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We report the use of streaming data interfaces to perform fully online data processing for serial crystallography experiments, without storing intermediate data on disk. The system produces Bragg reflection intensity measurements suitable for scaling and merging, with a latency of less than 1 s per frame. Our system uses the CrystFEL software in combination with the ASAP::O data framework. In a series of user experiments at PETRA III, frames from a 16 megapixel Dectris EIGER2 X detector were searched for peaks, indexed and integrated at the maximum full-frame readout speed of 133 frames per second. The computational resources required depend on various factors, most significantly the fraction of non-blank frames (`hits'). The average single-thread processing time per frame was 242 ms for blank frames and 455 ms for hits, meaning that a single 96-core computing node was sufficient to keep up with the data, with ample headroom for unexpected throughput reductions. Further significant improvements are expected, for example by binning pixel intensities together to reduce the pixel count. We discuss the implications of real-time data processing on the `data deluge' problem from recent and future photon-science experiments, in particular on calibration requirements, computing access patterns and the need for the preservation of raw data.

VMXm joins the suite of operational macromolecular crystallography beamlines at Diamond Light Source. It has been designed to optimize rotation data collections from protein crystals less than 10 µm and down to below 1 µm in size. The beamline has a fully focused beam of 0.3 × 2.3 µm (vertical × horizontal) with a tuneable energy range (6–28 keV) and high flux (1.6 × 1012 photons s−1 at 12.5 keV). The crystals are housed within a vacuum chamber to minimize background scatter from air. Crystals are plunge-cooled on cryo-electron microscopy grids, allowing much of the liquid surrounding the crystals to be removed. These factors improve the signal-to-noise during data collection and the lifetime of the microcrystals can be prolonged by exploiting photoelectron escape. A novel in vacuo sample environment has been designed which also houses a scanning electron microscope to aid with sample visualization. This combination of features at VMXm allows measurements at the physical limits of X-ray crystallography on biomacromolecules to be explored and exploited.

Metals are essential components for the structure and function of many proteins. However, accurate modelling of their coordination environments remains a challenge due to the complexity and diversity of metal‐coordination geometries. To address this, a method is presented for extracting and analysing coordination information, including bond lengths and angles, from the Crystallography Open Database. By using these data, comprehensive descriptions of metal‐containing components are generated. A stereochemical information generator for a particular component within a specific macromolecule leverages an example PDB/mmCIF file containing the component to account for the actual surrounding environment. A matching process has been developed and implemented to align the derived metal structures with idealized coordinates from a coordination geometry library. Additionally, various strategies, depending on the quality of the matches, were employed to compile distance and angle statistics for the refinement of macromolecular structures. The developed methods were implemented in a new program, MetalCoord, that classifies and utilizes the metal‐coordination geometry. The effectiveness of the developed algorithms was tested using metal‐containing components from the PDB. As a result, metal‐containing components from the CCP4 monomer library have been updated. The updated monomer dictionaries, in concert with the derived restraints, can be used in most structural biology computations, including macromolecular crystallography, single‐particle cryo‐EM and even molecular mechanics. [ABSTRACT FROM AUTHOR]

In macromolecular crystallography (MX), a complete diffraction dataset is essential for determining the three-dimensional structure. However, collecting a complete experimental dataset using a single crystal is frequently unsuccessful due to poor crystal quality or radiation damage, resulting in the collection of multiple incomplete datasets. This issue can be solved by merging incomplete diffraction datasets to generate a complete dataset. This study introduced a new approach for merging incomplete datasets from MX to generate a complete dataset using serial crystallography (SX). Six incomplete diffraction datasets of β-glucosidase from Thermoanaerobacterium saccharolyticum (TsaBgl) were processed using CrystFEL, an SX program. The statistics of the merged data, such as completeness, CC, CC*, Rsplit, Rwork, and Rfree, demonstrated a complete dataset, indicating improved quality compared with the incomplete datasets and enabling structural determination. Also, the merging of the incomplete datasets was processed using four different indexing algorithms, and their statistics were compared. In conclusion, this approach for generating a complete dataset using SX will provide a new opportunity for determining the crystal structure of macromolecules using multiple incomplete MX datasets. [ABSTRACT FROM AUTHOR]

VMXm joins the suite of operational macromolecular crystallography beamlines at Diamond Light Source. It has been designed to optimize rotation data collections from protein crystals less than 10 µm and down to below 1 µm in size. The beamline has a fully focused beam of 0.3 × 2.3 µm (vertical × horizontal) with a tuneable energy range (6–28 keV) and high flux (1.6 × 1012 photons s−1 at 12.5 keV). The crystals are housed within a vacuum chamber to minimize background scatter from air. Crystals are plunge‐cooled on cryo‐electron microscopy grids, allowing much of the liquid surrounding the crystals to be removed. These factors improve the signal‐to‐noise during data collection and the lifetime of the microcrystals can be prolonged by exploiting photoelectron escape. A novel in vacuo sample environment has been designed which also houses a scanning electron microscope to aid with sample visualization. This combination of features at VMXm allows measurements at the physical limits of X‐ray crystallography on biomacromolecules to be explored and exploited. [ABSTRACT FROM AUTHOR]

