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Aguirre-Sampieri S, Casañal A, Emsley P, Garza-Ramos G. Cryo-EM structure of bacterial nitrilase reveals insight into oligomerization, substrate recognition, and catalysis. J Struct Biol 2024; 216:108093. [PMID: 38615726 DOI: 10.1016/j.jsb.2024.108093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/26/2024] [Accepted: 04/12/2024] [Indexed: 04/16/2024]
Abstract
Many enzymes can self-assemble into higher-order structures with helical symmetry. A particularly noteworthy example is that of nitrilases, enzymes in which oligomerization of dimers into spiral homo-oligomers is a requirement for their enzymatic function. Nitrilases are widespread in nature where they catalyze the hydrolysis of nitriles into the corresponding carboxylic acid and ammonia. Here, we present the Cryo-EM structure, at 3 Å resolution, of a C-terminal truncate nitrilase from Rhodococcus sp. V51B that assembles in helical filaments. The model comprises a complete turn of the helical arrangement with a substrate-intermediate bound to the catalytic cysteine. The structure was solved having added the substrate to the protein. The length and stability of filaments was made more substantial in the presence of the aromatic substrate, benzonitrile, but not for aliphatic nitriles or dinitriles. The overall structure maintains the topology of the nitrilase family, and the filament is formed by the association of dimers in a chain-like mechanism that stabilizes the spiral. The active site is completely buried inside each monomer, while the substrate binding pocket was observed within the oligomerization interfaces. The present structure is in a closed configuration, judging by the position of the lid, suggesting that the intermediate is one of the covalent adducts. The proximity of the active site to the dimerization and oligomerization interfaces, allows the dimer to sense structural changes once the benzonitrile was bound, and translated to the rest of the filament, stabilizing the helical structure.
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Affiliation(s)
- Sergio Aguirre-Sampieri
- Universidad Nacional Autónoma de México, Facultad de Medicina, Departamento de Bioquímica, Circuito Escolar S/N, Ciudad Universitaria, CDMX, Mexico
| | - Ana Casañal
- Human Technopole, Palazzo Italia, Viale Rita Levi‑Montalcini, 1, 20157 Milan, Italy
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Structural Studies Division, Francis Crick Avenue, CB2 0QH Cambridge, England
| | - Georgina Garza-Ramos
- Universidad Nacional Autónoma de México, Facultad de Medicina, Departamento de Bioquímica, Circuito Escolar S/N, Ciudad Universitaria, CDMX, Mexico.
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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. Res Sq 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] [What about the content of this article? (0)] [Affiliation(s)] [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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3
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Agirre J, Atanasova M, Bagdonas H, Ballard CB, Baslé A, Beilsten-Edmands J, Borges RJ, Brown DG, Burgos-Mármol JJ, Berrisford JM, Bond PS, Caballero I, Catapano L, Chojnowski G, Cook AG, Cowtan KD, Croll TI, Debreczeni JÉ, Devenish NE, Dodson EJ, Drevon TR, Emsley P, Evans G, Evans PR, Fando M, Foadi J, Fuentes-Montero L, Garman EF, Gerstel M, Gildea RJ, Hatti K, Hekkelman ML, Heuser P, Hoh SW, Hough MA, Jenkins HT, Jiménez E, Joosten RP, Keegan RM, Keep N, Krissinel EB, Kolenko P, Kovalevskiy O, Lamzin VS, Lawson DM, Lebedev AA, Leslie AGW, Lohkamp B, Long F, Malý M, McCoy AJ, McNicholas SJ, Medina A, Millán C, Murray JW, Murshudov GN, Nicholls RA, Noble MEM, Oeffner R, Pannu NS, Parkhurst JM, Pearce N, Pereira J, Perrakis A, Powell HR, Read RJ, Rigden DJ, Rochira W, Sammito M, Sánchez Rodríguez F, Sheldrick GM, Shelley KL, Simkovic F, Simpkin AJ, Skubak P, Sobolev E, Steiner RA, Stevenson K, Tews I, Thomas JMH, Thorn A, Valls JT, Uski V, Usón I, Vagin A, Velankar S, Vollmar M, Walden H, Waterman D, Wilson KS, Winn MD, Winter G, Wojdyr M, Yamashita K. The CCP4 suite: integrative software for macromolecular crystallography. Acta Crystallogr D Struct Biol 2023; 79:449-461. [PMID: 37259835 PMCID: PMC10233625 DOI: 10.1107/s2059798323003595] [Citation(s) in RCA: 84] [Impact Index Per Article: 84.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 04/19/2023] [Indexed: 06/02/2023] Open
Abstract
The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.
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Affiliation(s)
- Jon Agirre
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Mihaela Atanasova
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Haroldas Bagdonas
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Charles B. Ballard
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Arnaud Baslé
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, United Kingdom
| | - James Beilsten-Edmands
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Rafael J. Borges
- The Center of Medicinal Chemistry (CQMED), Center for Molecular Biology and Genetic Engineering (CBMEG), University of Campinas (UNICAMP), Av. Dr. André Tosello 550, 13083-886 Campinas, Brazil
| | - David G. Brown
- Laboratoires Servier SAS Institut de Recherches, Croissy-sur-Seine, France
| | - J. Javier Burgos-Mármol
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - John M. Berrisford
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Paul S. Bond
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Iracema Caballero
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Lucrezia Catapano
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
- Randall Centre for Cell and Molecular Biophysics, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, United Kingdom
| | - Grzegorz Chojnowski
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Atlanta G. Cook
- The Wellcome Centre for Cell Biology, University of Edinburgh, Michael Swann Building, Max Born Crescent, The King’s Buildings, Edinburgh EH9 3BF, United Kingdom
| | - Kevin D. Cowtan
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Tristan I. Croll
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
- Altos Labs, Portway Building, Granta Park, Great Abington, Cambridge CB21 6GP, United Kingdom
| | - Judit É. Debreczeni
- Discovery Sciences, R&D BioPharmaceuticals, AstraZeneca, Darwin Building, Cambridge Science Park, Milton Road, Cambridge CB4 0WG, United Kingdom
| | - Nicholas E. Devenish
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Eleanor J. Dodson
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Tarik R. Drevon
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Gwyndaf Evans
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Didcot OX11 0QS, United Kingdom
| | - Phil R. Evans
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Maria Fando
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - James Foadi
- Department of Mathematical Sciences, University of Bath, Bath, United Kingdom
| | - Luis Fuentes-Montero
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Elspeth F. Garman
- Department of Biochemistry, University of Oxford, Dorothy Crowfoot Hodgkin Building, Oxford OX1 3QU, United Kingdom
| | - Markus Gerstel
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Richard J. Gildea
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Kaushik Hatti
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Maarten L. Hekkelman
- Oncode Institute and Department of Biochemistry, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Philipp Heuser
- European Molecular Biology Laboratory, c/o DESY, Notkestrasse 85, 22607 Hamburg, Germany
| | - Soon Wen Hoh
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Michael A. Hough
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
- School of Life Sciences, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom
| | - Huw T. Jenkins
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Elisabet Jiménez
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Robbie P. Joosten
- Oncode Institute and Department of Biochemistry, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Ronan M. Keegan
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Nicholas Keep
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck College, London WC1E 7HX, United Kingdom
| | - Eugene B. Krissinel
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Petr Kolenko
- Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Břehová 7, 115 19 Prague 1, Czech Republic
- Institute of Biotechnology of the Czech Academy of Sciences, BIOCEV, Průmyslová 55, 252 50 Vestec, Czech Republic
| | - Oleg Kovalevskiy
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Victor S. Lamzin
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - David M. Lawson
- Department of Biochemistry and Metabolism, John Innes Centre, Norwich NR4 7UH, United Kingdom
| | - Andrey A. Lebedev
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Andrew G. W. Leslie
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Bernhard Lohkamp
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Fei Long
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Martin Malý
- Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Břehová 7, 115 19 Prague 1, Czech Republic
- Institute of Biotechnology of the Czech Academy of Sciences, BIOCEV, Průmyslová 55, 252 50 Vestec, Czech Republic
- Biological Sciences, Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Airlie J. McCoy
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Stuart J. McNicholas
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Ana Medina
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Claudia Millán
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - James W. Murray
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Garib N. Murshudov
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Robert A. Nicholls
