XFELs for structure and dynamics in biology

Going around the Kok cycle of the water oxidation reaction with femtosecond X-ray crystallography

The water oxidation reaction in photosystem II (PS II) produces most of the molecular oxygen in the atmosphere, which sustains life on Earth, and in this process releases four electrons and four protons that drive the downstream process of CO2 fixation in the photosynthetic apparatus. The catalytic center of PS II is an oxygen-bridged Mn4Ca complex (Mn4CaO5) which is progressively oxidized upon the absorption of light by the chlorophyll of the PS II reaction center, and the accumulation of four oxidative equivalents in the catalytic center results in the oxidation of two waters to dioxygen in the last step. The recent emergence of X-ray free-electron lasers (XFELs) with intense femtosecond X-ray pulses has opened up opportunities to visualize this reaction in PS II as it proceeds through the catalytic cycle. In this review, we summarize our recent studies of the catalytic reaction in PS II by following the structural changes along the reaction pathway via room-temperature X-ray crystallography using XFELs. The evolution of the electron density changes at the Mn complex reveals notable structural changes, including the insertion of OX from a new water molecule, which disappears on completion of the reaction, implicating it in the O-O bond formation reaction. We were also able to follow the structural dynamics of the protein coordinating with the catalytic complex and of channels within the protein that are important for substrate and product transport, revealing well orchestrated conformational changes in response to the electronic changes at the Mn4Ca cluster.

Autocorrelation analysis for cryo-EM with sparsity constraints: Improved sample complexity and projection-based algorithms

The number of noisy images required for molecular reconstruction in single-particle cryoelectron microscopy (cryo-EM) is governed by the autocorrelations of the observed, randomly oriented, noisy projection images. In this work, we consider the effect of imposing sparsity priors on the molecule. We use techniques from signal processing, optimization, and applied algebraic geometry to obtain theoretical and computational contributions for this challenging nonlinear inverse problem with sparsity constraints. We prove that molecular structures modeled as sums of Gaussians are uniquely determined by the second-order autocorrelation of their projection images, implying that the sample complexity is proportional to the square of the variance of the noise. This theory improves upon the nonsparse case, where the third-order autocorrelation is required for uniformly oriented particle images and the sample complexity scales with the cube of the noise variance. Furthermore, we build a computational framework to reconstruct molecular structures which are sparse in the wavelet basis. This method combines the sparse representation for the molecule with projection-based techniques used for phase retrieval in X-ray crystallography.

Low-pass spectral analysis of time-resolved serial femtosecond crystallography data

Low-pass spectral analysis (LPSA) is a recently developed dynamics retrieval algorithm showing excellent retrieval properties when applied to model data affected by extreme incompleteness and stochastic weighting. In this work, we apply LPSA to an experimental time-resolved serial femtosecond crystallography (TR-SFX) dataset from the membrane protein bacteriorhodopsin (bR) and analyze its parametric sensitivity. While most dynamical modes are contaminated by nonphysical high-frequency features, we identify two dominant modes, which are little affected by spurious frequencies. The dynamics retrieved using these modes shows an isomerization signal compatible with previous findings. We employ synthetic data with increasing timing uncertainty, increasing incompleteness level, pixel-dependent incompleteness, and photon counting errors to investigate the root cause of the high-frequency contamination of our TR-SFX modes. By testing a range of methods, we show that timing errors comparable to the dynamical periods to be retrieved produce a smearing of dynamical features, hampering dynamics retrieval, but with no introduction of spurious components in the solution, when convergence criteria are met. Using model data, we are able to attribute the high-frequency contamination of low-order dynamical modes to the high levels of noise present in the data. Finally, we propose a method to handle missing observations that produces a substantial dynamics retrieval improvement from synthetic data with a significant static component. Reprocessing of the bR TR-SFX data using the improved method yields dynamical movies with strong isomerization signals compatible with previous findings.

Inter-Bragg crystallographic phase retrieval from shape transforms, stacking faults and substitutional disorder

One of the brilliant ideas of John Spence when he saw the first diffraction patterns from the Linac Coherent Light Source was that one could solve the crystallographic phase problem by utilising the intensities between Bragg peaks. Because these intensities are due to the Fourier transform of the shape of the crystal, the approach came to be known as "shape-transform phasing." Shape-transform phasing was developed over the next ten years and formed the basis for many other interesting ideas and pursuits. Here we describe the current best implementation of the original idea using a lattice occupancy formalism and show that certain types of crystal defects can also be modelled via this approach, allowing the molecular structure to be recovered from the additional information offered by the inter-Bragg intensities from these crystal defects.

Crystal diffraction prediction and partiality estimation using Gaussian basis functions

The recent diversification of macromolecular crystallographic experiments including the use of pink beams, convergent electron diffraction and serial snapshot crystallography has shown the limitations of using the Laue equations for diffraction prediction. This article gives a computationally efficient way of calculating approximate crystal diffraction patterns given varying distributions of the incoming beam, crystal shapes and other potentially hidden parameters. This approach models each pixel of a diffraction pattern and improves data processing of integrated peak intensities by enabling the correction of partially recorded reflections. The fundamental idea is to express the distributions as weighted sums of Gaussian functions. The approach is demonstrated on serial femtosecond crystallography data sets, showing a significant decrease in the required number of patterns to refine a structure to a given error.

Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization

For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures. Competition from single-particle cryo-electron microscopy and micro-electron diffraction, increased interest in functionally relevant information that may be missing or corrupted in structures determined at cryogenic temperature, and interest in time-resolved studies of the biomolecular response to chemical and optical stimuli have driven renewed interest in data collection at room temperature and, more generally, at temperatures from the protein-solvent glass transition near 200 K to ∼350 K. Fischer has recently reviewed practical methods for room-temperature data collection and analysis [Fischer (2021), Q. Rev. Biophys. 54, e1]. Here, the key advantages and physical principles of, and methods for, crystallographic data collection at noncryogenic temperatures and some factors relevant to interpreting the resulting data are discussed. For room-temperature data collection to realize its potential within the structural biology toolkit, streamlined and standardized methods for delivering crystals prepared in the home laboratory to the synchrotron and for automated handling and data collection, similar to those for cryocrystallography, should be implemented.

