1
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Usón I, Sheldrick GM. Modes and model building in SHELXE. Acta Crystallogr D Struct Biol 2024; 80:4-15. [PMID: 38088896 PMCID: PMC10833347 DOI: 10.1107/s2059798323010082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 11/21/2023] [Indexed: 01/12/2024] Open
Abstract
Density modification is a standard step to provide a route for routine structure solution by any experimental phasing method, with single-wavelength or multi-wavelength anomalous diffraction being the most popular methods, as well as to extend fragments or incomplete models into a full solution. The effect of density modification on the starting maps from either source is illustrated in the case of SHELXE. The different modes in which the program can run are reviewed; these include less well known uses such as reading external phase values and weights or phase distributions encoded in Hendrickson-Lattman coefficients. Typically in SHELXE, initial phases are calculated from experimental data, from a partial model or map, or from a combination of both sources. The initial phase set is improved and extended by density modification and, if the resolution of the data and the type of structure permits, polyalanine tracing. As a feature to systematically eliminate model bias from phases derived from predicted models, the trace can be set to exclude the area occupied by the starting model. The trace now includes an extension into the gamma position or hydrophobic and aromatic side chains if a sequence is provided, which is performed in every tracing cycle. Once a correlation coefficient of over 30% between the structure factors calculated from such a trace and the native data indicates that the structure has been solved, the sequence is docked in all model-building cycles and side chains are fitted if the map supports it. The extensions to the tracing algorithm brought in to provide a complete model are discussed. The improvement in phasing performance is assessed using a set of tests.
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Affiliation(s)
- Isabel Usón
- ICREA, Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys, 23, Barcelona, E-08003, Spain
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB-CSIC), Barcelona Science Park, Helix Building, Baldiri Reixach, 15, Barcelona, 08028, Spain
| | - George M. Sheldrick
- Department of Structural Chemistry, Georg-August Universität Göttingen, Tammannstrasse 4, 37077 Göttingen, Germany
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2
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Simpkin AJ, Caballero I, McNicholas S, Stevenson K, Jiménez E, Sánchez Rodríguez F, Fando M, Uski V, Ballard C, Chojnowski G, Lebedev A, Krissinel E, Usón I, Rigden DJ, Keegan RM. Predicted models and CCP4. Acta Crystallogr D Struct Biol 2023; 79:806-819. [PMID: 37594303 PMCID: PMC10478639 DOI: 10.1107/s2059798323006289] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 07/19/2023] [Indexed: 08/19/2023] Open
Abstract
In late 2020, the results of CASP14, the 14th event in a series of competitions to assess the latest developments in computational protein structure-prediction methodology, revealed the giant leap forward that had been made by Google's Deepmind in tackling the prediction problem. The level of accuracy in their predictions was the first instance of a competitor achieving a global distance test score of better than 90 across all categories of difficulty. This achievement represents both a challenge and an opportunity for the field of experimental structural biology. For structure determination by macromolecular X-ray crystallography, access to highly accurate structure predictions is of great benefit, particularly when it comes to solving the phase problem. Here, details of new utilities and enhanced applications in the CCP4 suite, designed to allow users to exploit predicted models in determining macromolecular structures from X-ray diffraction data, are presented. The focus is mainly on applications that can be used to solve the phase problem through molecular replacement.
