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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Carrozzini B, Cascarano GL, Giacovazzo C. The Automatic Solution of Macromolecular Crystal Structures via Molecular Replacement Techniques: REMO22 and Its Pipeline. Int J Mol Sci 2023; 24:ijms24076070. [PMID: 37047043 PMCID: PMC10094557 DOI: 10.3390/ijms24076070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 03/08/2023] [Accepted: 03/14/2023] [Indexed: 04/14/2023] Open
Abstract
A description of REMO22, a new molecular replacement program for proteins and nucleic acids, is provided. This program, as with REMO09, can use various types of prior information through appropriate conditional distribution functions. Its efficacy in model searching has been validated through several test cases involving proteins and nucleic acids. Although REMO22 can be configured with different protocols according to user directives, it has been developed primarily as an automated tool for determining the crystal structures of macromolecules. To evaluate REMO22's utility in the current crystallographic environment, its experimental results must be compared favorably with those of the most widely used Molecular Replacement (MR) programs. To accomplish this, we chose two leading tools in the field, PHASER and MOLREP. REMO22, along with MOLREP and PHASER, were included in pipelines that contain two additional steps: phase refinement (SYNERGY) and automated model building (CAB). To evaluate the effectiveness of REMO22, SYNERGY and CAB, we conducted experimental tests on numerous macromolecular structures. The results indicate that REMO22, along with its pipeline REMO22 + SYNERGY + CAB, presents a viable alternative to currently used phasing tools.
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Affiliation(s)
- Benedetta Carrozzini
- Istituto di Cristallografia, The National Research Council (CNR), Via G. Amendola 122/o, I-70126 Bari, Italy
| | - Giovanni Luca Cascarano
- Istituto di Cristallografia, The National Research Council (CNR), Via G. Amendola 122/o, I-70126 Bari, Italy
| | - Carmelo Giacovazzo
- Istituto di Cristallografia, The National Research Council (CNR), Via G. Amendola 122/o, I-70126 Bari, Italy
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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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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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7
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Pereira J, Simpkin AJ, Hartmann MD, Rigden DJ, Keegan RM, Lupas AN. High-accuracy protein structure prediction in CASP14. Proteins 2021; 89:1687-1699. [PMID: 34218458 DOI: 10.1002/prot.26171] [Citation(s) in RCA: 174] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/16/2021] [Accepted: 06/23/2021] [Indexed: 12/25/2022]
Abstract
The application of state-of-the-art deep-learning approaches to the protein modeling problem has expanded the "high-accuracy" category in CASP14 to encompass all targets. Building on the metrics used for high-accuracy assessment in previous CASPs, we evaluated the performance of all groups that submitted models for at least 10 targets across all difficulty classes, and judged the usefulness of those produced by AlphaFold2 (AF2) as molecular replacement search models with AMPLE. Driven by the qualitative diversity of the targets submitted to CASP, we also introduce DipDiff as a new measure for the improvement in backbone geometry provided by a model versus available templates. Although a large leap in high-accuracy is seen due to AF2, the second-best method in CASP14 out-performed the best in CASP13, illustrating the role of community-based benchmarking in the development and evolution of the protein structure prediction field.
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Affiliation(s)
- Joana Pereira
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Adam J Simpkin
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Marcus D Hartmann
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Daniel J Rigden
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Ronan M Keegan
- Department of Scientific Computing, Science and Technologies Facilities Council, UK Research and Innovation, Didcot, Oxfordshire, UK
| | - Andrei N Lupas
- Department of Protein Evolution, Max Planck Institute for Developmental Biology, Tübingen, Germany
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8
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Dodson E. Introduction to molecular replacement: a time perspective. Acta Crystallogr D Struct Biol 2021; 77:867-879. [PMID: 34196614 PMCID: PMC8251348 DOI: 10.1107/s2059798321004368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 04/23/2021] [Indexed: 11/25/2022] Open
Abstract
This article provides an introduction to the crystal phasing technique known as molecular replacement. The available software is reviewed, and the prospects for future developments are considered. Several examples are described in detail to illustrate potential problems. A brief account of past progress is included. The basic crystallographic equations underlying the procedures are given in an appendix.