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Martin E. M. Noble
- Translational and Clinical Research Institute, Newcastle University, Paul O’Gorman Building, Medical School, Framlington Place, Newcastle upon Tyne NE2 4HH, United Kingdom
| | - Robert Oeffner
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Navraj S. Pannu
- Department of Infectious Diseases, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - James M. Parkhurst
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
- Rosalind Franklin Institute, Harwell Science and Innovation Campus, Didcot OX11 0QS, United Kingdom
| | - Nicholas Pearce
- Department of Physics, Chemistry and Biology (IFM), Linköping University, SE-581 83 Linköping, Sweden
| | - Joana Pereira
- Biozentrum and SIB Swiss Institute of Bioinformatics, University of Basel, 4056 Basel, Switzerland
| | - Anastassis Perrakis
- Oncode Institute and Department of Biochemistry, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Harold R. Powell
- Department of Life Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Randy J. Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Daniel J. Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - William Rochira
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Massimo Sammito
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
- Discovery Centre, Biologics Engineering, AstraZeneca, Biomedical Campus, 1 Francis Crick Avenue, Trumpington, Cambridge CB2 0AA, United Kingdom
| | - Filomeno Sánchez Rodríguez
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - George M. Sheldrick
- Department of Structural Chemistry, Georg-August-Universität Göttingen, Tammannstrasse 4, 37077 Göttingen, Germany
| | - Kathryn L. Shelley
- Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Felix Simkovic
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Adam J. Simpkin
- Laboratoires Servier SAS Institut de Recherches, Croissy-sur-Seine, France
| | - Pavol Skubak
- Department of Infectious Diseases, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands
| | - Egor Sobolev
- European Molecular Biology Laboratory, c/o DESY, Notkestrasse 85, 22607 Hamburg, Germany
| | - Roberto A. Steiner
- Randall Centre for Cell and Molecular Biophysics, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, United Kingdom
- Department of Biomedical Sciences, University of Padova, Italy
| | - Kyle Stevenson
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Ivo Tews
- Biological Sciences, Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
| | - Jens M. H. Thomas
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Andrea Thorn
- Institute for Nanostructure and Solid State Physics, Universität Hamburg, 22761 Hamburg, Germany
| | - Josep Triviño Valls
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Ville Uski
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Isabel Usón
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
- ICREA, Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, 08003 Barcelona, Spain
| | - Alexei Vagin
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Melanie Vollmar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL–EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Helen Walden
- School of Molecular Biosciences, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - David Waterman
- STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
- CCP4, Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot OX11 0FA, United Kingdom
| | - Keith S. Wilson
- York Structural Biology Laboratory, Department of Chemistry, University of York, York YO10 5DD, United Kingdom
| | - Martyn D. Winn
- Scientific Computing Department, Science and Technology Facilities Council, Didcot OX11 0FA, United Kingdom
| | - Graeme Winter
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, United Kingdom
| | - Marcin Wojdyr
- Global Phasing Limited (United Kingdom), Sheraton House, Castle Park, Cambridge CB3 0AX, United Kingdom
| | - Keitaro Yamashita
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
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4
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Nicholls RA, Wojdyr M, Joosten RP, Catapano L, Long F, Fischer M, Emsley P, Murshudov GN. The missing link: covalent linkages in structural models. Acta Crystallogr D Struct Biol 2021; 77:727-745. [PMID: 34076588 PMCID: PMC8171067 DOI: 10.1107/s2059798321003934] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 04/13/2021] [Indexed: 11/10/2022] Open
Abstract
Covalent linkages between constituent blocks of macromolecules and ligands have been subject to inconsistent treatment during the model-building, refinement and deposition process. This may stem from a number of sources, including difficulties with initially detecting the covalent linkage, identifying the correct chemistry, obtaining an appropriate restraint dictionary and ensuring its correct application. The analysis presented herein assesses the extent of problems involving covalent linkages in the Protein Data Bank (PDB). Not only will this facilitate the remediation of existing models, but also, more importantly, it will inform and thus improve the quality of future linkages. By considering linkages of known type in the CCP4 Monomer Library (CCP4-ML), failure to model a covalent linkage is identified to result in inaccurate (systematically longer) interatomic distances. Scanning the PDB for proximal atom pairs that do not have a corresponding type in the CCP4-ML reveals a large number of commonly occurring types of unannotated potential linkages; in general, these may or may not be covalently linked. Manual consideration of the most commonly occurring cases identifies a number of genuine classes of covalent linkages. The recent expansion of the CCP4-ML is discussed, which has involved the addition of over 16 000 and the replacement of over 11 000 component dictionaries using AceDRG. As part of this effort, the CCP4-ML has also been extended using AceDRG link dictionaries for the aforementioned linkage types identified in this analysis. This will facilitate the identification of such linkage types in future modelling efforts, whilst concurrently easing the process involved in their application. The need for a universal standard for maintaining link records corresponding to covalent linkages, and references to the associated dictionaries used during modelling and refinement, following deposition to the PDB is emphasized. The importance of correctly modelling covalent linkages is demonstrated using a case study, which involves the covalent linkage of an inhibitor to the main protease in various viral species, including SARS-CoV-2. This example demonstrates the importance of properly modelling covalent linkages using a comprehensive restraint dictionary, as opposed to just using a single interatomic distance restraint or failing to model the covalent linkage at all.
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Affiliation(s)
- Robert A. Nicholls
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Marcin Wojdyr
- Global Phasing Limited, Sheraton House, Castle Park, Cambridge CB3 0AX, United Kingdom
| | - Robbie P. Joosten
- Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Oncode Institute, The Netherlands
| | - Lucrezia Catapano
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
- Randall Centre for Cell and Molecular Biophysics, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, United Kingdom
| | - Fei Long
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Marcus Fischer
- Chemical Biology and Therapeutics and Structural Biology, St Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105-3678, USA
| | - Paul Emsley
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Garib N. Murshudov
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
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5
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Nicholls RA, Joosten RP, Long F, Wojdyr M, Lebedev A, Krissinel E, Catapano L, Fischer M, Emsley P, Murshudov GN. Modelling covalent linkages in CCP4. Acta Crystallogr D Struct Biol 2021; 77:712-726. [PMID: 34076587 PMCID: PMC8171069 DOI: 10.1107/s2059798321001753] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 02/12/2021] [Indexed: 11/10/2022] Open
Abstract
In this contribution, the current protocols for modelling covalent linkages within the CCP4 suite are considered. The mechanism used for modelling covalent linkages is reviewed: the use of dictionaries for describing changes to stereochemistry as a result of the covalent linkage and the application of link-annotation records to structural models to ensure the correct treatment of individual instances of covalent linkages. Previously, linkage descriptions were lacking in quality compared with those of contemporary component dictionaries. Consequently, AceDRG has been adapted for the generation of link dictionaries of the same quality as for individual components. The approach adopted by AceDRG for the generation of link dictionaries is outlined, which includes associated modifications to the linked components. A number of tools to facilitate the practical modelling of covalent linkages available within the CCP4 suite are described, including a new restraint-dictionary accumulator, the Make Covalent Link tool and AceDRG interface in Coot, the 3D graphical editor JLigand and the mechanisms for dealing with covalent linkages in the CCP4i2 and CCP4 Cloud environments. These integrated solutions streamline and ease the covalent-linkage modelling workflow, seamlessly transferring relevant information between programs. Current recommended practice is elucidated by means of instructive practical examples. By summarizing the different approaches to modelling linkages that are available within the CCP4 suite, limitations and potential pitfalls that may be encountered are highlighted in order to raise awareness, with the intention of improving the quality of future modelled covalent linkages in macromolecular complexes.