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Affiliation(s)
- Adam J. Simpkin
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Iracema Caballero
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona, Spain
| | - Stuart McNicholas
- York Structural Biology Laboratory, Department of Chemistry, The University of York, York YO10 5DD, United Kingdom
| | - Kyle Stevenson
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Elisabet Jiménez
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona, Spain
| | - Filomeno Sánchez Rodríguez
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
- York Structural Biology Laboratory, Department of Chemistry, The University of York, York YO10 5DD, United Kingdom
| | - Maria Fando
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Ville Uski
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Charles Ballard
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Grzegorz Chojnowski
- European Molecular Biology Laboratory, Hamburg Unit, Notkestrasse 85, 22607 Hamburg, Germany
| | - Andrey Lebedev
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Eugene Krissinel
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Isabel Usón
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona, Spain
- ICREA, Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, 08003 Barcelona, Spain
| | - Daniel J. Rigden
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Ronan M. Keegan
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
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3
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Huang L, Tam KS, Xie W. Structural and Biochemical Studies of the Novel Hexameric Endoribonuclease YicC. ACS Chem Biol 2023; 18:1738-1747. [PMID: 37535940 DOI: 10.1021/acschembio.3c00091] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
The decay of mRNA is an essential process to bacteria. The newly identified E. coli protein YicC is a founding member of the UPF0701 family, and biochemical studies indicated that it is an RNase involved in mRNA degradation. However, its biochemical properties and catalytic mechanism are poorly understood. Here, we report the crystal structure of YicC, which shows an extended shape consisting of modular domains. While the backbone trace of the monomer forms a unique, nearly closed loop, the three monomers present in the asymmetric unit make a "shoulder-by-shoulder" trimer. In vitro RNA cleavage assays indicated that this endoribonuclease mainly recognizes the consensus GUG motif, with a preference for an extended CGUG sequence. Additionally, the active enzyme exists as a hexamer in solution and assumes a funnel shape. Structural analysis indicated that the hexamer interface is mainly formed by the hexamerization domain consisting of D71-D124 and that the disruption of the oligomeric form greatly diminished the enzymatic activity. By studying the surface charge potential and the sequence conservation, we identified a series of residues that play critical functional roles, which helps to reveal the catalytic mechanism of this divalent metal-ion-dependent RNase. Last but not least, we discovered that the catalytic domain of YicC did not share similarity with any known nuclease fold, suggesting that the enzyme adopts a novel fold to perform its catalysis and in vivo functions. In summary, our investigations into YicC provide an in-depth understanding of the functions of the UPF0701 protein family and the DUF1732 domain in general.
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Affiliation(s)
- Lin Huang
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, The Sun Yat-Sen University, Guangzhou, Guangdong 510006, People's Republic of China
| | - King Sing Tam
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, The Sun Yat-Sen University, Guangzhou, Guangdong 510006, People's Republic of China
| | - Wei Xie
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory for Biocontrol, School of Life Sciences, The Sun Yat-Sen University, Guangzhou, Guangdong 510006, People's Republic of China
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4
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Simpkin AJ, Thomas JMH, Keegan RM, Rigden DJ. MrParse: finding homologues in the PDB and the EBI AlphaFold database for molecular replacement and more. ACTA CRYSTALLOGRAPHICA SECTION D STRUCTURAL BIOLOGY 2022; 78:553-559. [PMID: 35503204 PMCID: PMC9063843 DOI: 10.1107/s2059798322003576] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 03/29/2022] [Indexed: 11/10/2022]
Abstract
Crystallographers have an array of search-model options for structure solution by molecular replacement (MR). The well established options of homologous experimental structures and regular secondary-structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may be carried out locally or may use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help to streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any experimental homologues found using eLLG, which indicates the likelihood that a given search model will work in MR. Inbuilt displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians.
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5
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McCoy AJ, Sammito MD, Read RJ. Implications of AlphaFold2 for crystallographic phasing by molecular replacement. Acta Crystallogr D Struct Biol 2022; 78:1-13. [PMID: 34981757 PMCID: PMC8725160 DOI: 10.1107/s2059798321012122] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 11/13/2021] [Indexed: 12/11/2022] Open
Abstract
The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high-coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models.
