The effect of boron in BxGa1−xN/SiC heteroepitaxy was established by X-ray diffraction reciprocal-space maps on symmetric 0002 and asymmetric 11 {overline 2} 4 reflections. The density of screw and edge threading dislocations was quantified in the framework of the mosaic model.

BGaN epilayers with boron contents up to 5.6% were grown on SiC substrates by metal–organic chemical vapor deposition. The effects of boron incorporation on the structural and optical properties were studied by high-resolution X-ray diffraction (XRD), atomic force microscopy (AFM), Raman spectroscopy and photoluminescence (PL) spectroscopy. XRD reciprocal-space maps around the symmetric 0002 and asymmetric 11 {overline 2} 4 reflections allowed evaluation of the lattice constants and lattice mismatch with respect to the underlying substrate. XRD rocking curves and AFM measurements indicated the mosaic microstructure of the epilayer. The impact of boron content on crystallite size, tilt and twist is evaluated and the correlation with threading dislocation density is discussed. The deterioration of optical properties with increasing boron content was assessed by Raman and PL spectroscopy.

The results of a study of the structural and reflective characteristics of short-period multilayer X-ray mirrors based on Mo/B4C at wavelengths 1.54 Å, 9.89 Å and 17.59 Å are presented. The period of the samples varied in the range 8–35 Å. The average widths of the interfaces were ∼3.5 and 2.2 Å at one and the other boundaries, with a tendency for weak growth with any decrease in the period. The interlayer roughness was ∼1 Å. The research results indicate promising prospects for the use of multilayer Mo/B4C mirrors for synchrotron applications.

The ForMAX beamline at the MAX IV Laboratory provides multiscale and multimodal structural characterization of hierarchical materials in the nanometre to millimetre range by combining small- and wide-angle X-ray scattering with full-field microtomography. The modular design of the beamline is optimized for easy switching between different experimental modalities. The beamline has a special focus on the development of novel fibrous materials from forest resources, but it is also well suited for studies within, for example, food science and biomedical research.

Hard X-ray absorption spectroscopy is a valuable in situ probe for non-destructive diagnostics of metal sites. The low-energy interval of a spectrum (XANES) contains information about the metal oxidation state, ligand type, symmetry and distances in the first coordination shell but shows almost no dependency on the bridged metal–metal bond length. The higher-energy interval (EXAFS), on the contrary, is more sensitive to the coordination numbers and can decouple the contribution from distances in different coordination shells. Supervised machine-learning methods can combine information from different intervals of a spectrum; however, computational approaches for the near-edge region of the spectrum and higher energies are different. This work aims to keep all benefits of XANES and extend its sensitivity towards the interatomic distances in the first and second coordination shells. Using a binuclear bridged copper complex as a case study and cross-validation analysis as a quantitative tool it is shown that the first 170 eV above the edge are already sufficient to balance the contributions of Cu–O/N scattering and Cu–Cu scattering. As a more general outcome this work highlights the trivial but often overlooked importance of using `longer' energy intervals of XANES for structural refinement and machine-learning predictions. The first 200 eV above the absorption edge still do not require parametrization of Debye–Waller damping and can be calculated within full multiple scattering or finite difference approximations with only moderately increased computational costs.

X-ray and neutron scattering have long been used for structural characterization of cellulose in plants. Due to averaging over the illuminated sample volume, these measurements traditionally overlooked the compositional and morphological heterogeneity within the sample. Here, a scanning tomographic imaging method is described, using contrast derived from the X-ray scattering intensity, for virtually sectioning the sample to reveal its internal structure at a resolution of a few micrometres. This method provides a means for retrieving the local scattering signal that corresponds to any voxel within the virtual section, enabling characterization of the local structure using traditional data-analysis methods. This is accomplished through tomographic reconstruction of the spatial distribution of a handful of mathematical components identified by non-negative matrix factorization from the large dataset of X-ray scattering intensity. Joint analysis of multiple datasets, to find similarity between voxels by clustering of the decomposed data, could help elucidate systematic differences between samples, such as those expected from genetic modifications, chemical treatments or fungal decay. The spatial distribution of the microfibril angle can also be analyzed, based on the tomographically reconstructed scattering intensity as a function of the azimuthal angle.

The inherent ambiguity in reconstructed images from coherent diffraction imaging (CDI) poses an intrinsic challenge, as images derived from the same dataset under varying initial conditions often display inconsistencies. This study introduces a method that employs the Noise2Noise approach combined with neural networks to effectively mitigate these ambiguities. We applied this methodology to hundreds of ambiguous reconstructed images retrieved from a single diffraction pattern using a conventional retrieval algorithm. Our results demonstrate that ambiguous features in these reconstructions are effectively treated as inter-reconstruction noise and are significantly reduced. The post-Noise2Noise treated images closely approximate the average and singular value decomposition analysis of various reconstructions, providing consistent and reliable reconstructions.

The crystal structure of 1,4-bis­(neopent­yloxy)pillar[5]arene, C95H140N2O10 (TbuP), featuring two encapsulated pyridine mol­ecules, reveals significant host–guest inter­actions. Inter­estingly, the pyridine guests are positioned near the neopent­yloxy substituents instead of the electron-rich aromatic core of the pillar[5]arene. This spatial arrangement suggests a preference for the pyridine mol­ecules to engage with the aliphatic regions of the host. Detailed analysis of the structural characteristics of this host–guest system (TbuP·2Py), as well as its packing pattern within the crystal network, is presented and discussed.