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Affiliation(s)
- Robert A. Nicholls
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Robbie P. Joosten
- Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
- Oncode Institute, The Netherlands
| | - Fei Long
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Marcin Wojdyr
- Global Phasing Limited, Sheraton House, Castle Park, Cambridge CB3 0AX, United Kingdom
| | - Andrey Lebedev
- CCP4, STFC Rutherford Appleton Laboratory, Chilton, Didcot OX11 0QX, United Kingdom
| | - Eugene Krissinel
- CCP4, STFC Rutherford Appleton Laboratory, Chilton, Didcot OX11 0QX, United Kingdom
| | - Lucrezia Catapano
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
- Randall Centre for Cell and Molecular Biophysics, Faculty of Life Sciences and Medicine, King’s College London, London SE1 9RT, United Kingdom
| | - Marcus Fischer
- Chemical Biology and Therapeutics and Structural Biology, St Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105-3678, USA
| | - Paul Emsley
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Garib N. Murshudov
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
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6
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Todd H, Emsley P. Development and assessment of CootVR, a virtual reality computer program for model building. Acta Crystallogr D Struct Biol 2021; 77:19-27. [PMID: 33404522 PMCID: PMC7787110 DOI: 10.1107/s2059798320013625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 10/12/2020] [Indexed: 12/03/2022]
Abstract
Virtual reality-specific tools for model building are possible, and can provide an order-of-magnitude speedup over mouse-and-keyboard tools in certain situations. Biological macromolecules have complex three-dimensional shapes that are experimentally examined using X-ray crystallography and electron cryo-microscopy. Interpreting the data that these methods yield involves building 3D atomic models. With almost every data set, some portion of the time put into creating these models must be spent manually modifying the model in order to make it consistent with the data; this is difficult and time-consuming, in part because the data are ‘blurry’ in three dimensions. This paper describes the design and assessment of CootVR (available at http://hamishtodd1.github.io/cvr), a prototype computer program for performing this task in virtual reality, allowing structural biologists to build molecular models into cryo-EM and crystallographic data using their hands. CootVR was timed against Coot for a very specific model-building task, and was found to give an order-of-magnitude speedup for this task. A from-scratch model build using CootVR was also attempted; from this experience it is concluded that currently CootVR does not give a speedup over Coot overall.
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Affiliation(s)
- Hamish Todd
- Huawei Research and Development, Cambridge, United Kingdom
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge, United Kingdom
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7
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Casañal A, Lohkamp B, Emsley P. Current developments in Coot for macromolecular model building of Electron Cryo-microscopy and Crystallographic Data. Protein Sci 2020; 29:1069-1078. [PMID: 31730249 PMCID: PMC7096722 DOI: 10.1002/pro.3791] [Citation(s) in RCA: 334] [Impact Index Per Article: 83.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 11/13/2019] [Accepted: 11/14/2019] [Indexed: 12/20/2022]
Abstract
Coot is a tool widely used for model building, refinement, and validation of macromolecular structures. It has been extensively used for crystallography and, more recently, improvements have been introduced to aid in cryo‐EM model building and refinement, as cryo‐EM structures with resolution ranging 2.5–4 A are now routinely available. Model building into these maps can be time‐consuming and requires experience in both biochemistry and building into low‐resolution maps. To simplify and expedite the model building task, and minimize the needed expertise, new tools are being added in Coot. Some examples include morphing, Geman‐McClure restraints, full‐chain refinement, and Fourier‐model based residue‐type‐specific Ramachandran restraints. Here, we present the current state‐of‐the‐art in Coot usage.
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Affiliation(s)
- Ana Casañal
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK
| | - Bernhard Lohkamp
- Division of Molecular Structural Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge, UK
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8
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Nicholls R, Emsley P, Kovalevskiy O, Long F, Murshudov G. Tools to aid macromolecular refinement at low resolution. Acta Crystallogr A Found Adv 2019. [DOI: 10.1107/s2053273319094026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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9
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van Beusekom B, Wezel N, Hekkelman ML, Perrakis A, Emsley P, Joosten RP. Building and rebuilding N-glycans in protein structure models. Acta Crystallogr D Struct Biol 2019; 75:416-425. [PMID: 30988258 PMCID: PMC6465985 DOI: 10.1107/s2059798319003875] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 03/20/2019] [Indexed: 01/16/2023]
Abstract
Carbohydrates are automatically built and rebuilt using Coot in the PDB-REDO pipeline. N-Glycosylation is one of the most common post-translational modifications and is implicated in, for example, protein folding and interaction with ligands and receptors. N-Glycosylation trees are complex structures of linked carbohydrate residues attached to asparagine residues. While carbohydrates are typically modeled in protein structures, they are often incomplete or have the wrong chemistry. Here, new tools are presented to automatically rebuild existing glycosylation trees, to extend them where possible, and to add new glycosylation trees if they are missing from the model. The method has been incorporated in the PDB-REDO pipeline and has been applied to build or rebuild 16 452 carbohydrate residues in 11 651 glycosylation trees in 4498 structure models, and is also available from the PDB-REDO web server. With better modeling of N-glycosylation, the biological function of this important modification can be better and more easily understood.
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Affiliation(s)
- Bart van Beusekom
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Natasja Wezel
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Maarten L Hekkelman
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Anastassis Perrakis
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
| | - Paul Emsley
- MRC Laboratory for Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
| | - Robbie P Joosten
- Department of Biochemistry, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands
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11
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Abstract
Coot is a graphics application that is used to build or manipulate macromolecular models; its particular forte is manipulation of the model at the residue level. The model-building tools of Coot have been combined and extended to assist or automate the building of N-linked glycans. The model is built by the addition of monosaccharides, placed by variation of internal coordinates. The subsequent model is refined by real-space refinement, which is stabilized with modified and additional restraints. It is hoped that these enhanced building tools will help to reduce building errors of N-linked glycans and improve our knowledge of the structures of glycoproteins.
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Affiliation(s)
- Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
| | - Max Crispin
- Centre for Biological Sciences and the Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, England
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12
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Casañal A, Kumar A, Hill CH, Easter AD, Emsley P, Degliesposti G, Gordiyenko Y, Santhanam B, Wolf J, Wiederhold K, Dornan GL, Skehel M, Robinson CV, Passmore LA. Architecture of eukaryotic mRNA 3'-end processing machinery. Science 2017; 358:1056-1059. [PMID: 29074584 PMCID: PMC5788269 DOI: 10.1126/science.aao6535] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 10/12/2017] [Indexed: 12/31/2022]
Abstract
Newly transcribed eukaryotic precursor messenger RNAs (pre-mRNAs) are processed at their 3' ends by the ~1-megadalton multiprotein cleavage and polyadenylation factor (CPF). CPF cleaves pre-mRNAs, adds a polyadenylate tail, and triggers transcription termination, but it is unclear how its various enzymes are coordinated and assembled. Here, we show that the nuclease, polymerase, and phosphatase activities of yeast CPF are organized into three modules. Using electron cryomicroscopy, we determined a 3.5-angstrom-resolution structure of the ~200-kilodalton polymerase module. This revealed four β propellers, in an assembly markedly similar to those of other protein complexes that bind nucleic acid. Combined with in vitro reconstitution experiments, our data show that the polymerase module brings together factors required for specific and efficient polyadenylation, to help coordinate mRNA 3'-end processing.
