The title compound, [Fe(C84H52N12O4)Cl], crystallizes in space group C2/c. The central FeIII cation (site symmetry 2) is coordinated in a fivefold manner, with four pyrrole N atoms of the porphyrin core in the basal sites and one Cl atom (site symmetry 2) in the apical position, which completes a slightly distorted square-pyramidal environment. The porphyrin macrocycle shows a characteristic ruffled-shape distortion and the iron atom is displaced out of the porphyrin plane by 0.42 Å with the average Fe—N distance being 2.054 (4) Å; the Fe—Cl bond length is 2.2042 (7) Å. Inter­molecular C—H⋯N and C—H⋯O hydrogen bonds occur in the crystal structure.

In the title compound, [Mn(C68H44N12O4)(C5H8N2)]·2C6H5Cl, the central MnII ion is coordinated by four pyrrole N atoms of the porphyrin core in the basal sites and one N atom of the 2,5-di­methyl­imidazole ligand in the apical site. Two chloro­benzene solvent mol­ecules are also present in the asymmetric unit. Due to the apical imidazole ligand, the Mn atom is displaced out of the 24-atom porphyrin mean plane by 0.66 Å. The average Mn—Np (p = porphyrin) bond length is 2.143 (8) Å, and the axial Mn—NIm (Im = 2,5-di­methyl­imidazole) bond length is 2.171 (8) Å. The structure displays inter­molecular and intra­molecular N—H⋯O, N—H⋯N, C—H⋯O and C—H⋯N hydrogen bonding. The crystal studied was refined as a two-component inversion twin.

The title compound, [Fe(C4H8O)4(H2O)2][Fe4Ga4(C2H6O2Si)Cl4(CO)15]·4C4H8O, consists of an iron(II) cation octa­hedrally coordinated by two water mol­ecules (trans) with four tetra­hydro­furans (THF) at equatorial sites. Two additional THF mol­ecules are hydrogen bonded to each of the water mol­ecules. The dianion of the title compound is an organometallic butterfly complex with a dimethyl siloxane core and two iron-gallium fragments. The lengths of the iron to gallium metal–metal bonds range from 2.3875 (6) to 2.4912 (6) Å.

The reaction of nickel(II) chloride with 3-meth­oxy­aniline yielded di­chlorido­tetra­kis­(3-meth­oxy­aniline)nickel(II), [NiCl2(C7H9NO)4], as yellow crystals. The NiII ion is pseudo-octa­hedral with the chloride ions trans to each other. The four 3-meth­oxy­aniline ligands differ primarily due to different conformations about the Ni—N bond, which also affect the hydrogen bonding. Inter­molecular N—H⋯ Cl hydrogen bonds and short Cl⋯Cl contacts between mol­ecules link them into chains parallel to the b axis.

The title compound, [Ni2(C8H6N3)2(C2H3O2)2(C5H8N2)2] or [Ni(μ-OOCCH3)(2-PyPz)(Me2PzH)]2 (1) [2-PyPz = 3-(pyridin-2-yl) pyrazole; Me2PzH = 3,5-dimethyl pyrazole] was synthesized from Ni(OOCCH3)2·4H2O, 2-PyPzH, Me2PzH and tri­ethyl­amine as a base. Compound 1 {[Ni2(C30H34N10Ni2O4)]} at 100 K has monoclinic (P21/n) symmetry and the mol­ecules have crystallographic inversion symmetry. Mol­ecules of 1 comprise an almost planar dinuclear NiII core with an N4O2 coordination environment. The equatorial plane consists of N3,O coordination derived from one of the bidentate acetate O atoms and three of the N atoms of the chelating 2-PyPz ligand while the axial positions are occupied by neutral Me2PzH and the second O atom of the acetate unit. The Ni atoms are bridged by the nitro­gen atom of a deprotonated 2-PyPz ligand. Compound 1 exhibits various inter- and intra­molecular C—H⋯O and N—H⋯O hydrogen bonds.

The title structure, {[Cu(C4H11NO)3][Cu4(CN)6]·[Cu(C4H10NO)2(H2O)]·H2O}n, is made up of diperiodic honeycomb CuICN networks built from [Cu4(CN)6]2− units, together with two independent CuII complexes: six-coord­inate [Cu(CH3CH2CH(NH2)CH2OH)3]2+ cations, and five-coordinate [Cu(CH3CH2CH(NH2)CH2O)2·H2O] neutral species. The two CuII complexes are not covalently bonded to the CuICN networks. Strong O—H⋯O hydrogen bonds link the CuII complexes into pairs and the pairs are hydrogen bonded into chains along the crystallographic b axis via the hydrate water mol­ecule. In addition, O—H⋯(CN) and N—H⋯(CN) hydrogen bonds link the cations to the CuCN network. In the honeycomb polymeric moiety, all bridging cyanido ligands are disordered over two orientations, head-to-tail and tail-to-head, with occupancies for C and N atoms varying for each CN group.

α-d-2'-De­oxy­ribonucleosides are products of the γ-irradiation of DNA under oxygen-free conditions and are constituents of anomeric DNA. They are not found as natural building blocks of canonical DNA. Reports on their conformational properties are limited. Herein, the single-crystal X-ray structure of α-d-2'-de­oxy­adenosine (α-dA), C10H13N5O3, and its conformational parameters were determined. In the crystalline state, α-dA forms two conformers in the asymmetric unit which are connected by hydro­gen bonds. The sugar moiety of each conformer is arranged in a `clamp'-like fashion with respect to the other conformer, forming hydro­gen bonds to its nucleobase and sugar residue. For both conformers, a syn conformation of the nucleobase with respect to the sugar moiety was found. This is contrary to the anti conformation usually preferred by α-nucleosides. The sugar conformation of both conformers is C2'-endo, and the 5'-hydroxyl groups are in a +sc orientation, probably due to the hydro­gen bonds formed by the conformers. The formation of the supra­molecular assembly of α-dA is controlled by hydro­gen bonding and stacking inter­actions, which was verified by a Hirshfeld and curvedness surface analysis. Chains of hydro­gen-bonded nucleobases extend parallel to the b direction and are linked to equivalent chains by hydro­gen bonds involving the sugar moieties to form a sheet. A com­parison of the solid-state structures of the anomeric 2'-de­oxy­adenosines revealed significant differences of their conformational parameters.