Electrically stimulated droplet injector for reduced sample consumption in serial crystallography

With advances in X-ray free-electron lasers (XFELs), serial femtosecond crystallography (SFX) has enabled the static and dynamic structure determination for challenging proteins such as membrane protein complexes. In SFX with XFELs, the crystals are typically destroyed after interacting with a single XFEL pulse. Therefore, thousands of new crystals must be sequentially introduced into the X-ray beam to collect full data sets. Because of the serial nature of any SFX experiment, up to 99% of the sample delivered to the X-ray beam during its "off-time" between X-ray pulses is wasted due to the intrinsic pulsed nature of all current XFELs. To solve this major problem of large and often limiting sample consumption, we report on improvements of a revolutionary sample-saving method that is compatible with all current XFELs. We previously reported 3D-printed injection devices coupled with gas dynamic virtual nozzles (GDVNs) capable of generating samples containing droplets segmented by an immiscible oil phase for jetting crystal-laden droplets into the path of an XFEL. Here, we have further improved the device design by including metal electrodes inducing electrowetting effects for improved control over droplet generation frequency to stimulate the droplet release to matching the XFEL repetition rate by employing an electrical feedback mechanism. We report the improvements in this electrically triggered segmented flow approach for sample conservation in comparison with a continuous GDVN injection using the microcrystals of lysozyme and 3-deoxy-D-manno-octulosonate 8-phosphate synthase and report the segmented flow approach for sample injection applied at the Macromolecular Femtosecond Crystallography instrument at the Linear Coherent Light Source for the first time.

Light-induced reversible reorganizations in closed Type II reaction centre complexes: physiological roles and physical mechanisms

The purpose of this review is to outline our understanding of the nature, mechanism and physiological significance of light-induced reversible reorganizations in closed Type II reaction centre (RC) complexes. In the so-called 'closed' state, purple bacterial RC (bRC) and photosystem II (PSII) RC complexes are incapable of generating additional stable charge separation. Yet, upon continued excitation they display well-discernible changes in their photophysical and photochemical parameters. Substantial stabilization of their charge-separated states has been thoroughly documented-uncovering light-induced reorganizations in closed RCs and revealing their physiological importance in gradually optimizing the operation of the photosynthetic machinery during the dark-to-light transition. A range of subtle light-induced conformational changes has indeed been detected experimentally in different laboratories using different bRC and PSII-containing preparations. In general, the presently available data strongly suggest similar structural dynamics of closed bRC and PSII RC complexes, and similar physical mechanisms, in which dielectric relaxation processes and structural memory effects of proteins are proposed to play important roles.

Redox-controlled reorganization and flavin strain within the ribonucleotide reductase R2b-NrdI complex monitored by serial femtosecond crystallography

Redox reactions are central to biochemistry and are both controlled by and induce protein structural changes. Here, we describe structural rearrangements and crosstalk within the Bacillus cereus ribonucleotide reductase R2b-NrdI complex, a di-metal carboxylate-flavoprotein system, as part of the mechanism generating the essential catalytic free radical of the enzyme. Femtosecond crystallography at an X-ray free electron laser was utilized to obtain structures at room temperature in defined redox states without suffering photoreduction. Together with density functional theory calculations, we show that the flavin is under steric strain in the R2b-NrdI protein complex, likely tuning its redox properties to promote superoxide generation. Moreover, a binding site in close vicinity to the expected flavin O₂ interaction site is observed to be controlled by the redox state of the flavin and linked to the channel proposed to funnel the produced superoxide species from NrdI to the di-manganese site in protein R2b. These specific features are coupled to further structural changes around the R2b-NrdI interaction surface. The mechanistic implications for the control of reactive oxygen species and radical generation in protein R2b are discussed.

A hybrid approach to study large conformational transitions of biomolecules from single particle XFEL diffraction data

X-ray free-electron laser (XFEL) is the latest generation of the X-ray source that could become an invaluable technique in structural biology. XFEL has ultrashort pulse duration, extreme peak brilliance, and high spatial coherence, which could enable the observation of the biological molecules in near nature state at room temperature without crystallization. However, for biological systems, due to their low diffraction power and complexity of sample delivery, experiments and data analysis are not straightforward, making it extremely challenging to reconstruct three-dimensional (3D) structures from single particle XFEL data. Given the current limitations to the amount and resolution of the data from such XFEL experiments, we propose a new hybrid approach for characterizing biomolecular conformational transitions by using a single 2D low-resolution XFEL diffraction pattern in combination with another known conformation. In our method, we represent the molecular structure with a coarse-grained model, the Gaussian mixture model, to describe large conformational transitions from low-resolution XFEL data. We obtain plausible 3D structural models that are consistent with the XFEL diffraction pattern by deforming an initial structural model to maximize the similarity between the target pattern and the simulated diffraction patterns from the candidate models. We tested the proposed algorithm on two biomolecules of different sizes with different complexities of conformational transitions, adenylate kinase, and elongation factor 2, using synthetic XFEL data. The results show that, with the proposed algorithm, we can successfully describe the conformational transitions by flexibly fitting the coarse-grained model of one conformation to become consistent with an XFEL diffraction pattern simulated from another conformation. In addition, we showed that the incident beam orientation has some effect on the accuracy of the 3D structure modeling and discussed the reasons for the inaccuracies for certain orientations. The proposed method could serve as an alternative approach for retrieving information on 3D conformational transitions from the XFEL diffraction patterns to interpret experimental data. Since the molecules are represented by Gaussian kernels and no atomic structure is needed in principle, such a method could also be used as a tool to seek initial models for 3D reconstruction algorithms.