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Affiliation(s)
- Ana Casañal
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Chris H Hill
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Yuliya Gordiyenko
- MRC Laboratory of Molecular Biology, Cambridge, UK.,Chemistry Research Laboratory, University of Oxford, Oxford, UK
| | | | - Jana Wolf
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | | | - Mark Skehel
- MRC Laboratory of Molecular Biology, Cambridge, UK
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13
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Thorn A, Parkhurst J, Emsley P, Nicholls RA, Vollmar M, Evans G, Murshudov GN. AUSPEX: a graphical tool for X-ray diffraction data analysis. Acta Crystallogr D Struct Biol 2017; 73:729-737. [PMID: 28876236 PMCID: PMC5586246 DOI: 10.1107/s205979831700969x] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Accepted: 07/01/2017] [Indexed: 11/10/2022]
Abstract
In this paper, AUSPEX, a new software tool for experimental X-ray data analysis, is presented. Exploring the behaviour of diffraction intensities and the associated estimated uncertainties facilitates the discovery of underlying problems and can help users to improve their data acquisition and processing in order to obtain better structural models. The program enables users to inspect the distribution of observed intensities (or amplitudes) against resolution as well as the associated estimated uncertainties (sigmas). It is demonstrated how AUSPEX can be used to visually and automatically detect ice-ring artefacts in integrated X-ray diffraction data. Such artefacts can hamper structure determination, but may be difficult to identify from the raw diffraction images produced by modern pixel detectors. The analysis suggests that a significant portion of the data sets deposited in the PDB contain ice-ring artefacts. Furthermore, it is demonstrated how other problems in experimental X-ray data caused, for example, by scaling and data-conversion procedures can be detected by AUSPEX.
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Affiliation(s)
- Andrea Thorn
- Hamburg Centre for Ultrafast Imaging, Universität Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - James Parkhurst
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, England
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
| | - Robert A Nicholls
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
| | - Melanie Vollmar
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, England
| | - Gwyndaf Evans
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot OX11 0DE, England
| | - Garib N Murshudov
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
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14
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Emsley P. Using Coot to model N-linked carbohydrates. Acta Crystallogr A Found Adv 2017. [DOI: 10.1107/s0108767317095927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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15
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Abstract
Coot is a molecular-graphics program primarily aimed at model building using X-ray data. Recently, tools for the manipulation and representation of ligands have been introduced. Here, these new tools for ligand validation and comparison are described. Ligands in the wwPDB have been scored by density-fit, distortion and atom-clash metrics. The distributions of these scores can be used to assess the relative merits of the particular ligand in the protein-ligand complex of interest by means of `sliders' akin to those now available for each accession code on the wwPDB websites.
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Affiliation(s)
- Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge CB2 0QH, England
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16
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Long F, Nicholls RA, Emsley P, Gražulis S, Merkys A, Vaitkus A, Murshudov GN. AceDRG: a stereochemical description generator for ligands. Acta Crystallogr D Struct Biol 2017; 73:112-122. [PMID: 28177307 PMCID: PMC5297914 DOI: 10.1107/s2059798317000067] [Citation(s) in RCA: 196] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Accepted: 01/03/2017] [Indexed: 11/11/2022] Open
Abstract
The program AceDRG is designed for the derivation of stereochemical information about small molecules. It uses local chemical and topological environment-based atom typing to derive and organize bond lengths and angles from a small-molecule database: the Crystallography Open Database (COD). Information about the hybridization states of atoms, whether they belong to small rings (up to seven-membered rings), ring aromaticity and nearest-neighbour information is encoded in the atom types. All atoms from the COD have been classified according to the generated atom types. All bonds and angles have also been classified according to the atom types and, in a certain sense, bond types. Derived data are tabulated in a machine-readable form that is freely available from CCP4. AceDRG can also generate stereochemical information, provided that the basic bonding pattern of a ligand is known. The basic bonding pattern is perceived from one of the computational chemistry file formats, including SMILES, mmCIF, SDF MOL and SYBYL MOL2 files. Using the bonding chemistry, atom types, and bond and angle tables generated from the COD, AceDRG derives the `ideal' bond lengths, angles, plane groups, aromatic rings and chirality information, and writes them to an mmCIF file that can be used by the refinement program REFMAC5 and the model-building program Coot. Other refinement and model-building programs such as PHENIX and BUSTER can also use these files. AceDRG also generates one or more coordinate sets corresponding to the most favourable conformation(s) of a given ligand. AceDRG employs RDKit for chemistry perception and for initial conformation generation, as well as for the interpretation of SMILES strings, SDF MOL and SYBYL MOL2 files.
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Affiliation(s)
- Fei Long
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Robert A. Nicholls
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Paul Emsley
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Saulius Gražulis
- Institute of Biotechnology, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania
| | - Andrius Merkys
- Institute of Biotechnology, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania
| | - Antanas Vaitkus
- Institute of Biotechnology, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania
| | - Garib N. Murshudov
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
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17
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Abstract
An introduction to the Proceedings of the 2016 CCP4 Study Weekend on protein-ligand complex structures.
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Affiliation(s)
- Judit É Debreczeni
- Structure & Biophysics, Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, 310 Cambridge Science Park, Cambridge, Cambridgeshire CB4 0WG, England
| | - Paul Emsley
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
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18
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Long F, Nicholls RA, Emsley P, Gražulis S, Merkys A, Vaitkus A, Murshudov GN. Validation and extraction of molecular-geometry information from small-molecule databases. Acta Crystallogr D Struct Biol 2017; 73:103-111. [PMID: 28177306 PMCID: PMC5297913 DOI: 10.1107/s2059798317000079] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 01/03/2017] [Indexed: 11/18/2022] Open
Abstract
A freely available small-molecule structure database, the Crystallography Open Database (COD), is used for the extraction of molecular-geometry information on small-molecule compounds. The results are used for the generation of new ligand descriptions, which are subsequently used by macromolecular model-building and structure-refinement software. To increase the reliability of the derived data, and therefore the new ligand descriptions, the entries from this database were subjected to very strict validation. The selection criteria made sure that the crystal structures used to derive atom types, bond and angle classes are of sufficiently high quality. Any suspicious entries at a crystal or molecular level were removed from further consideration. The selection criteria included (i) the resolution of the data used for refinement (entries solved at 0.84 Å resolution or higher) and (ii) the structure-solution method (structures must be from a single-crystal experiment and all atoms of generated molecules must have full occupancies), as well as basic sanity checks such as (iii) consistency between the valences and the number of connections between atoms, (iv) acceptable bond-length deviations from the expected values and (v) detection of atomic collisions. The derived atom types and bond classes were then validated using high-order moment-based statistical techniques. The results of the statistical analyses were fed back to fine-tune the atom typing. The developed procedure was repeated four times, resulting in fine-grained atom typing, bond and angle classes. The procedure will be repeated in the future as and when new entries are deposited in the COD. The whole procedure can also be applied to any source of small-molecule structures, including the Cambridge Structural Database and the ZINC database.
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Affiliation(s)
- Fei Long
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Robert A. Nicholls
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Paul Emsley
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Saulius Gražulis
- Institute of Biotechnology, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania
| | - Andrius Merkys
- Institute of Biotechnology, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania
| | - Antanas Vaitkus
- Institute of Biotechnology, Saulėtekio al. 7, LT-10257 Vilnius, Lithuania
| | - Garib N. Murshudov
- Structural Studies, MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
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19
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Adams PD, Aertgeerts K, Bauer C, Bell JA, Berman HM, Bhat TN, Blaney JM, Bolton E, Bricogne G, Brown D, Burley SK, Case DA, Clark KL, Darden T, Emsley P, Feher VA, Feng Z, Groom CR, Harris SF, Hendle J, Holder T, Joachimiak A, Kleywegt GJ, Krojer T, Marcotrigiano J, Mark AE, Markley JL, Miller M, Minor W, Montelione GT, Murshudov G, Nakagawa A, Nakamura H, Nicholls A, Nicklaus M, Nolte RT, Padyana AK, Peishoff CE, Pieniazek S, Read RJ, Shao C, Sheriff S, Smart O, Soisson S, Spurlino J, Stouch T, Svobodova R, Tempel W, Terwilliger TC, Tronrud D, Velankar S, Ward SC, Warren GL, Westbrook JD, Williams P, Yang H, Young J. Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop. Structure 2016; 24:502-508. [PMID: 27050687 DOI: 10.1016/j.str.2016.02.017] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 02/24/2016] [Accepted: 02/25/2016] [Indexed: 10/22/2022]
Abstract
Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.