X-ray and electron diffraction methods independently identify the S-enanti­omer of Berkecoumarin [systematic name: (S)-8-hy­droxy-3-(2-hy­droxy­prop­yl)-6-meth­oxy-2H-chromen-2-one]. Isolated from Berkeley Pit Lake Penicillium sp., Berkecoumarin is a natural product with a light-atom com­position (C13H14O5) that challenges in-house absolute structure determination by anomalous scattering. This study further demonstrates the utility of dynamical refinement of electron-diffraction data for absolute structure determination.

We report on the latest advancements in Microcrystal Electron Diffraction (3D ED/MicroED), as discussed during a symposium at the National Center for CryoEM Access and Training housed at the New York Structural Biology Center. This snapshot describes cutting-edge developments in various facets of the field and identifies potential avenues for continued progress. Key sections discuss instrumentation access, research applications for small mol­ecules and biomacromolecules, data collection hardware and software, data reduction software, and finally reporting and validation. 3D ED/MicroED is still early in its wide adoption by the structural science community with ample opportunities for expansion, growth, and innovation.

The well-known copper car­box­yl­ate dimer, with four car­box­yl­ate ligands ex­ten­ding outwards towards the corners of a square, has been employed to generate a series of crystalline com­pounds. In particular, this work centres on the use of the 4-hy­droxy­benzoate anion (Hhba−) and its deprotonated phe­nol­ate form 4-oxidobenzoate (hba2−) to obtain complexes with the general formula [Cu2(Hhba)4–x(hba)xL2–y]x−, where L is an axial coligand (including solvent mol­ecules), x = 0, 1 or 2, and y = 0 or 1. In some cases, short hy­dro­gen bonds result in complexes which may be represented as [Cu2(Hhba)2(H0.5hba)2L2]−. The main focus of the investigation is on the formation of a variety of extended networks through hy­dro­gen bonding and, in some crystals, coordinate bonds when bridging coligands (L) are employed. Crystals of [Cu2(Hhba)4(di­ox­ane)2]·4(di­ox­ane) consist of the expected Cu dimer with the Hhba− anions forming hy­dro­gen bonds to 1,4-di­ox­ane mol­ecules which block network formation. In the case of crystals of com­position [Et4N][Cu2(Hhba)2(H0.5hba)2(CH3OH)(H2O)]·2(di­ox­ane), Li[Cu2(Hhba)2(H0.5hba)2(H2O)2]·3(di­ox­ane)·4H2O and [Cu2(Hhba)2(H0.5hba)2(H0.5DABCO)2]·3CH3OH (DABCO is 1,4-di­aza­bicyclo­[2.2.2]octa­ne), square-grid hy­dro­gen-bonded networks are generated in which the complex serves as one type of 4-con­necting node, whilst a second 4-con­necting node is a hy­dro­gen-bonding motif assembled from four phenol/phenolate groups. Another two-dimensional (2D) network based upon a related square-grid structure is formed in the case of [Et4N]2[Cu2(Hhba)2(hba)2(di­ox­ane)2][Cu2(Hhba)4(di­ox­ane)(H2O)]·CH3OH. In [Cu2(Hhba)4(H2O)2]·2(Et4NNO3), a square-grid structure is again apparent, but, in this case, a pair of nitrate anions, along with four phenolic groups and a pair of water mol­ecules, combine to form a second type of 4-con­necting node. When 1,8-bis­(di­methyl­amino)­naphthalene (bdn, `proton sponge') is used as a base, another square-grid network is generated, i.e. [Hbdn]2[Cu2(Hhba)2(hba)2(H2O)2]·3(di­ox­ane)·H2O, but with only the copper dimer complex serving as a 4-con­necting node. Complex three-dimensional networks are formed in [Cu2(Hhba)4(O-bipy)]·H2O and [Cu2(Hhba)4(O-bipy)2]·2(di­ox­ane), where the potentially bridging 4,4'-bi­pyridine N,N'-dioxide (O-bipy) ligand is employed. Rare cases of mixed car­box­yl­ate copper dimer complexes were obtained in the cases of [Cu2(Hhba)3(OAc)(di­ox­ane)]·3.5(di­ox­ane) and [Cu2(Hhba)2(OAc)2(DABCO)2]·10(di­ox­ane), with each structure possessing a 2D network structure. The final com­pound re­por­ted is a simple hy­dro­gen-bonded chain of com­position (H0.5DABCO)(H1.5hba), formed from the reaction of H2hba and DABCO.