Skopi: a simulation package for diffractive imaging of noncrystalline biomolecules

X-ray free-electron lasers (XFELs) have the ability to produce ultra-bright femtosecond X-ray pulses for coherent diffraction imaging of biomolecules. While the development of methods and algorithms for macromolecular crystallography is now mature, XFEL experiments involving aerosolized or solvated biomolecular samples offer new challenges in terms of both experimental design and data processing. Skopi is a simulation package that can generate single-hit diffraction images for reconstruction algorithms, multi-hit diffraction images of aggregated particles for training machine learning classifiers using labeled data, diffraction images of randomly distributed particles for fluctuation X-ray scattering algorithms, and diffraction images of reference and target particles for holographic reconstruction algorithms. Skopi is a resource to aid feasibility studies and advance the development of algorithms for noncrystalline experiments at XFEL facilities.

Single-Image Super-Resolution Improvement of X-ray Single-Particle Diffraction Images Using a Convolutional Neural Network

Femtosecond X-ray pulse lasers are promising probes for the elucidation of the multiconformational states of biomolecules because they enable snapshots of single biomolecules to be observed as coherent diffraction images. Multi-image processing using an X-ray free-electron laser has proven to be a successful structural analysis method for viruses. However, the performance of single-particle analysis (SPA) for flexible biomolecules with sizes ≤100 nm remains difficult. Owing to the multiconformational states of biomolecules and noisy character of diffraction images, diffraction image improvement by multi-image processing is often ineffective for such molecules. Herein, a single-image super-resolution (SR) model was constructed using an SR convolutional neural network (SRCNN). Data preparation was performed in silico to consider the actual observation situation with unknown molecular orientations and the fluctuation of molecular structure and incident X-ray intensity. It was demonstrated that the trained SRCNN model improved the single-particle diffraction image quality, corresponding to an observed image with an incident X-ray intensity (approximately three to seven times higher than the original X-ray intensity), while retaining the individuality of the diffraction images. The feasibility of SPA for flexible biomolecules with sizes ≤100 nm was dramatically increased by introducing the SRCNN improvement at the beginning of the various structural analysis schemes.

Dynamics retrieval from stochastically weighted incomplete data by low-pass spectral analysis

Time-resolved serial femtosecond crystallography (TR-SFX) provides access to protein dynamics on sub-picosecond timescales, and with atomic resolution. Due to the nature of the experiment, these datasets are often highly incomplete and the measured diffracted intensities are affected by partiality. To tackle these issues, one established procedure is that of splitting the data into time bins, and averaging the multiple measurements of equivalent reflections within each bin. This binning and averaging often involve a loss of information. Here, we propose an alternative approach, which we call low-pass spectral analysis (LPSA). In this method, the data are projected onto the subspace defined by a set of trigonometric functions, with frequencies up to a certain cutoff. This approach attenuates undesirable high-frequency features and facilitates retrieving the underlying dynamics. A time-lagged embedding step can be included prior to subspace projection to improve the stability of the results with respect to the parameters involved. Subsequent modal decomposition allows to produce a low-rank description of the system's evolution. Using a synthetic time-evolving model with incomplete and partial observations, we analyze the LPSA results in terms of quality of the retrieved signal, as a function of the parameters involved. We compare the performance of LPSA to that of a range of other sophisticated data analysis techniques. We show that LPSA allows to achieve excellent dynamics reconstruction at modest computational cost. Finally, we demonstrate the superiority of dynamics retrieval by LPSA compared to time binning and merging, which is, to date, the most commonly used method to extract dynamical information from TR-SFX data.

A multi-million image Serial Femtosecond Crystallography dataset collected at the European XFEL

Serial femtosecond crystallography is a rapidly developing method for determining the structure of biomolecules for samples which have proven challenging with conventional X-ray crystallography, such as for membrane proteins and microcrystals, or for time-resolved studies. The European XFEL, the first high repetition rate hard X-ray free electron laser, provides the ability to record diffraction data at more than an order of magnitude faster than previously achievable, putting increased demand on sample delivery and data processing. This work describes a publicly available serial femtosecond crystallography dataset collected at the SPB/SFX instrument at the European XFEL. This dataset contains information suitable for algorithmic development for detector calibration, image classification and structure determination, as well as testing and training for future users of the European XFEL and other XFELs.

Measurement(s)	lysozyme measurement
Technology Type(s)	X-ray crystallography

Serial crystallography captures dynamic control of sequential electron and proton transfer events in a flavoenzyme

Flavin coenzymes are universally found in biological redox reactions. DNA photolyases, with their flavin chromophore (FAD), utilize blue light for DNA repair and photoreduction. The latter process involves two single-electron transfers to FAD with an intermittent protonation step to prime the enzyme active for DNA repair. Here we use time-resolved serial femtosecond X-ray crystallography to describe how light-driven electron transfers trigger subsequent nanosecond-to-microsecond entanglement between FAD and its Asn/Arg-Asp redox sensor triad. We found that this key feature within the photolyase-cryptochrome family regulates FAD re-hybridization and protonation. After first electron transfer, the FAD^•- isoalloxazine ring twists strongly when the arginine closes in to stabilize the negative charge. Subsequent breakage of the arginine-aspartate salt bridge allows proton transfer from arginine to FAD^•-. Our molecular videos demonstrate how the protein environment of redox cofactors organizes multiple electron/proton transfer events in an ordered fashion, which could be applicable to other redox systems such as photosynthesis.

Conformational alterations in unidirectional ion transport of a light-driven chloride pump revealed using X-ray free electron lasers

Light-driven chloride pumps have been identified in various species, including archaea and marine flavobacteria. The function of ion transportation controllable by light is utilized for optogenetics tools in neuroscience. Chloride pumps differ among species, in terms of amino acid homology and structural similarity. Our time-resolved crystallographic studies using X-ray free electron lasers reveal the molecular mechanism of halide ion transfer in a light-driven chloride pump from a marine flavobacterium. Our data indicate a common mechanism in chloride pumping rhodopsins, as compared to previous low-temperature trapping studies of chloride pumps. These findings are significant not only for further improvements of optogenetic tools but also for a general understanding of the ion pumping mechanisms of microbial rhodopsins.