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Affiliation(s)
- Paul D Adams
- Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley Laboratory, Department of Bioengineering, UC Berkeley, Berkeley, CA 94720-8235, USA
| | | | - Cary Bauer
- Bruker AXS, Inc., Madison, WI 53711, USA
| | | | - Helen M Berman
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Talapady N Bhat
- Biosystems and Biomaterials Division, NIST, Gaithersburg, MD 20899, USA
| | | | - Evan Bolton
- National Center for Biotechnology Information, U.S. National Library of Medicine, Bethesda, MD 20894, USA
| | | | - David Brown
- School of Biosciences, University of Kent, Canterbury CT2 7NH, UK; Charles River Ltd., Structural Biology and Biophysics, Cambridge CB10 1XL, UK
| | - Stephen K Burley
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Skaggs School of Pharmacy and Pharmaceutical Sciences and San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA.
| | - David A Case
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Kirk L Clark
- Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA
| | - Tom Darden
- OpenEye Scientific, Cambridge, MA 02142, USA
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK
| | - Victoria A Feher
- Drug Design Data Resource and Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Zukang Feng
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Colin R Groom
- Cambridge Crystallographic Data Centre, Cambridge CB2 1EZ, UK.
| | | | - Jorg Hendle
- Structural Biology, Lilly Biotechnology Center, San Diego, CA 92121, USA
| | | | - Andrzej Joachimiak
- Structural Biology Center, Biosciences, Argonne National Laboratory, Argonne, IL 60439, USA
| | - Gerard J Kleywegt
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Tobias Krojer
- Structural Genomics Consortium, University of Oxford, Oxford OX3 7DQ, UK
| | - Joseph Marcotrigiano
- Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Alan E Mark
- School of Chemistry & Molecular Biosciences, University of Queensland, St Lucia, QLD 4072, Australia
| | - John L Markley
- BioMagResBank, Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706-1544, USA
| | - Matthew Miller
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Wladek Minor
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22908, USA
| | - Gaetano T Montelione
- Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Molecular Biology and Biochemistry, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | | | - Atsushi Nakagawa
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Osaka 565-0871, Japan
| | - Haruki Nakamura
- Protein Data Bank Japan, Institute for Protein Research, Osaka University, Osaka 565-0871, Japan
| | | | - Marc Nicklaus
- Computer-Aided Drug Design Group, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA
| | | | | | | | - Susan Pieniazek
- Bristol-Myers Squibb Research and Development, Pennington, NJ 08534, USA
| | - Randy J Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Cambridge CB2 0XY, UK
| | - Chenghua Shao
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Steven Sheriff
- Bristol-Myers Squibb Research and Development, Princeton, NJ 08543, USA
| | - Oliver Smart
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | | | - John Spurlino
- Janssen Pharmaceuticals, Inc., Spring House, PA 19002, USA
| | - Terry Stouch
- Science For Solutions, LLC, West Windsor, NJ 08550, USA
| | - Radka Svobodova
- CEITEC-Central European Institute of Technology and National Centre for Biomolecular Research, Masaryk University Brno, 625 00 Brno, Czech Republic
| | - Wolfram Tempel
- Structural Genomics Consortium, University of Toronto, Toronto, ON M5G 1L7, Canada
| | | | - Dale Tronrud
- Department of Biochemistry and Biophysics, Oregon State University, Corvallis, OR 97331, USA
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Suzanna C Ward
- Cambridge Crystallographic Data Centre, Cambridge CB2 1EZ, UK
| | | | - John D Westbrook
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | | | - Huanwang Yang
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jasmine Young
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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20
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Abstract
The frequency of glycosylated protein 3D structures in the Protein Data Bank (PDB) is significantly lower than the proportion of glycoproteins in nature, and if glycan 3D structures are present, then they often exhibit a large degree of errors. There are various reasons for this, one of which is a comparably low support of carbohydrates in software tools for 3D structure determination and validation. This chapter illustrates the current features that assist crystallographers with handling glycans during 3D structure determination in Coot and CNS and with validation of the results.
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Affiliation(s)
- Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0QH, UK
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21
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Brown A, Long F, Nicholls RA, Toots J, Emsley P, Murshudov G. Tools for macromolecular model building and refinement into electron cryo-microscopy reconstructions. Acta Crystallogr D Biol Crystallogr 2015; 71:136-53. [PMID: 25615868 PMCID: PMC4304694 DOI: 10.1107/s1399004714021683] [Citation(s) in RCA: 424] [Impact Index Per Article: 47.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Accepted: 10/01/2014] [Indexed: 11/24/2022]
Abstract
The recent rapid development of single-particle electron cryo-microscopy (cryo-EM) now allows structures to be solved by this method at resolutions close to 3 Å. Here, a number of tools to facilitate the interpretation of EM reconstructions with stereochemically reasonable all-atom models are described. The BALBES database has been repurposed as a tool for identifying protein folds from density maps. Modifications to Coot, including new Jiggle Fit and morphing tools and improved handling of nucleic acids, enhance its functionality for interpreting EM maps. REFMAC has been modified for optimal fitting of atomic models into EM maps. As external structural information can enhance the reliability of the derived atomic models, stabilize refinement and reduce overfitting, ProSMART has been extended to generate interatomic distance restraints from nucleic acid reference structures, and a new tool, LIBG, has been developed to generate nucleic acid base-pair and parallel-plane restraints. Furthermore, restraint generation has been integrated with visualization and editing in Coot, and these restraints have been applied to both real-space refinement in Coot and reciprocal-space refinement in REFMAC.
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Affiliation(s)
- Alan Brown
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Fei Long
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Robert A. Nicholls
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Jaan Toots
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
| | - Garib Murshudov
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, England
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22
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Thorn A, Nicholls R, Emsley P, Long F, Murshudov G. Low Resolution Refinement with ProSMART, COOT and REFMAC5. Acta Crystallogr A Found Adv 2014. [DOI: 10.1107/s205327331409651x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Membrane proteins and large assemblies are currently a major focus of molecular biology and molecular medicine. Due to their size and flexibility, these structures may only yield poor quality crystals for which diffraction intensities can be measured to merely mid-low resolution. Nevertheless, these data contain valuable structural information. Here, it will be shown how new features in COOT [1], REFMAC5 [2] and ProSMART [3] can help to exploit low resolution data for model building and refinement, as well as aid model validation. Refinement at low resolution can be stabilised with regularisers, such as jelly-body and external restraints. These allow to routinely obtain good quality models even in cases where only low-resolution data are available (e.g. >3Å). External restraints (available for protein and DNA/RNA) exploit structural prior knowledge, utilising the assertion that local interatomic distances should agree with previous observations. Sources for such prior knowledge include isomorphous and homologous structures, hydrogen bonding patterns, and typical conformations of secondary structure elements. Importantly, global rigidity is not enforced by these restraints – the approach presented allows for dramatic conformational differences between target and reference models. Consequently, restraints may be generated using homologous reference models resolved in different crystal forms. COOT facilitates model building at low resolution by removing degrees of freedom through so-called "backrub rotamers" and torsion angle restraints, as well as providing semi-automatic building options such as model morphing and jiggle fit . Map sharpening and blurring, now available in both COOT and REFMAC5, can be employed to provide further insight regarding the validity of a model, as well as aiding the model building process. General guidelines for the application of these features are provided, along with examples demonstrating their usage.
