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Daren
Fearon
,
Ailsa
Powell
,
Alice
Douangamath
,
Alexandre
Dias
,
Charles W. E.
Tomlinson
,
Blake H.
Balcomb
,
Jasmin C.
Aschenbrenner
,
Anthony
Aimon
,
Isabel A.
Barker
,
Jose
Brandao-Neto
,
Patrick
Collins
,
Louise E.
Dunnett
,
Michael
Fairhead
,
Richard J.
Gildea
,
Mathew
Golding
,
Tyler
Gorrie-Stone
,
Paul V.
Hathaway
,
Lizbe
Koekemoer
,
Tobias
Krojer
,
Ryan
Lithgo
,
Elizabeth M.
Maclean
,
Peter G.
Marples
,
Xiaomin
Ni
,
Rachael
Skyner
,
Romain
Talon
,
Warren
Thompson
,
Conor F.
Wild
,
Max
Winokan
,
Nathan D.
Wright
,
Graeme
Winter
,
Elizabeth J.
Shotton
,
Frank
Von Delft
Open Access
Abstract: Fragment-based drug discovery is a well-established method for the identification of chemical starting points for development into clinical candidates. Historically, crystallographic fragment screening was perceived to be low-throughput and time consuming. However, thanks to advances in synchrotron capabilities and the introduction of dedicated facilities, such as the XChem platform at Diamond Light Source, there have been substantial improvements in throughput and integration between sample preparation, data collection and hit identification. Herein we share our experiences of establishing a crystallographic fragment screening facility, our learnings from operating a user programme for ten years and our perspective on applying structural enablement to rapidly progress initial fragment hits to lead-like molecules.
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Nov 2024
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I23-Long wavelength MX
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Yishun
Lu
,
Ramona
Duman
,
James
Beilsten-Edmands
,
Graeme
Winter
,
Mark
Basham
,
Gwyndaf
Evans
,
Jos J. A. G.
Kamps
,
Allen M.
Orville
,
Hok-Sau
Kwong
,
Konstantinos
Beis
,
Wesley
Armour
,
Armin
Wagner
Open Access
Abstract: rocessing of single-crystal X-ray diffraction data from area detectors can be separated into two steps. First, raw intensities are obtained by integration of the diffraction images, and then data correction and reduction are performed to determine structure-factor amplitudes and their uncertainties. The second step considers the diffraction geometry, sample illumination, decay, absorption and other effects. While absorption is only a minor effect in standard macromolecular crystallography (MX), it can become the largest source of uncertainty for experiments performed at long wavelengths. Current software packages for MX typically employ empirical models to correct for the effects of absorption, with the corrections determined through the procedure of minimizing the differences in intensities between symmetry-equivalent reflections; these models are well suited to capturing smoothly varying experimental effects. However, for very long wavelengths, empirical methods become an unreliable approach to model strong absorption effects with high fidelity. This problem is particularly acute when data multiplicity is low. This paper presents an analytical absorption correction strategy (implemented in new software AnACor) based on a volumetric model of the sample derived from X-ray tomography. Individual path lengths through the different sample materials for all reflections are determined by a ray-tracing method. Several approaches for absorption corrections (spherical harmonics correction, analytical absorption correction and a combination of the two) are compared for two samples, the membrane protein OmpK36 GD, measured at a wavelength of λ = 3.54 Å, and chlorite dismutase, measured at λ = 4.13 Å. Data set statistics, the peak heights in the anomalous difference Fourier maps and the success of experimental phasing are used to compare the results from the different absorption correction approaches. The strategies using the new analytical absorption correction are shown to be superior to the standard spherical harmonics corrections. While the improvements are modest in the 3.54 Å data, the analytical absorption correction outperforms spherical harmonics in the longer-wavelength data (λ = 4.13 Å), which is also reflected in the reduced amount of data being required for successful experimental phasing.