The synthesis and structural characterization of four novel supra­molecular hy­dro­gen-bonded arrangements based on self-assembly from mol­ecular `[Cu(2,2'-bi­imid­az­ole)]' modules and malonate anions are pre­sent­ed, namely, tetra­kis­(2,2'-bi­imid­az­ole)di-μ-chlorido-dimal­on­atotricopper(II) penta­hydrate, [Cu3(C3H2O4)2Cl2(C6H6N4)4]·5H2O or [Cu(H2biim)2(μ-Cl)Cu0.5(mal)]2·5H2O, aqua­(2,2'-bi­imid­az­ole)­mal­on­atocopper(II) dihydrate, [Cu(C3H2O4)(C6H6N4)(H2O)]·2H2O or [Cu(H2biim)(mal)(H2O)]·2H2O, bis­[aqua­bis­(2,2'-bi­imid­az­ole)­cop­per(II)] di­mal­on­atodi­perchloratocopper(II) 2.2-hydrate, [Cu(C6H6N4)2(H2O)]2[Cu(C3H2O4)(ClO4)2]·2.2H2O or [Cu(H2biim)2(H2O)]2[Cu(mal)2(ClO4)2]·2.2H2O, and bis­(2,2'-bi­imid­az­ole)­copper(II) bis­[bis­(2,2'-bi­imid­az­ole)(2-carb­oxy­acetato)mal­on­atocopper(II)] tridecahydrate, [Cu(C6H6N4)2][Cu(C3H2O4)(C3H3O4)(C6H6N4)2]·13H2O or [Cu(H2biim)2][Cu(H2biim)2(Hmal)(mal)]2·13H2O. These as­sem­blies are characterized by self-com­plementary donor–acceptor mol­ecular inter­actions, demonstrating a recurrent and distinctive pattern of hy­dro­gen-bonding preferences among the carboxyl­ate, carb­oxy­lic acid and N—H groups of the coordinated 2,2'-bi­imid­az­ole and malonate ligands. Additionally, co­or­din­ation of the carboxyl­ate group with the metallic centre helps sustain re­mark­able supra­molecular assemblies, such as layers, helices, double helix columns or 3D channeled architectures, including mixed-metal com­plexes, into a single structure.

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

To identify starting points for therapeutics targeting SARS-CoV-2, the Paul Scherrer Institute and Idorsia decided to collaboratively perform an X-ray crystallographic fragment screen against its main protease. Fragment-based screening was carried out using crystals with a pronounced open conformation of the substrate-binding pocket. Of 631 soaked fragments, a total of 29 hits bound either in the active site (24 hits), a remote binding pocket (three hits) or at crystal-packing interfaces (two hits). Notably, two fragments with a pose that was sterically incompatible with a more occluded crystal form were identified. Two isatin-based electrophilic fragments bound covalently to the catalytic cysteine residue. The structures also revealed a surprisingly strong influence of the crystal form on the binding pose of three published fragments used as positive controls, with implications for fragment screening by crystallography.

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

Mevalonate kinase is central to the isoprenoid biosynthesis pathway. Here, high-resolution X-ray crystal structures of two mevalonate kinases are presented: a eukaryotic protein from Ramazzottius varieornatus and an archaeal protein from Methanococcoides burtonii. Both enzymes possess the highly conserved motifs of the GHMP enzyme superfamily, with notable differences between the two enzymes in the N-terminal part of the structures. Biochemical characterization of the two enzymes revealed major differences in their sensitivity to geranyl pyrophosphate and farnesyl pyrophosphate, and in their thermal stabilities. This work adds to the understanding of the structural basis of enzyme inhibition and thermostability in mevalonate kinases.

Data acquisition and processing for cryo-electron tomography can be a significant bottleneck for users. To simplify and streamline the cryo-ET workflow, Tomo Live, an on-the-fly solution that automates the alignment and reconstruction of tilt-series data, enabling real-time data-quality assessment, has been developed. Through the integration of Tomo Live into the data-acquisition workflow for cryo-ET, motion correction is performed directly after each of the acquired tilt angles. Immediately after the tilt-series acquisition has completed, an unattended tilt-series alignment and reconstruction into a 3D volume is performed. The results are displayed in real time in a dedicated remote web platform that runs on the microscope hardware. Through this web platform, users can review the acquired data (aligned stack and 3D volume) and several quality metrics that are obtained during the alignment and reconstruction process. These quality metrics can be used for fast feedback for subsequent acquisitions to save time. Parameters such as Alignment Accuracy, Deleted Tilts and Tilt Axis Correction Angle are visualized as graphs and can be used as filters to export only the best tomograms (raw data, reconstruction and intermediate data) for further processing. Here, the Tomo Live algorithms and workflow are described and representative results on several biological samples are presented. The Tomo Live workflow is accessible to both expert and non-expert users, making it a valuable tool for the continued advancement of structural biology, cell biology and histology.

Cryo-electron tomography (cryo-ET) enables molecular-resolution 3D imaging of complex biological specimens such as viral particles, cellular sections and, in some cases, whole cells. This enables the structural characterization of molecules in their near-native environments, without the need for purification or separation, thereby preserving biological information such as conformational states and spatial relationships between different molecular species. Subtomogram averaging is an image-processing workflow that allows users to leverage cryo-ET data to identify and localize target molecules, determine high-resolution structures of repeating molecular species and classify different conformational states. Here, STOPGAP, an open-source package for subtomogram averaging that is designed to provide users with fine control over each of these steps, is described. In providing detailed descriptions of the image-processing algorithms that STOPGAP uses, this manuscript is also intended to serve as a technical resource to users as well as for further community-driven software development.

Type VII secretion (T7S) systems, also referred to as ESAT-6 secretion (ESX) systems, are molecular machines that have gained great attention due to their implications in cell homeostasis and in host–pathogen interactions in mycobacteria. The latter include important human pathogens such as Mycobacterium tuberculosis (Mtb), the etiological cause of human tuberculosis, which constitutes a pandemic accounting for more than one million deaths every year. The ESX-5 system is exclusively found in slow-growing pathogenic mycobacteria, where it mediates the secretion of a large family of virulence factors: the PE and PPE proteins. The secretion driving force is provided by EccC5, a multidomain ATPase that operates using four globular cytosolic domains: an N-terminal domain of unknown function (EccC5DUF) and three FtsK/SpoIIIE ATPase domains. Recent structural and functional studies of ESX-3 and ESX-5 systems have revealed EccCDUF to be an ATPase-like fold domain with potential ATPase activity, the functionality of which is essential for secretion. Here, the crystal structure of the MtbEccC5DUF domain is reported at 2.05 Å resolution, which reveals a nucleotide-free structure with degenerated cis-acting and trans-acting elements involved in ATP binding and hydrolysis. This crystallographic study, together with a biophysical assessment of the interaction of MtbEccC5DUF with ATP/Mg2+, supports the absence of ATPase activity proposed for this domain. It is shown that this degeneration is also present in DUF domains from other ESX and ESX-like systems, which are likely to exhibit poor or null ATPase activity. Moreover, based on an in silico model of the N-terminal region of MtbEccC5DUF, it is hypothesized that MtbEccC5DUF is a degenerated ATPase domain that may have retained the ability to hexamerize. These observations draw attention to DUF domains as structural elements with potential implications in the opening and closure of the membrane pore during the secretion process via their involvement in inter-protomer interactions.