The structures of five ammonium salt forms of mono­sulfonated azo dyes, derivatives of 4-(2-phenyldiazen-1-yl)benzenesulfonate, with the general formula [NH4][O3S(C6H4)NN(C6H3)RR']·XH2O [R = OH, NH2 or N(C2H4OH)2; R' = H or OH] are presented. All form simple layered structures with alternating hydro­phobic (organic) and hydro­philic (cation, solvent and polar groups) layers. To assess for isostructural behaviour of the ammonium cation with M+ ions, the packing of these structures is compared with literature examples. To aid this comparison, the corresponding structures of four potassium salt forms of the mono­sulfonated azo dyes are also presented herein. Of the five ammonium salts it is found that three have isostructural equivalents. In two cases this equivalent is a potassium salt form and in one case it is a rubidium salt form. The isostructurality of ion packing and of unit-cell symmetry and dimensions tolerates cases where the ammonium ions form somewhat different inter­action types with coformer species than do the potassium or rubidium ions. No sodium salt forms are found to be isostructural with any ammonium equivalent. However, similarities in the anion packing within a single hydro­phobic layer are found for a group that consists of the ammonium and rubidium salt forms of one azo anion species and the sodium and silver salt forms of a different azo species.

Beauveriolides, including the main beauveriolide I {systematic name: (3R,6S,9S,13S)-9-benzyl-13-[(2S)-hexan-2-yl]-6-methyl-3-(2-methyl­prop­yl)-1-oxa-4,7,10-tri­aza­cyclo­tridecane-2,5,8,11-tetrone, C27H41N3O5}, are a series of cyclo­depsipeptides that have shown promising results in the treatment of Alzheimer's disease and in the prevention of foam cell formation in atherosclerosis. Their crystal structure studies have been difficult due to their tiny crystal size and fibre-like morphology, until now. Recent developments in 3D electron diffraction methodology have made it possible to accurately study the crystal structures of submicron crystals by overcoming the problems of beam sensitivity and dynamical scattering. In this study, the absolute structure of beauveriolide I was determined by 3D electron diffraction. The cyclo­dep­si­peptide crystallizes in the space group I2 with lattice parameters a = 40.2744 (4), b = 5.0976 (5), c = 27.698 (4) Å and β = 105.729 (6)°. After dynamical refinement, its absolute structure was determined by comparing the R factors and calculating the z-scores of the two possible enanti­omorphs of beauveriolide I.

The synthesis and structural characterization of three families of coordination com­plexes synthesized from 4'-phenyl-2,2':6',2''-terpyridine (8, Ph-TPY), 4'-(4-chloro­phen­yl)-2,2':6',2''-terpyridine (9, ClPh-TPY) and 4'-(4-meth­oxy­phen­yl)-2,2':6',2''-terpyridine (10, MeOPh-TPY) ligands with the divalent metals Co2+, Fe2+, Mn2+ and Ni2+ are reported. The com­pounds were synthesized from a 1:2 mixture of the metal and ligand, resulting in a series of com­plexes with the general formula [M(R-TPY)2](ClO4)2 (where M = Co2+, Fe2+, Mn2+ and Ni2+, and R-TPY = Ph-TPY, ClPh-TPY and MeOPh-TPY). The general formula and structural and supra­molecular features were determinated by single-crystal X-ray diffraction for bis­(4'-phenyl-2,2':6',2''-terpyridine)­nickel(II) bis­(per­chlo­rate), [Ni(C21H15N3)2](ClO4)2 or [Ni(Ph-TPY)2](ClO4)2, bis­[4'-(4-meth­oxy­phen­yl)-2,2':6',2''-terpyridine]­manganese(II) bis­(per­chlo­rate), [Mn(C22H17N3O)2](ClO4)2 or [Mn(MeOPh-TPY)2](ClO4)2, and bis­(4'-phenyl-2,2':6',2''-ter­py­ridine)­manganese(II) bis­(per­chlo­rate), [Mn(C21H15N3)2](ClO4)2 or [Mn(Ph-TPY)2](ClO4)2. In all three cases, the com­plexes present distorted octa­hedral coordination polyhedra and the crystal packing is determined mainly by weak C—H⋯π inter­actions. All the com­pounds (except for the Ni derivatives, for which FT–IR, UV–Vis and thermal analysis are reported) were fully characterized by spectroscopic (FT–IR, UV–Vis and NMR spectroscopy) and thermal (TGA–DSC, thermogravimetric analysis–differential scanning calorimetry) methods.

The crystal structure of the salt calcium (2R,3R)-tar­trate tetra­hydrate {sys­tem­atic name: poly[[di­aqua­[μ4-(2R,3R)-2,3-di­hydroxy­butane­dioato]calcium(II)] di­hydrate]}, {[Ca(C4H8O8)(H2O)2]·2H2O}n, is reported. The absolute configuration of the crystal was established unambiguously using anomalous dispersion effects in the diffraction patterns. High-quality data also allowed the location and free refinement of all the H atoms, and therefore to a careful analysis of the hy­dro­gen-bond inter­actions.

Phenuiviridae nucleoprotein is the main structural and functional component of the viral cycle, protecting the viral RNA and mediating the essential replication/transcription processes. The nucleoprotein (N) binds the RNA using its globular core and polymerizes through the N-terminus, which is presented as a highly flexible arm, as demonstrated in this article. The nucleoprotein exists in an `open' or a `closed' conformation. In the case of the closed conformation the flexible N-terminal arm folds over the RNA-binding cleft, preventing RNA adsorption. In the open conformation the arm is extended in such a way that both RNA adsorption and N polymerization are possible. In this article, single-crystal X-ray diffraction and small-angle X-ray scattering were used to study the N protein of Toscana virus complexed with a single-chain camelid antibody (VHH) and it is shown that in the presence of the antibody the nucleoprotein is unable to achieve a functional assembly to form a ribonucleoprotein complex.

The axoneme, a microtubule-based array at the center of every cilium, has been the subject of structural investigations for decades, but only recent advances in cryo-EM and cryo-ET have allowed a molecular-level interpretation of the entire complex to be achieved. The unique properties of the nine doublet microtubules and central pair of singlet microtubules that form the axoneme, including the highly decorated tubulin lattice and the docking of massive axonemal complexes, provide opportunities and challenges for sample preparation, 3D reconstruction and atomic modeling. Here, the approaches used for cryo-EM and cryo-ET of axonemes are reviewed, while highlighting the unique opportunities provided by the latest generation of AI-guided tools that are transforming structural biology.

