Innovative Strategies in X-ray Crystallography for Exploring Structural Dynamics and Reaction Mechanisms in Metabolic Disorders.

Enzymes are crucial in metabolic processes, and their dysfunction can lead to severe metabolic disorders. Structural biology, particularly X-ray crystallography, has advanced our understanding of these diseases by providing 3D structures of pathological enzymes. However, traditional X-ray crystallography faces limitations, such as difficulties in obtaining suitable protein crystals and studying protein dynamics. X-ray free-electron lasers (XFELs) have revolutionized this field with their bright and brief X-ray pulses, providing high-resolution structures of radiation-sensitive and hard-to-crystallize proteins. XFELs also enable the study of protein dynamics through room temperature structures and time-resolved serial femtosecond crystallography, offering comprehensive insights into the molecular mechanisms of metabolic diseases. Understanding these dynamics is vital for developing effective therapies. This review highlights the contributions of protein dynamics studies using XFELs and synchrotrons to metabolic disorder research and their application in designing better therapies. It also discusses G protein-coupled receptors (GPCRs), which, though not enzymes, play key roles in regulating physiological systems and are implicated in many metabolic disorders.

TORO Indexer: a PyTorch-based indexing algorithm for kilohertz serial crystallography.

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.

In situ serial crystallography facilitates 96-well plate structural analysis at low symmetry.

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 Šresolution. 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.

Exploring serial crystallography for drug discovery.

Structure-based drug design is highly dependent on the availability of structures of the protein of interest in complex with lead compounds. Ideally, this information can be used to guide the chemical optimization of a compound into a pharmaceutical drug candidate. A limitation of the main structural method used today - conventional X-ray crystallography - is that it only provides structural information about the protein complex in its frozen state. Serial crystallography is a relatively new approach that offers the possibility to study protein structures at room temperature (RT). Here, we explore the use of serial crystallography to determine the structures of the pharmaceutical target, soluble epoxide hydrolase. We introduce a new method to screen for optimal microcrystallization conditions suitable for use in serial crystallography and present a number of RT ligand-bound structures of our target protein. From a comparison between the RT structural data and previously published cryo-temperature structures, we describe an example of a temperature-dependent difference in the ligand-binding mode and observe that flexible loops are better resolved at RT. Finally, we discuss the current limitations and potential future advances of serial crystallography for use within pharmaceutical drug discovery.

A snapshot love story: what serial crystallography has done and will do for us.

Serial crystallography, born from groundbreaking experiments at the Linac Coherent Light Source in 2009, has evolved into a pivotal technique in structural biology. Initially pioneered at X-ray free-electron laser facilities, it has now expanded to synchrotron-radiation facilities globally, with dedicated experimental stations enhancing its accessibility. This review gives an overview of current developments in serial crystallography, emphasizing recent results in time-resolved crystallography, and discussing challenges and shortcomings.

Resolving DJ-1 Glyoxalase Catalysis Using Mix-and-Inject Serial Crystallography at a Synchrotron.

DJ-1 (PARK7) is an intensively studied protein whose cytoprotective activities are dysregulated in multiple diseases. DJ-1 has been reported as having two distinct enzymatic activities in defense against reactive carbonyl species that are difficult to distinguish in conventional biochemical experiments. Here, we establish the mechanism of DJ-1 using a synchrotron-compatible version of mix-and-inject-serial crystallography (MISC), which was previously performed only at XFELs, to directly observe DJ-1 catalysis. We designed and used new diffusive mixers to collect time-resolved Laue diffraction data of DJ-1 catalysis at a pink beam synchrotron beamline. Analysis of structurally similar methylglyoxal-derived intermediates formed through the DJ-1 catalytic cycle shows that the enzyme catalyzes nearly two turnovers in the crystal and defines key aspects of its glyoxalase mechanism. In addition, DJ-1 shows allosteric communication between a distal site at the dimer interface and the active site that changes during catalysis. Our results rule out the widely cited deglycase mechanism for DJ-1 action and provide an explanation for how DJ-1 produces L-lactate with high chiral purity.

Crystal structure via fluctuation scattering.

Crystallography is a quintessential method for determining the atomic structure of crystals. The most common implementation of crystallography uses single crystals that must be of sufficient size, typically tens of micrometres or larger, depending on the complexity of the crystal structure. The emergence of serial data-collection methods in crystallography, particularly for time-resolved experiments, opens up opportunities to develop new routes to structure determination for nanocrystals and ensembles of crystals. Fluctuation X-ray scattering is a correlation-based approach for single-particle imaging from ensembles of identical particles, but has yet to be applied to crystal structure determination. Here, an iterative algorithm is presented that recovers crystal structure-factor intensities from fluctuation X-ray scattering correlations. The capabilities of this algorithm are demonstrated by recovering the structure of three small-molecule crystals and a protein crystal from simulated fluctuation X-ray scattering correlations. This method could facilitate the recovery of structure-factor intensities from crystals in serial crystallography experiments and relax sample requirements for crystallography experiments.