Light-driven chloride-pumping rhodopsins actively transport anions, including various halide ions, across cell membranes. Recent studies using time-resolved serial femtosecond crystallography (TR-SFX) have uncovered the structural changes and ion transfer mechanisms in light-driven cation-pumping rhodopsins. However, the mechanism by which the conformational changes pump an anion to achieve unidirectional ion transport, from the extracellular side to the cytoplasmic side, in anion-pumping rhodopsins remains enigmatic. We have collected TR-SFX data of Nonlabens marinus rhodopsin-3 (NM-R3), derived from a marine flavobacterium, at 10-µs and 1-ms time points after photoexcitation. Our structural analysis reveals the conformational alterations during ion transfer and after ion release. Movements of the retinal chromophore initially displace a conserved tryptophan to the cytoplasmic side of NM-R3, accompanied by a slight shift of the halide ion bound to the retinal. After ion release, the inward movements of helix C and helix G and the lateral displacements of the retinal block access to the extracellular side of NM-R3. Anomalous signal data have also been obtained from NM-R3 crystals containing iodide ions. The anomalous density maps provide insight into the halide binding site for ion transfer in NM-R3.

Crystal structure of CmABCB1 multi-drug exporter in lipidic mesophase revealed by LCP-SFX

CmABCB1 is a Cyanidioschyzon merolae homolog of human ABCB1, a well known ATP-binding cassette (ABC) transporter responsible for multi-drug resistance in various cancers. Three-dimensional structures of ABCB1 homologs have revealed the snapshots of inward- and outward-facing states of the transporters in action. However, sufficient information to establish the sequential movements of the open-close cycles of the alternating-access model is still lacking. Serial femtosecond crystallography (SFX) using X-ray free-electron lasers has proven its worth in determining novel structures and recording sequential conformational changes of proteins at room temperature, especially for medically important membrane proteins, but it has never been applied to ABC transporters. In this study, 7.7 mono-acyl-glycerol with cholesterol as the host lipid was used and obtained well diffracting microcrystals of the 130 kDa CmABCB1 dimer. Successful SFX experiments were performed by adjusting the viscosity of the crystal suspension of the sponge phase with hy-droxy-propyl methyl-cellulose and using the high-viscosity sample injector for data collection at the SACLA beamline. An outward-facing structure of CmABCB1 at a maximum resolution of 2.22 Å is reported, determined by SFX experiments with crystals formed in the lipidic cubic phase (LCP-SFX), which has never been applied to ABC transporters. In the type I crystal, CmABCB1 dimers interact with adjacent molecules via not only the nucleotide-binding domains but also the transmembrane domains (TMDs); such an interaction was not observed in the previous type II crystal. Although most parts of the structure are similar to those in the previous type II structure, the substrate-exit region of the TMD adopts a different configuration in the type I structure. This difference between the two types of structures reflects the flexibility of the substrate-exit region of CmABCB1, which might be essential for the smooth release of various substrates from the transporter.

Imaging of femtosecond bond breaking and charge dynamics in ultracharged peptides

X-ray free-electrons lasers have revolutionized the method of imaging biological macromolecules such as proteins, viruses and cells by opening the door to structural determination of both single particles and crystals at room temperature. By utilizing high intensity X-ray pulses on femtosecond timescales, the effects of radiation damage can be reduced. Achieving high resolution structures will likely require knowledge of how radiation damage affects the structure on an atomic scale, since the experimentally obtained electron densities will be reconstructed in the presence of radiation damage. Detailed understanding of the expected damage scenarios provides further information, in addition to guiding possible corrections that may need to be made to obtain a damage free reconstruction. In this work, we have quantified the effects of ionizing photon-matter interactions using first principles molecular dynamics. We utilize density functional theory to calculate bond breaking and charge dynamics in three ultracharged molecules and two different structural conformations that are important to the structural integrity of biological macromolecules, comparing to our previous studies on amino acids. The effects of the ultracharged states and subsequent bond breaking in real space are studied in reciprocal space using coherent diffractive imaging of an ensemble of aligned biomolecules in the gas phase.

Mapping Enzyme Landscapes by Time-Resolved Crystallography with Synchrotron and X-Ray Free Electron Laser Light

Directly observing enzyme catalysis in real time at the molecular level has been a long-standing goal of structural enzymology. Time-resolved serial crystallography methods at synchrotron and X-ray free electron laser (XFEL) sources have enabled researchers to follow enzyme catalysis and other nonequilibrium events at ambient conditions with unprecedented time resolution. X-ray crystallography provides detailed information about conformational heterogeneity and protein dynamics, which is enhanced when time-resolved approaches are used. This review outlines the ways in which information about the underlying energy landscape of a protein can be extracted from X-ray crystallographic data, with an emphasis on new developments in XFEL and synchrotron time-resolved crystallography. The emerging view of enzyme catalysis afforded by these techniques can be interpreted as enzymes moving on a time-dependent energy landscape. Some consequences of this view are discussed, including the proposal that irreversible enzymes or enzymes that use covalent catalytic mechanisms may commonly exhibit catalysis-activated motions. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Microcrystal electron diffraction in macromolecular and pharmaceutical structure determination

Microcrystal electron diffraction (MicroED) has recently shown to be a promising technique for structure determination in structural biology and pharmaceutical chemistry. Here, we discuss the unique properties of electrons and motivate its use for diffraction experiments. We review the latest developments in MicroED, and illustrate its applications in macromolecular crystallography, fragment screening and structure guided drug discovery. We discuss the perspectives of MicroED in synthetic chemistry and pharmaceutical development. We anticipate that the rapid advances MicroED showcased here will promote further development of electron crystallography and open up new opportunities for drug discovery.

Finding order in chaos - nanocrystals in amorphous protein gels

Measurements of protein dense phases reveal the presence of highly ordered protein nanostructures. Such phases may be candidates for structural biology measurements on next-generation instruments for molecules that are difficult or impossible to crystallize.