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Affiliation(s)
- Airlie J. McCoy
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Massimo D. Sammito
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
| | - Randy J. Read
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, United Kingdom
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6
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Kryshtafovych A, Moult J, Albrecht R, Chang GA, Chao K, Fraser A, Greenfield J, Hartmann MD, Herzberg O, Josts I, Leiman PG, Linden SB, Lupas AN, Nelson DC, Rees SD, Shang X, Sokolova ML, Tidow H. Computational models in the service of X-ray and cryo-electron microscopy structure determination. Proteins 2021; 89:1633-1646. [PMID: 34449113 PMCID: PMC8616789 DOI: 10.1002/prot.26223] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 08/11/2021] [Accepted: 08/17/2021] [Indexed: 01/20/2023]
Abstract
Critical assessment of structure prediction (CASP) conducts community experiments to determine the state of the art in computing protein structure from amino acid sequence. The process relies on the experimental community providing information about not yet public or about to be solved structures, for use as targets. For some targets, the experimental structure is not solved in time for use in CASP. Calculated structure accuracy improved dramatically in this round, implying that models should now be much more useful for resolving many sorts of experimental difficulties. To test this, selected models for seven unsolved targets were provided to the experimental groups. These models were from the AlphaFold2 group, who overall submitted the most accurate predictions in CASP14. Four targets were solved with the aid of the models, and, additionally, the structure of an already solved target was improved. An a posteriori analysis showed that, in some cases, models from other groups would also be effective. This paper provides accounts of the successful application of models to structure determination, including molecular replacement for X-ray crystallography, backbone tracing and sequence positioning in a cryo-electron microscopy structure, and correction of local features. The results suggest that, in future, there will be greatly increased synergy between computational and experimental approaches to structure determination.
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Affiliation(s)
| | - John Moult
- Institute for Bioscience and Biotechnology Research, Department of Cell Biology and Molecular genetics, University of Maryland, 9600 Gudelsky Drive, Rockville, MD 20850, USA
| | - Reinhard Albrecht
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany
| | - Geoffrey A. Chang
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA, 92093, USA
- Department of Pharmacology, University of California-San Diego, La Jolla, CA, 92093, USA
| | - Kinlin Chao
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA
| | - Alec Fraser
- Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics (SCSB), The University of Texas Medical Branch at Galveston, TX 77555, USA
| | - Julia Greenfield
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA
| | - Marcus D. Hartmann
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany
| | - Osnat Herzberg
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA
- Department of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742, USA
| | - Inokentijs Josts
- The Hamburg Advanced Research Center for Bioorganic Chemistry (HARBOR) & Department of Chemistry, Institute for Biochemistry and Molecular Biology, University of Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany
| | - Petr G. Leiman
- Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics (SCSB), The University of Texas Medical Branch at Galveston, TX 77555, USA
| | - Sara B. Linden
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA
| | - Andrei N. Lupas
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany
| | - Daniel C. Nelson
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA
- Department of Veterinary Medicine, University of Maryland, College Park, MD 20742, USA
| | - Steven D. Rees
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA, 92093, USA
| | - Xiaoran Shang
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, MD 20850, USA
| | - Maria L. Sokolova
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Henning Tidow
- The Hamburg Advanced Research Center for Bioorganic Chemistry (HARBOR) & Department of Chemistry, Institute for Biochemistry and Molecular Biology, University of Hamburg, Luruper Chaussee 149, 22761 Hamburg, Germany
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7
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Simpkin AJ, Winn MD, Rigden DJ, Keegan RM. Redeployment of automated MrBUMP search-model identification for map fitting in cryo-EM. Acta Crystallogr D Struct Biol 2021; 77:1378-1385. [PMID: 34726166 PMCID: PMC8561737 DOI: 10.1107/s2059798321009165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 09/03/2021] [Indexed: 11/22/2022] Open
Abstract
In crystallography, the phase problem can often be addressed by the careful preparation of molecular-replacement search models. This has led to the development of pipelines such as MrBUMP that can automatically identify homologous proteins from an input sequence and edit them to focus on the areas that are most conserved. Many of these approaches can be applied directly to cryo-EM to help discover, prepare and correctly place models (here called cryo-EM search models) into electrostatic potential maps. This can significantly reduce the amount of manual model building that is required for structure determination. Here, MrBUMP is repurposed to fit automatically obtained PDB-derived chains and domains into cryo-EM maps. MrBUMP was successfully able to identify and place cryo-EM search models across a range of resolutions. Methods such as map segmentation are also explored as potential routes to improved performance. Map segmentation was also found to improve the effectiveness of the pipeline for higher resolution (<8 Å) data sets.