The expansive scientific software ecosystem, characterized by millions of titles across various platforms and formats, poses significant challenges in maintaining reproducibility and provenance in scientific research. The diversity of independently developed applications, evolving versions and heterogeneous components highlights the need for rigorous methodologies to navigate these complexities. In response to these challenges, the SBGrid team builds, installs and configures over 530 specialized software applications for use in the on-premises and cloud-based computing environments of SBGrid Consortium members. To address the intricacies of supporting this diverse application collection, the team has developed the Capsule Software Execution Environment, generally referred to as Capsules. Capsules rely on a collection of programmatically generated bash scripts that work together to isolate the runtime environment of one application from all other applications, thereby providing a transparent cross-platform solution without requiring specialized tools or elevated account privileges for researchers. Capsules facilitate modular, secure software distribution while maintaining a centralized, conflict-free environment. The SBGrid platform, which combines Capsules with the SBGrid collection of structural biology applications, aligns with FAIR goals by enhancing the findability, accessibility, interoperability and reusability of scientific software, ensuring seamless functionality across diverse computing environments. Its adaptability enables application beyond structural biology into other scientific fields.

Tryptophan is the most prominent amino acid found in proteins, with multiple functional roles. Its side chain is made up of the hydrophobic indole moiety, with two groups that act as donors in hydrogen bonds: the Nɛ—H group, which is a potent donor in canonical hydrogen bonds, and a polarized Cδ1—H group, which is capable of forming weaker, noncanonical hydrogen bonds. Due to adjacent electron-withdrawing moieties, C—H⋯O hydrogen bonds are ubiquitous in macromolecules, albeit contingent on the polarization of the donor C—H group. Consequently, Cα—H groups (adjacent to the carbonyl and amino groups of flanking peptide bonds), as well as the Cɛ1—H and Cδ2—H groups of histidines (adjacent to imidazole N atoms), are known to serve as donors in hydrogen bonds, for example stabilizing parallel and antiparallel β-sheets. However, the nature and the functional role of interactions involving the Cδ1—H group of the indole ring of tryptophan are not well characterized. Here, data mining of high-resolution (r ≤ 1.5 Å) crystal structures from the Protein Data Bank was performed and ubiquitous close contacts between the Cδ1—H groups of tryptophan and a range of electronegative acceptors were identified, specifically main-chain carbonyl O atoms immediately upstream and downstream in the polypeptide chain. The stereochemical analysis shows that most of the interactions bear all of the hallmarks of proper hydrogen bonds. At the same time, their cohesive nature is confirmed by quantum-chemical calculations, which reveal interaction energies of 1.5–3.0 kcal mol−1, depending on the specific stereochemistry.

Several proteins from plant pathogenesis-related family 10 (PR10) are highly abundant in the latex of opium poppy and have recently been shown to play diverse and important roles in the biosynthesis of benzylisoquinoline alkaloids (BIAs). The recent determination of the first crystal structures of PR10-10 showed how large conformational changes in a surface loop and adjacent β-strand are coupled to the binding of BIA compounds to the central hydrophobic binding pocket. A more detailed analysis of these conformational changes is now reported to further clarify how ligand binding is coupled to the formation and cleavage of an intermolecular disulfide bond that is only sterically allowed when the BIA binding pocket is empty. To decouple ligand binding from disulfide-bond formation, each of the two highly conserved cysteine residues (Cys59 and Cys155) in PR10-10 was replaced with serine using site-directed mutagenesis. Crystal structures of the Cys59Ser mutant were determined in the presence of papaverine and in the absence of exogenous BIA compounds. A crystal structure of the Cys155Ser mutant was also determined in the absence of exogenous BIA compounds. All three of these crystal structures reveal conformations similar to that of wild-type PR10-10 with bound BIA compounds. In the absence of exogenous BIA compounds, the Cys59Ser and Cys155Ser mutants appear to bind an unidentified ligand or mixture of ligands that was presumably introduced during expression of the proteins in Escherichia coli. The analysis of conformational changes triggered by the binding of BIA compounds suggests a molecular mechanism coupling ligand binding to the disruption of an intermolecular disulfide bond. This mechanism may be involved in the regulation of biosynthetic reactions in plants and possibly other organisms.

A key prerequisite for the successful application of protein crystallography in drug discovery is to establish a robust crystallization system for a new drug-target protein fast enough to deliver crystal structures when the first inhibitors have been identified in the hit-finding campaign or, at the latest, in the subsequent hit-to-lead process. The first crucial step towards generating well folded proteins with a high likelihood of crystallizing is the identification of suitable truncation variants of the target protein. In some cases an optimal length variant alone is not sufficient to support crystallization and additional surface mutations need to be introduced to obtain suitable crystals. In this contribution, four case studies are presented in which rationally designed surface modifications were key to establishing crystallization conditions for the target proteins (the protein kinases Aurora-C, IRAK4 and BUB1, and the KRAS–SOS1 complex). The design process which led to well diffracting crystals is described and the crystal packing is analysed to understand retrospectively how the specific surface mutations promoted successful crystallization. The presented design approaches are routinely used in our team to support the establishment of robust crystallization systems which enable structure-guided inhibitor optimization for hit-to-lead and lead-optimization projects in pharmaceutical research.

β-Glucosidase from the thermophilic bacterium Caldicellulosiruptor saccharo­lyticus (Bgl1) has been denoted as having an attractive catalytic profile for various industrial applications. Bgl1 catalyses the final step of in the decomposition of cellulose, an unbranched glucose polymer that has attracted the attention of researchers in recent years as it is the most abundant renewable source of reduced carbon in the biosphere. With the aim of enhancing the thermostability of Bgl1 for a broad spectrum of biotechnological processes, it has been subjected to structural studies. Crystal structures of Bgl1 and its complex with glucose were determined at 1.47 and 1.95 Å resolution, respectively. Bgl1 is a member of glycosyl hydrolase family 1 (GH1 superfamily, EC 3.2.1.21) and the results showed that the 3D structure of Bgl1 follows the overall architecture of the GH1 family, with a classical (β/α)8 TIM-barrel fold. Comparisons of Bgl1 with sequence or structural homologues of β-glucosidase reveal quite similar structures but also unique structural features in Bgl1 with plausible functional roles.