MicroED for the study of protein–ligand interactions and the potential for drug discovery

Microcrystal electron diffraction (MicroED) is an electron cryo-microscopy (cryo-EM) technique used to determine molecular structures with crystals that are a millionth the size needed for traditional single-crystal X-ray crystallography. An exciting use of MicroED is in drug discovery and development, where it can be applied to the study of proteins and small molecule interactions, and for structure determination of natural products. The structures are then used for rational drug design and optimization. In this Perspective, we discuss the current applications of MicroED for structure determination of protein-ligand complexes and potential future applications in drug discovery.

Metalloprotein catalysis: structural and mechanistic insights into oxidoreductases from neutron protein crystallography

Metalloproteins catalyze a range of reactions, with enhanced chemical functionality due to their metal cofactor. The reaction mechanisms of metalloproteins have been experimentally characterized by spectroscopy, macromolecular crystallography and cryo-electron microscopy. An important caveat in structural studies of metalloproteins remains the artefacts that can be introduced by radiation damage. Photoreduction, radiolysis and ionization deriving from the electromagnetic beam used to probe the structure complicate structural and mechanistic interpretation. Neutron protein diffraction remains the only structural probe that leaves protein samples devoid of radiation damage, even when data are collected at room temperature. Additionally, neutron protein crystallography provides information on the positions of light atoms such as hydrogen and deuterium, allowing the characterization of protonation states and hydrogen-bonding networks. Neutron protein crystallography has further been used in conjunction with experimental and computational techniques to gain insight into the structures and reaction mechanisms of several transition-state metal oxidoreductases with iron, copper and manganese cofactors. Here, the contribution of neutron protein crystallography towards elucidating the reaction mechanism of metalloproteins is reviewed.

The Natural Breakup Length of a Steady Capillary Jet: Application to Serial Femtosecond Crystallography

One of the most successful ways to introduce samples in Serial Femtosecond Crystallography has been the use of microscopic capillary liquid jets produced by gas flow focusing, whose length-to-diameter ratio and velocity are essential to fulfill the requirements of the high pulse rates of current XFELs. In this work, we demonstrate the validity of a classical scaling law with two universal constants to calculate that length as a function of the liquid properties and operating conditions. These constants are determined by fitting the scaling law to a large set of experimental and numerical measurements, including previously published data. Both the experimental and numerical jet lengths conform remarkably well to the proposed scaling law. We show that, while a capillary jet is a globally unstable system to linear perturbations above a critical length, its actual and shorter long-term average intact length is determined by the nonlinear perturbations coming from the jet breakup itself. Therefore, this length is determined solely by the properties of the liquid, the average velocity of the liquid and the flow rate expelled. This confirms the very early observations from Smith and Moss 1917, Proc R Soc Lond A Math Phys Eng, 93, 373, to McCarthy and Molloy 1974, Chem Eng J, 7, 1, among others, while it contrasts with the classical conception of temporal stability that attributes the natural breakup length to the jet birth conditions in the ejector or small interactions with the environment.

Protocol for Retrieving Three-Dimensional Biological Shapes for a Few XFEL Single-Particle Diffraction Patterns

X-ray free-electron laser (XFEL) scattering promises to probe single biomolecular complexes without crystallization, enabling the study of biomolecular structures under near-physiological conditions at room temperature. However, such structural determination of biomolecules is extremely challenging thus far. In addition to the large numbers of diffraction patterns required, the orientation of each diffraction pattern needs to be accurately estimated and the missing phase information needs to be recovered for three-dimensional (3D) structure reconstruction. Given the current limitations to the amount and resolution of the data available from single-particle XFEL scattering experiments, we propose an alternative approach to find plausible 3D biological shapes from a limited number of diffraction patterns to serve as a starting point for further analyses. In our proposed strategy, small sets of input (e.g., five) XFEL diffraction patterns were matched against a library of diffraction patterns simulated from 1628 electron microscopy (EM) models to find potential matching 3D models that are consistent with the input diffraction patterns. This approach was tested for three example cases: EMD-3457 (Thermoplasma acidophilum 20S proteasome), EMD-5141 (Escherichia coli 70S ribosome complex), and EMD-5152 (budding yeast Nup84 complex). We observed that choosing the best strategy to define matching regions on the diffraction patterns is critical for identifying correctly matching diffraction patterns. While increasing the number of input diffraction patterns improved the matches in some cases, we found that the resulting matches are more dependent on the uniqueness or complexity of the shape as captured in the individual input diffraction patterns and the availability of a similar 3D biological shape in the search library. The protocol could be useful for finding candidate models for a limited amount of low-resolution data, even when insufficient for reconstruction, performing a quick exploration of new data upon collection, and the analysis of the conformational heterogeneity of the particle of interest as captured within the diffraction patterns.

Protein orientation in time-dependent electric fields: orientation before destruction

Proteins often have nonzero electric dipole moments, making them interact with external electric fields and offering a means for controlling their orientation. One application that is known to benefit from orientation control is single-particle imaging with x-ray free-electron lasers, in which diffraction is recorded from proteins in the gas phase to determine their structures. To this point, theoretical investigations into this phenomenon have assumed that the field experienced by the proteins is constant or a perfect step function, whereas any real-world pulse will be smooth. Here, we explore the possibility of orienting gas-phase proteins using time-dependent electric fields. We performed ab initio simulations to estimate the field strength required to break protein bonds, with 45 V/nm as a breaking point value. We then simulated ubiquitin in time-dependent electric fields using classical molecular dynamics. The minimal field strength required for orientation within 10 ns was on the order of 0.5 V/nm. Although high fields can be destructive for the structure, the structures in our simulations were preserved until orientation was achieved regardless of field strength, a principle we denote “orientation before destruction.”