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.

The Mycobacterium tuberculosis trifunctional enzyme (MtTFE) is an α2β2 tetrameric enzyme in which the α-chain harbors the 2E-enoyl-CoA hydratase (ECH) and 3S-hydroxyacyl-CoA dehydrogenase (HAD) active sites, and the β-chain provides the 3-ketoacyl-CoA thiolase (KAT) active site. Linear, medium-chain and long-chain 2E-enoyl-CoA molecules are the preferred substrates of MtTFE. Previous crystallographic binding and modeling studies identified binding sites for the acyl-CoA substrates at the three active sites, as well as the NAD binding pocket at the HAD active site. These studies also identified three additional CoA binding sites on the surface of MtTFE that are different from the active sites. It has been proposed that one of these additional sites could be of functional relevance for the substrate channeling (by surface crawling) of reaction intermediates between the three active sites. Here, 226 fragments were screened in a crystallographic fragment-binding study of MtTFE crystals, resulting in the structures of 16 MtTFE–fragment complexes. Analysis of the 121 fragment-binding events shows that the ECH active site is the `binding hotspot' for the tested fragments, with 41 binding events. The mode of binding of the fragments bound at the active sites provides additional insight into how the long-chain acyl moiety of the substrates can be accommodated at their proposed binding pockets. In addition, the 20 fragment-binding events between the active sites identify potential transient binding sites of reaction intermediates relevant to the possible channeling of substrates between these active sites. These results provide a basis for further studies to understand the functional relevance of the latter binding sites and to identify substrates for which channeling is crucial.

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 Å. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation-search step enhances the signal to noise. A Fourier-space likelihood-based local search approach, based on the previously published em_placement software, has been implemented in the new emplace_local program. Tests confirm that the local search approach enhances the speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular-graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed.

Proteins frequently undergo covalent modification at the post-translational level, which involves the covalent attachment of chemical groups onto amino acids. This can entail the singular or multiple addition of small groups, such as phosphorylation; long-chain modifications, such as glycosylation; small proteins, such as ubiquitination; as well as the interconversion of chemical groups, such as the formation of pyroglutamic acid. These post-translational modifications (PTMs) are essential for the normal functioning of cells, as they can alter the physicochemical properties of amino acids and therefore influence enzymatic activity, protein localization, protein–protein interactions and protein stability. Despite their inherent importance, accurately depicting PTMs in experimental studies of protein structures often poses a challenge. This review highlights the role of PTMs in protein structures, as well as the prevalence of PTMs in the Protein Data Bank, directing the reader to accurately built examples suitable for use as a modelling reference.

Eukaryotic TIR (Toll/interleukin-1 receptor protein) domains signal via TIR–TIR interactions, either by self-association or by interaction with other TIR domains. In mammals, TIR domains are found in Toll-like receptors (TLRs) and cytoplasmic adaptor proteins involved in pro-inflammatory signaling. Previous work revealed that the MAL TIR domain (MALTIR) nucleates the assembly of MyD88TIR into crystalline arrays in vitro. A microcrystal electron diffraction (MicroED) structure of the MyD88TIR assembly has previously been solved, revealing a two-stranded higher-order assembly of TIR domains. In this work, it is demonstrated that the TIR domain of TLR2, which is reported to signal as a heterodimer with either TLR1 or TLR6, induces the formation of crystalline higher-order assemblies of MyD88TIR in vitro, whereas TLR1TIR and TLR6TIR do not. Using an improved data-collection protocol, the MicroED structure of TLR2TIR-induced MyD88TIR microcrystals was determined at a higher resolution (2.85 Å) and with higher completeness (89%) compared with the previous structure of the MALTIR-induced MyD88TIR assembly. Both assemblies exhibit conformational differences in several areas that are important for signaling (for example the BB loop and CD loop) compared with their monomeric structures. These data suggest that TLR2TIR and MALTIR interact with MyD88 in an analogous manner during signaling, nucleating MyD88TIR assemblies uni­directionally.

Crystal polymorphism serves as a strategy to study the conformational flexibility of proteins. However, the relationship between protein crystal packing and protein conformation often remains elusive. In this study, two distinct crystal forms of a green fluorescent protein variant, NowGFP, are compared: a previously identified monoclinic form (space group C2) and a newly discovered ortho­rhombic form (space group P212121). Comparative analysis reveals that both crystal forms exhibit nearly identical linear assemblies of NowGFP molecules interconnected through similar crystal contacts. However, a notable difference lies in the stacking of these assemblies: parallel in the monoclinic form and perpendicular in the orthorhombic form. This distinct mode of stacking leads to different crystal contacts and induces structural alteration in one of the two molecules within the asymmetric unit of the orthorhombic crystal form. This new conformational state captured by orthorhombic crystal packing exhibits two unique features: a conformational shift of the β-barrel scaffold and a restriction of pH-dependent shifts of the key residue Lys61, which is crucial for the pH-dependent spectral shift of this protein. These findings demonstrate a clear connection between crystal packing and alternative conformational states of proteins, providing insights into how structural variations influence the function of fluorescent proteins.