A group of three deep‐learning tools, referred to collectively as CHiMP (Crystal Hits in My Plate), were created for analysis of micrographs of protein crystallization experiments at the Diamond Light Source (DLS) synchrotron, UK. The first tool, a classification network, assigns images into categories relating to experimental outcomes. The other two tools are networks that perform both object detection and instance segmentation, resulting in masks of individual crystals in the first case and masks of crystallization droplets in addition to crystals in the second case, allowing the positions and sizes of these entities to be recorded. The creation of these tools used transfer learning, where weights from a pre‐trained deep‐learning network were used as a starting point and repurposed by further training on a relatively small set of data. Two of the tools are now integrated at the VMXi macromolecular crystallography beamline at DLS, where they have the potential to absolve the need for any user input, both for monitoring crystallization experiments and for triggering in situ data collections. The third is being integrated into the XChem fragment‐based drug‐discovery screening platform, also at DLS, to allow the automatic targeting of acoustic compound dispensing into crystallization droplets. [ABSTRACT FROM AUTHOR]

Neutron diffraction is one of the three crystallographic techniques (X-ray, neutron and electron diffraction) used to determine the atomic structures of molecules. Its particular strengths derive from the fact that H (and D) atoms are strong neutron scatterers, meaning that their positions, and thus protonation states, can be derived from crystallographic maps. However, because of technical limitations and experimental obstacles, the quality of neutron diffraction data is typically much poorer (completeness, resolution and signal to noise) than that of X-ray diffraction data for the same sample. Further, refinement is more complex as it usually requires additional parameters to describe the H (and D) atoms. The increase in the number of parameters may be mitigated by using the `riding hydrogen' refinement strategy, in which the positions of H atoms without a rotational degree of freedom are inferred from their neighboring heavy atoms. However, this does not address the issues related to poor data quality. Therefore, neutron structure determination often relies on the presence of an X-ray data set for joint X-ray and neutron (XN) refinement. In this approach, the X-ray data serve to compensate for the deficiencies of the neutron diffraction data by refining one model simultaneously against the X-ray and neutron data sets. To be applicable, it is assumed that both data sets are highly isomorphous, and preferably collected from the same crystals and at the same temperature. However, the approach has a number of limitations that are discussed in this work by comparing four separately re-refined neutron models. To address the limitations, a new method for joint XN refinement is introduced that optimizes two different models against the different data sets. This approach is tested using neutron models and data deposited in the Protein Data Bank. The efficacy of refining models with H atoms as riding or as individual atoms is also investigated.

The advent of serial crystallography has rejuvenated and popularized room-temperature X-ray crystal structure determination. Structures determined at physiological temperature reveal protein flexibility and dynamics. In addition, challenging samples (e.g. large complexes, membrane proteins and viruses) form fragile crystals that are often difficult to harvest for cryo-crystallography. Moreover, a typical serial crystallography experiment requires a large number of microcrystals, mainly achievable through batch crystallization. Many medically relevant samples are expressed in mammalian cell lines, producing a meager quantity of protein that is incompatible with batch crystallization. This can limit the scope of serial crystallography approaches. Direct in situ data collection from a 96-well crystallization plate enables not only the identification of the best diffracting crystallization condition but also the possibility for structure determination under ambient conditions. Here, we describe an in situ serial crystallography (iSX) approach, facilitating direct measurement from crystallization plates mounted on a rapidly exchangeable universal plate holder deployed at a microfocus beamline, ID23-2, at the European Synchrotron Radiation Facility. We applied our iSX approach on a challenging project, autotaxin, a therapeutic target expressed in a stable human cell line, to determine the structure in the lowest-symmetry P1 space group at 3.0 Å resolution. Our in situ data collection strategy provided a complete dataset for structure determination while screening various crystallization conditions. Our data analysis reveals that the iSX approach is highly efficient at a microfocus beamline, improving throughput and demonstrating how crystallization plates can be routinely used as an alternative method of presenting samples for serial crystallography experiments at synchrotrons.

The success of experimental phasing in macromolecular crystallography relies primarily on the accurate locations of heavy atoms bound to the target crystal. To improve the process of substructure determination, a modified phase-retrieval algorithm built on the framework of the relaxed alternating averaged reflection (RAAR) algorithm has been developed. Importantly, the proposed algorithm features a combination of the π-half phase perturbation for weak reflections and enforces the direct-method-based tangent formula for strong reflections in reciprocal space. The proposed algorithm is extensively demonstrated on a total of 100 single-wavelength anomalous diffraction (SAD) experimental datasets, comprising both protein and nucleic acid structures of different qualities. Compared with the standard RAAR algorithm, the modified phase-retrieval algorithm exhibits significantly improved effectiveness and accuracy in SAD substructure determination, highlighting the importance of additional constraints for algorithmic performance. Furthermore, the proposed algorithm can be performed without human intervention under most conditions owing to the self-adaptive property of the input parameters, thus making it convenient to be integrated into the structural determination pipeline. In conjunction with the IPCAS software suite, we demonstrated experimentally that automatic de novo structure determination is possible on the basis of our proposed algorithm.