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23
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Brown A, Amunts A, Bai XC, Llácer J, Hussain T, Emsley P, Long F, Murshudov G, Scheres S, Ramakrishnan V. The Structure of the Yeast Mitochondrial Large Ribosomal Subunit. Acta Crystallogr A Found Adv 2014. [DOI: 10.1107/s2053273314089487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Mitochondria have specialized ribosomes that have diverged from their bacterial and cytoplasmic counterparts. We have solved the structure of the yeast mitoribosomal large subunit using single-particle electron cryo-microscopy. The resolution of 3.2 Ångstroms enabled a nearly complete atomic model to be built de novo and refined, including 39 proteins, 13 of which are unique to mitochondria, as well as expansion segments of mitoribosomal RNA. The structure reveals a new exit tunnel path and architecture, unique elements of the E site and a putative membrane docking site.
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24
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Emsley P. Protein-Ligand Analysis and Validation. Acta Crystallogr A Found Adv 2014. [DOI: 10.1107/s2053273314085192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
A number of tools related to handling of ligands have been added to Coot in recent years - these include 2D depictions, ligand binding pocket layout and a ligand scoring system. Coot also incorporates a number interface to other tools (CCP4's Refmac, Molprobity's probe and reduce and the CCDC's Mogul) to generate score for protein ligand complexes. This scoring system has been applied to models (with data) from the PDB. The details of the ligand scoring, and its application to one's own complex structure will be discussed.
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25
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Amunts A, Brown A, Bai XC, Llácer JL, Hussain T, Emsley P, Long F, Murshudov G, Scheres SHW, Ramakrishnan V. Structure of the yeast mitochondrial large ribosomal subunit. Science 2014; 343:1485-1489. [PMID: 24675956 DOI: 10.1126/science.1249410] [Citation(s) in RCA: 433] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Mitochondria have specialized ribosomes that have diverged from their bacterial and cytoplasmic counterparts. We have solved the structure of the yeast mitoribosomal large subunit using single-particle cryo-electron microscopy. The resolution of 3.2 angstroms enabled a nearly complete atomic model to be built de novo and refined, including 39 proteins, 13 of which are unique to mitochondria, as well as expansion segments of mitoribosomal RNA. The structure reveals a new exit tunnel path and architecture, unique elements of the E site, and a putative membrane docking site.
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Affiliation(s)
- Alexey Amunts
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Alan Brown
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Xiao-Chen Bai
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Jose L Llácer
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Tanweer Hussain
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Paul Emsley
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Fei Long
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Garib Murshudov
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - Sjors H W Scheres
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
| | - V Ramakrishnan
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
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26
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27
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Abstract
X-ray crystallography is a powerful technique for studying protein-ligand interactions. Advances in techniques have meant that it is now possible to routinely determine the structures of ligand complexes in the majority of cases where crystallization conditions and protein structures are already known. Ligand soaking or cocrystallization, together with the potential use of molecular replacement, provides data for determining the structures of a protein in complex with ligands. Furthermore, advances in protein structure model building facilitate automatic ligand fitting to residual electron density in the protein-ligand complex.
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Affiliation(s)
- Andrew P Turnbull
- CRT Discovery Laboratories, Department of Biological Sciences, Birkbeck, University of London, London, UK
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28
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Abstract
Coot is a molecular-graphics application primarily aimed to assist in model building and validation of biological macromolecules. Recently, tools have been added to work with small molecules. The newly incorporated tools for the manipulation and validation of ligands include interaction with PRODRG, subgraph isomorphism-based tools, representation of ligand chemistry, ligand fitting and analysis, and are described here.
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Affiliation(s)
- Judit É Debreczeni
- Structure and Biophysics, DS, AstraZeneca, Alderley Park SK10 4TG, England.
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29
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Read RJ, Adams PD, Arendall WB, Brunger AT, Emsley P, Joosten RP, Kleywegt GJ, Krissinel EB, Lütteke T, Otwinowski Z, Perrakis A, Richardson JS, Sheffler WH, Smith JL, Tickle IJ, Vriend G, Zwart PH. A new generation of crystallographic validation tools for the protein data bank. Structure 2012; 19:1395-412. [PMID: 22000512 PMCID: PMC3195755 DOI: 10.1016/j.str.2011.08.006] [Citation(s) in RCA: 332] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2011] [Revised: 08/02/2011] [Accepted: 08/02/2011] [Indexed: 11/26/2022]
Abstract
This report presents the conclusions of the X-ray Validation Task Force of the worldwide Protein Data Bank (PDB). The PDB has expanded massively since current criteria for validation of deposited structures were adopted, allowing a much more sophisticated understanding of all the components of macromolecular crystals. The size of the PDB creates new opportunities to validate structures by comparison with the existing database, and the now-mandatory deposition of structure factors creates new opportunities to validate the underlying diffraction data. These developments highlighted the need for a new assessment of validation criteria. The Task Force recommends that a small set of validation data be presented in an easily understood format, relative to both the full PDB and the applicable resolution class, with greater detail available to interested users. Most importantly, we recommend that referees and editors judging the quality of structural experiments have access to a concise summary of well-established quality indicators.
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Affiliation(s)
- Randy J Read
- CIMR, University of Cambridge, Cambridge CB2 0XY, UK.
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30
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Abstract
The use of 3D structures derived from X-ray crystal data in drug development has increased in recent years. Molecular graphics applications are important tools at the end of the data processing pipeline and provide means to build, refine and validate protein models and ligand structures. We describe the requirements on useful data, what such data provide and typical problems in dealing with protein-ligand complexes and how one might address them with an emphasis on the use of Coot.
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Affiliation(s)
- Paul Emsley
- Department of Biochemistry, University of Oxford, Oxford, UK.
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31
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Winn MD, Ballard CC, Cowtan KD, Dodson EJ, Emsley P, Evans PR, Keegan RM, Krissinel EB, Leslie AGW, McCoy A, McNicholas SJ, Murshudov GN, Pannu NS, Potterton EA, Powell HR, Read RJ, Vagin A, Wilson KS. Overview of the CCP4 suite and current developments. Acta Crystallogr D Biol Crystallogr 2011; 67:235-42. [PMID: 21460441 PMCID: PMC3069738 DOI: 10.1107/s0907444910045749] [Citation(s) in RCA: 9953] [Impact Index Per Article: 765.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/17/2010] [Accepted: 11/07/2010] [Indexed: 11/10/2022]
Abstract
The CCP4 (Collaborative Computational Project, Number 4) software suite is a collection of programs and associated data and software libraries which can be used for macromolecular structure determination by X-ray crystallography. The suite is designed to be flexible, allowing users a number of methods of achieving their aims. The programs are from a wide variety of sources but are connected by a common infrastructure provided by standard file formats, data objects and graphical interfaces. Structure solution by macromolecular crystallography is becoming increasingly automated and the CCP4 suite includes several automation pipelines. After giving a brief description of the evolution of CCP4 over the last 30 years, an overview of the current suite is given. While detailed descriptions are given in the accompanying articles, here it is shown how the individual programs contribute to a complete software package.
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Affiliation(s)
- Martyn D Winn
- STFC Daresbury Laboratory, Daresbury, Warrington, England.
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32
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Abstract
An introduction to the proceedings of the CCP4 study weekend is given.
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Affiliation(s)
- Kevin Cowtan
- Structural Biology Laboratory, Department of Chemistry, University of York, Heslington, York, United Kingdom
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33
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Emsley P, Lohkamp B, Scott WG, Cowtan K. Features and development of Coot. Acta Crystallogr D Biol Crystallogr 2010; 66:486-501. [PMID: 20383002 PMCID: PMC2852313 DOI: 10.1107/s0907444910007493] [Citation(s) in RCA: 19883] [Impact Index Per Article: 1420.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2009] [Accepted: 02/26/2010] [Indexed: 11/12/2022]
Abstract
Coot is a molecular-graphics program designed to assist in the building of protein and other macromolecular models. The current state of development and available features are presented. Coot is a molecular-graphics application for model building and validation of biological macromolecules. The program displays electron-density maps and atomic models and allows model manipulations such as idealization, real-space refinement, manual rotation/translation, rigid-body fitting, ligand search, solvation, mutations, rotamers and Ramachandran idealization. Furthermore, tools are provided for model validation as well as interfaces to external programs for refinement, validation and graphics. The software is designed to be easy to learn for novice users, which is achieved by ensuring that tools for common tasks are ‘discoverable’ through familiar user-interface elements (menus and toolbars) or by intuitive behaviour (mouse controls). Recent developments have focused on providing tools for expert users, with customisable key bindings, extensions and an extensive scripting interface. The software is under rapid development, but has already achieved very widespread use within the crystallographic community. The current state of the software is presented, with a description of the facilities available and of some of the underlying methods employed.