Fatty acid-derivative prodrugs have been utilized extensively to improve the physicochemical, biopharmaceutical and pharmacokinetic properties of active pharmaceutical ingredients. However, to our knowledge, the crystallization behavior of prodrugs modified with different fatty acids has not been explored. In the present work, a series of paliperidone aliphatic prodrugs with alkyl chain lengths ranging from C4 to C16 was investigated with respect to crystal structure, crystal morphology and crystallization kinetics. The paliperidone derivatives exhibited isostructural crystal packing, despite the different alkyl chain lengths, and crystallized with the dominant (100) face in both melt and solution. The rate of crystallization for paliperidone derivatives in the melt increases with alkyl chain length owing to greater molecular mobility. In contrast, the longer chains prolong the nucleation induction time and reduce the crystal growth kinetics in solution. The results show a correlation between difficulty of nucleation in solution and the interfacial energy. This work provides insight into the crystallization behavior of paliperidone aliphatic prodrugs and reveals that the role of alkyl chain length in the crystallization behavior has a strong dependence on the crystallization method.

The orientation ordering and assembly behavior of silica–nickel Janus particles in a static external magnetic field were probed by ultra small-angle X-ray scattering (USAXS). Even in a weak applied field, the net magnetic moments of the individual particles aligned in the direction of the field, as indicated by the anisotropy in the recorded USAXS patterns. X-ray photon correlation spectroscopy (XPCS) measurements on these suspensions revealed that the corresponding particle dynamics are primarily Brownian diffusion [Zinn, Sharpnack & Narayanan (2023). Soft Matter, 19, 2311–2318]. At higher fields, the magnetic forces led to chain-like configurations of particles, as indicated by an additional feature in the USAXS pattern. A theoretical framework is provided for the quantitative interpretation of the observed anisotropic scattering diagrams and the corresponding degree of orientation. No anisotropy was detected when the magnetic field was applied along the beam direction, which is also replicated by the model. The method presented here could be useful for the interpretation of oriented scattering patterns from a wide variety of particulate systems. The combination of USAXS and XPCS is a powerful approach for investigating asymmetric colloidal particles in external fields.

Speckle-tracking X-ray imaging is an attractive candidate for dynamic X-ray imaging owing to its flexible setup and simultaneous yields of phase, transmission and scattering images. However, traditional speckle-tracking imaging methods suffer from phase distortion at locations with abrupt changes in density, which is always the case for real samples, limiting the applications of the speckle-tracking X-ray imaging method. In this paper, we report a deep-learning based method which can achieve dynamic X-ray speckle-tracking imaging with high-accuracy phase retrieval. The calibration results of a phantom show that the profile of the retrieved phase is highly consistent with the theoretical one. Experiments of polyurethane foaming demonstrated that the proposed method revealed the evolution of the complicated microstructure of the bubbles accurately. The proposed method is a promising solution for dynamic X-ray imaging with high-accuracy phase retrieval, and has extensive applications in metrology and quantitative analysis of dynamics in material science, physics, chemistry and biomedicine.

Bacterial ABC toxin complexes (Tcs) comprise three core proteins: TcA, TcB and TcC. The TcA protein forms a pentameric assembly that attaches to the surface of target cells and penetrates the cell membrane. The TcB and TcC proteins assemble as a heterodimeric TcB–TcC subcomplex that makes a hollow shell. This TcB–TcC subcomplex self-cleaves and encapsulates within the shell a cytotoxic `cargo' encoded by the C-terminal region of the TcC protein. Here, we describe the structure of a previously uncharacterized TcC protein from Yersinia entomophaga, encoded by a gene at a distant genomic location from the genes encoding the rest of the toxin complex, in complex with the TcB protein. When encapsulated within the TcB–TcC shell, the C-terminal toxin adopts an unfolded and disordered state, with limited areas of local order stabilized by the chaperone-like inner surface of the shell. We also determined the structure of the toxin cargo alone and show that when not encapsulated within the shell, it adopts an ADP-ribosyltransferase fold most similar to the catalytic domain of the SpvB toxin from Salmonella typhimurium. Our structural analysis points to a likely mechanism whereby the toxin acts directly on actin, modifying it in a way that prevents normal polymerization.

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 Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules (e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

Categorization underlies understanding. Conceptualizing solid-state structures of organic molecules with `archetype crystal structures' bridges established categories of disorder, polymorphism and solid solutions and is herein extended to special position and high-Z' structures. The concept was developed in the context of disorder modelling [Dittrich, B. (2021). IUCrJ, 8, 305–318] and relies on adding quantum chemical energy differences between disorder components to other criteria as an explanation as to why disorder – and disappearing disorder – occurs in an average structure. Part of the concept is that disorder, as probed by diffraction, affects entire molecules, rather than just the parts of a molecule with differing conformations, and the finding that an R·T energy difference between disorder archetypes is usually not exceeded. An illustrative example combining disorder and special positions is the crystal structure of oestradiol hemihydrate analysed here, where its space-group/subgroup relationship is required to explain its disorder of hydrogen-bonded hydrogen atoms. In addition, we show how high-Z' structures can also be analysed energetically and understood via archetypes: high-Z' structures occur when an energy gain from combining different rather than overall alike conformations in a crystal significantly exceeds R·T, and this finding is discussed in the context of earlier explanations in the literature. Twinning is not related to archetype structures since it involves macroscopic domains of the same crystal structure. Archetype crystal structures are distinguished from crystal structure prediction trial structures in that an experimental reference structure is required for them. Categorization into archetype structures also has practical relevance, leading to a new practice of disorder modelling in experimental least-squares refinement alluded to in the above-mentioned publication.

