheran University, Tacoma, WA USA
| | - Jianlin Cheng
- grid.134936.a0000 0001 2162 3504Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO USA
| | - Grzegorz Chojnowski
- grid.475756.20000 0004 0444 5410European Molecular Biology Laboratory, c/o DESY, Hamburg, Germany
| | - Kevin Cowtan
- grid.5685.e0000 0004 1936 9668York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Ken A. Dill
- grid.36425.360000 0001 2216 9681Laufer Center, Stony Brook University, Stony Brook, NY USA
| | - Frank DiMaio
- grid.34477.330000000122986657Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA USA
| | - Daniel P. Farrell
- grid.34477.330000000122986657Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA USA
| | - James S. Fraser
- grid.266102.10000 0001 2297 6811Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA USA
| | - Mark A. Herzik
- grid.266100.30000 0001 2107 4242Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA USA
| | - Soon Wen Hoh
- grid.5685.e0000 0004 1936 9668York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Jie Hou
- grid.262962.b0000 0004 1936 9342Department of Computer Science, Saint Louis University, St. Louis, MO USA
| | - Li-Wei Hung
- grid.148313.c0000 0004 0428 3079Los Alamos National Laboratory, Los Alamos, NM USA
| | - Maxim Igaev
- grid.418140.80000 0001 2104 4211Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Agnel P. Joseph
- grid.465239.fScientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Daisuke Kihara
- grid.169077.e0000 0004 1937 2197Department of Biological Sciences, Purdue University, West Lafayette, IN USA ,grid.169077.e0000 0004 1937 2197Department of Computer Science, Purdue University, West Lafayette, IN USA
| | - Dilip Kumar
- grid.39382.330000 0001 2160 926XVerna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX USA
| | - Sumit Mittal
- grid.215654.10000 0001 2151 2636Biodesign Institute, Arizona State University, Tempe, AZ USA ,grid.411530.20000 0001 0694 3745School of Advanced Sciences and Languages, VIT Bhopal University, Bhopal, India
| | - Bohdan Monastyrskyy
- grid.27860.3b0000 0004 1936 9684Genome Center, University of California, Davis, CA USA
| | - Mateusz Olek
- grid.5685.e0000 0004 1936 9668York Structural Biology Laboratory, Department of Chemistry, University of York, York, UK
| | - Colin M. Palmer
- grid.465239.fScientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Ardan Patwardhan
- grid.225360.00000 0000 9709 7726The European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Alberto Perez
- grid.15276.370000 0004 1936 8091Department of Chemistry, University of Florida, Gainesville, FL USA
| | - Jonas Pfab
- grid.462982.30000 0000 8883 2602Division of Computing & Software Systems, University of Washington, Bothell, WA USA
| | - Grigore D. Pintilie
- grid.168010.e0000000419368956Department of Bioengineering, Stanford University, Stanford, CA USA
| | - Jane S. Richardson
- grid.26009.3d0000 0004 1936 7961Department of Biochemistry, Duke University, Durham, NC USA
| | - Peter B. Rosenthal
- grid.451388.30000 0004 1795 1830Structural Biology of Cells and Viruses Laboratory, Francis Crick Institute, London, UK
| | - Daipayan Sarkar
- grid.169077.e0000 0004 1937 2197Department of Biological Sciences, Purdue University, West Lafayette, IN USA ,grid.215654.10000 0001 2151 2636Biodesign Institute, Arizona State University, Tempe, AZ USA
| | - Luisa U. Schäfer
- grid.8385.60000 0001 2297 375XInstitute of Biological Information Processing (IBI-7: Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany
| | - Michael F. Schmid
- grid.168010.e0000000419368956Division of CryoEM and Biomaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA USA
| | - Gunnar F. Schröder
- grid.8385.60000 0001 2297 375XInstitute of Biological Information Processing (IBI-7: Structural Biochemistry) and Jülich Centre for Structural Biology (JuStruct), Forschungszentrum Jülich, Jülich, Germany ,grid.411327.20000 0001 2176 9917Physics Department, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mrinal Shekhar
- grid.215654.10000 0001 2151 2636Biodesign Institute, Arizona State University, Tempe, AZ USA ,grid.66859.34Center for Development of Therapeutics, Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Dong Si
- grid.462982.30000 0000 8883 2602Division of Computing & Software Systems, University of Washington, Bothell, WA USA
| | - Abishek Singharoy
- grid.215654.10000 0001 2151 2636Biodesign Institute, Arizona State University, Tempe, AZ USA
| | - Genki Terashi
- grid.418140.80000 0001 2104 4211Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | | | - Andrea Vaiana
