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  1. Article ; Online: Welcoming five new Co-editors.

    Bond, Charles S / Garman, Elspeth F / Read, Randy J

    Acta crystallographica. Section D, Structural biology

    2024  Volume 80, Issue Pt 3, Page(s) 147

    Abstract: Five new Co-editors are appointed to the Editorial Board of Acta Cryst. D - Structural Biology. ...

    Abstract Five new Co-editors are appointed to the Editorial Board of Acta Cryst. D - Structural Biology.
    Language English
    Publishing date 2024-02-29
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798324002006
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Michael James (1940-2023).

    Glover, J N Mark / Kay, Cyril M / Lemieux, Joanne / Read, Randy J

    Acta crystallographica. Section D, Structural biology

    2023  Volume 79, Issue Pt 10, Page(s) 953–955

    Abstract: Michael James is remembered. ...

    Abstract Michael James is remembered.
    Language English
    Publishing date 2023-09-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798323006976
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Adaptive Cartesian and torsional restraints for interactive model rebuilding.

    Croll, Tristan Ian / Read, Randy J

    Acta crystallographica. Section D, Structural biology

    2021  Volume 77, Issue Pt 4, Page(s) 438–446

    Abstract: When building atomic models into weak and/or low-resolution density, a common strategy is to restrain their conformation to that of a higher resolution model of the same or similar sequence. When doing so, it is important to avoid over-restraining to the ...

    Abstract When building atomic models into weak and/or low-resolution density, a common strategy is to restrain their conformation to that of a higher resolution model of the same or similar sequence. When doing so, it is important to avoid over-restraining to the reference model in the face of disagreement with the experimental data. The most common strategy for this is the use of `top-out' potentials. These act like simple harmonic restraints within a defined range, but gradually weaken when the deviation between the model and reference grows beyond that range. In each current implementation the rate at which the potential flattens at large deviations follows a fixed form, although the form chosen varies among implementations. A restraint potential with a tuneable rate of flattening would provide greater flexibility to encode the confidence in any given restraint. Here, two new such potentials are described: a Cartesian distance restraint derived from a recent generalization of common loss functions and a periodic torsion restraint based on a renormalization of the von Mises distribution. Further, their implementation as user-adjustable/switchable restraints in ISOLDE is described and their use in some real-world examples is demonstrated.
    MeSH term(s) Computer Simulation ; Models, Molecular ; Molecular Conformation ; Nucleic Acids/chemistry ; Proteins/chemistry
    Chemical Substances Nucleic Acids ; Proteins
    Language English
    Publishing date 2021-03-30
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798321001145
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Three new Co-editors appointed to Acta Crystallographica Section D, Structural Biology.

    Read, Randy J / Garman, Elspeth F

    Acta crystallographica. Section D, Structural biology

    2020  Volume 76, Issue Pt 7, Page(s) 612

    Keywords covid19
    Language English
    Publishing date 2020-07-02
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798320008815
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: AlphaFold and the future of structural biology.

    Read, Randy J / Baker, Edward N / Bond, Charles S / Garman, Elspeth F / van Raaij, Mark J

    IUCrJ

    2023  Volume 10, Issue Pt 4, Page(s) 377–379

    Abstract: This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology. ...

    Abstract This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.
    MeSH term(s) Cryoelectron Microscopy ; Crystallography, X-Ray ; Machine Learning ; Biology
    Language English
    Publishing date 2023-07-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 2754953-7
    ISSN 2052-2525 ; 2052-2525
    ISSN (online) 2052-2525
    ISSN 2052-2525
    DOI 10.1107/S2052252523004943
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: AlphaFold and the future of structural biology.

    Read, Randy J / Baker, Edward N / Bond, Charles S / Garman, Elspeth F / van Raaij, Mark J

    Acta crystallographica. Section F, Structural biology communications

    2023  Volume 79, Issue Pt 7, Page(s) 166–168

    Abstract: This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology. ...