Detecting anomalies in X-ray diffraction images using convolutional neural networks

Our understanding of life is based upon the interpretation of macromolecular structures and their dynamics. Almost 90% of currently known macromolecular models originated from electron density maps constructed using X-ray diffraction images. Even though diffraction images are critical for structure determination, due to their vast amounts and noisy, non-intuitive nature, their quality is rarely inspected. In this paper, we use recent advances in machine learning to automatically detect seven types of anomalies in X-ray diffraction images. For this purpose, we utilize a novel X-ray beam center detection algorithm, propose three different image representations, and compare the predictive performance of general-purpose classifiers and deep convolutional neural networks (CNNs). In benchmark tests on a set of 6,311 X-ray diffraction images, the proposed CNN achieved between 87% and 99% accuracy depending on the type of anomaly. Experimental results show that the proposed anomaly detection system can be considered suitable for early detection of sub-optimal data collection conditions and malfunctions at X-ray experimental stations.

Biophysical applications in structural and molecular biology

The main objective of structural biology is to model proteins and other biological macromolecules and link the structural information to function and dynamics. The biological functions of protein molecules and nucleic acids are inherently dependent on their conformational dynamics. Imaging of individual molecules and their dynamic characteristics is an ample source of knowledge that brings new insights about mechanisms of action. The atomic-resolution structural information on most of the biomolecules has been solved by biophysical techniques; either by X-ray diffraction in single crystals or by nuclear magnetic resonance (NMR) spectroscopy in solution. Cryo-electron microscopy (cryo-EM) is emerging as a new tool for analysis of a larger macromolecule that couldn't be solved by X-ray crystallography or NMR. Now a day's low-resolution Cryo-EM is used in combination with either X-ray crystallography or NMR. The present review intends to provide updated information on applications like X-ray crystallography, cryo-EM and NMR which can be used independently and/or together in solving structures of biological macromolecules for our full comprehension of their biological mechanisms.

Discerning best practices in XFEL-based biological crystallography - standards for nonstandard experiments

Serial femtosecond crystallography (SFX) at X-ray free-electron lasers (XFELs) is a novel tool in structural biology. In contrast to conventional crystallography, SFX relies on merging partial intensities acquired with X-ray beams of often randomly fluctuating properties from a very large number of still diffraction images of generally randomly oriented microcrystals. For this reason, and possibly due to limitations of the still evolving data-analysis programs, XFEL-derived SFX data are typically of a lower quality than 'standard' crystallographic data. In contrast with this, the studies performed at XFELs often aim to investigate issues that require precise high-resolution data, for example to determine structures of intermediates at low occupancy, which often display very small conformational changes. This is a potentially dangerous combination and underscores the need for a critical evaluation of procedures including data-quality standards in XFEL-based structural biology. Here, such concerns are addressed.

Resonant X-ray emission spectroscopy from broadband stochastic pulses at an X-ray free electron laser

Hard X-ray spectroscopy is an element specific probe of electronic state, but signals are weak and require intense light to study low concentration samples. Free electron laser facilities offer the highest intensity X-rays of any available light source. The light produced at such facilities is stochastic, with spikey, broadband spectra that change drastically from shot to shot. Here, using aqueous ferrocyanide, we show that the resonant X-ray emission (RXES) spectrum can be inferred by correlating for each shot the fluorescence intensity from the sample with spectra of the fluctuating, self-amplified spontaneous emission (SASE) source. We obtain resolved narrow and chemically rich information in core-to-valence transitions of the pre-edge region at the Fe K-edge. Our approach avoids monochromatization, provides higher photon flux to the sample, and allows non-resonant signals like elastic scattering to be simultaneously recorded. The spectra obtained match well with spectra measured using a monochromator. We also show that inaccurate measurements of the stochastic light spectra reduce the measurement efficiency of our approach.

Advancements in macromolecular crystallography: from past to present

Protein Crystallography or Macromolecular Crystallography (MX) started as a new discipline of science with the pioneering work on the determination of the protein crystal structures by John Kendrew in 1958 and Max Perutz in 1960. The incredible achievements in MX are attributed to the development of advanced tools, methodologies, and automation in every aspect of the structure determination process, which have reduced the time required for solving protein structures from years to a few days, as evident from the tens of thousands of crystal structures of macromolecules available in PDB. The advent of brilliant synchrotron sources, fast detectors, and novel sample delivery methods has shifted the paradigm from static structures to understanding the dynamic picture of macromolecules; further propelled by X-ray Free Electron Lasers (XFELs) that explore the femtosecond regime. The revival of the Laue diffraction has also enabled the understanding of macromolecules through time-resolved crystallography. In this review, we present some of the astonishing method-related and technological advancements that have contributed to the progress of MX. Even with the rapid evolution of several methods for structure determination, the developments in MX will keep this technique relevant and it will continue to play a pivotal role in gaining unprecedented atomic-level details as well as revealing the dynamics of biological macromolecules. With many exciting developments awaiting in the upcoming years, MX has the potential to contribute significantly to the growth of modern biology by unraveling the mechanisms of complex biological processes as well as impacting the area of drug designing.

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MALTIR) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88TIR). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MALTIR. We demonstrate via mutagenesis that the MyD88TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88TIR. Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

X-ray-Based Techniques to Study the Nano-Bio Interface

X-ray-based analytics are routinely applied in many fields, including physics, chemistry, materials science, and engineering. The full potential of such techniques in the life sciences and medicine, however, has not yet been fully exploited. We highlight current and upcoming advances in this direction. We describe different X-ray-based methodologies (including those performed at synchrotron light sources and X-ray free-electron lasers) and their potentials for application to investigate the nano-bio interface. The discussion is predominantly guided by asking how such methods could better help to understand and to improve nanoparticle-based drug delivery, though the concepts also apply to nano-bio interactions in general. We discuss current limitations and how they might be overcome, particularly for future use in vivo.