- grid.418140.80000 0001 2104 4211Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Liguo Wang
- grid.34477.330000000122986657Department of Biological Structure, University of Washington, Seattle, WA USA
| | - Zhe Wang
- grid.225360.00000 0000 9709 7726The European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, UK
| | - Stephanie A. Wankowicz
- grid.266102.10000 0001 2297 6811Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA USA ,grid.266102.10000 0001 2297 6811Biophysics Graduate Program, University of California, San Francisco, CA USA
| | | | - Martyn Winn
- grid.465239.fScientific Computing Department, UKRI Science and Technology Facilities Council, Research Complex at Harwell, Didcot, UK
| | - Tianqi Wu
- grid.134936.a0000 0001 2162 3504Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO USA
| | - Xiaodi Yu
- grid.497530.c0000 0004 0389 4927SMPS, Janssen Research and Development, Spring House, PA USA
| | - Kaiming Zhang
- grid.168010.e0000000419368956Department of Bioengineering, Stanford University, Stanford, CA USA
| | - Helen M. Berman
- grid.430387.b0000 0004 1936 8796Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ USA ,grid.42505.360000 0001 2156 6853Department of Biological Sciences and Bridge Institute, University of Southern California, Los Angeles, CA USA
| | - Wah Chiu
- grid.168010.e0000000419368956Department of Bioengineering, Stanford University, Stanford, CA USA ,grid.168010.e0000000419368956Division of CryoEM and Biomaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA USA
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Lawson CL, Berman HM, Chiu W. Evolving data standards for cryo-EM structures. STRUCTURAL DYNAMICS (MELVILLE, N.Y.) 2020; 7:014701. [PMID: 32002441 PMCID: PMC6980868 DOI: 10.1063/1.5138589] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 01/07/2020] [Indexed: 05/04/2023]
Abstract
Electron cryo-microscopy (cryo-EM) is increasingly being used to determine 3D structures of a broad spectrum of biological specimens from molecules to cells. Anticipating this progress in the early 2000s, an international collaboration of scientists with expertise in both cryo-EM and structure data archiving was established (EMDataResource, previously known as EMDataBank). The major goals of the collaboration have been twofold: to develop the necessary infrastructure for archiving cryo-EM-derived density maps and models, and to promote development of cryo-EM structure validation standards. We describe how cryo-EM data archiving and validation have been developed and jointly coordinated for the Electron Microscopy Data Bank and Protein Data Bank archives over the past two decades, as well as the impact of evolving technology on data standards. Just as for X-ray crystallography and nuclear magnetic resonance, engaging the scientific community via workshops and challenging activities has played a central role in developing recommendations and requirements for the cryo-EM structure data archives.
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Affiliation(s)
- Catherine L. Lawson
- Institute for Quantitative Biomedicine and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, Piscataway, New Jersey 08854, USA
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Kryshtafovych A, Malhotra S, Monastyrskyy B, Cragnolini T, Joseph AP, Chiu W, Topf M. Cryo-electron microscopy targets in CASP13: Overview and evaluation of results. Proteins 2019; 87:1128-1140. [PMID: 31576602 PMCID: PMC7197460 DOI: 10.1002/prot.25817] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 08/30/2019] [Accepted: 09/13/2019] [Indexed: 11/07/2022]
Abstract
Structures of seven CASP13 targets were determined using cryo-electron microscopy (cryo-EM) technique with resolution between 3.0 and 4.0 Å. We provide an overview of the experimentally derived structures and describe results of the numerical evaluation of the submitted models. The evaluation is carried out by comparing coordinates of models to those of reference structures (CASP-style evaluation), as well as checking goodness-of-fit of modeled structures to the cryo-EM density maps. The performance of contributing research groups in the CASP-style evaluation is measured in terms of backbone accuracy, all-atom local geometry and similarity of inter-subunit interfaces. The results on the cryo-EM targets are compared with those on the whole set of eighty CASP13 targets. A posteriori refinement of the best models in their corresponding cryo-EM density maps resulted in structures that are very close to the reference structure, including some regions with better fit to the density.