Investigation of isostructurality leads to a deeper understanding of close-packing principles and contributes to the ability of crystal engineering. A given packing motif may tolerate small molecular changes within a limit. Slight alterations of a crystal packing arrangement are carried out in order to fine-tune the structural and macroscopic properties, keeping the balance of the spatial requirements and electrostatic effects of the altered molecules in the crystals, preserving their isostructurality. Even so, the definition of isostructurality is not explicit about several issues. Are the corresponding structures required to have the same stoichiometry, Z', symmetry elements and the same space group? Because it is not obvious in the definition, studies on structure analysis and software calculating various numerical descriptors developed for the quantitative comparison of the degree of similarity of isostructural crystals self-define their criteria. The extent of the difference between corresponding crystal structures referred to as isostructural is not limited. Should it be determined numerically? There is nothing in the definition about a demand for similar supramolecular arrangements in isostructural crystals. Should the similarity of supramolecular interactions be a criterion of isostructurality? The definition of isostructurality deserves reconsideration regarding symmetry, measure of similarity and formation of supramolecular interactions.

As an important characterization method, pair distribution function (PDF) has been extensively used in structural analysis of nanomaterials, providing key insights into the degree of crystallinity, atomic structure, local disorder etc. The collection of scattering signals with good statistics is necessary for a reliable structural analysis. However, current conventional electron diffraction experiments using PDF (ePDF) are limited in their ability to acquire continuous diffraction rings for large nanoparticles. Herein, a new method – tilt-ePDF – is proposed to improve the data quality and compatibility of ePDF by a combination of electron diffraction and specimen tilting. In the present work, a tilt-series of electron diffraction patterns was collected from gold nanoparticles with three different sizes and a standard sample polycrystalline aluminium film for ePDF analysis. The results show that tilt-ePDF can not only enhance the continuity of diffraction rings, but can also improve the signal-to-noise ratio in the high scattering angle range. As a result, compared with conventional ePDF data, tilt-ePDF data provide structure parameters with a better accuracy and lower residual factors in the refinement against the crystal structure. This method provides a new way of utilizing ePDF to obtain accurate local structure information from nanoparticles.

The discovery of lytic polysaccharide monooxygenases (LPMOs), a family of copper-dependent enzymes that play a major role in polysaccharide degradation, has revealed the importance of oxidoreductases in the biological utilization of biomass. In fungi, a range of redox proteins have been implicated as working in harness with LPMOs to bring about polysaccharide oxidation. In bacteria, less is known about the interplay between redox proteins and LPMOs, or how the interaction between the two contributes to polysaccharide degradation. We therefore set out to characterize two previously unstudied proteins from the shipworm symbiont Teredinibacter turnerae that were initially identified by the presence of carbohydrate binding domains appended to uncharacterized domains with probable redox functions. Here, X-ray crystal structures of several domains from these proteins are presented together with initial efforts to characterize their functions. The analysis suggests that the target proteins are unlikely to function as LPMO electron donors, raising new questions as to the potential redox functions that these large extracellular multi-haem-containing c-type cytochromes may perform in these bacteria.

Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. The method is named KINNTREX (kinetics-informed NN for time-resolved X-ray crystallography). To validate KINNTREX, multiple realistic scenarios were simulated with increasing levels of complexity. For the simulations, time-resolved X-ray data were generated that mimic data collected from the photocycle of the photoactive yellow protein. KINNTREX only requires the number of intermediates and approximate relaxation times (both obtained from a singular valued decomposition) and does not require an assumption of a candidate mechanism. It successfully predicts a consistent chemical kinetic mechanism, together with difference electron-density maps of the intermediates that appear during the reaction. These features make KINNTREX attractive for tackling a wide range of biomolecular questions. In addition, the versatility of KINNTREX can inspire more NN-based applications to time-resolved data from biological macromolecules obtained by other methods.

The large Bunyavirales order includes several families of viruses with a segmented ambisense (−) RNA genome and a cytoplasmic life cycle that starts by synthesizing viral mRNA. The initiation of transcription, which is common to all members, relies on an endonuclease activity that is responsible for cap-snatching. In La Crosse virus, an orthobunyavirus, it has previously been shown that the cap-snatching endonuclease resides in the N-terminal domain of the L protein. Orthobunyaviruses are transmitted by arthropods and cause diseases in cattle. However, California encephalitis virus, La Crosse virus and Jamestown Canyon virus are North American species that can cause encephalitis in humans. No vaccines or antiviral drugs are available. In this study, three known Influenza virus endonuclease inhibitors (DPBA, L-742,001 and baloxavir) were repurposed on the La Crosse virus endonuclease. Their inhibition was evaluated by fluorescence resonance energy transfer and their mode of binding was then assessed by differential scanning fluorimetry and microscale thermophoresis. Finally, two crystallographic structures were obtained in complex with L-742,001 and baloxavir, providing access to the structural determinants of inhibition and offering key information for the further development of Bunyavirales endonuclease inhibitors.

Immunodominant membrane protein (IMP) is a prevalent membrane protein in phytoplasma and has been confirmed to be an F-actin-binding protein. However, the intricate molecular mechanisms that govern the function of IMP require further elucidation. In this study, the X-ray crystallographic structure of IMP was determined and insights into its interaction with plant actin are provided. A comparative analysis with other proteins demonstrates that IMP shares structural homology with talin rod domain-containing protein 1 (TLNRD1), which also functions as an F-actin-binding protein. Subsequent molecular-docking studies of IMP and F-actin reveal that they possess complementary surfaces, suggesting a stable interaction. The low potential energy and high confidence score of the IMP–F-actin binding model indicate stable binding. Additionally, by employing immunoprecipitation and mass spectrometry, it was discovered that IMP serves as an interaction partner for the phytoplasmal effector causing phyllody 1 (PHYL1). It was then shown that both IMP and PHYL1 are highly expressed in the S2 stage of peanut witches' broom phytoplasma-infected Catharanthus roseus. The association between IMP and PHYL1 is substantiated through in vivo immunoprecipitation, an in vitro cross-linking assay and molecular-docking analysis. Collectively, these findings expand the current understanding of IMP interactions and enhance the comprehension of the interaction of IMP with plant F-actin. They also unveil a novel interaction pathway that may influence phytoplasma pathogenicity and host plant responses related to PHYL1. This discovery could pave the way for the development of new strategies to overcome phytoplasma-related plant diseases.