Advances in structural biology have relied heavily on synchrotron cryo‐crystallography and cryogenic electron microscopy to elucidate biological processes and for drug discovery. However, disparities between cryogenic and room‐temperature (RT) crystal structures pose challenges. Here, Cryo2RT, a high‐throughput RT data‐collection method from cryo‐cooled crystals that leverages the cryo‐crystallography workflow, is introduced. Tested on endothiapepsin crystals with four soaked fragments, thaumatin and SARS‐CoV‐2 3CLpro, Cryo2RT reveals unique ligand‐binding poses, offers a comparable throughput to cryo‐crystallography and eases the exploration of structural dynamics at various temperatures. [ABSTRACT FROM AUTHOR]

Serial crystallography (SX) involves combining observations from a very large number of diffraction patterns coming from crystals in random orientations. To compile a complete data set, these patterns must be indexed (i.e. their orientation determined), integrated and merged. Introduced here is TORO (Torch‐powered robust optimization) Indexer, a robust and adaptable indexing algorithm developed using the PyTorch framework. TORO is capable of operating on graphics processing units (GPUs), central processing units (CPUs) and other hardware accelerators supported by PyTorch, ensuring compatibility with a wide variety of computational setups. In tests, TORO outpaces existing solutions, indexing thousands of frames per second when running on GPUs, which positions it as an attractive candidate to produce real‐time indexing and user feedback. The algorithm streamlines some of the ideas introduced by previous indexers like DIALS real‐space grid search [Gildea, Waterman, Parkhurst, Axford, Sutton, Stuart, Sauter, Evans & Winter (2014). Acta Cryst. D70, 2652–2666] and XGandalf [Gevorkov, Yefanov, Barty, White, Mariani, Brehm, Tolstikova, Grigat & Chapman (2019). Acta Cryst. A75, 694–704] and refines them using faster and principled robust optimization techniques which result in a concise code base consisting of less than 500 lines. On the basis of evaluations across four proteins, TORO consistently matches, and in certain instances outperforms, established algorithms such as XGandalf and MOSFLM [Powell (1999). Acta Cryst. D55, 1690–1695], occasionally amplifying the quality of the consolidated data while achieving superior indexing speed. The inherent modularity of TORO and the versatility of PyTorch code bases facilitate its deployment into a wide array of architectures, software platforms and bespoke applications, highlighting its prospective significance in SX. [ABSTRACT FROM AUTHOR]

In macromolecular crystallographic structure refinement, ligands present challenges for the generation of geometric restraints due to their large chemical variability, their possible novel nature and their specific interaction with the binding pocket of the protein. Quantum-mechanical approaches are useful for providing accurate ligand geometries, but can be plagued by the number of minima in flexible molecules. In an effort to avoid these issues, the Quantum Mechanical Restraints (QMR) procedure optimizes the ligand geometry in situ, thus accounting for the influence of the macromolecule on the local energy minima of the ligand. The optimized ligand geometry is used to generate target values for geometric restraints during the crystallographic refinement. As demonstrated using a sample of >2330 ligand instances in >1700 protein-ligand models, QMR restraints generally result in lower deviations from the target stereochemistry compared with conventionally generated restraints. In particular, the QMR approach provides accurate torsion restraints for ligands and other entities.

Metal-based complexes with their unique chemical properties, including multiple oxidation states, radio-nuclear capabilities and various coordination geometries yield value as potential pharmaceuticals. Understanding the interactions between metals and biological systems will prove key for site-specific coordination of new metal-based lead compounds. This study merges the concepts of target coordination with fragment-based drug methodologies, supported by varying the anomalous scattering of rhenium along with infrared spectroscopy, and has identified rhenium metal sites bound covalently with two amino acid types within the model protein. A time-based series of lysozyme-rhenium-imidazole (HEWL-Re-Imi) crystals was analysed systematically over a span of 38 weeks. The main rhenium covalent coordination is observed at His15, Asp101 and Asp119. Weak (i.e. noncovalent) interactions are observed at other aspartic, asparagine, proline, tyrosine and tryptophan side chains. Detailed bond distance comparisons, including precision estimates, are reported, utilizing the diffraction precision index supplemented with small-molecule data from the Cambridge Structural Database. Key findings include changes in the protein structure induced at the rhenium metal binding site, not observed in similar metal-free structures. The binding sites are typically found along the solvent-channel-accessible protein surface. The three primary covalent metal binding sites are consistent throughout the time series, whereas binding to neighbouring amino acid residues changes through the time series. Co-crystallization was used, consistently yielding crystals four days after setup. After crystal formation, soaking of the compound into the crystal over 38 weeks is continued and explains these structural adjustments. It is the covalent bond stability at the three sites, their proximity to the solvent channel and the movement of residues to accommodate the metal that are important, and may prove useful for future radiopharmaceutical development including target modification.

Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open-access global archive housing three-dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB-designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction). The RCSB PDB research-focused web portal (RCSB.org) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal (PDB101.RCSB.org) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB-designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org; and (v) supports training, outreach, and education via PDB101.RCSB.org. New tools and features at RCSB.org are presented using examples drawn from high-resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

Diffuse scattering is a promising method to gain additional insight into protein dynamics from macromolecular crystallography experiments. Bragg intensities yield the average electron density, while the diffuse scattering can be processed to obtain a three‐dimensional reciprocal‐space map that is further analyzed to determine correlated motion. To make diffuse scattering techniques more accessible, software for data processing called mdx2 has been created that is both convenient to use and simple to extend and modify. mdx2 is written in Python, and it interfaces with DIALS to implement self‐contained data‐reduction workflows. Data are stored in NeXus format for software interchange and convenient visualization. mdx2 can be run on the command line or imported as a package, for instance to encapsulate a complete workflow in a Jupyter notebook for reproducible computing and education. Here, mdx2 version 1.0 is described, a new release incorporating state‐of‐the‐art techniques for data reduction. The implementation of a complete multi‐crystal scaling and merging workflow is described, and the methods are tested using a high‐redundancy data set from cubic insulin. It is shown that redundancy can be leveraged during scaling to correct systematic errors and obtain accurate and reproducible measurements of weak diffuse signals. [ABSTRACT FROM AUTHOR]

G protein-coupled receptors (GPCRs) play a key role in the transduction of extracellular signals to cells and regulation of many biological processes, which makes these membrane proteins one of the most important targets for pharmacological agents. A significant increase in the number of resolved atomic structures of GPCRs has opened the possibility of developing pharmaceuticals targeting these receptors via structure-based drug design (SBDD). SBDD employs information on the structure of receptor–ligand complexes to search for selective ligands without the need for an extensive high-throughput experimental ligand screening and can significantly expand the chemical space for ligand search. In this review, we describe the process of deciphering GPCR structures using X-ray diffraction analysis and cryoelectron microscopy as an important stage in the rational design of drugs targeting this receptor class. Our main goal was to present modern developments and key features of experimental methods used in SBDD of GPCR-targeting agents to a wide range of specialists. [ABSTRACT FROM AUTHOR]

In macromolecular crystallography (MX), a complete diffraction dataset is essential for determining the three-dimensional structure. However, collecting a complete experimental dataset using a single crystal is frequently unsuccessful due to poor crystal quality or radiation damage, resulting in the collection of multiple incomplete datasets. This issue can be solved by merging incomplete diffraction datasets to generate a complete dataset. This study introduced a new approach for merging incomplete datasets from MX to generate a complete dataset using serial crystallography (SX). Six incomplete diffraction datasets of β-glucosidase from Thermoanaerobacterium saccharolyticum (TsaBgl) were processed using CrystFEL, an SX program. The statistics of the merged data, such as completeness, CC, CC*, Rsplit, Rwork, and Rfree, demonstrated a complete dataset, indicating improved quality compared with the incomplete datasets and enabling structural determination. Also, the merging of the incomplete datasets was processed using four different indexing algorithms, and their statistics were compared. In conclusion, this approach for generating a complete dataset using SX will provide a new opportunity for determining the crystal structure of macromolecules using multiple incomplete MX datasets.

Serial and time-resolved macromolecular crystallography are on the rise. However, beam time at X-ray free-electron lasers is limited and most third-generation synchrotron-based macromolecular crystallography beamlines do not offer the necessary infrastructure yet. Here, a new setup is demonstrated, based on the JUNGFRAU detector and Jungfraujoch data-acquisition system, that enables collection of kilohertz serial crystallography data at fourth-generation synchrotrons. More importantly, it is shown that this setup is capable of collecting multiple-time-point time-resolved protein dynamics at kilohertz rates, allowing the probing of microsecond to second dynamics at synchrotrons in a fraction of the time needed previously. A high-quality complete X-ray dataset was obtained within 1 min from lysozyme microcrystals, and the dynamics of the light-driven sodium-pump membrane protein KR2 with a time resolution of 1 ms could be demonstrated. To make the setup more accessible for researchers, downstream data handling and analysis will be automated to allow on-the-fly spot finding and indexing, as well as data processing.