Appreciating that the role of the solute–solvent and other outer-sphere interactions is essential for understanding chemistry and chemical dynamics in solution, experimental approaches are needed to address the structural consequences of these interactions, complementing condensed-matter simulations and coarse-grained theories. High-energy X-ray scattering (HEXS) combined with pair distribution function analysis presents the opportunity to probe these structures directly and to develop quantitative, atomistic models of molecular systems in situ in the solution phase. However, at concentrations relevant to solution-phase chemistry, the total scattering signal is dominated by the bulk solvent, prompting researchers to adopt a differential approach to eliminate this unwanted background. Though similar approaches are well established in quantitative structural studies of macromolecules in solution by small- and wide-angle X-ray scattering (SAXS/WAXS), analogous studies in the HEXS regime—where sub-ångström spatial resolution is achieved—remain underdeveloped, in part due to the lack of a rigorous theoretical description of the experiment. To address this, herein we develop a framework for differential solution scattering experiments conducted at high energies, which includes concepts of the solvent-excluded volume introduced to describe SAXS/WAXS data, as well as concepts from the time-resolved X-ray scattering community. Our theory is supported by numerical simulations and experiment and paves the way for establishing quantitative methods to determine the atomic structures of small molecules in solution with resolution approaching that of crystallography.

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.

Stimulated by informal conversations at the XVII International Small Angle Scattering (SAS) conference (Traverse City, 2017), an international team of experts undertook a round-robin exercise to produce a large dataset from proteins under standard solution conditions. These data were used to generate consensus SAS profiles for xylose isomerase, urate oxidase, xylanase, lysozyme and ribonuclease A. Here, we apply a new protocol using maximum likelihood with a larger number of the contributed datasets to generate improved consensus profiles. We investigate the fits of these profiles to predicted profiles from atomic coordinates that incorporate different models to account for the contribution to the scattering of water molecules of hydration surrounding proteins in solution. Programs using an implicit, shell-type hydration layer generally optimize fits to experimental data with the aid of two parameters that adjust the volume of the bulk solvent excluded by the protein and the contrast of the hydration layer. For these models, we found the error-weighted residual differences between the model and the experiment generally reflected the subsidiary maxima and minima in the consensus profiles that are determined by the size of the protein plus the hydration layer. By comparison, all-atom solute and solvent molecular dynamics (MD) simulations are without the benefit of adjustable parameters and, nonetheless, they yielded at least equally good fits with residual differences that are less reflective of the structure in the consensus profile. Further, where MD simulations accounted for the precise solvent composition of the experiment, specifically the inclusion of ions, the modelled radius of gyration values were significantly closer to the experiment. The power of adjustable parameters to mask real differences between a model and the structure present in solution is demonstrated by the results for the conformationally dynamic ribonuclease A and calculations with pseudo-experimental data. This study shows that, while methods invoking an implicit hydration layer have the unequivocal advantage of speed, care is needed to understand the influence of the adjustable parameters. All-atom solute and solvent MD simulations are slower but are less susceptible to false positives, and can account for thermal fluctuations in atomic positions, and more accurately represent the water molecules of hydration that contribute to the scattering profile.

Here, the novel technique of extended-range high-energy-resolution fluorescence detection (XR-HERFD) has successfully observed the n = 2 satellite in manganese to a high accuracy. The significance of the satellite signature presented is many hundreds of standard errors and well beyond typical discovery levels of three to six standard errors. This satellite is a sensitive indicator for all manganese-containing materials in condensed matter. The uncertainty in the measurements has been defined, which clearly observes multiple peaks and structure indicative of complex physical quantum-mechanical processes. Theoretical calculations of energy eigenvalues, shake-off probability and Auger rates are also presented, which explain the origin of the satellite from physical n = 2 shake-off processes. The evolution in the intensity of this satellite is measured relative to the full Kα spectrum of manganese to investigate satellite structure, and therefore many-body processes, as a function of incident energy. Results demonstrate that the many-body reduction factor S02 should not be modelled with a constant value as is currently done. This work makes a significant contribution to the challenge of understanding many-body processes and interpreting HERFD or resonant inelastic X-ray scattering spectra in a quantitative manner.

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.

Sialic acids play crucial roles in cell surface glycans of both eukaryotic and prokaryotic organisms, mediating various biological processes, including cell–cell interactions, development, immune response, oncogenesis and host–pathogen interactions. This review focuses on the β-anomeric form of N-acetyl­neuraminic acid (Neu5Ac), particularly its binding affinity towards various proteins, as elucidated by solved protein structures. Specifically, we delve into the binding mechanisms of Neu5Ac to proteins involved in sequestering and transporting Neu5Ac in Gram-negative bacteria, with implications for drug design targeting these proteins as antimicrobial agents. Unlike the initial assumptions, structural analyses revealed significant variability in the Neu5Ac binding pockets among proteins, indicating diverse evolutionary origins and binding modes. By comparing these findings with existing structures from other systems, we can effectively highlight the intricate relationship between protein structure and Neu5Ac recognition, emphasizing the need for tailored drug design strategies to inhibit Neu5Ac-binding proteins across bacterial species.

Crystallographic texture is a key organization feature of many technical and biological materials. In these materials, especially hierarchically structured ones, the preferential alignment of the nano constituents heavily influences the macroscopic behavior of the material. To study local crystallographic texture with both high spatial and angular resolution, we developed Texture Tomography (TexTOM). This approach allows the user to model the diffraction data of polycrystalline materials using the full reciprocal space of the crystal ensemble and describe the texture in each voxel via an orientation distribution function, hence it provides 3D reconstructions of the local texture by measuring the probabilities of all crystal orientations. The TexTOM approach addresses limitations associated with existing models: it correlates the intensities from several Bragg reflections, thus reducing ambiguities resulting from symmetry. Further, it yields quantitative probability distributions of local real space crystal orientations without further assumptions about the sample structure. Finally, its efficient mathematical formulation enables reconstructions faster than the time scale of the experiment. This manuscript presents the mathematical model, the inversion strategy and its current experimental implementation. We show characterizations of simulated data as well as experimental data obtained from a synthetic, inorganic model sample: the silica–witherite biomorph. TexTOM provides a versatile framework to reconstruct 3D quantitative texture information for polycrystalline samples; it opens the door for unprecedented insights into the nanostructural makeup of natural and technical materials.