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Affiliation(s)
- Eleanor Dodson
- Department of Chemistry, University of York, Heslington, York YO10 5DD, United Kingdom
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9
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Sánchez Rodríguez F, Simpkin AJ, Davies OR, Keegan RM, Rigden DJ. Helical ensembles outperform ideal helices in molecular replacement. ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2020; 76:962-970. [PMID: 33021498 PMCID: PMC7543657 DOI: 10.1107/s205979832001133x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 08/18/2020] [Indexed: 03/21/2023]
Abstract
Helical ensembles solve more structures by MR with AMPLE than do ideal helices and at no greater CPU cost. The conventional approach in molecular replacement is the use of a related structure as a search model. However, this is not always possible as the availability of such structures can be scarce for poorly characterized families of proteins. In these cases, alternative approaches can be explored, such as the use of small ideal fragments that share high, albeit local, structural similarity with the unknown protein. Earlier versions of AMPLE enabled the trialling of a library of ideal helices, which worked well for largely helical proteins at suitable resolutions. Here, the performance of libraries of helical ensembles created by clustering helical segments is explored. The impacts of different B-factor treatments and different degrees of structural heterogeneity are explored. A 30% increase in the number of solutions obtained by AMPLE was observed when using this new set of ensembles compared with the performance with ideal helices. The boost in performance was notable across three different fold classes: transmembrane, globular and coiled-coil structures. Furthermore, the increased effectiveness of these ensembles was coupled to a reduction in the time required by AMPLE to reach a solution. AMPLE users can now take full advantage of this new library of search models by activating the ‘helical ensembles’ mode.
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Affiliation(s)
- Filomeno Sánchez Rodríguez
- Institute of Structural, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Adam J Simpkin
- Institute of Structural, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Owen R Davies
- Institute for Cell and Molecular Biosciences, Newcastle University, Framlington Place, Newcastle upon Tyne NE2 4HH, United Kingdom
| | - Ronan M Keegan
- 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
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10
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Richards LS, Millán C, Miao J, Martynowycz MW, Sawaya MR, Gonen T, Borges RJ, Usón I, Rodriguez JA. Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER. Acta Crystallogr D Struct Biol 2020; 76:703-712. [PMID: 32744252 PMCID: PMC7397493 DOI: 10.1107/s2059798320008049] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 06/16/2020] [Indexed: 12/15/2022] Open
Abstract
Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO, a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Å resolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE. The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.
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Affiliation(s)
- Logan S. Richards
- Department of Chemistry and Biochemistry; UCLA–DOE Institute for Genomics and Proteomics; STROBE, NSF Science and Technology Center, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Claudia Millán
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - Jennifer Miao
- Department of Chemistry and Biochemistry; UCLA–DOE Institute for Genomics and Proteomics; STROBE, NSF Science and Technology Center, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Michael W. Martynowycz
- Howard Hughes Medical Institute, University of California Los Angeles (UCLA), Los Angeles, California, USA
- Department of Biological Chemistry, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Michael R. Sawaya
- Howard Hughes Medical Institute, University of California Los Angeles (UCLA), Los Angeles, California, USA
- Department of Biological Chemistry, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
| | - Tamir Gonen
- Howard Hughes Medical Institute, University of California Los Angeles (UCLA), Los Angeles, California, USA
- Department of Biological Chemistry, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
- Department of Physiology, University of California Los Angeles (UCLA), Los Angeles, California, USA
| | - Rafael J. Borges
- Crystallographic Methods, Institute of Molecular Biology of Barcelona (IBMB–CSIC), Barcelona Science Park, Helix Building, Baldiri Reixac 15, 08028 Barcelona, Spain
| | - 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
| | - Jose A. Rodriguez
- Department of Chemistry and Biochemistry; UCLA–DOE Institute for Genomics and Proteomics; STROBE, NSF Science and Technology Center, University of California Los Angeles (UCLA), Los Angeles, CA 90095, USA