Robust image descriptor for machine learning based data reduction in serial crystallography.

Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as 'hit' and 'miss', respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers.

The Pixel Anomaly Detection Tool: a user-friendly GUI for classifying detector frames using machine-learning approaches.

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

Droplet microfluidics for time-resolved serial crystallography.

Serial crystallography requires large numbers of microcrystals and robust strategies to rapidly apply substrates to initiate reactions in time-resolved studies. Here, we report the use of droplet miniaturization for the controlled production of uniform crystals, providing an avenue for controlled substrate addition and synchronous reaction initiation. The approach was evaluated using two enzymatic systems, yielding 3 µm crystals of lysozyme and 2 µm crystals of Pdx1, an Arabidopsis enzyme involved in vitamin B6 biosynthesis. A seeding strategy was used to overcome the improbability of Pdx1 nucleation occurring with diminishing droplet volumes. Convection within droplets was exploited for rapid crystal mixing with ligands. Mixing times of <2 ms were achieved. Droplet microfluidics for crystal size engineering and rapid micromixing can be utilized to advance time-resolved serial crystallography.

Efficient in situ screening of and data collection from microcrystals in crystallization plates.

A considerable bottleneck in serial crystallography at XFEL and synchrotron sources is the efficient production of large quantities of homogenous, well diffracting microcrystals. Efficient high-throughput screening of batch-grown microcrystals and the determination of ground-state structures from different conditions is thus of considerable value in the early stages of a project. Here, a highly sample-efficient methodology to measure serial crystallography data from microcrystals by raster scanning within standard in situ 96-well crystallization plates is described. Structures were determined from very small quantities of microcrystal suspension and the results were compared with those from other sample-delivery methods. The analysis of a two-dimensional batch crystallization screen using this method is also described as a useful guide for further optimization and the selection of appropriate conditions for scaling up microcrystallization.

An electropneumatic cleaning device for piezo-actuator-driven picolitre-droplet dispensers.

Recently, we introduced the liquid application method for time-resolved analyses (LAMA). The time-consuming cleaning cycles required for the substrate solution exchange and storage of the sensitive droplet-dispenser nozzles present practical challenges. In this work, a dispenser cleaning system for the semi-automated cleaning of the piezo-actuator-driven picolitre-droplet dispensers required for LAMA is introduced to streamline typical workflows.

Guide to serial synchrotron crystallography.

Serial crystallography (SX) is an emerging technique that can be used to determine the noncryogenic crystal structure of macromolecules while minimizing radiation damage. Applying SX using pump-probe or mix-and-inject techniques enables the observation of time-resolved molecular reactions and dynamics in macromolecules. After the successful demonstration of the SX experimental technique with structure determination in serial femtosecond crystallography using an X-ray free electron laser, this method was adapted to the synchrotron, leading to the development of serial synchrotron crystallography (SSX). SSX offers new opportunities for researchers to leverage SX techniques, contributing to the advancement of structural biology and offering a deeper understanding of the structure and function of macromolecules. This review covers the background and advantages of SSX and its experimental approach. It also discusses important considerations when conducting SSX experiments.

Data reduction in protein serial crystallography.

Serial crystallography (SX) has become an established technique for protein structure determination, especially when dealing with small or radiation-sensitive crystals and investigating fast or irreversible protein dynamics. The advent of newly developed multi-megapixel X-ray area detectors, capable of capturing over 1000 images per second, has brought about substantial benefits. However, this advancement also entails a notable increase in the volume of collected data. Today, up to 2 PB of data per experiment could be easily obtained under efficient operating conditions. The combined costs associated with storing data from multiple experiments provide a compelling incentive to develop strategies that effectively reduce the amount of data stored on disk while maintaining the quality of scientific outcomes. Lossless data-compression methods are designed to preserve the information content of the data but often struggle to achieve a high compression ratio when applied to experimental data that contain noise. Conversely, lossy compression methods offer the potential to greatly reduce the data volume. Nonetheless, it is vital to thoroughly assess the impact of data quality and scientific outcomes when employing lossy compression, as it inherently involves discarding information. The evaluation of lossy compression effects on data requires proper data quality metrics. In our research, we assess various approaches for both lossless and lossy compression techniques applied to SX data, and equally importantly, we describe metrics suitable for evaluating SX data quality.

Deep residual networks for crystallography trained on synthetic data.

The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and training residual neural networks on these data. Here, two per-pattern capabilities of Resonet are demonstrated: (i) interpretation of crystal resolution and (ii) identification of overlapping lattices. Resonet was tested across a compilation of diffraction images from synchrotron experiments and X-ray free-electron laser experiments. Crucially, these models readily execute on graphics processing units and can thus significantly outperform conventional algorithms. While Resonet is currently utilized to provide real-time feedback for macromolecular crystallography users at the Stanford Synchrotron Radiation Lightsource, its simple Python-based interface makes it easy to embed in other processing frameworks. This work highlights the utility of physics-based simulation for training deep neural networks and lays the groundwork for the development of additional models to enhance diffraction collection and analysis.