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Affiliation(s)
- Adam J. Simpkin
- Institute of Structural, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Martyn D. Winn
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
| | - Daniel J. Rigden
- Institute of Structural, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Ronan M. Keegan
- UKRI–STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom
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8
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Flower TG, Hurley JH. Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8. Protein Sci 2021; 30:728-734. [PMID: 33625752 PMCID: PMC7980513 DOI: 10.1002/pro.4050] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 02/21/2021] [Accepted: 02/22/2021] [Indexed: 12/01/2022]
Abstract
The majority of crystal structures are determined by the method of molecular replacement (MR). The range of application of MR is limited mainly by the need for an accurate search model. In most cases, pre-existing experimentally determined structures are used as search models. In favorable cases, ab initio predicted structures have yielded search models adequate for MR. The ORF8 protein of SARS-CoV-2 represents a challenging case for MR using an ab initio prediction because ORF8 has an all β-sheet fold and few orthologs. We previously determined experimentally the structure of ORF8 using the single anomalous dispersion (SAD) phasing method, having been unable to find an MR solution to the crystallographic phase problem. Following a report of an accurate prediction of the ORF8 structure, we assessed whether the predicted model would have succeeded as an MR search model. A phase problem solution was found, and the resulting structure was refined, yielding structural parameters equivalent to the original experimental solution.
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Affiliation(s)
- Thomas G. Flower
- Department of Molecular and Cell Biology and California Institute for Quantitative BiosciencesUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - James H. Hurley
- Department of Molecular and Cell Biology and California Institute for Quantitative BiosciencesUniversity of CaliforniaBerkeleyCaliforniaUSA
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9
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Antila HS, M. Ferreira T, Ollila OHS, Miettinen MS. Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics. J Chem Inf Model 2021; 61:938-949. [PMID: 33496579 PMCID: PMC7903423 DOI: 10.1021/acs.jcim.0c01299] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Indexed: 01/08/2023]
Abstract
Molecular dynamics (MD) simulations are widely used to monitor time-resolved motions of biomacromolecules, although it often remains unknown how closely the conformational dynamics correspond to those occurring in real life. Here, we used a large set of open-access MD trajectories of phosphatidylcholine (PC) lipid bilayers to benchmark the conformational dynamics in several contemporary MD models (force fields) against nuclear magnetic resonance (NMR) data available in the literature: effective correlation times and spin-lattice relaxation rates. We found none of the tested MD models to fully reproduce the conformational dynamics. That said, the dynamics in CHARMM36 and Slipids are more realistic than in the Amber Lipid14, OPLS-based MacRog, and GROMOS-based Berger force fields, whose sampling of the glycerol backbone conformations is too slow. The performance of CHARMM36 persists when cholesterol is added to the bilayer, and when the hydration level is reduced. However, for conformational dynamics of the PC headgroup, both with and without cholesterol, Slipids provides the most realistic description because CHARMM36 overestimates the relative weight of ∼1 ns processes in the headgroup dynamics. We stress that not a single new simulation was run for the present work. This demonstrates the worth of open-access MD trajectory databanks for the indispensable step of any serious MD study: benchmarking the available force fields. We believe this proof of principle will inspire other novel applications of MD trajectory databanks and thus aid in developing biomolecular MD simulations into a true computational microscope-not only for lipid membranes but for all biomacromolecular systems.
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Affiliation(s)
- Hanne S. Antila
- Department
of Theory and Bio-Systems, Max Planck Institute
of Colloids and Interfaces, 14424 Potsdam, Germany
| | - Tiago M. Ferreira
- NMR
Group−Institute for Physics, Martin-Luther
University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | | | - Markus S. Miettinen
- Department
of Theory and Bio-Systems, Max Planck Institute
of Colloids and Interfaces, 14424 Potsdam, Germany
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10
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Flower TG, Hurley JH. Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.01.05.425441. [PMID: 33442695 PMCID: PMC7805452 DOI: 10.1101/2021.01.05.425441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The majority of crystal structures are determined by the method of molecular replacement (MR). The range of application of MR is limited mainly by the need for an accurate search model. In most cases, pre-existing experimentally determined structures are used as search models. In favorable cases, ab initio predicted structures have yielded search models adequate for molecular replacement. The ORF8 protein of SARS-CoV-2 represents a challenging case for MR using an ab initio prediction because ORF8 has an all β-sheet fold and few orthologs. We previously determined experimentally the structure of ORF8 using the single anomalous dispersion (SAD) phasing method, having been unable to find an MR solution to the crystallographic phase problem. Following a report of an accurate prediction of the ORF8 structure, we assessed whether the predicted model would have succeeded as an MR search model. A phase problem solution was found, and the resulting structure was refined, yielding structural parameters equivalent to the original experimental solution.