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.

Identifying and characterizing metal-binding sites (MBS) within macromolecular structures is imperative for elucidating their biological functions. CheckMyMetal (CMM) is a web based tool that facilitates the interactive valid­ation of MBS in structures determined through X-ray crystallography and cryo-electron microscopy (cryo-EM). Recent updates to CMM have significantly enhanced its capability to efficiently handle large datasets generated from cryo-EM structural analyses. In this study, we address various challenges inherent in validating MBS within both X-ray and cryo-EM structures. Specifically, we examine the difficulties associated with accurately identifying metals and modeling their coordination environments by considering the ongoing reproducibility challenges in structural biology and the critical importance of well annotated, high-quality experimental data. CMM employs a sophisticated framework of rules rooted in the valence bond theory for MBS validation. We explore how CMM validation parameters correlate with the resolution of experimentally derived structures of macromolecules and their complexes. Additionally, we showcase the practical utility of CMM by analyzing a representative cryo-EM structure. Through a comprehensive examination of experimental data, we demonstrate the capability of CMM to advance MBS characterization and identify potential instances of metal misassignment.

Conformational heterogeneity of biological macromolecules is a challenge in single-particle averaging (SPA). Current standard practice is to employ classification and filtering methods that may allow a discrete number of conformational states to be reconstructed. However, the conformation space accessible to these molecules is continuous and, therefore, explored incompletely by a small number of discrete classes. Recently developed heterogeneous reconstruction algorithms (HRAs) to analyse continuous heterogeneity rely on machine-learning methods that employ low-dimensional latent space representations. The non-linear nature of many of these methods poses a challenge to their validation and interpretation and to identifying functionally relevant conformational trajectories. These methods would benefit from in-depth benchmarking using high-quality synthetic data and concomitant ground truth information. We present a framework for the simulation and subsequent analysis with respect to the ground truth of cryo-EM micrographs containing particles whose conformational heterogeneity is sourced from molecular dynamics simulations. These synthetic data can be processed as if they were experimental data, allowing aspects of standard SPA workflows as well as heterogeneous reconstruction methods to be compared with known ground truth using available utilities. The simulation and analysis of several such datasets are demonstrated and an initial investigation into HRAs is presented.

The absence of solvent molecules in high-resolution protein crystal structure models deposited in the Protein Data Bank (PDB) contradicts the fact that, for proteins crystallized from aqueous media, water molecules are always expected to bind to the protein surface, as well as to some sites in the protein interior. An analysis of the contents of the PDB indicated that the expected ratio of the number of water molecules to the number of amino-acid residues exceeds 1.5 in atomic resolution structures, decreasing to 0.25 at around 2.5 Å resolution. Nevertheless, almost 800 protein crystal structures determined at a resolution of 2.5 Å or higher are found in the current release of the PDB without any water molecules, whereas some other depositions have unusually low or high occupancies of modeled solvent. Detailed analysis of these depositions revealed that the lack of solvent molecules might be an indication of problems with either the diffraction data, the refinement protocol, the deposition process or a combination of these factors. It is postulated that problems with solvent structure should be flagged by the PDB and addressed by the depositors.

Density functional theory methods are applied to crystal structures and stabilities of phases from the aleksite homologous series, PbnBi4Te4Sn+2 (n = homologue number). The seven phases investigated correspond to n = 0 (tetradymite), 2 (aleksite-21R and -42R), 4 (saddlebackite-9H and -18H), 6 (unnamed Pb6Bi4Te4S8), 8 (unnamed Pb8Bi4Te4S10), 10 (hitachiite) and 12 (unnamed Pb12Bi4Te4S14). These seven phases correspond to nine single- or double-module structures, each comprising an odd number of atom layers, 5, 7, (5.9), 9, (7.11), 11, 13, 15 and 17, expressed by the formula: S(MpXp+1)·L(Mp+1Xp+2), where M = Pb, Bi and X = Te, S, p ≥ 2, and S and L = number of short and long modules, respectively. Relaxed structures show a and c values within 1.5% of experimental data; a and the interlayer distance dsub decrease with increasing PbS content. Variable Pb—S bond lengths contrast with constant Pb—S bond lengths in galena. All phases are n-fold superstructures of a rhombohedral subcell with c/3 = dsub*. Electron diffraction patterns show two brightest reflections at the centre of dsub*, described by the modulation vector qF = (i/N) · dsub*, i = S + L. A second modulation vector, q = γ · csub*, shows a decrease in γ, from 1.8 to 1.588, across the n = 0 to n = 12 interval. The linear relationship between γ and dsub allows the prediction of any theoretical phases beyond the studied compositional range. The upper PbS-rich limit of the series is postulated as n = 398 (Pb398Bi4Te4S400), a phase with dsub (1.726 Å) identical to that of trigonal PbS within experimental error. The aleksite series is a prime example of mixed layer compounds built with accretional homology principles.

K3FeTe2O8(OH)2(H2O)2 was synthesized under hydrothermal conditions from Te(OH)6, FeSO4·7H2O and 85 wt% KOH in a 1:2:6 molar ratio. The crystal structure is built of a triperiodic network. One disordered water molecule per formula unit is located in a channel and can be partially removed by heating. Systematic one-dimensional diffuse scattering indicates a polytypic character, which is best described by application of the order–disorder theory. The major polytype is monoclinic with pseudo-orthorhombic metrics. It is interrupted by fragments of an orthorhombic polytype. The diffraction intensities are analyzed using structure factor calculations.