New perspectives in macromolecular powder diffraction using single-photon-counting strip detectors: high-resolution structure of the pharmaceutical peptide octreotide

Advances in instrumentation, as well as the development of powerful crystallographic software have significantly facilitated the collection of high-resolution diffraction data and have made X-ray powder diffraction (XRPD) particularly useful for the extraction of structural information; this is true even for complex molecules, especially when combined with synchrotron radiation. In this study, in-line with past instrumental profile studies, an improved data collection strategy exploiting the MYTHEN II detector system together with significant beam focusing and tailored data collection options was introduced and optimized for protein samples at the Material Science beamline at the Swiss Light Source. Polycrystalline precipitates of octreotide, a somatostatin analog of particular pharmaceutical interest, were examined with this novel approach. XRPD experiments resulted in high angular and d-spacing (1.87 Å) resolution data, from which electron-density maps of enhanced quality were extracted, revealing the molecule's structural properties. Since microcrystalline precipitates represent a viable alternative for administration of therapeutic macromolecules, XRPD has been acknowledged as the most applicable tool for examining a wide spectrum of physicochemical properties of such materials and performing studies ranging from phase identification to complete structural characterization.

Macromolecular crystallography using microcrystal electron diffraction

Microcrystal electron diffraction (MicroED) has recently emerged as a promising method for macromolecular structure determination in structural biology. Since the first protein structure was determined in 2013, the method has been evolving rapidly. Several protein structures have been determined and various studies indicate that MicroED is capable of (i) revealing atomic structures with charges, (ii) solving new protein structures by molecular replacement, (iii) visualizing ligand-binding interactions and (iv) determining membrane-protein structures from microcrystals embedded in lipidic mesophases. However, further development and optimization is required to make MicroED experiments more accurate and more accessible to the structural biology community. Here, we provide an overview of the current status of the field, and highlight the ongoing development, to provide an indication of where the field may be going in the coming years. We anticipate that MicroED will become a robust method for macromolecular structure determination, complementing existing methods in structural biology.

Beyond X-rays: an overview of emerging structural biology methods

Structural biologists rely on X-ray crystallography as the main technique for determining the three-dimensional structures of macromolecules; however, in recent years, new methods that go beyond X-ray-based technologies are broadening the selection of tools to understand molecular structure and function. Simultaneously, national facilities are developing programming tools and maintaining personnel to aid novice structural biologists in de novo structure determination. The combination of X-ray free electron lasers (XFELs) and serial femtosecond crystallography (SFX) now enable time-resolved structure determination that allows for capture of dynamic processes, such as reaction mechanism and conformational flexibility. XFEL and SFX, along with microcrystal electron diffraction (MicroED), help side-step the need for large crystals for structural studies. Moreover, advances in cryogenic electron microscopy (cryo-EM) as a tool for structure determination is revolutionizing how difficult to crystallize macromolecules and/or complexes can be visualized at the atomic scale. This review aims to provide a broad overview of these new methods and to guide readers to more in-depth literature of these methods.

C-phycocyanin as a highly attractive model system in protein crystallography: unique crystallization properties and packing-diversity screening

The unique crystallization properties of the antenna protein C-phycocyanin (C-PC) from the thermophilic cyanobacterium Thermosynechococcus elongatus are reported and discussed. C-PC crystallizes in hundreds of significantly different conditions within a broad pH range and in the presence of a wide variety of precipitants and additives. Remarkably, the crystal dimensions vary from a few micrometres, as used in serial crystallography, to several hundred micrometres, with a very diverse crystal morphology. More than 100 unique single-crystal X-ray diffraction data sets were collected from randomly selected crystals and analysed. The addition of small-molecule additives revealed three new crystal packings of C-PC, which are discussed in detail. The high propensity of this protein to crystallize, combined with its natural blue colour and its fluorescence characteristics, make it an excellent candidate as a superior and highly adaptable model system in crystallography. C-PC can be used in technical and methods development approaches for X-ray and neutron diffraction techniques, and as a system for comprehending the fundamental principles of protein crystallography.

An encryption-decryption framework to validating single-particle imaging

We propose an encryption-decryption framework for validating diffraction intensity volumes reconstructed using single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) when the ground truth volume is absent. This conceptual framework exploits each reconstructed volumes' ability to decipher latent variables (e.g. orientations) of unseen sentinel diffraction patterns. Using this framework, we quantify novel measures of orientation disconcurrence, inconsistency, and disagreement between the decryptions by two independently reconstructed volumes. We also study how these measures can be used to define data sufficiency and its relation to spatial resolution, and the practical consequences of focusing XFEL pulses to smaller foci. This conceptual framework overcomes critical ambiguities in using Fourier Shell Correlation (FSC) as a validation measure for SPI. Finally, we show how this encryption-decryption framework naturally leads to an information-theoretic reformulation of the resolving power of XFEL-SPI, which we hope will lead to principled frameworks for experiment and instrument design.

Dynamic Structural Biology Experiments at XFEL or Synchrotron Sources

Macromolecular crystallography (MX) leverages the methods of physics and the language of chemistry to reveal fundamental insights into biology. Often beautifully artistic images present MX results to support profound functional hypotheses that are vital to entire life science research community. Over the past several decades, synchrotrons around the world have been the workhorses for X-ray diffraction data collection at many highly automated beamlines. The newest tools include X-ray-free electron lasers (XFELs) located at facilities in the USA, Japan, Korea, Switzerland, and Germany that deliver about nine orders of magnitude higher brightness in discrete femtosecond long pulses. At each of these facilities, new serial femtosecond crystallography (SFX) strategies exploit slurries of micron-size crystals by rapidly delivering individual crystals into the XFEL X-ray interaction region, from which one diffraction pattern is collected per crystal before it is destroyed by the intense X-ray pulse. Relatively simple adaptions to SFX methods produce time-resolved data collection strategies wherein reactions are triggered by visible light illumination or by chemical diffusion/mixing. Thus, XFELs provide new opportunities for high temporal and spatial resolution studies of systems engaged in function at physiological temperature. In this chapter, we summarize various issues related to microcrystal slurry preparation, sample delivery into the X-ray interaction region, and some emerging strategies for time-resolved SFX data collection.