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Affiliation(s)
- P Emsley
- Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, England.
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34
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Emsley P. Macromolecular model-building and validation using COOT. Acta Crystallogr A 2008. [DOI: 10.1107/s0108767308099327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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35
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Joosten K, Cohen SX, Emsley P, Mooij W, Lamzin VS, Perrakis A. A knowledge-driven approach for crystallographic protein model completion. Acta Crystallogr D Biol Crystallogr 2008; 64:416-24. [PMID: 18391408 PMCID: PMC2467521 DOI: 10.1107/s0907444908001558] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2007] [Accepted: 01/15/2008] [Indexed: 11/17/2022]
Abstract
A novel method that uses the conformational distribution of Cα atoms in known structures is used to build short missing regions (‘loops’) in protein models. An initial tree of possible loop paths is pruned according to structural and electron-density criteria and the most likely loop conformation(s) are selected and built. One of the most cumbersome and time-demanding tasks in completing a protein model is building short missing regions or ‘loops’. A method is presented that uses structural and electron-density information to build the most likely conformations of such loops. Using the distribution of angles and dihedral angles in pentapeptides as the driving parameters, a set of possible conformations for the Cα backbone of loops was generated. The most likely candidate is then selected in a hierarchical manner: new and stronger restraints are added while the loop is built. The weight of the electron-density correlation relative to geometrical considerations is gradually increased until the most likely loop is selected on map correlation alone. To conclude, the loop is refined against the electron density in real space. This is started by using structural information to trace a set of models for the Cα backbone of the loop. Only in later steps of the algorithm is the electron-density correlation used as a criterion to select the loop(s). Thus, this method is more robust in low-density regions than an approach using density as a primary criterion. The algorithm is implemented in a loop-building program, Loopy, which can be used either alone or as part of an automatic building cycle. Loopy can build loops of up to 14 residues in length within a couple of minutes. The average root-mean-square deviation of the Cα atoms in the loops built during validation was less than 0.4 Å. When implemented in the context of automated model building in ARP/wARP, Loopy can increase the completeness of the built models.
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Affiliation(s)
- Krista Joosten
- Department of Molecular Carcinogenesis, Netherlands Cancer Institute, The Netherlands
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36
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Bahar M, Ballard C, Cohen SX, Cowtan KD, Dodson EJ, Emsley P, Esnouf RM, Keegan R, Lamzin V, Langer G, Levdikov V, Long F, Meier C, Muller A, Murshudov GN, Perrakis A, Siebold C, Stein N, Turkenburg MGW, Vagin AA, Winn M, Winter G, Wilson KS. SPINE workshop on automated X-ray analysis: a progress report. Acta Crystallogr D Biol Crystallogr 2006; 62:1170-83. [PMID: 17001094 DOI: 10.1107/s0907444906032197] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2006] [Accepted: 08/14/2006] [Indexed: 11/10/2022]
Abstract
The Structural Proteomics In Europe (SPINE) consortium contained a workpackage to address the automated X-ray analysis of macromolecules. The aim of this workpackage was to increase the throughput of three-dimensional structures while maintaining the high quality of conventional analyses. SPINE was able to bring together developers of software with users from the partner laboratories. Here, the results of a workshop organized by the consortium to evaluate software developed in the member laboratories against a set of bacterial targets are described. The major emphasis was on molecular-replacement suites, where automation was most advanced. Data processing and analysis, use of experimental phases and model construction were also addressed, albeit at a lower level.
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Affiliation(s)
- M Bahar
- The Division of Structural Biology and Oxford Protein Production Facility, The Wellcome Trust Centre for Human Genetics, Oxford, England
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Rolfe D, Ballard C, Emsley P. HAPPy – an experimental phasing and model building pipeline from CCP4. Acta Crystallogr A 2006. [DOI: 10.1107/s010876730609502x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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38
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Krissinel EB, Winn MD, Ballard CC, Ashton AW, Patel P, Potterton EA, McNicholas SJ, Cowtan KD, Emsley P. The new CCP4 Coordinate Library as a toolkit for the design of coordinate-related applications in protein crystallography. Acta Crystallogr D Biol Crystallogr 2004; 60:2250-5. [PMID: 15572778 DOI: 10.1107/s0907444904027167] [Citation(s) in RCA: 55] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2004] [Accepted: 10/25/2004] [Indexed: 11/10/2022]
Abstract
The new CCP4 Coordinate Library is a development aiming to provide a common layer of coordinate-related functionality to the existing applications in the CCP4 suite, as well as a variety of tools that can simplify the design of new applications where they relate to atomic coordinates. The Library comprises a wide spectrum of useful functions, ranging from parsing coordinate formats and elementary editing operations on the coordinate hierarchy of biomolecules, to high-level functionality such as calculation of secondary structure, interatomic bonds, atomic contacts, symmetry transformations, structure superposition and many others. Most of the functions are available in a C++ object interface; however, a Fortran interface is provided for compatibility with older CCP4 applications. The paper describes the general principles of the Library design and the most important functionality. The Library, together with documentation, is available under the LGPL license from the CCP4 suite version 5.0 and higher.
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Affiliation(s)
- E B Krissinel
- European Bioinformatics Institute, Genome Campus, Hinxton, Cambridge CB10 1SD, England.
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Emsley P, Cowtan K. Coot: model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr 2004; 60:2126-32. [PMID: 15572765 DOI: 10.1107/s0907444904019158] [Citation(s) in RCA: 24371] [Impact Index Per Article: 1218.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 02/26/2004] [Accepted: 08/04/2004] [Indexed: 11/10/2022]
Abstract
CCP4mg is a project that aims to provide a general-purpose tool for structural biologists, providing tools for X-ray structure solution, structure comparison and analysis, and publication-quality graphics. The map-fitting tools are available as a stand-alone package, distributed as 'Coot'.
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Affiliation(s)
- Paul Emsley
- York Structural Biology Laboratory, University of York, Heslington, York YO10 5YW, England.
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Potterton L, McNicholas S, Krissinel E, Gruber J, Cowtan K, Emsley P, Murshudov GN, Cohen S, Perrakis A, Noble M. Developments in the CCP4 molecular-graphics project. Acta Crystallogr D Biol Crystallogr 2004; 60:2288-94. [PMID: 15572783 DOI: 10.1107/s0907444904023716] [Citation(s) in RCA: 492] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2004] [Accepted: 09/22/2004] [Indexed: 11/11/2022]
Abstract
Progress towards structure determination that is both high-throughput and high-value is dependent on the development of integrated and automatic tools for electron-density map interpretation and for the analysis of the resulting atomic models. Advances in map-interpretation algorithms are extending the resolution regime in which fully automatic tools can work reliably, but at present human intervention is required to interpret poor regions of macromolecular electron density, particularly where crystallographic data is only available to modest resolution [for example, I/sigma(I) < 2.0 for minimum resolution 2.5 A]. In such cases, a set of manual and semi-manual model-building molecular-graphics tools is needed. At the same time, converting the knowledge encapsulated in a molecular structure into understanding is dependent upon visualization tools, which must be able to communicate that understanding to others by means of both static and dynamic representations. CCP4 mg is a program designed to meet these needs in a way that is closely integrated with the ongoing development of CCP4 as a program suite suitable for both low- and high-intervention computational structural biology. As well as providing a carefully designed user interface to advanced algorithms of model building and analysis, CCP4 mg is intended to present a graphical toolkit to developers of novel algorithms in these fields.