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Jun 2024
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I03-Macromolecular Crystallography
I23-Long wavelength MX
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Kamel
El Omari
,
Ramona
Duman
,
Vitaliy
Mykhaylyk
,
Christian M.
Orr
,
Merlyn
Latimer-Smith
,
Graeme
Winter
,
Vinay
Grama
,
Feng
Qu
,
Kiran
Bountra
,
Hok Sau
Kwong
,
Maria
Romano
,
Rosana
Reis
,
Lutz
Vogeley
,
Luca
Vecchia
,
C. David
Owen
,
Sina
Wittmann
,
Max
Renner
,
Miki
Senda
,
Naohiro
Matsugaki
,
Yoshiaki
Kawano
,
Thomas A.
Bowden
,
Isabel
Moraes
,
Jonathan M.
Grimes
,
Erika J.
Mancini
,
Martin A.
Walsh
,
Cristiane R.
Guzzo
,
Raymond J.
Owens
,
E. Yvonne
Jones
,
David G.
Brown
,
Dave I.
Stuart
,
Konstantinos
Beis
,
Armin
Wagner
Open Access
Abstract: Despite recent advances in cryo-electron microscopy and artificial intelligence-based model predictions, a significant fraction of structure determinations by macromolecular crystallography still requires experimental phasing, usually by means of single-wavelength anomalous diffraction (SAD) techniques. Most synchrotron beamlines provide highly brilliant beams of X-rays of between 0.7 and 2 Å wavelength. Use of longer wavelengths to access the absorption edges of biologically important lighter atoms such as calcium, potassium, chlorine, sulfur and phosphorus for native-SAD phasing is attractive but technically highly challenging. The long-wavelength beamline I23 at Diamond Light Source overcomes these limitations and extends the accessible wavelength range to λ = 5.9 Å. Here we report 22 macromolecular structures solved in this extended wavelength range, using anomalous scattering from a range of elements which demonstrate the routine feasibility of lighter atom phasing. We suggest that, in light of its advantages, long-wavelength crystallography is a compelling option for experimental phasing.
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Oct 2023
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Krios I-Titan Krios I at Diamond
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Open Access
Abstract: Electron diffraction from three dimensional crystals, as a technique for solving molecular structures, is rapidly increasing in popularity. The development of methodology and software has borrowed, to great effect, from macromolecular X-ray crystallography. However, standardization lags behind the development of the technique, and practitioners are forced to work with inadequate data formats that are unable to capture a full description of their experiments. This creates obstacles that are increasingly difficult to overcome as experiments become ever faster and the need for data autoprocessing becomes more pressing. We present a data format standard based on best practice from macromolecular crystallography and demonstrate how the adoption of this standard enabled autoprocessing of datasets collected with a high-throughput detector system.
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Aug 2023
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Jon
Agirre
,
Mihaela
Atanasova
,
Haroldas
Bagdonas
,
Charles B.
Ballard
,
Arnaud
Basle
,
James
Beilsten-Edmands
,
Rafael J.
Borges
,
David G.
Brown
,
J. Javier
Burgos-Marmol
,
John M.
Berrisford
,
Paul S.
Bond
,
Iracema
Caballero
,
Lucrezia
Catapano
,
Grzegorz
Chojnowski
,
Atlanta G.
Cook
,
Kevin D.
Cowtan
,
Tristan I.
Croll
,
Judit É.
Debreczeni
,
Nicholas E.
Devenish
,
Eleanor J.
Dodson
,
Tarik R.
Drevon
,
Paul
Emsley
,
Gwyndaf
Evans
,
Phil R.
Evans
,
Maria
Fando
,
James
Foadi
,
Luis
Fuentes-Montero
,
Elspeth F.
Garman
,
Markus
Gerstel
,
Richard J.
Gildea
,
Kaushik
Hatti
,
Maarten L.
Hekkelman
,
Philipp
Heuser
,
Soon Wen
Hoh
,
Michael A.
Hough
,
Huw T.
Jenkins
,
Elisabet
Jiménez
,
Robbie P.