Beyond integration: modeling every pixel to obtain better structure factors from stills

Most crystallographic data processing methods use pixel integration. In serial femtosecond crystallography (SFX), the intricate interaction between the reciprocal lattice point and the Ewald sphere is integrated out by averaging symmetrically equivalent observations recorded across a large number (104-106) of exposures. Although sufficient for generating biological insights, this approach converges slowly, and using it to accurately measure anomalous differences has proved difficult. This report presents a novel approach for increasing the accuracy of structure factors obtained from SFX data. A physical model describing all observed pixels is defined to a degree of complexity such that it can decouple the various contributions to the pixel intensities. Model dependencies include lattice orientation, unit-cell dimensions, mosaic structure, incident photon spectra and structure factor amplitudes. Maximum likelihood estimation is used to optimize all model parameters. The application of prior knowledge that structure factor amplitudes are positive quantities is included in the form of a reparameterization. The method is tested using a synthesized SFX dataset of ytterbium(III) lysozyme, where each X-ray laser pulse energy is centered at 9034 eV. This energy is 100 eV above the Yb3+ L-III absorption edge, so the anomalous difference signal is stable at 10 electrons despite the inherent energy jitter of each femtosecond X-ray laser pulse. This work demonstrates that this approach allows the determination of anomalous structure factors with very high accuracy while requiring an order-of-magnitude fewer shots than conventional integration-based methods would require to achieve similar results.

Serial Crystallography for Structure-Based Drug Discovery

Rational drug discovery has greatly accelerated the development of safer and more efficacious therapeutics, assisted significantly by insights from experimentally determined 3D structures of ligands in complex with their targets. Serial crystallography (SX) with X-ray free-electron lasers has enabled structural determination using micrometer- or nanometer-size crystals. This technology, applied in the past decade to solve structures of notoriously difficult-to-study drug targets at room temperature, has now been adapted for use in synchrotron radiation facilities. Ultrashort time scales allow time-resolved characterization of dynamic structural changes and pave the road to study the molecular mechanisms by 'molecular movie.' This article summarizes the latest progress in SX technology and deliberates its demanding applications in future structure-based drug discovery.

Advances in long-wavelength native phasing at X-ray free-electron lasers

Long-wavelength pulses from the Swiss X-ray free-electron laser (XFEL) have been used for de novo protein structure determination by native single-wavelength anomalous diffraction (native-SAD) phasing of serial femtosecond crystallography (SFX) data. In this work, sensitive anomalous data-quality indicators and model proteins were used to quantify improvements in native-SAD at XFELs such as utilization of longer wavelengths, careful experimental geometry optimization, and better post-refinement and partiality correction. Compared with studies using shorter wavelengths at other XFELs and older software versions, up to one order of magnitude reduction in the required number of indexed images for native-SAD was achieved, hence lowering sample consumption and beam-time requirements significantly. Improved data quality and higher anomalous signal facilitate so-far underutilized de novo structure determination of challenging proteins at XFELs. Improvements presented in this work can be used in other types of SFX experiments that require accurate measurements of weak signals, for example time-resolved studies.

Pixel modelling - a new age in SFX data analysis

A new program, diffBragg, employs per-pixel maximum likelihood optimization of X-ray pulse and crystal parameters to improve the accuracy of structure factor amplitudes attainable in SFX experiments.

Recent results in time resolved serial femtosecond crystallography at XFELs

Time-resolved serial femtosecond crystallography (tr-SFX) methods exploit slurries of crystalline samples that range in size from hundreds of nanometers to a few tens of micrometers, at near-physiological temperature and pressure, to generate atomic resolution models and probe authentic function with the same experiment. 'Dynamic structural biology' is often used to encompass the research philosophy and techniques. Reaction cycles for tr-SFX studies are initiated by photons or ligand addition/mixing strategies, wherein the latter are potentially generalizable across enzymology. Thus, dynamic structural biology often creates stop-motion molecular movies of macromolecular function. In metal-dependent systems, complementary spectroscopic information can also be collected from the same samples and X-ray pulses, which provides even more detailed mechanistic insights. These types of experimental data also complement quantum mechanical and classical dynamics numerical calculations. Correlated structural-functional results will yield more detailed mechanistic insights and will likely translate into better drugs and treatments impacting human health, and better catalysis for clean energy and agriculture.

Crystallization of ApoA1 and ApoE4 nanolipoprotein particles and initial XFEL-based structural studies

Nanolipoprotein particles (NLPs), also called “nanodiscs”, are discoidal particles with a patch of lipid bilayer corralled by apolipoproteins. NLPs have long been of interest due to both their utility as membrane-model systems into which membrane proteins can be inserted and solubilized and their physiological role in lipid and cholesterol transport via HDL and LDL maturation, which are important for human health. Serial femtosecond crystallography (SFX) at X-ray free electron lasers (XFELs) is a powerful approach for structural biology of membrane proteins, which are traditionally difficult to crystallize as large single crystals capable of producing high-quality diffraction suitable for structure determination. To facilitate understanding of the specific role of two apolipoprotein/lipid complexes, ApoA1 and ApoE4, in lipid binding and HDL/LDL particle maturation dynamics and develop new SFX methods involving NLP membrane protein encapsulation, we have prepared and crystallized homogeneous populations of ApoA1 and ApoE4 NLPs. Crystallization of empty NLPs yields semi-ordered objects that appear crystalline and give highly anisotropic and diffuse X-ray diffraction, similar in characteristics to fiber diffraction. Several unit cell parameters were approximately determined for both NLPs from these measurements. Thus, low-background, sample conservative methods of delivery are critical. Here we implemented a fixed target sample delivery scheme utilizing the Roadrunner fast-scanning system and ultra-thin polymer/graphene support films, providing a low-volume, low-background approach to membrane protein SFX. This study represents initial steps in obtaining structural information for ApoA1 and ApoE4 NLPs and developing this system as a supporting scaffold for future structural studies of membrane proteins crystalized in a native lipid environment.