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Affiliation(s)
- Liz Potterton
- Department of Chemistry, University of York, England.
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Fotinou C, Blackburn P, Emsley P, Isaacs NW. Towards the structure determination of P30: an autotransporter domain. Acta Crystallogr A 2002. [DOI: 10.1107/s0108767302096812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023] Open
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Fotinou C, Emsley P, Black I, Ando H, Ishida H, Kiso M, Sinha KA, Fairweather NF, Isaacs NW. The crystal structure of tetanus toxin Hc fragment complexed with a synthetic GT1b analogue suggests cross-linking between ganglioside receptors and the toxin. J Biol Chem 2001; 276:32274-81. [PMID: 11418600 DOI: 10.1074/jbc.m103285200] [Citation(s) in RCA: 154] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Tetanus toxin, a member of the family of Clostridial neurotoxins, is one of the most potent toxins known. The crystal structure of the complex of the COOH-terminal fragment of the heavy chain with an analogue of its ganglioside receptor, GT1b, provides the first direct identification and characterization of the ganglioside-binding sites. The ganglioside induces cross-linking by binding to two distinct sites on the Hc molecule. The structure sheds new light on the binding of Clostridial neurotoxins to receptors on neuronal cells and provides important information relevant to the design of anti-tetanus and anti-botulism therapeutic agents.
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Affiliation(s)
- C Fotinou
- Department of Chemistry, University of Glasgow, Glasgow, G12 8QQ, Scotland, United Kingdom
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Fotinou C, Shina KA, Ando H, Ishida H, Black I, Emsley P, Kiso M, Fairweather N, Isaacs NW. The first step of tetanus toxin into nerve cell. Acta Crystallogr A 2000. [DOI: 10.1107/s0108767300026039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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45
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Emsley P, Fotinou C, Black I, Fairweather NF, Charles IG, Watts C, Hewitt E, Isaacs NW. The structures of the H(C) fragment of tetanus toxin with carbohydrate subunit complexes provide insight into ganglioside binding. J Biol Chem 2000; 275:8889-94. [PMID: 10722735 DOI: 10.1074/jbc.275.12.8889] [Citation(s) in RCA: 117] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The entry of tetanus neurotoxin into neuronal cells proceeds through the initial binding of the toxin to gangliosides on the cell surface. The carboxyl-terminal fragment of the heavy chain of tetanus neurotoxin contains the ganglioside-binding site, which has not yet been fully characterized. The crystal structures of native H(C) and of H(C) soaked with carbohydrates reveal a number of binding sites and provide insight into the possible mode of ganglioside binding.
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Affiliation(s)
- P Emsley
- Department of Chemistry, University of Glasgow, Glasgow G12 8QQ, United Kingdom
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Fotinou C, Beauchamp J, Emsley P, deHaan A, Schielen WJ, Bos E, Isaacs NW. Structure of an Fab fragment against a C-terminal peptide of hCG at 2.0 A resolution. J Biol Chem 1998; 273:22515-8. [PMID: 9712877 DOI: 10.1074/jbc.273.35.22515] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
3A2 is an antibody raised against human chorionic gonadotropin and recognizes a linear epitope on the C-terminal peptide of the human chorionic gonadotropin beta-subunit. Its three-dimensional structure has been determined to 2-A resolution using molecular replacement and refined to a conventional R-factor of 18.2%. The protein exhibits the typical immunoglobulin fold, and the model contains 944 ordered water molecules and one sulfate ion. A comparison of the complementarity-determining regions of the Fab3A2 with those from the Protein Data Bank following the canonical structure method reveals a canonical main chain conformation. This antibody belongs to the canonical structure class (combination of canonical conformations of the complementarity determining loops) that shows a preference for haptens and not for peptides. However, the shape of the surface of the antigen binding loops resembles that of an anti-peptide antibody.
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Affiliation(s)
- C Fotinou
- Department of Chemistry, University of Glasgow, Glasgow G12 8QQ, United Kingdom
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Watts C, Antoniou A, Manoury B, Hewitt EW, Mckay LM, Grayson L, Fairweather NF, Emsley P, Isaacs N, Simitsek PD. Modulation by epitope-specific antibodies of class II MHC-restricted presentation of the tetanus toxin antigen. Immunol Rev 1998; 164:11-6. [PMID: 9795759 DOI: 10.1111/j.1600-065x.1998.tb01203.x] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Above a certain affinity the dissociation rate of monovalent antigen from antibody becomes slower than the time taken for antigen capture, endocytosis and processing by professional antigen presenting cells. Thus, when high affinity antibodies drive antigen uptake, either directly via B-cell membrane immunoglobulin or indirectly via Fc receptors, the substrate for processing may frequently be an antigen/antibody complex. Here we review studies using the tetanus toxin antigen which show that bound antibodies can dramatically affect proteolytic processing, dependent on the epitope specificity and multiplicity of antibodies bound. Certain antibodies protect or 'footprint' specific domains of the antigen during processing in B-cell clones resulting in modulation of loading of class II MHC-restricted T-cell epitopes. Processing and class II MHC loading of some T-cell epitopes within the footprinted region was hindered, as might be expected, but, surprisingly, presentation of other T-cell epitopes was boosted considerably. These studies show that protein/protein complexes can be processed in an unpredictable fashion by antigen presenting cells and indicate a possible mechanism whereby cryptic T-cell epitopes might be revealed in autoimmune disease.
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Affiliation(s)
- C Watts
- Department of Biochemistry, University of Dundee, UK.
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Fotinou C, Beauchamp J, Emsley P, Black I, DeHaan A, Bos E, Isaacs NW. Crystallization of two hCG-specific monoclonal antibody fragments. Acta Crystallogr D Biol Crystallogr 1998; 54:405-6. [PMID: 9761910 DOI: 10.1107/s0907444997011074] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The Fab fragments of two monoclonal antibodies (Fab3A2, Fab6A) raised against epitopes of human chorionic gonadotrophin (hCG) have been crystallized using the vapour-diffusion technique. The Fab3A2 antibody recognises an epitope on the C-terminal peptide of the beta-subunit and the Fab6A a conformational epitope of hCG. Both Fab crystals grow as hexagonal rods from ammonium sulfate solutions. The Fab3A2 crystals belong to space group P3121 with a = b = 74.84, c = 198.2 A and diffract to 1.33 A at the ESRF. The Fab6A crystals are in the space group P3221 with a = b = 129.53, c = 74.40 A and diffract to 2.7 A at the Daresbury SRS. One Fab molecule per asymmetric unit is present in both crystals.
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Affiliation(s)
- C Fotinou
- Department of Chemistry, University of Glasgow, Glasgow G12 8QQ, Scotland
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Emsley P, Charles I, Fairweather NF, Isaacs NW. P69 pertactin: LRR, PRR and efficacious vaccine. Acta Crystallogr A 1996. [DOI: 10.1107/s0108767396090150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Abstract
A new generation of whooping-cough vaccines contain P.69 pertactin, a surface-exposed domain of an outer membrane protein expressed by the virulent bacterium Bordetella pertussis. This protein is a virulence factor that mediates adhesion to target mammalian cells, a reaction that is in part mediated by an RGD sequence. The X-ray crystal structure of P.69 pertactin has been determined to 2.5 A. The protein fold consists of a 16-stranded parallel beta-helix with a V-shaped cross-section, and is the largest beta-helix known to date. Several between-strand weakly conserved amino-acid repeats form internal and external ladders. The structure appears as a helix from which several loops protrude, which contain sequence motifs associated with the biological activity of the protein. One particular (GGXXP)5 sequence is located directly after the RGD motif, and may mediate interaction with epithelial cells. The carboxy-terminal region of P.69 pertactin incorporates a (PQP)5 motif loop containing the major immunoprotective epitope.
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Affiliation(s)
- P Emsley
- Department of Chemistry, University of Glasgow, UK
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