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Affiliation(s)
- Andriy Kryshtafovych
- Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Sony Malhotra
- Institute of Structural and Molecular Biology, Birkbeck, University College London, Malet Street, London WC1E 7HX, UK
| | - Bohdan Monastyrskyy
- Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Tristan Cragnolini
- Institute of Structural and Molecular Biology, Birkbeck, University College London, Malet Street, London WC1E 7HX, UK
| | - Agnel-Praveen Joseph
- Institute of Structural and Molecular Biology, Birkbeck, University College London, Malet Street, London WC1E 7HX, UK
| | - Wah Chiu
- Department of Bioengineering, Microbiology and Immunology and Photon Science, Stanford University, James H. Clark Center, MC5447, 318 Campus Drive, Stanford, CA 94305, USA
| | - Maya Topf
- Institute of Structural and Molecular Biology, Birkbeck, University College London, Malet Street, London WC1E 7HX, UK
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8
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Chen M, Baker ML. Automation and assessment of de novo modeling with Pathwalking in near atomic resolution cryoEM density maps. J Struct Biol 2018; 204:555-563. [DOI: 10.1016/j.jsb.2018.09.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Revised: 08/28/2018] [Accepted: 09/08/2018] [Indexed: 01/30/2023]
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9
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Wang Y, Shekhar M, Thifault D, Williams CJ, McGreevy R, Richardson J, Singharoy A, Tajkhorshid E. Constructing atomic structural models into cryo-EM densities using molecular dynamics - Pros and cons. J Struct Biol 2018; 204:319-328. [PMID: 30092279 PMCID: PMC6394829 DOI: 10.1016/j.jsb.2018.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 07/31/2018] [Accepted: 08/05/2018] [Indexed: 01/11/2023]
Abstract
Accurate structure determination from electron density maps at 3-5 Å resolution necessitates a balance between extensive global and local sampling of atomistic models, yet with the stereochemical correctness of backbone and sidechain geometries. Molecular Dynamics Flexible Fitting (MDFF), particularly through a resolution-exchange scheme, ReMDFF, provides a robust way of achieving this balance for hybrid structure determination. Employing two high-resolution density maps, namely that of β-galactosidase at 3.2 Å and TRPV1 at 3.4 Å, we showcase the quality of ReMDFF-generated models, comparing them against ones submitted by independent research groups for the 2015-2016 Cryo-EM Model Challenge. This comparison offers a clear evaluation of ReMDFF's strengths and shortcomings, and those of data-guided real-space refinements in general. ReMDFF results scored highly on the various metric for judging the quality-of-fit and quality-of-model. However, some systematic discrepancies are also noted employing a Molprobity analysis, that are reproducible across multiple competition entries. A space of key refinement parameters is explored within ReMDFF to observe their impact within the final model. Choice of force field parameters and initial model seem to have the most significant impact on ReMDFF model-quality. To this end, very recently developed CHARMM36m force field parameters provide now more refined ReMDFF models than the ones originally submitted to the Cryo-EM challenge. Finally, a set of good-practices is prescribed for the community to benefit from the MDFF developments.
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Affiliation(s)
- Yuhang Wang
- Center for Biophysics and Quantitative Biology, College of Medicine, Department of Biochemistry, Beckman Institute for Advanced Science and Technology, and University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Mrinal Shekhar
- Center for Biophysics and Quantitative Biology, College of Medicine, Department of Biochemistry, Beckman Institute for Advanced Science and Technology, and University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Darren Thifault
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University, Tempe, AZ 85287, United States
| | | | - Ryan McGreevy
- Center for Biophysics and Quantitative Biology, College of Medicine, Department of Biochemistry, Beckman Institute for Advanced Science and Technology, and University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
| | - Jane Richardson
- Department of Biochemistry, Duke University, Durham, NC 27710, United States
| | - Abhishek Singharoy
- School of Molecular Sciences, Center for Applied Structural Discovery, Arizona State University, Tempe, AZ 85287, United States.