To date, accurate modelling of the solvation process is challenging, often over-simplifying the solvent–solute interactions. The interplay between the molecular arrangement associated with the solvation process and crystal nucleation has been investigated by analysis of the piezo-solvatochromic behaviour of Reichardt's dye, ET(1), in methanol, ethanol and acetone under high pressure. High-pressure single-crystal X-ray diffraction and UV–Vis spectroscopy reveal the impact of solute–solvent interactions on the optical properties of ET(1). The study underscores the intricate relationship between solvent properties, molecular conformation and crystal packing. The connection between liquid and solid phases emphasizes the capabilities of high-pressure methods for expanding the field of crystal engineering. The high-pressure environment allowed the determination of the crystal structures reported here that are built from organic molecules fourfold solvated with ethanol or methanol: ET(1)·4CH3OH and ET(1)·4C2H5OH·H2O. The observed piezo-solvatochromic effects highlight the potential of ET(1) in nonlinear optoelectronics and expand the application of solvatochromic chemical indicators to pressure sensors.

Investigation of the analyte soaking conditions on the crystalline sponge {[(ZnI2)3(tpt)2·x(solvent)]n} method using a statistical design of experiments model has provided fundamental insights into the influence of experimental variables. This approach focuses on a single analyte tested via 60 experiments (20 unique conditions) to identify the main effects for success and overall guest structure quality. This is employed as a basis for the development of a novel molecular structure grading system that enables the quantification of guest exchange quality.

In the folded state, biomolecules exchange between multiple conformational states crucial for their function. However, most structural models derived from experiments and computational predictions only encode a single state. To represent biomolecules accurately, we must move towards modeling and predicting structural ensembles. Information about structural ensembles exists within experimental data from X-ray crystallography and cryo-electron microscopy. Although new tools are available to detect conformational and compositional heterogeneity within these ensembles, the legacy PDB data structure does not robustly encapsulate this complexity. We propose modifications to the macromolecular crystallographic information file (mmCIF) to improve the representation and interrelation of conformational and compositional heterogeneity. These modifications will enable the capture of macromolecular ensembles in a human and machine-interpretable way, potentially catalyzing breakthroughs for ensemble–function predictions, analogous to the achievements of AlphaFold with single-structure prediction.

Spectroscopic data, particularly diffraction data, are essential for materials characterization due to their comprehensive crystallographic information. The current crystallographic phase identification, however, is very time consuming. To address this challenge, we have developed a real-time crystallographic phase identifier based on a convolutional self-attention neural network (CPICANN). Trained on 692 190 simulated powder X-ray diffraction (XRD) patterns from 23 073 distinct inorganic crystallographic information files, CPICANN demonstrates superior phase-identification power. Single-phase identification on simulated XRD patterns yields 98.5 and 87.5% accuracies with and without elemental information, respectively, outperforming JADE software (68.2 and 38.7%, respectively). Bi-phase identification on simulated XRD patterns achieves 84.2 and 51.5% accuracies, respectively. In experimental settings, CPICANN achieves an 80% identification accuracy, surpassing JADE software (61%). Integration of CPICANN into XRD refinement software will significantly advance the cutting-edge technology in XRD materials characterization.

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

Mineral identification and quantification are key to the understanding and, hence, the capacity to predict material properties. The method of choice for mineral quantification is powder X-ray diffraction (XRD), generally using a Rietveld refinement approach. However, a successful Rietveld refinement requires preliminary identification of the phases that make up the sample. This is generally carried out manually, and this task becomes extremely long or virtually impossible in the case of very large datasets such as those from synchrotron X-ray diffraction computed tomography. To circumvent this issue, this article proposes a novel neural network (NN) method for automating phase identification and quantification. An XRD pattern calculation code was used to generate large datasets of synthetic data that are used to train the NN. This approach offers significant advantages, including the ability to construct databases with a substantial number of XRD patterns and the introduction of extensive variability into these patterns. To enhance the performance of the NN, a specifically designed loss function for proportion inference was employed during the training process, offering improved efficiency and stability compared with traditional functions. The NN, trained exclusively with synthetic data, proved its ability to identify and quantify mineral phases on synthetic and real XRD patterns. Trained NN errors were equal to 0.5% for phase quantification on the synthetic test set, and 6% on the experimental data, in a system containing four phases of contrasting crystal structures (calcite, gibbsite, dolomite and hematite). The proposed method is freely available on GitHub and allows for major advances since it can be applied to any dataset, regardless of the mineral phases present.

The TIR (Toll/interleukin-1 receptor) domain represents a vital structural element shared by proteins with roles in immunity signalling pathways across phyla (from humans and plants to bacteria). Decades of research have finally led to identifying the key features of the molecular basis of signalling by these domains, including the formation of open-ended (filamentous) assemblies (responsible for the signalling by cooperative assembly formation mechanism, SCAF) and enzymatic activities involving the cleavage of nucleotides. We present a historical perspective of the research that led to this understanding, highlighting the roles that different structural methods played in this process: X-ray crystallography (including serial crystallography), microED (micro-crystal electron diffraction), NMR (nuclear magnetic resonance) spectroscopy and cryo-EM (cryogenic electron microscopy) involving helical reconstruction and single-particle analysis. This perspective emphasizes the complementarity of different structural approaches.