Temperature directly influences the function and structure of proteins. Crystal structures determined at room temperature offer more biologically relevant structural information regarding flexibility, rigidity, and thermal motion than those determined by conventional cryocrystallography. Crystal structures can be determined at room temperature using conventional macromolecular crystallography (MX) or serial crystallography (SX) techniques. Among these, MX may theoretically be affected by radiation damage or X-ray heating, potentially resulting in differences between the room temperature structures determined by MX and SX, but this has not been fully elucidated. In this study, the room temperature structure of xylanase GH11 from Thermoanaerobacterium saccharolyticum was determined by MX (RT-TsaGH11-MX). The RT-TsaGH11-MX exhibited both the open and closed conformations of the substrate-binding cleft within the β-sandwich fold. The RT-TsaGH11-MX showed distinct structural changes and molecular flexibility when compared with the RT-TsaGH11 determined via serial synchrotron crystallography. The notable molecular conformation and flexibility of the RT-TsaGH11-MX may be induced by radiation damage and X-ray heating. These findings will broaden our understanding of the potential limitations of room temperature structures determined by MX. [ABSTRACT FROM AUTHOR]

To resolve photons hungry for weak diffraction samples by the crystallographic method, a double-multilayer monochromator (DMM) was employed on an undulator beamline (BL17UM) at the Shanghai Synchrotron Radiation Facility (SSRF) to provide a focused sub-micron beam with high brightness for macromolecular crystallography experiments. High-quality crystallographic datasets from model protein crystal samples were collected and processed by an existing crystallographic program for structure solution and refinement. The data quality was compared with datasets from a normal silicon crystal monochromator to evaluate the bandwidth of the DMM effect on these crystallographic data. This experiment demonstrates that multilayer optics on an undulator beamline may play a valuable role in satisfying the demands of structure-related research, which requires novel methods. [ABSTRACT FROM AUTHOR]

The ability to view structures of proteins at atomic resolution, facilitated by the rise of macromolecular crystallography, has had a tremendous impact in many areas of sciences, including molecular pharmacology, drug discovery and biotechnology. However, the teaching of macromolecular crystallography in universities across the globe has been less than optimal. This could be attributed to the interdisciplinary nature of this subject, making it appear esoteric and incomprehensible, at least at first glance, for students who have exclusive training in only one specific discipline. For the instructor, this problem is compounded further by the plethora of complex concepts and specialized terminologies that the science of macromolecular crystallography has accumulated over the course of its evolution. Moreover, the advent of robotics and several sophisticated software algorithms have reduced the incentive to understand the beautiful conceptual bedrock on which this subject is based. As a way of addressing some of the challenges delineated above, this Words of Advice article attempts to formulate the broad framework within which the teaching and learning of macromolecular crystallography should be approached. It advocates the acknowledgement that this is an interdisciplinary field, with substantial contributions from chemical, physical, biological and mathematical sciences, requiring the evolution of teaching approaches that acknowledge this reality. Moreover, it suggests the use of visual tools, use of computational resources and history to make the subject more relatable to students. [ABSTRACT FROM AUTHOR]

The JUNGFRAU 4-megapixel (4M) charge-integrating pixel-array detector, when operated at a full 2 kHz frame rate, streams data at a rate of 17 GB s−1. To operate this detector for macromolecular crystallography beamlines, a data-acquisition system called Jungfraujoch was developed. The system, running on a single server with field-programmable gate arrays and general-purpose graphics processing units, is capable of handling data produced by the JUNGFRAU 4M detector, including conversion of raw pixel readout to photon counts, compression and on-the-fly spot finding. It was also demonstrated that 30 GB s−1 can be handled in performance tests, indicating that the operation of even larger and faster detectors will be achievable in the future. The source code is available from a public repository.

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. [ABSTRACT FROM AUTHOR]

The Protein Data Bank (PDB) is the single global archive of atomic‐level, three‐dimensional structures of biological macromolecules experimentally determined by macromolecular crystallography, nuclear magnetic resonance spectroscopy or three‐dimensional cryo‐electron microscopy. The PDB is growing continuously, with a recent rapid increase in new structure depositions from Asia. In 2022, the Worldwide Protein Data Bank (wwPDB; https://www.wwpdb.org/) partners welcomed Protein Data Bank China (PDBc; https://www.pdbc.org.cn) to the organization as an Associate Member. PDBc is based in the National Facility for Protein Science in Shanghai which is associated with the Shanghai Advanced Research Institute of Chinese Academy of Sciences, the Shanghai Institute for Advanced Immunochemical Studies and the iHuman Institute of ShanghaiTech University. This letter describes the history of the wwPDB, recently established mechanisms for adding new wwPDB data centers and the processes developed to bring PDBc into the partnership. [ABSTRACT FROM AUTHOR]

Sequence‐register shifts remain one of the most elusive errors in experimental macromolecular models. They may affect model interpretation and propagate to newly built models from older structures. In a recent publication, it was shown that register shifts in cryo‐EM models of proteins can be detected using a systematic reassignment of short model fragments to the target sequence. Here, it is shown that the same approach can be used to detect register shifts in crystal structure models using standard, model‐bias‐corrected electron‐density maps (2mFo − DFc). Five register‐shift errors in models deposited in the PDB detected using this method are described in detail. [ABSTRACT FROM AUTHOR]

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

This letter announces that PDBx/mmCIF format files will become mandatory for crystallographic depositions to the Protein Data Bank (PDB).