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11
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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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12
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Burla MC, Carrozzini B, Cascarano GL, Giacovazzo C, Polidori G. How far are we from automatic crystal structure solution via molecular-replacement techniques? ACTA CRYSTALLOGRAPHICA SECTION D-STRUCTURAL BIOLOGY 2020; 76:9-18. [PMID: 31909739 PMCID: PMC6939436 DOI: 10.1107/s2059798319015468] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 11/15/2019] [Indexed: 11/10/2022]
Abstract
Although the success of molecular-replacement techniques requires the solution of a six-dimensional problem, this is often subdivided into two three-dimensional problems. REMO09 is one of the programs which have adopted this approach. It has been revisited in the light of a new probabilistic approach which is able to directly derive conditional distribution functions without passing through a previous calculation of the joint probability distributions. The conditional distributions take into account various types of prior information: in the rotation step the prior information may concern a non-oriented model molecule alone or together with one or more located model molecules. The formulae thus obtained are used to derive figures of merit for recognizing the correct orientation in the rotation step and the correct location in the translation step. The phases obtained by this new version of REMO09 are used as a starting point for a pipeline which in its first step extends and refines the molecular-replacement phases, and in its second step creates the final electron-density map which is automatically interpreted by CAB, an automatic model-building program for proteins and DNA/RNA structures.
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Affiliation(s)
- Maria Cristina Burla
- Dipartimento di Fisica e Geologia, Università di Perugia, Piazza Università, I-06123 Perugia, Italy
| | | | | | - Carmelo Giacovazzo
- Istituto di Cristallografia, CNR, Via Amendola 122/O, I-70126 Bari, Italy
| | - Giampiero Polidori
- Istituto di Cristallografia, CNR, Via Amendola 122/O, I-70126 Bari, Italy
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Simpkin AJ, Thomas JMH, Simkovic F, Keegan RM, Rigden DJ. Molecular replacement using structure predictions from databases. Acta Crystallogr D Struct Biol 2019; 75:1051-1062. [PMID: 31793899 PMCID: PMC6889911 DOI: 10.1107/s2059798319013962] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 10/12/2019] [Indexed: 01/19/2023] Open
Abstract
Molecular replacement (MR) is the predominant route to solution of the phase problem in macromolecular crystallography. Where the lack of a suitable homologue precludes conventional MR, one option is to predict the target structure using bioinformatics. Such modelling, in the absence of homologous templates, is called ab initio or de novo modelling. Recently, the accuracy of such models has improved significantly as a result of the availability, in many cases, of residue-contact predictions derived from evolutionary covariance analysis. Covariance-assisted ab initio models representing structurally uncharacterized Pfam families are now available on a large scale in databases, potentially representing a valuable and easily accessible supplement to the PDB as a source of search models. Here, the unconventional MR pipeline AMPLE is employed to explore the value of structure predictions in the GREMLIN and PconsFam databases. It was tested whether these deposited predictions, processed in various ways, could solve the structures of PDB entries that were subsequently deposited. The results were encouraging: nine of 27 GREMLIN cases were solved, covering target lengths of 109-355 residues and a resolution range of 1.4-2.9 Å, and with target-model shared sequence identity as low as 20%. The cluster-and-truncate approach in AMPLE proved to be essential for most successes. For the overall lower quality structure predictions in the PconsFam database, remodelling with Rosetta within the AMPLE pipeline proved to be the best approach, generating ensemble search models from single-structure deposits. Finally, it is shown that the AMPLE-obtained search models deriving from GREMLIN deposits are of sufficiently high quality to be selected by the sequence-independent MR pipeline SIMBAD. Overall, the results help to point the way towards the optimal use of the expanding databases of ab initio structure predictions.
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Affiliation(s)
- Adam J. Simpkin
- 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
| | - Felix Simkovic
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
| | - Ronan M. Keegan
- STFC, Rutherford Appleton Laboratory, Research Complex at Harwell, Didcot OX11 0FA, England
| | - Daniel J. Rigden
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, England
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