MltG, a membrane-bound lytic transglycosyl­ase, has roles in terminating glycan polymerization in peptidoglycan and incorporating glycan chains into the cell wall, making it significant in bacterial cell-wall biosynthesis and remodeling. This study provides the first reported MltG structure from Mycobacterium abscessus (maMltG), a superbug that has high antibiotic resistance. Our structural and biochemical analyses revealed that MltG has a flexible peptidoglycan-binding domain and exists as a monomer in solution. Further, the putative active site of maMltG was disclosed using structural analysis and sequence comparison. Overall, this study contributes to our understanding of the transglycosyl­ation reaction of the MltG family, aiding the design of next-generation antibiotics targeting M. abscessus.

Three solid solutions of [CH3NH3]CoxNi1−x(HCOO)3, with x = 0.25 (1), x = 0.50 (2) and x = 0.75 (3), were synthesized and their nuclear structures and magnetic properties were characterized using single-crystal neutron diffraction and magnetization measurements. At room temperature, all three compounds crystallize in the Pnma orthorhombic space group, akin to the cobalt and nickel end series members. On cooling, each compound undergoes a distinct series of structural transitions to modulated structures. Compound 1 exhibits a phase transition to a modulated structure analogous to the pure Ni compound [Cañadillas-Delgado, L., Mazzuca, L., Fabelo, O., Rodríguez-Carvajal, J. & Petricek, V. (2020). Inorg. Chem. 59, 17896–17905], whereas compound 3 maintains the behaviour observed in the pure Co compound reported previously [Canadillas-Delgado, L., Mazzuca, L., Fabelo, O., Rodriguez-Velamazan, J. A. & Rodriguez-Carvajal, J. (2019). IUCrJ, 6, 105–115], although in both cases the temperatures at which the phase transitions occur differ slightly from the pure phases. Monochromatic neutron diffraction measurements showed that the structural evolution of 2 diverges from that of either parent compound, with competing hydrogen bond interactions that drive the modulation throughout the series, producing a unique sequence of phases. It involves two modulated phases below 96 (3) and 59 (3) K, with different q vectors, similar to the pure Co compound (with modulated phases below 128 and 96 K); however, it maintains the modulated phase below magnetic order [at 22.5 (7) K], resembling the pure Ni compound (which presents magnetic order below 34 K), resulting in an improper modulated magnetic structure. Despite these large-scale structural changes, magnetometry data reveal that the bulk magnetic properties of these solid solutions form a linear continuum between the end members. Notably, doping of the metal site in these solid solutions allows for tuning of bulk magnetic properties, including magnetic ordering temperature, transition temperatures and the nature of nuclear phase transitions, through adjustment of metal ratios.

Regolith draws intensive research attention because of its importance as the basis for fabricating materials for future human space exploration. Martian regolith is predicted to consist of defect-rich crystal structures due to long-term space weathering. The present report focuses on the structural differences between defect-rich and defect-poor forsterite (Mg2SiO4) – one of the major phases in Martian regolith. In this work, forsterites were synthesized using reverse strike co-precipitation and high-energy ball milling (BM). Subsequent post-processing was also carried out using BM to enhance the defects. The crystal structures of the samples were characterized by X-ray powder diffraction and total scattering using Cu and synchrotron radiation followed by Rietveld refinement and pair distribution function (PDF) analysis, respectively. The structural models were deduced by density functional theory assisted PDF refinements, describing both long-range and short-range order caused by defects. The Raman spectral features of the synthetic forsterites complement the ab initio simulation for an in-depth understanding of the associated structural defects.

The title complex, [ZnCl(C12H15N3O2)2][ZnCl3(CH3CN)], was synthesized and its structure was fully characterized through single-crystal X-ray diffraction analysis. The complex crystallizes in the ortho­rhom­bic system, space group Pbca (61), with a central zinc atom coordinating one chlorine atom and two pyrrolidinyl-4-meth­oxy­phenyl azoformamide ligands in a bidentate manner, utilizing both the nitro­gen and oxygen atoms in a 1,3-heterodiene (N=N—C=O) motif for coordinative bonding, yielding an overall positively (+1) charged complex. The complex is accompanied by a [(CH3CN)ZnCl3]− counter-ion. The crystal data show that the harder oxygen atoms in the heterodiene zinc chelate form bonding inter­actions with distances of 2.002 (3) and 2.012 (3) Å, while nitro­gen atoms are coordinated by the central zinc cation with bond lengths of 2.207 (3) and 2.211 (3) Å. To gain further insight into the inter­molecular inter­actions within the crystal, Hirshfeld surface analysis was performed, along with the calculation of two-dimensional fingerprint plots. This analysis revealed that H⋯H (39.9%), Cl⋯H/H⋯Cl (28.2%) and C⋯H/H⋯C (7.2%) inter­actions are dominant. This unique crystal structure sheds light on arrangement and bonding inter­actions with azo­formamide ligands, and their unique qualities over similar semicarbazone and azo­thio­formamide structures.

Lanthanide-containing materials are of inter­est in the field of crystal engin­eering because of their unique properties and distinct structure types. In this context, a new samarium–sodium heterometallic coordination polymer, poly[tetra­kis­(μ2-2-formyl-6-meth­oxy­phenolato)samarium(III)sodium(I)], {[SmNa(C8H7O3)4]·solvent}n (Sm-1), was synthesized and crystallized via slow evaporation from a mixture of ethanol and aceto­nitrile. The compound features alternating SmIII and NaI ions, which are linked by ortho-vanillin (o-vanillin) ligands to form a mono-periodic chain-like coordination polymer. The chains propagate along the [001] direction. Residual electron density of disordered solvent mol­ecules in the void space could not be reasonably modeled, thus the SQUEEZE function was applied. The structural, vibrational, and optical properties are reported.