The highly automated macromolecular crystallography beamline AMX/17-ID-1 is an undulator-based high-intensity (>5 × 1012 photons s−1), micro-focus (7 µm × 5 µm), low-divergence (1 mrad × 0.35 mrad) energy-tunable (5–18 keV) beamline at the NSLS-II, Brookhaven National Laboratory, Upton, NY, USA. It is one of the three life science beamlines constructed by the NIH under the ABBIX project and it shares sector 17-ID with the FMX beamline, the frontier micro-focus macromolecular crystallography beamline. AMX saw first light in March 2016 and started general user operation in February 2017. At AMX, emphasis has been placed on high throughput, high capacity, and automation to enable data collection from the most challenging projects using an intense micro-focus beam. Here, the current state and capabilities of the beamline are reported, and the different macromolecular crystallography experiments that are routinely performed at AMX/17-ID-1 as well as some plans for the near future are presented.

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. [ABSTRACT FROM AUTHOR]

Serial femtosecond crystallography was initially developed for room‐temperature X‐ray diffraction studies of macromolecules at X‐ray free electron lasers. When combined with tools that initiate biological reactions within microcrystals, time‐resolved serial crystallography allows the study of structural changes that occur during an enzyme catalytic reaction. Serial synchrotron X‐ray crystallography (SSX), which extends serial crystallography methods to synchrotron radiation sources, is expanding the scientific community using serial diffraction methods. This report presents a simple flow cell that can be used to deliver microcrystals across an X‐ray beam during SSX studies. This device consists of an X‐ray transparent glass capillary mounted on a goniometer‐compatible 3D‐printed support and is connected to a syringe pump via lightweight tubing. This flow cell is easily mounted and aligned, and it is disposable so can be rapidly replaced when blocked. This system was demonstrated by collecting SSX data at MAX IV Laboratory from microcrystals of the integral membrane protein cytochrome c oxidase from Thermus thermophilus, from which an X‐ray structure was determined to 2.12 Å resolution. This simple SSX platform may help to lower entry barriers for non‐expert users of SSX. [ABSTRACT FROM AUTHOR]

Temperature directly influences the function and structure of proteins. Crystal structures determined at room temperature offer more biologically relevant structural information regarding flexibility, rigidity, and thermal motion than those determined by conventional cryocrystallography. Crystal structures can be determined at room temperature using conventional macromolecular crystallography (MX) or serial crystallography (SX) techniques. Among these, MX may theoretically be affected by radiation damage or X-ray heating, potentially resulting in differences between the room temperature structures determined by MX and SX, but this has not been fully elucidated. In this study, the room temperature structure of xylanase GH11 from Thermoanaerobacterium saccharolyticum was determined by MX (RT-TsaGH11-MX). The RT-TsaGH11-MX exhibited both the open and closed conformations of the substrate-binding cleft within the β-sandwich fold. The RT-TsaGH11-MX showed distinct structural changes and molecular flexibility when compared with the RT-TsaGH11 determined via serial synchrotron crystallography. The notable molecular conformation and flexibility of the RT-TsaGH11-MX may be induced by radiation damage and X-ray heating. These findings will broaden our understanding of the potential limitations of room temperature structures determined by MX.

To resolve photons hungry for weak diffraction samples by the crystallographic method, a double-multilayer monochromator (DMM) was employed on an undulator beamline (BL17UM) at the Shanghai Synchrotron Radiation Facility (SSRF) to provide a focused sub-micron beam with high brightness for macromolecular crystallography experiments. High-quality crystallographic datasets from model protein crystal samples were collected and processed by an existing crystallographic program for structure solution and refinement. The data quality was compared with datasets from a normal silicon crystal monochromator to evaluate the bandwidth of the DMM effect on these crystallographic data. This experiment demonstrates that multilayer optics on an undulator beamline may play a valuable role in satisfying the demands of structure-related research, which requires novel methods.

Diffraction‐based structural methods contribute a large fraction of the biomolecular structural models available, providing a critical understanding of macromolecular architecture. These methods require crystallization of the target molecule, which remains a primary bottleneck in crystal‐based structure determination. The National High‐Throughput Crystallization Center at Hauptman–Woodward Medical Research Institute has focused on overcoming obstacles to crystallization through a combination of robotics‐enabled high‐throughput screening and advanced imaging to increase the success of finding crystallization conditions. This paper will describe the lessons learned from over 20 years of operation of our high‐throughput crystallization services. The current experimental pipelines, instrumentation, imaging capabilities and software for image viewing and crystal scoring are detailed. New developments in the field and opportunities for further improvements in biomolecular crystallization are reflected on. [ABSTRACT FROM AUTHOR]