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Affiliation(s)
- Thomas G. Flower
- Department of Molecular and Cell Biology and California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720
| | - James H. Hurley
- Department of Molecular and Cell Biology and California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA 94720
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11
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Abriata LA, Dal Peraro M. State-of-the-art web services for de novo protein structure prediction. Brief Bioinform 2020; 22:5870389. [PMID: 34020540 DOI: 10.1093/bib/bbaa139] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 06/04/2020] [Accepted: 06/05/2020] [Indexed: 02/06/2023] Open
Abstract
Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent in the last round of the Critical Assessment of Structure Prediction (CASP), which presented several very good models for the hardest targets. Unfortunately, literature reporting on these advances often lacks digests tailored to lay end users; moreover, some of the top-ranking predictors do not provide webservers that can be used by nonexperts. How can then end users benefit from these advances and correctly interpret the predicted models? Here we review the web resources that biologists can use today to take advantage of these state-of-the-art methods in their research, including not only the best de novo modeling servers but also datasets of models precomputed by experts for structurally uncharacterized protein families. We highlight their features, advantages and pitfalls for predicting structures of proteins without clear templates. We present a broad number of applications that span from driving forward biochemical investigations that lack experimental structures to actually assisting experimental structure determination in X-ray diffraction, cryo-EM and other forms of integrative modeling. We also discuss issues that must be considered by users yet still require further developments, such as global and residue-wise model quality estimates and sources of residue coevolution other than monomeric tertiary structure.
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Affiliation(s)
- Luciano A Abriata
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Matteo Dal Peraro
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
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12
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Borges RJ, Meindl K, Triviño J, Sammito M, Medina A, Millán C, Alcorlo M, Hermoso JA, Fontes MRDM, Usón I. SEQUENCE SLIDER: expanding polyalanine fragments for phasing with multiple side-chain hypotheses. Acta Crystallogr D Struct Biol 2020; 76:221-237. [PMID: 32133987 PMCID: PMC7057211 DOI: 10.1107/s2059798320000339] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 01/13/2020] [Indexed: 02/07/2023] Open
Abstract
Fragment-based molecular-replacement methods can solve a macromolecular structure quasi-ab initio. ARCIMBOLDO, using a common secondary-structure or tertiary-structure template or a library of folds, locates these with Phaser and reveals the rest of the structure by density modification and autotracing in SHELXE. The latter stage is challenging when dealing with diffraction data at lower resolution, low solvent content, high β-sheet composition or situations in which the initial fragments represent a low fraction of the total scattering or where their accuracy is low. SEQUENCE SLIDER aims to overcome these complications by extending the initial polyalanine fragment with side chains in a multisolution framework. Its use is illustrated on test cases and previously unknown structures. The selection and order of fragments to be extended follows the decrease in log-likelihood gain (LLG) calculated with Phaser upon the omission of each single fragment. When the starting substructure is derived from a remote homolog, sequence assignment to fragments is restricted by the original alignment. Otherwise, the secondary-structure prediction is matched to that found in fragments and traces. Sequence hypotheses are trialled in a brute-force approach through side-chain building and refinement. Scoring the refined models through their LLG in Phaser may allow discrimination of the correct sequence or filter the best partial structures for further density modification and autotracing. The default limits for the number of models to pursue are hardware dependent. In its most economic implementation, suitable for a single laptop, the main-chain trace is extended as polyserine rather than trialling models with different sequence assignments, which requires a grid or multicore machine. SEQUENCE SLIDER has been instrumental in solving two novel structures: that of MltC from 2.7 Å resolution data and that of a pneumococcal lipoprotein with 638 residues and 35% solvent content.