The title compound, C12H16N2O, is a hy­droxy-substituted mono­amine alkaloid, and the primary metabolite of the naturally occurring psychedelic compound psilocybin. Crystalline forms of psilocin are known, but their characterization by single-crystal structure analysis is limited. Herein, two anhydrous polymorphic forms (I and II) of psilocin are described. The crystal structure of polymorphic Form I, in space group P21/c, was first reported in 1974. Along with the redeterm­ination to modern standards and unambiguous location of the acidic H atom and variable-temperature single-crystal unit-cell determinations for Form I, the Form II polymorph of the title compound, which crystallizes in the monoclinic space group P21/n, is described for the first time. The psilocin mol­ecules are present in both forms in their phenol–amine tautomeric forms (not resolved in the 1974 report). The mol­ecules in Forms I and II, however, feature different conformations of their N,N-dimethyl ethyl­ene substituent, with the N—C—C—C link in Form I being trans and in Form II being gauche, allowing the latter to bend back to the hydroxyl group of the same mol­ecule, leading to the formation of a strong intra­molecular O—H⋯N hydrogen bond between the hydroxyl moiety and ethyl­amino-nitro­gen group. In the extended structure of Form II, the mol­ecules form one-dimensional strands through N—H⋯O hydrogen bonds from the indole group to the oxygen atom of the hydroxyl moiety of an adjacent mol­ecule. Form II exhibits whole-mol­ecule disorder due to a pseudo-mirror operation, with an occupancy ratio of 0.689 (5):0.311 (5) for the two components. In contrast, Form I does not feature intra­molecular hydrogen bonds but forms a layered structure through inter­molecular N—H⋯O and O—H⋯N hydrogen bonds.

Three organoplatinum(II) complexes bearing natural aryl­olefin and quinoline derivatives, namely, [4-meth­oxy-5-(2-meth­oxy-2-oxoeth­oxy)-2-(prop-2-en-1-yl)phen­yl](quinolin-8-olato)platinum(II), [Pt(C13H15O4)(C9H6NO)], (I), [4-meth­oxy-5-(2-oxo-2-propoxyeth­oxy)-2-(prop-2-en-1-yl)phen­yl](quinoline-2-carboxy­l­ato)platinum(II), [Pt(C15H19O4)(C10H6NO2)], (II), and chlorido­[4-meth­oxy-5-(2-oxo-2-propoxyeth­oxy)-2-(prop-2-en-1-yl)phen­yl](quinoline)­plat­inum(II), [Pt(C15H19O4)Cl(C9H7N)], (III), were synthesized and structurally characterized by IR and 1H NMR spectroscopy, and by single-crystal X-ray diffraction. The results showed that the cyclo­platinated aryl­olefin coordinates with PtII via the carbon atom of the phenyl ring and the C=Colefinic group. The deprotonated 8-hy­droxy­quinoline (C9H6NO) and quinoline-2-carb­oxy­lic acid (C10H6NO2) coordinate with the PtII atom via the N and O atoms in complexes (I) and (II) while the quinoline (C9H7N) coordinates via the N atom in (III). Moreover, the coordinating N atom in complexes (I)–(III) is in the cis position compared to the C=Colefinic group. The crystal packing is characterized by C—H⋯π, C—H⋯O [for (II) and (III)], C—H⋯Cl [for (III) and π–π [for (I)] inter­actions.

Crystal formation of penta­sodium nona­deca­cesium tetra­cosa­tungstate(VI) heneikosahydrate, Na5Cs19[W24O84]·21H2O, was successfully achieved by the conversion of [H2W12O42]10− through the addition of excess Cs+. The crystal structure comprising the toroidal isopolyoxidometalate is presented, as well as its Raman spectrum. Na5Cs19(H2O)21W24O84 crystallizes in the rhombohedral space group Roverline{3} with an obverse centering. The title compound represents the addition of a new member to the isopolytungstate family with mixed alkali counter-ions and contains rarely observed five-coordinate tungsten(VI) atoms in the [W24O84]24− anion (site symmetry C3i) arising from the conversion mediated by Cs+ counter-ions.

The structural characterization is reported of the supra­molecular complex between the tetra­quinoxaline-based cavitand 2,8,14,20-tetra­hexyl-6,10:12,16:18,22:24,4-O,O'-tetra­kis­(quinoxaline-2,3-di­yl)calix[4]resorcinarene (QxCav) with benzo­nitrile. The complex, of general formula C84H80N8O8·2C7H5N, crystallizes in the space group Poverline{1} with two independent mol­ecules in the asymmetric unit, displaying very similar geometrical parameters. For each complex, one of the benzo­nitrile mol­ecules is engulfed inside the cavity, while the other is located among the alkyl legs at the lower rim. The host and the guests mainly inter­act through weak C—H⋯π, C—H⋯N and dispersion inter­actions. These inter­actions help to consolidate the formation of supra­molecular chains running along the crystallographic b-axis direction.

Reaction of thorium(IV) nitrate with 2-[(4-phenyl-1H-1,2,3-triazol-1-yl)meth­yl]pyridine (L) yielded (LH)2[Th(NO3)6] or (C14H13N4)2[Th(NO3)6] (1), instead of the expected mixed-ligand complex [Th(NO3)4L2], which was detected in the mass spectrum of 1. In the structure, the [Th(NO3)6]2− anions display an icosa­hedral coordination geometry and are connected by LH+ cations through C—H⋯O hydrogen bonds. The LH+ cations inter­act via N—H⋯N hydrogen bonds. Hirshfeld surface analysis indicates that the most important inter­actions are O⋯H/H⋯O hydrogen-bonding inter­actions, which represent a 55.2% contribution.

The X-ray crystal structure data of 12-α-fluoro-3β-hy­droxy­olean-28,13β-olide methanol hemisolvate, 2C30H47FO3·CH3OH, (1), and 12-α-fluoro-3β-hy­droxy­taraxer-28,14β-olide methanol hemisolvate, 2C30H47FO3·CH3OH, (2), are described. The fluoro­lactonization of oleanolic acid using SelectfluorTM yielded a mixture of the six-membered δ-lactone (1) and the unusual seven-membered γ-lactone (2) following a 1,2-shift of methyl C-27 from C-14 to C-13.