| | - Emad Tajkhorshid
- NIH Center for Macromolecular Modeling and Bioinformatics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
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10
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Richardson JS, Williams CJ, Videau LL, Chen VB, Richardson DC. Assessment of detailed conformations suggests strategies for improving cryoEM models: Helix at lower resolution, ensembles, pre-refinement fixups, and validation at multi-residue length scale. J Struct Biol 2018; 204:301-312. [PMID: 30107233 PMCID: PMC6163098 DOI: 10.1016/j.jsb.2018.08.007] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 08/01/2018] [Accepted: 08/08/2018] [Indexed: 11/17/2022]
Abstract
We find that the overall quite good methods used in the CryoEM Model Challenge could still benefit greatly from several strategies for improving local conformations. Our assessments primarily use validation criteria from the MolProbity web service. Those criteria include MolProbity's all-atom contact analysis, updated versions of standard conformational validations for protein and RNA, plus two recent additions: first, flags for cis-nonPro and twisted peptides, and second, the CaBLAM system for diagnosing secondary structure, validating Cα backbone, and validating adjacent peptide CO orientations in the context of the Cα trace. In general, automated ab initio building of starting models is quite good at backbone connectivity but often fails at local conformation or sequence register, especially at poorer than 3.5 Å resolution. However, we show that even if criteria (such as Ramachandran or rotamer) are explicitly restrained to improve refinement behavior and overall validation scores, automated optimization of a deposited structure seldom corrects specific misfittings that start in the wrong local minimum, but just hides them. Therefore, local problems should be identified, and as many as possible corrected, before starting refinement. Secondary structures are confusing at 3-4 Å but can be better recognized at 6-8 Å. In future model challenges, specific steps being tested (such as segmentation) and the required documentation (such as PDB code of starting model) should each be explicitly defined, so competing methods on a given task can be meaningfully compared. Individual local examples are presented here, to understand what local mistakes and corrections look like in 3D, how they probably arise, and what possible improvements to methodology might help avoid them. At these resolutions, both structural biologists and end-users need meaningful estimates of local uncertainty, perhaps through explicit ensembles. Fitting problems can best be diagnosed by validation that spans multiple residues; CaBLAM is such a multi-residue tool, and its effectiveness is demonstrated.
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Affiliation(s)
| | | | - Lizbeth L Videau
- Department of Biochemistry, Duke University, Durham, NC 27710, USA
| | - Vincent B Chen
- Department of Biochemistry, Duke University, Durham, NC 27710, USA
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Affiliation(s)
- Catherine L Lawson
- Institute for Quantitative Biomedicine, Rutgers University, Piscataway, NJ 08854, USA.
| | - Wah Chiu
- Division of Cryo-EM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Stanford University, Menlo Park, CA 94025, USA; Department of Bioengineering, Department of Microbiology and Immunology, James H. Clark Center, Stanford University, Stanford, CA 94305, USA.
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12
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Kryshtafovych A, Monastyrskyy B, Adams PD, Lawson CL, Chiu W. Distribution of evaluation scores for the models submitted to the second cryo-EM model challenge. Data Brief 2018; 20:1629-1638. [PMID: 30263915 PMCID: PMC6157618 DOI: 10.1016/j.dib.2018.08.214] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 08/24/2018] [Accepted: 08/31/2018] [Indexed: 01/02/2023] Open
Abstract
142 protein structure models were submitted to second Cryo-EM model challenge (2015–2016). Accuracy of the models was evaluated with 54 evaluation scores. Results of the descriptive statistical analysis of the scores are provided in this article.
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Affiliation(s)
- Andriy Kryshtafovych
- Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Bohdan Monastyrskyy
- Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Paul D Adams
- Molecular Biophysics & Integrated Bioimaging, LBNL, CA 94720, USA.,Department of Bioengineering, University of California Berkeley, CA 94720, USA
| | - Catherine L Lawson
- Institute for Quantitative Biomedicine and Research Collaboratory for Structural Bioinformatics, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854, USA
| | - Wah Chiu
- Department of Bioengineering, Microbiology and Immunology and Photon Science, Stanford University, James H. Clark Center, MC5447, 318 Campus Drive, Stanford, CA 94305-5447, USA
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