Joosten
,
Ronan M.
Keegan
,
Nicholas
Keep
,
Eugene B.
Krissinel
,
Petr
Kolenko
,
Oleg
Kovalevskiy
,
Victor S.
Lamzin
,
David M.
Lawson
,
Andrey
Lebedev
,
Andrew G. W.
Leslie
,
Bernhard
Lohkamp
,
Fei
Long
,
Martin
Maly
,
Airlie
Mccoy
,
Stuart J.
Mcnicholas
,
Ana
Medina
,
Claudia
Millán
,
James W.
Murray
,
Garib N.
Murshudov
,
Robert A.
Nicholls
,
Martin E. M.
Noble
,
Robert
Oeffner
,
Navraj S.
Pannu
,
James M.
Parkhurst
,
Nicholas
Pearce
,
Joana
Pereira
,
Anastassis
Perrakis
,
Harold R.
Powell
,
Randy J.
Read
,
Daniel J.
Rigden
,
William
Rochira
,
Massimo
Sammito
,
Filomeno
Sanchez Rodriguez
,
George M.
Sheldrick
,
Kathryn L.
Shelley
,
Felix
Simkovic
,
Adam J.
Simpkin
,
Pavol
Skubak
,
Egor
Sobolev
,
Roberto A.
Steiner
,
Kyle
Stevenson
,
Ivo
Tews
,
Jens M. H.
Thomas
,
Andrea
Thorn
,
Josep Triviño
Valls
,
Ville
Uski
,
Isabel
Uson
,
Alexei
Vagin
,
Sameer
Velankar
,
Melanie
Vollmar
,
Helen
Walden
,
David
Waterman
,
Keith S.
Wilson
,
Martyn
Winn
,
Graeme
Winter
,
Marcin
Wojdyr
,
Keitaro
Yamashita
Open Access
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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Jun 2023
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I24-Microfocus Macromolecular Crystallography
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Richard J.
Gildea
,
James
Beilsten-Edmands
,
Danny
Axford
,
Sam
Horrell
,
Pierre
Aller
,
James
Sandy
,
Juan
Sanchez-Weatherby
,
C. David
Owen
,
Petra
Lukacik
,
Claire
Strain-Damerell
,
Robin L.
Owen
,
Martin A.
Walsh
,
Graeme
Winter
Diamond Proposal Number(s):
[26986, 27088]
Open Access
Abstract: In macromolecular crystallography, radiation damage limits the amount of data that can be collected from a single crystal. It is often necessary to merge data sets from multiple crystals; for example, small-wedge data collections from micro-crystals, in situ room-temperature data collections and data collection from membrane proteins in lipidic mesophases. Whilst the indexing and integration of individual data sets may be relatively straightforward with existing software, merging multiple data sets from small wedges presents new challenges. The identification of a consensus symmetry can be problematic, particularly in the presence of a potential indexing ambiguity. Furthermore, the presence of non-isomorphous or poor-quality data sets may reduce the overall quality of the final merged data set. To facilitate and help to optimize the scaling and merging of multiple data sets, a new program, xia2.multiplex, has been developed which takes data sets individually integrated with DIALS and performs symmetry analysis, scaling and merging of multi-crystal data sets. xia2.multiplex also performs analysis of various pathologies that typically affect multi-crystal data sets, including non-isomorphism, radiation damage and preferential orientation. After the description of a number of use cases, the benefit of xia2.multiplex is demonstrated within a wider autoprocessing framework in facilitating a multi-crystal experiment collected as part of in situ room-temperature fragment-screening experiments on the SARS-CoV-2 main protease.
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Jun 2022
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Open Access
Abstract: The DIALS software for the processing of X-ray diffraction data is presented, with an emphasis on how the suite may be used as a toolkit for data processing. The description starts with an overview of the history and intent of the toolkit, usage as an automated system, command-line use, and ultimately how new tools can be written using the API to perform bespoke analysis. Consideration is also made to the application of DIALS to techniques outside of macromolecular X-ray crystallography.