The JUNGFRAU 4-megapixel (4M) charge-integrating pixel-array detector, when operated at a full 2 kHz frame rate, streams data at a rate of 17 GB s-1. To operate this detector for macromolecular crystallography beamlines, a dataacquisition system called Jungfraujoch was developed. The system, running on a single server with field-programmable gate arrays and general-purpose graphics processing units, is capable of handling data produced by the JUNGFRAU 4M detector, including conversion of raw pixel readout to photon counts, compression and on-the-fly spot finding. It was also demonstrated that 30 GB s-1 can be handled in performance tests, indicating that the operation of even larger and faster detectors will be achievable in the future. The source code is available from a public repository. [ABSTRACT FROM AUTHOR]

Structural biology investigations using synchrotron radiation have a long history at the photon science facilities at DESY. Presently, EMBL and DESY operate state-of-the-art macromolecular crystallography and biological SAXS stations at the synchrotron radiation source PETRA III for the international user community. New experimental opportunities for experiments with femtosecond temporal resolution and for extremely small macromolecular crystals have become available with the advent of X-ray free-electron lasers (XFELs) such as the European XFEL. Within large international collaborations, groups at DESY and the European XFEL have contributed significantly to the development of experimental and data analysis methods to enable serial crystallography experiments at both XFELs and high-brilliance synchrotron radiation sources. The available portfolio of analytical infrastructure in photon science at DESY has attracted several campus partners to contribute to the development of instruments and methods and provide their own complementary experimental techniques, thereby establishing a fruitful scientific environment to make significant contributions to present and future societal challenges in the field of life sciences., (open access.)

Since the groundbreaking determination of the first protein crystal structure by J. C. Kendrew in 1959, macromolecular crystallography (MX) has remained at the forefront of structural biology, driven by continuous technological advancements. The advent of synchrotron radiation in the 1990s revolutionized the field, enhancing data quality, introducing novel phasing methods, and broadening the scope of target samples to include membrane proteins and supramolecular complexes. In 1997, Japan inaugurated SPring-8, one of the world's largest third-generation synchrotron radiation facilities. With its high-brilliance radiation from insertion devices, SPring-8 has dramatically increased the capability of MX. This paper describes MX's evolution, current developments, and prospects at SPring-8 and SACLA., (open access.)

Algorithms and procedures to fully automate retuning of synchrotron radiation beamlines over wide energy ranges are discussed. The discussion is based on the implementation at the National Institute of General Medical Sciences and the National Cancer Institute Structural Biology Facility at the Advanced Photon Source. When a user selects a new beamline energy, software synchronously controls the beamline monochromator and undulator to maintain the X-ray beam flux after the monochromator, preserves beam attenuation by determining a new set of attenuator foils, changes, as needed, mirror reflecting stripes and the undulator harmonic, preserves beam focal distance of compound refractive lens focusing by changing the In/Out combination of lenses in the transfocator, and, finally, restores beam position at the sample by on-the-fly scanning of either the Kirkpatrick–Baez mirror angles or the transfocator up/down and inboard/outboard positions. The sample is protected from radiation damage by automatically moving it out of the beam during the energy change and optimization.

ID23-2 is a fixed-energy (14.2 keV) microfocus beamline at the European Synchrotron Radiation Facility (ESRF) dedicated to macromolecular crystallography. The optics and sample environment have recently been redesigned and rebuilt to take full advantage of the upgrade of the ESRF to the fourth generation Extremely Brilliant Source (ESRF-EBS). The upgraded beamline now makes use of two sets of compound refractive lenses and multilayer mirrors to obtain a highly intense (>1013 photons s−1) focused microbeam (minimum size 1.5 µm × 3 µm full width at half-maximum). The sample environment now includes a FLEX-HCD sample changer/storage system, as well as a state-of-the-art MD3Up high-precision multi-axis diffractometer. Automatic data reduction and analysis are also provided for more advanced protocols such as synchrotron serial crystallographic experiments.

The highly automated macromolecular crystallography beamline AMX/17-ID-1 is an undulator-based high-intensity (>5 - 1012 photons s-1), micro-focus (7 mm - 5 mm), low-divergence (1 mrad - 0.35 mrad) energy-tunable (5-18 keV) beamline at the NSLS-II, Brookhaven National Laboratory, Upton, NY, USA. It is one of the three life science beamlines constructed by the NIH under the ABBIX project and it shares sector 17-ID with the FMX beamline, the frontier micro-focus macromolecular crystallography beamline. AMX saw first light in March 2016 and started general user operation in February 2017. At AMX, emphasis has been placed on high throughput, high capacity, and automation to enable data collection from the most challenging projects using an intense micro-focus beam. Here, the current state and capabilities of the beamline are reported, and the different macromolecular crystallography experiments that are routinely performed at AMX/17-ID-1 as well as some plans for the near future are presented. [ABSTRACT FROM AUTHOR]

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide. [ABSTRACT FROM AUTHOR]