From femtoseconds to minutes: time-resolved macromolecular crystallography at XFELs and synchrotrons.

Over the last decade, the development of time-resolved serial crystallography (TR-SX) at X-ray free-electron lasers (XFELs) and synchrotrons has allowed researchers to study phenomena occurring in proteins on the femtosecond-to-minute timescale, taking advantage of many technical and methodological breakthroughs. Protein crystals of various sizes are presented to the X-ray beam in either a static or a moving medium. Photoactive proteins were naturally the initial systems to be studied in TR-SX experiments using pump-probe schemes, where the pump is a pulse of visible light. Other reaction initiations through small-molecule diffusion are gaining momentum. Here, selected examples of XFEL and synchrotron time-resolved crystallography studies will be used to highlight the specificities of the various instruments and methods with respect to time resolution, and are compared with cryo-trapping studies.

A versatile approach to high-density microcrystals in lipidic cubic phase for room-temperature serial crystallography.

Serial crystallography has emerged as an important tool for structural studies of integral membrane proteins. The ability to collect data from micrometre-sized weakly diffracting crystals at room temperature with minimal radiation damage has opened many new opportunities in time-resolved studies and drug discovery. However, the production of integral membrane protein microcrystals in lipidic cubic phase at the desired crystal density and quantity is challenging. This paper introduces VIALS (versatile approach to high-density microcrystals in lipidic cubic phase for serial crystallography), a simple, fast and efficient method for preparing hundreds of microlitres of high-density microcrystals suitable for serial X-ray diffraction experiments at both synchrotron and free-electron laser sources. The method is also of great benefit for rational structure-based drug design as it facilitates in situ crystal soaking and rapid determination of many co-crystal structures. Using the VIALS approach, room-temperature structures are reported of (i) the archaerhodopsin-3 protein in its dark-adapted state and 110 ns photocycle intermediate, determined to 2.2 and 1.7 Å, respectively, and (ii) the human A2A adenosine receptor in complex with two different ligands determined to a resolution of 3.5 Å.

Kilohertz serial crystallography with the JUNGFRAU detector at a fourth-generation synchrotron source.

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.

Anaerobic fixed-target serial crystallography using sandwiched silicon nitride membranes.

In recent years, the emergence of serial crystallography, initially pioneered at X-ray free-electron lasers (XFELs), has sparked a growing interest in collecting macromolecular crystallographic data at room temperature. Various fixed-target serial crystallography techniques have been developed, ranging from commercially available chips to in-house designs implemented at different synchrotron facilities. Nevertheless, there is currently no commercially available chip (known to the authors) specifically designed for the direct handling of oxygen-sensitive samples. This study presents a methodology employing silicon nitride chips arranged in a `sandwich' configuration, enabling reliable room-temperature data collection from oxygen-sensitive samples. The method involves the utilization of a custom-made 3D-printed assembling tool and a MX sample holder. To validate the effectiveness of the proposed method, deoxyhemoglobin and methemoglobin samples were investigated using the BioMAX X-ray macromolecular crystallography beamline, the Balder X-ray absorption spectroscopy beamline and UV-Vis absorption spectroscopy.

Micro-structured polymer fixed targets for serial crystallography at synchrotrons and XFELs.

Fixed targets are a popular form of sample-delivery system used in serial crystallography at synchrotron and X-ray free-electron laser sources. They offer a wide range of sample-preparation options and are generally easy to use. The supports are typically made from silicon, quartz or polymer. Of these, currently, only silicon offers the ability to perform an aperture-aligned data collection where crystals are loaded into cavities in precise locations and sequentially rastered through, in step with the X-ray pulses. The polymer-based fixed targets have lacked the precision fabrication to enable this data-collection strategy and have been limited to directed-raster scans with crystals randomly distributed across the polymer surface. Here, the fabrication and first results from a new polymer-based fixed target, the micro-structured polymer fixed targets (MISP chips), are presented. MISP chips, like those made from silicon, have a precise array of cavities and fiducial markers. They consist of a structured polymer membrane and a stabilization frame. Crystals can be loaded into the cavities and the excess crystallization solution removed through apertures at their base. The fiducial markers allow for a rapid calculation of the aperture locations. The chips have a low X-ray background and, since they are optically transparent, also allow for an a priori analysis of crystal locations. This location mapping could, ultimately, optimize hit rates towards 100%. A black version of the MISP chip was produced to reduce light contamination for optical-pump/X-ray probe experiments. A study of the loading properties of the chips reveals that these types of fixed targets are best optimized for crystals of the order of 25 µm, but quality data can be collected from crystals as small as 5 µm. With the development of these chips, it has been proved that polymer-based fixed targets can be made with the precision required for aperture-alignment-based data-collection strategies. Further work can now be directed towards more cost-effective mass fabrication to make their use more sustainable for serial crystallography facilities and users.