Lopinavir is a potent protease inhibitor that is used as a first-line pharmaceutical drug for the treatment of HIV. The multi-component solvated Lopinavir crystal, systematic name (2S)-N-[(2S,4S,5S)-5-[2-(2,6-di­methyl­phen­oxy)acetamido]-4-hy­droxy-1,6-di­phenyl­hexan-2-yl]-3-methyl-2-(2-oxo-1,3-diazinan-1-yl)butanamide–ethane-1,2-diol–water (8/3/7) 8C37H48N4O5·3C2H6O2·7H2O, was prepared using evaporative methods. The crystalline material obtained from this experimental synthesis was characterized and elucidated by single-crystal X-ray diffraction (SC-XRD). The crystal structure is unusual in that the unit cell contains 18 mol­ecules. The stoichiometric ratio of this crystal is eight Lopinavir mol­ecules [8(C37H48N4O5)], three ethane-1,2-diol mol­ecules [3(C2H6O2)] and seven water mol­ecules [7(H2O)]. The crystal packing features both bi- and trifurcated hydrogen bonds between atoms.

In cellulo crystallization is a rare event in nature. Recent advances that have made use of heterologous overexpression can promote the intracellular formation of protein crystals, but new tools are required to detect and characterize these targets in the complex cell environment. The present work makes use of Mask R-CNN, a convolutional neural network (CNN)-based instance segmentation method, for the identification of either single or multi-shaped crystals growing in living insect cells, using conventional bright field images. The algorithm can be rapidly adapted to recognize different targets, with the aim of extracting relevant information to support a semi-automated screening pipeline, in order to aid the development of the intracellular protein crystallization approach.

X-ray reflectometry (XRR) is a powerful tool for probing the structural characteristics of nanoscale films and layered structures, which is an important field of nanotechnology and is often used in semiconductor and optics manufacturing. This study introduces a novel approach for conducting quantitative high-resolution millisecond monochromatic XRR measurements. This is an order of magnitude faster than in previously published work. Quick XRR (qXRR) enables real time and in situ monitoring of nanoscale processes such as thin film formation during spin coating. A record qXRR acquisition time of 1.4 ms is demonstrated for a static gold thin film on a silicon sample. As a second example of this novel approach, dynamic in situ measurements are performed during PMMA spin coating onto silicon wafers and fast fitting of XRR curves using machine learning is demonstrated. This investigation primarily focuses on the evolution of film structure and surface morphology, resolving for the first time with qXRR the initial film thinning via mass transport and also shedding light on later thinning via solvent evaporation. This innovative millisecond qXRR technique is of significance for in situ studies of thin film deposition. It addresses the challenge of following intrinsically fast processes, such as thin film growth of high deposition rate or spin coating. Beyond thin film growth processes, millisecond XRR has implications for resolving fast structural changes such as photostriction or diffusion processes.

Due to the ambiguity related to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This ambiguity poses limitations on standard neural networks, constraining the range and number of considered parameters in previous machine learning solutions. To overcome this challenge, a novel training procedure has been designed which incorporates dynamic prior boundaries for each physical parameter as additional inputs to the neural network. In this manner, the neural network can be trained simultaneously on all well-posed subintervals of a larger parameter space in which the inverse problem is underdetermined. During inference, users can flexibly input their own prior knowledge about the physical system to constrain the neural network prediction to distinct target subintervals in the parameter space. The effectiveness of the method is demonstrated in various scenarios, including multilayer structures with a box model parameterization and a physics-inspired special parameterization of the scattering length density profile for a multilayer structure. In contrast to previous methods, this approach scales favourably when increasing the complexity of the inverse problem, working properly even for a five-layer multilayer model and a periodic multilayer model with up to 17 open parameters.

From the historical roots of metalworking to the forefront of modern nanotechnology, functional materials have played a pivotal role in transforming societies, and their influence is poised to persist into the future. Encompassing a wide array of solid-state materials, spanning semiconductors to polymers, molecular crystals to nanoparticles, functional materials find application in critical sectors such as electronics, computers, information, communication, bio­technology, aerospace, defense, environment, energy, medicine and consumer products. This feature article delves into diverse instances of functional materials, exploring their structures, their properties and the underlying mechanisms that contribute to their outstanding performance across fields like batteries, photovoltaics, magnetics and heterogeneous catalysts. The field of structural sciences serves as the cornerstone for unraveling the intricate relationship between structure, dynamics and function. Acting as a bridge, it connects the fundamental understanding of materials to their practical applications.

Recent developments in synchrotron radiation facilities have increased the amount of data generated during acquisitions considerably, requiring fast and efficient data processing techniques. Here, the application of dense neural networks (DNNs) to data treatment of X-ray diffraction computed tomography (XRD-CT) experiments is presented. Processing involves mapping the phases in a tomographic slice by predicting the phase fraction in each individual pixel. DNNs were trained on sets of calculated XRD patterns generated using a Python algorithm developed in-house. An initial Rietveld refinement of the tomographic slice sum pattern provides additional information (peak widths and integrated intensities for each phase) to improve the generation of simulated patterns and make them closer to real data. A grid search was used to optimize the network architecture and demonstrated that a single fully connected dense layer was sufficient to accurately determine phase proportions. This DNN was used on the XRD-CT acquisition of a mock-up and a historical sample of highly heterogeneous multi-layered decoration of a late medieval statue, called `applied brocade'. The phase maps predicted by the DNN were in good agreement with other methods, such as non-negative matrix factorization and serial Rietveld refinements performed with TOPAS, and outperformed them in terms of speed and efficiency. The method was evaluated by regenerating experimental patterns from predictions and using the R-weighted profile as the agreement factor. This assessment allowed us to confirm the accuracy of the results.

This article presents a Python-based program, DFT2FEFFIT, to regress theoretical extended X-ray absorption fine structure (EXAFS) spectra calculated from density functional theory structure models against experimental EXAFS spectra. To showcase its application, Ce-doped fluorapatite [Ca10(PO4)6F2] is revisited as a representative of a material difficult to analyze by conventional multi-shell least-squares fitting of EXAFS spectra. The software is open source and publicly available.