    Abstract This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.
    MeSH term(s) Cryoelectron Microscopy ; Crystallography, X-Ray ; Biology ; Protein Conformation
    Language English
    Publishing date 2023-06-26
    Publishing country United States
    Document type Journal Article
    ISSN 2053-230X
    ISSN (online) 2053-230X
    DOI 10.1107/S2053230X23004934
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: AlphaFold and the future of structural biology.

    Read, Randy J / Baker, Edward N / Bond, Charles S / Garman, Elspeth F / van Raaij, Mark J

    Acta crystallographica. Section D, Structural biology

    2023  Volume 79, Issue Pt 7, Page(s) 556–558

    Abstract: This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology. ...

    Abstract This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.
    MeSH term(s) Cryoelectron Microscopy ; Crystallography, X-Ray ; Machine Learning ; Biology ; Protein Conformation
    Language English
    Publishing date 2023-07-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798323004928
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Likelihood-based signal and noise analysis for docking of models into cryo-EM maps.

    Read, Randy J / Millán, Claudia / McCoy, Airlie J / Terwilliger, Thomas C

    Acta crystallographica. Section D, Structural biology

    2023  Volume 79, Issue Pt 4, Page(s) 271–280

    Abstract: Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in ...

    Abstract Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in both crystallography and cryo-EM. Indeed, previous crystallographic work on the errors in structural models is directly applicable to likelihood targets in cryo-EM. Likelihood targets in Fourier space are derived here to characterize, based on the comparison of half-maps, the direction- and resolution-dependent variation in the strength of both signal and noise in the data. Because the signal depends on local features, the signal and noise are analysed in local regions of the cryo-EM reconstruction. The likelihood analysis extends to prediction of the signal that will be achieved in any docking calculation for a model of specified quality and completeness. A related calculation generalizes a previous measure of the information gained by making the cryo-EM reconstruction.
    MeSH term(s) Cryoelectron Microscopy ; Likelihood Functions ; Models, Molecular ; Crystallography
    Language English
    Publishing date 2023-03-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798323001596
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Likelihood-based docking of models into cryo-EM maps.

    Millán, Claudia / McCoy, Airlie J / Terwilliger, Thomas C / Read, Randy J

    Acta crystallographica. Section D, Structural biology

    2023  Volume 79, Issue Pt 4, Page(s) 281–289

    Abstract: Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can ...

    Abstract Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can be employed to establish plausible orientations in a docking search. A phased likelihood translation function yields scores for the placement and rigid-body refinement of oriented models. Optimized strategies for choices of the resolution of data from the cryo-EM maps to use in the calculations and the size of search volumes are based on expected log-likelihood-gain scores computed in advance of the search calculation. Tests demonstrate that the new procedure is fast, robust and effective at placing models into even challenging cryo-EM maps.
    MeSH term(s) Proteins/chemistry ; Likelihood Functions ; Models, Molecular ; Cryoelectron Microscopy/methods ; Crystallography, X-Ray ; Protein Conformation
    Chemical Substances Proteins
    Language English
    Publishing date 2023-03-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798323001602
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Implications of AlphaFold2 for crystallographic phasing by molecular replacement.

    McCoy, Airlie J / Sammito, Massimo D / Read, Randy J

    Acta crystallographica. Section D, Structural biology

    2022  Volume 78, Issue Pt 1, Page(s) 1–13

    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 ... ...

    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.
    MeSH term(s) Animals ; Computational Biology/methods ; Computer Simulation ; Crystallography, X-Ray/methods ; Deep Learning ; Humans ; Models, Molecular ; Molecular Structure ; Protein Conformation ; Software
    Language English
    Publishing date 2022-01-01
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2968623-4
    ISSN 2059-7983 ; 0907-4449
    ISSN (online) 2059-7983
    ISSN 0907-4449
    DOI 10.1107/S2059798321012122
    Database MEDical Literature Analysis and Retrieval System OnLINE

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