Room-temperature structural studies of SARS-CoV-2 protein NendoU with an X-ray free-electron laser

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.

Structure-based approaches against COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has had a major impact on human life. This review highlights the versatile roles of both classical and modern structure-based approaches for COVID-19. X-ray crystallography, nuclear magnetic resonance spectroscopy, and cryogenic electron microscopy are the three cornerstones of classical structural biology. These technologies have helped provide fundamental and detailed knowledge regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the related human host proteins as well as enabled the identification of its target sites, facilitating the cessation of its transmission. Further progress into protein structure modeling was made using modern structure-based approaches derived from homology modeling and integrated with artificial intelligence (AI), facilitating advanced computational simulation tools to actively guide the design of new vaccines and the development of anti-SARS-CoV-2 drugs. This review presents the practical contributions and future directions of structure-based approaches for COVID-19.

Review of serial femtosecond crystallography including the COVID-19 pandemic impact and future outlook

Serial femtosecond crystallography (SFX) revolutionized macromolecular crystallography over the past decade by enabling the collection of X-ray diffraction data from nano- or micrometer sized crystals while outrunning structure-altering radiation damage effects at room temperature. The serial manner of data collection from millions of individual crystals coupled with the femtosecond duration of the ultrabright X-ray pulses enables time-resolved studies of macromolecules under near-physiological conditions to unprecedented temporal resolution. In 2020 the rapid spread of the coronavirus SARS-CoV-2 resulted in a global pandemic of coronavirus disease-2019. This led to a shift in how serial femtosecond experiments were performed, along with rapid funding and free electron laser beamtime availability dedicated to SARS-CoV-2-related studies. This review outlines the current state of SFX research, the milestones that were achieved, the impact of the global pandemic on this field as well as an outlook into exciting future directions.

A user-friendly plug-and-play cyclic olefin copolymer-based microfluidic chip for room-temperature, fixed-target serial crystallography

Over the past two decades, serial X-ray crystallography has enabled the structure determination of a wide range of proteins. With the advent of X-ray free-electron lasers (XFELs), ever-smaller crystals have yielded high-resolution diffraction and structure determination. A crucial need to continue advancement is the efficient delivery of fragile and micrometre-sized crystals to the X-ray beam intersection. This paper presents an improved design of an all-polymer microfluidic `chip' for room-temperature fixed-target serial crystallography that can be tailored to broadly meet the needs of users at either synchrotron or XFEL light sources. The chips are designed to be customized around different types of crystals and offer users a friendly, quick, convenient, ultra-low-cost and robust sample-delivery platform. Compared with the previous iteration of the chip [Gilbile et al. (2021), Lab Chip, 21, 4831-4845], the new design eliminates cleanroom fabrication. It has a larger imaging area to volume, while maintaining crystal hydration stability for both in situ crystallization or direct crystal slurry loading. Crystals of two model proteins, lysozyme and thaumatin, were used to validate the effectiveness of the design at both synchrotron (lysozyme and thaumatin) and XFEL (lysozyme only) facilities, yielding complete data sets with resolutions of 1.42, 1.48 and 1.70 Å, respectively. Overall, the improved chip design, ease of fabrication and high modifiability create a powerful, all-around sample-delivery tool that structural biologists can quickly adopt, especially in cases of limited sample volume and small, fragile crystals.

Modular droplet injector for sample conservation providing new structural insight for the conformational heterogeneity in the disease-associated NQO1 enzyme

Droplet injection strategies are a promising tool to reduce the large amount of sample consumed in serial femtosecond crystallography (SFX) measurements at X-ray free electron lasers (XFELs) with continuous injection approaches. Here, we demonstrate a new modular microfluidic droplet injector (MDI) design that was successfully applied to deliver microcrystals of the human NAD(P)H:quinone oxidoreductase 1 (NQO1) and phycocyanin. We investigated droplet generation conditions through electrical stimulation for both protein samples and implemented hardware and software components for optimized crystal injection at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Stanford Linac Coherent Light Source (LCLS). Under optimized droplet injection conditions, we demonstrate that up to 4-fold sample consumption savings can be achieved with the droplet injector. In addition, we collected a full data set with droplet injection for NQO1 protein crystals with a resolution up to 2.7 Å, leading to the first room-temperature structure of NQO1 at an XFEL. NQO1 is a flavoenzyme associated with cancer, Alzheimer's and Parkinson's disease, making it an attractive target for drug discovery. Our results reveal for the first time that residues Tyr128 and Phe232, which play key roles in the function of the protein, show an unexpected conformational heterogeneity at room temperature within the crystals. These results suggest that different substates exist in the conformational ensemble of NQO1 with functional and mechanistic implications for the enzyme's negative cooperativity through a conformational selection mechanism. Our study thus demonstrates that microfluidic droplet injection constitutes a robust sample-conserving injection method for SFX studies on protein crystals that are difficult to obtain in amounts necessary for continuous injection, including the large sample quantities required for time-resolved mix-and-inject studies.

Kinetic analysis of RNA cleavage by coronavirus Nsp15 endonuclease: Evidence for acid base catalysis and substrate dependent metal ion activation

Understanding the functional properties of SARS-CoV-2 nonstructural proteins is essential for defining their roles in the viral life cycle, developing improved therapeutics and diagnostics, and countering future variants. Coronavirus nonstructural protein Nsp15 is a hexameric U-specific endonuclease whose functions, substrate specificity, mechanism, and dynamics have not been fully defined. Previous studies report SARS-CoV-2 Nsp15 requires Mn²⁺ ions for optimal activity; however, the effects of divalent ions on Nsp15 reaction kinetics have not been investigated in detail. Here, we analyzed the single and multiple turnover kinetics for model single-stranded RNA substrates. Our data confirm that divalent ions are dispensable for catalysis and show that Mn²⁺ activates Nsp15 cleavage of two different ssRNA oligonucleotide substrates, but not a dinucleotide. Furthermore, biphasic kinetics of ssRNA substrates demonstrates that Mn²⁺ stabilizes alternative enzyme states that have faster substrate cleavage on the enzyme. However, we did not detect Mn²⁺-induced conformational changes using CD and fluorescence spectroscopy. The pH-rate profiles in the presence and absence of Mn²⁺ are consistent with active site ionizable groups with similar pK_as of ca. 4.8-5.2. We found the Rp stereoisomer phosphorothioate modification at the scissile phosphate had minimal effect on catalysis, which supports a mechanism involving an anionic transition state. In contrast, the Sp stereoisomer is inactive due to weak binding, consistent with models that position the non-bridging phosphoryl oxygen deep in the active site. Together, these kinetic data demonstrate that Nsp15 employs a conventional acid-base catalytic mechanism passing through an anionic transition state, and that divalent ion activation is substrate-dependent.