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Affiliation(s)
- Rafael Junqueira Borges
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Baldiri Reixach 15, 08028 Barcelona, Spain
- Departamento de Física e Biofísica, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Botucatu-SP 18618-689, Brazil
| | - Kathrin Meindl
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Baldiri Reixach 15, 08028 Barcelona, Spain
| | - Josep Triviño
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Baldiri Reixach 15, 08028 Barcelona, Spain
| | - Massimo Sammito
- Department of Haematology, Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, England
| | - Ana Medina
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Baldiri Reixach 15, 08028 Barcelona, Spain
| | - Claudia Millán
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Baldiri Reixach 15, 08028 Barcelona, Spain
| | - Martin Alcorlo
- Department of Crystallography and Structural Biology, Instituto de Química-Física ‘Rocasolano’, Consejo Superior de Investigaciones Científicas (CSIC), 28006 Madrid, Spain
| | - Juan A. Hermoso
- Department of Crystallography and Structural Biology, Instituto de Química-Física ‘Rocasolano’, Consejo Superior de Investigaciones Científicas (CSIC), 28006 Madrid, Spain
| | - Marcos Roberto de Mattos Fontes
- Departamento de Física e Biofísica, Instituto de Biociências, Universidade Estadual Paulista (UNESP), Botucatu-SP 18618-689, Brazil
| | - Isabel Usón
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Baldiri Reixach 15, 08028 Barcelona, Spain
- ICREA at IBMB–CSIC, Baldiri Reixach 13-15, 08028 Barcelona, Spain
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Simpkin AJ, Simkovic F, Thomas JMH, Savko M, Lebedev A, Uski V, Ballard CC, Wojdyr M, Shepard W, Rigden DJ, Keegan RM. Using Phaser and ensembles to improve the performance of SIMBAD. ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2020; 76:1-8. [PMID: 31909738 PMCID: PMC6939438 DOI: 10.1107/s2059798319015031] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 11/06/2019] [Indexed: 01/07/2023]
Abstract
The conventional approach to search-model identification in molecular replacement (MR) is to screen a database of known structures using the target sequence. However, this strategy is not always effective, for example when the relationship between sequence and structural similarity fails or when the crystal contents are not those expected. An alternative approach is to identify suitable search models directly from the experimental data. SIMBAD is a sequence-independent MR pipeline that uses either a crystal lattice search or MR functions to directly locate suitable search models from databases. The previous version of SIMBAD used the fast AMoRe rotation-function search. Here, a new version of SIMBAD which makes use of Phaser and its likelihood scoring to improve the sensitivity of the pipeline is presented. It is shown that the additional compute time potentially required by the more sophisticated scoring is counterbalanced by the greater sensitivity, allowing more cases to trigger early-termination criteria, rather than running to completion. Using Phaser solved 17 out of 25 test cases in comparison to the ten solved with AMoRe, and it is shown that use of ensemble search models produces additional performance benefits.
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Affiliation(s)
- Adam J Simpkin
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
| | - Felix Simkovic
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
| | - Jens M H Thomas
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
| | - Martin Savko
- Synchrotron SOLEIL, L'Orme des Merisiers, BP 48, 91192 Saint Aubin, Gif-sur-Yvette, France
| | - Andrey Lebedev
- STFC, Rutherford Appleton Laboratory, Harwell Oxford, Didcot OX11 0FA, England
| | - Ville Uski
- STFC, Rutherford Appleton Laboratory, Harwell Oxford, Didcot OX11 0FA, England
| | - Charles C Ballard
- STFC, Rutherford Appleton Laboratory, Harwell Oxford, Didcot OX11 0FA, England
| | | | - William Shepard
- Synchrotron SOLEIL, L'Orme des Merisiers, BP 48, 91192 Saint Aubin, Gif-sur-Yvette, France
| | - Daniel J Rigden
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
| | - Ronan M Keegan
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
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