Often similar structures need to be compared to reveal local differences throughout the entire model or between related copies within the model. Therefore, a program to compare multiple structures and enable correction any differences not supported by the density map was written within the Phenix framework (Adams et al., Acta Cryst 2010; D66:213-221). This program, called Structure Comparison, can also be used for structures with multiple copies of the same protein chain in the asymmetric unit, that is, as a result of non-crystallographic symmetry (NCS). Structure Comparison was designed to interface with Coot(Emsley et al., Acta Cryst 2010; D66:486-501) and PyMOL(DeLano, PyMOL 0.99; 2002) to facilitate comparison of large numbers of related structures. Structure Comparison analyzes collections of protein structures using several metrics, such as the rotamer conformation of equivalent residues, displays the results in tabular form and allows superimposed protein chains and density maps to be quickly inspected and edited (via the tools in Coot) for consistency, completeness and correctness.

X-ray-induced radiation damage is a limiting factor for the macromolecular crystallographer and data must often be merged from many crystals to yield complete data sets for the structure solution of challenging samples. Increasing the X-ray energy beyond the typical 10–15 keV range promises to provide an extension of crystal lifetime via an increase in diffraction efficiency. To date, however, hardware limitations have negated any possible gains. Through the first use of a cadmium telluride EIGER2 detector and a beamline optimized for high-energy data collection, it is shown that at higher energies fewer crystals will be required to obtain complete data, as the diffracted intensity per unit dose increases by a factor of more than two between 12.4 and 25 keV. Additionally, these higher energy data can provide more information, as shown by a systematic increase in the high-resolution cutoff of the data collected. Taken together, these gains point to a high-energy future for synchrotron-based macromolecular crystallography.

Nowadays, progress in the determination of three‐dimensional macromolecular structures from diffraction images is achieved partly at the cost of increasing data volumes. This is due to the deployment of modern high‐speed, high‐resolution detectors, the increased complexity and variety of crystallographic software, the use of extensive databases and high‐performance computing. This limits what can be accomplished with personal, offline, computing equipment in terms of both productivity and maintainability. There is also an issue of long‐term data maintenance and availability of structure‐solution projects as the links between experimental observations and the final results deposited in the PDB. In this article, CCP4 Cloud, a new front‐end of the CCP4 software suite, is presented which mitigates these effects by providing an online, cloud‐based environment for crystallographic computation. CCP4 Cloud was developed for the efficient delivery of computing power, database services and seamless integration with web resources. It provides a rich graphical user interface that allows project sharing and long‐term storage for structure‐solution projects, and can be linked to data‐producing facilities. The system is distributed with the CCP4 software suite version 7.1 and higher, and an online publicly available instance of CCP4 Cloud is provided by CCP4. [ABSTRACT FROM AUTHOR]

Central challenges in the design of large and dynamic macromolecular assemblies for synthetic biology lie in developing effective methods for testing design strategies and their outcomes, including comprehensive assessments of solution behavior. We created and validated an advanced design of a 600-kDa protein homododecamer that self-assembles into a symmetric tetrahedral cage. The monomeric unit is composed of a trimerizing apex-forming domain genetically linked to an edge-forming dimerizing domain. Enhancing the crystallographic results, high-throughput small-angle x-ray scattering (SAXS) comprehensively contrasted our modifications under diverse solution conditions. To generate a phase diagram associating structure and assembly, we developed force plots that measure dissimilarity among multiple SAXS data sets. These new tools, which provided effective feedback on experimental constructs relative to design, have general applicability in analyzing the solution behavior of heterogeneous nanosystems and have been made available as a web-based application. Specifically, our results probed the influence of solution conditions and symmetry on stability and structural adaptability, identifying the dimeric interface as the weak point in the assembly. Force plots comparing SAXS data sets further reveal more complex and controllable behavior in solution than captured by our crystal structures. These methods for objectively and comprehensively comparing SAXS profiles for systems critically affected by solvent conditions and structural heterogeneity provide an enabling technology for advancing the design and bioengineering of nanoscale biological materials.

This paper describes the introduction of synchrotron-based macromolecular crystallography (MX) into an undergraduate laboratory class. An introductory 2 week experimental module on MX, consisting of four laboratory sessions and two classroom lectures, was incorporated into a senior-level biochemistry class focused on a survey of biochemical techniques, including the experimental characterization of proteins. Students purified recombinant protein samples, set up crystallization plates and flash-cooled crystals for shipping to a synchrotron. Students then collected X-ray diffraction data sets from their crystals via the remote interface of the Molecular Biology Consortium beamline (4.2.2) at the Advanced Light Source in Berkeley, CA, USA. Processed diffraction data sets were transferred back to the laboratory and used in conjunction with partial protein models provided to the students for refinement and model building. The laboratory component was supplemented by up to 2 h of lectures by faculty with expertise in MX. This module can be easily adapted for implementation into other similar undergraduate classes, assuming the availability of local crystallographic expertise and access to remote data collection at a synchrotron source.