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Nov 2021
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Herbert J.
Bernstein
,
Andreas
Forster
,
Asmit
Bhowmick
,
Aaron S.
Brewster
,
Sandor
Brockhauser
,
Luca
Gelisio
,
David R.
Hall
,
Filip
Leonarski
,
Valerio
Mariani
,
Gianluca
Santoni
,
Clemens
Vonrhein
,
Graeme
Winter
Open Access
Abstract: Macromolecular crystallography (MX) is the dominant means of determining the three-dimensional structures of biological macromolecules. Over the last few decades, most MX data have been collected at synchrotron beamlines using a large number of different detectors produced by various manufacturers and taking advantage of various protocols and goniometries. These data came in their own formats: sometimes proprietary, sometimes open. The associated metadata rarely reached the degree of completeness required for data management according to Findability, Accessibility, Interoperability and Reusability (FAIR) principles. Efforts to reuse old data by other investigators or even by the original investigators some time later were often frustrated. In the culmination of an effort dating back more than two decades, a large portion of the research community concerned with high data-rate macromolecular crystallography (HDRMX) has now agreed to an updated specification of data and metadata for diffraction images produced at synchrotron light sources and X-ray free-electron lasers (XFELs). This `Gold Standard' will facilitate the processing of data sets independent of the facility at which they were collected and enable data archiving according to FAIR principles, with a particular focus on interoperability and reusability. This agreed standard builds on the NeXus/HDF5 NXmx application definition and the International Union of Crystallography (IUCr) imgCIF/CBF dictionary, and it is compatible with major data-processing programs and pipelines. Just as with the IUCr CBF/imgCIF standard from which it arose and to which it is tied, the NeXus/HDF5 NXmx Gold Standard application definition is intended to be applicable to all detectors used for crystallography, and all hardware and software developers in the field are encouraged to adopt and contribute to the standard.
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Sep 2020
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Open Access
Abstract: In processing X-ray diffraction data, the intensities obtained from integration of the diffraction images must be corrected for experimental effects in order to place all intensities on a common scale both within and between data collections. Scaling corrects for effects such as changes in sample illumination, absorption and, to some extent, global radiation damage that cause the measured intensities of symmetry-equivalent observations to differ throughout a data set. This necessarily requires a prior evaluation of the point-group symmetry of the crystal. This paper describes and evaluates the scaling algorithms implemented within the DIALS data-processing package and demonstrates the effectiveness and key features of the implementation on example macromolecular crystallographic rotation data. In particular, the scaling algorithms enable new workflows for the scaling of multi-crystal or multi-sweep data sets, providing the analysis required to support current trends towards collecting data from ever-smaller samples. In addition, the implementation of a free-set validation method is discussed, which allows the quantification of the suitability of scaling-model and algorithm choices.
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Apr 2020
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Data acquisition
Detectors
|
Open Access
Abstract: The Diamond Light Source data analysis infrastructure, Zocalo, is built on a messaging framework. Analysis tasks are processed by a scalable pool of workers running on cluster nodes. Results can be written to a common file system, sent to another worker for further downstream processing and/or streamed to a LIMS. Zocalo allows increased parallelization of computationally expensive tasks and makes the use of computational resources more efficient. The infrastructure is low-latency, fault-tolerant, and allows for highly dynamic data processing. Moving away from static workflows expressed in shell scripts we can easily re-trigger processing tasks in the event that an issue is found. It allows users to re-run tasks with additional input and ensures that automatically and manually triggered processing results are treated equally. Zocalo was originally conceived to cope with the additional demand on infrastructure by the introduction of Eiger detectors with up to 18 Mpixels and running at up to 560 Hz framerate on single crystal diffraction beamlines. We are now adapting Zocalo to manage processing tasks for ptychography, tomography, cryo-EM, and serial crystallography workloads.
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Oct 2019
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