A significant part of the present and future of optoelectronic devices lies on thin multilayer heterostructures. Their optical properties depend strongly on strain, being essential to the knowledge of the stress level to optimize the growth process. Here the structural and microstructural characteristics of sub-micron a-ZnO epilayers (12 to 770 nm) grown on r-sapphire by metal–organic chemical vapour deposition are studied. Morphological and structural studies have been made using scanning electron microscopy and high-resolution X-ray diffraction. Plastic unit-cell distortion and corresponding strain have been determined as a function of film thickness. A critical thickness has been observed as separating the non-elastic/elastic states with an experimental value of 150–200 nm. This behaviour has been confirmed from ultraviolet photoelectron spectroscopy, X-ray photoelectron spectroscopy and high-resolution transmission electron microscopy measurements. An equation that gives the balance of strains is proposed as an interesting method to experimentally determine this critical thickness. It is concluded that in the thinnest films an elongation of the Zn—O bond takes place and that the plastic strained ZnO films relax through nucleation of misfit dislocations, which is a consequence of three-dimensional surface morphology.

Traditional X-ray methods are extensively applied to commercial cement samples in order to determine their physical and chemical properties. Powder patterns are routinely used to quantify the composition of these phase mixtures, but structure determination becomes difficult because of reflection overlapping caused by the high number of different crystal structures. The fast-growing 3D electron diffraction technique and its related automated acquisition protocols arise as a potentially very interesting tool for the cement industry, since they enable the fast and systematic acquisition of diffraction data from individual particles. In this context, electron diffraction has been used in the investigation of the different crystalline phases present in various commercial clinkers for cement. Automated data collection procedures and subsequent data processing have enabled the structural characterization of the different crystal structures from which the α'H polymorph of Ca2SiO4 (belite) exhibited satellite reflections. Its average crystal structure has been known since 1971 and satellite reflections have been reported previously, yet the modulation was never fully described by means of the superspace formalism. Here, the incommensurately modulated structure is solved and refined using harmonic and crenel functions in the superspace group Pnma(α00)0ss, showing the potential of 3D electron diffraction for systematic crystallographic characterizations of cement. A full description of the different belite polymorphs is provided considering this modulated structure.

It is pointed out that many authors are unaware that the particular choice of unit-cell origin determines the irreducible representations to which octahedral tilts in perovskites belong. Furthermore, a recommendation is made that the preferred option is with the origin at the B-cation site rather than that of the A site.

A polycrystalline sample LuCrO3 has been characterized by neutron powder diffraction (NPD) and magnetization measurements. Its crystal structure has been Rietveld refined from NPD data in space group Pnma; this perovskite contains strongly tilted CrO6 octahedra with extremely bent Cr—O—Cr superexchange angles of ∼142°. The NPD data show that below Néel temperature (TN ≃ 131 K), the magnetic structure can be defined as an A-type antiferromagnetic arrangement of Cr3+ magnetic moments, aligned along the b axis, with a canting along the c axis. A noticeable magneto­strictive effect is observed in the unit-cell parameters and volume upon cooling down across TN. The AC magnetic susceptibility indicates the onset of magnetic ordering below 112.6 K; the magnetization isotherms below TN show a nonlinear behaviour that is associated with the described canting of the Cr3+ magnetic moments. From the Curie–Weiss law, the effective moment of the Cr3+ sublattice is found to be μeff = 3.55 μB (calculated 3.7 μB) while the ΘCW parameter yields a value of −155 K, indicating antiferromagnetic interactions. There is a conspicuous increase of TN upon the application of external pressure, which must be due to shortening of the Cr—O bond length under compression that increases the orbital overlap integral.

Synthesis experiments were conducted in the quaternary system K2O–Na2O–CaO–SiO2, resulting in the formation of a previously unknown compound with the composition K0.72Na1.71Ca5.79Si6O19. Single crystals of sufficient size and quality were recovered from a starting mixture with a K2O:Na2O:CaO:SiO2 molar ratio of 1.5:0.5:2:3. The mixture was confined in a closed platinum tube and slowly cooled from 1150°C at a rate of 0.1°C min−1 to 700°C before being finally quenched in air. The structure has tetragonal symmetry and belongs to space group P4122 (No. 91), with a = 7.3659 (2), c = 32.2318 (18) Å, V = 1748.78 (12) Å3, and Z = 4. The silicate anion consists of highly puckered, unbranched six-membered oligomers with the composition [Si6O19] and point group symmetry 2 (C2). Although several thousands of natural and synthetic oxosilicates have been structurally characterized, this compound is the first representative of a catena-hexasilicate anion, to the best of our knowledge. Structural investigations were completed using Raman spectroscopy. The spectroscopic data was interpreted and the bands were assigned to certain vibrational species with the support of density functional theory at the HSEsol level of theory. To determine the stability properties of the novel oligosilicate compared to those of the chemically and structurally similar cyclo­silicate combeite, we calculated the electronegativity of the respective structures using the electronegativity equalization method. The results showed that the molecular electronegativity of the cyclo­silicate was significantly higher than that of the oligostructure due to the different connectivities of the oxygen atoms within the molecular units.

The embedded call to a special version of the web-based Bilbao Crystallographic Server tool k-SUBGROUPSMAG from within GSAS-II to form a list of all possible commensurate magnetic subgroups of a parent magnetic grey group is described. It facilitates the selection and refinement of the best commensurate magnetic structure model by having all the analysis tools including Rietveld refinement in one place as part of GSAS-II. It also provides the chosen magnetic space group as one of the 1421 possible standard Belov–Neronova–Smirnova forms or equivalent non-standard versions.