It is well known that Hirshfeld surfaces provide an easy and straightforward way of analysing inter­molecular inter­actions in the crystal environment. The use of atomic Hirshfeld surfaces has also demonstrated that such surfaces carry information related to chemical bonds which allow a deeper evaluation of the structures. Here we briefly summarize the approach of atomic Hirshfeld surfaces while further evaluating the kind of information that can be retrieved from them. We show that the analysis of the metal-centre Hirshfeld surfaces from structures refined via Hirshfeld Atom Refinement (HAR) allow accurate evaluation of contacts of type M⋯H, and that such contacts can be related to the overall shape of the surfaces. The com­pounds analysed were tetra­aqua­bis­(3-carb­oxy­propionato)metal(II), [M(C4H3O4)2(H2O)4], for metal(II)/M = manganese/Mn, cobalt/Co, nickel/Ni and zinc/Zn. We also evaluate the sensitivity of the surfaces by an investigation of seemingly flat surfaces through analysis of the curvature functions in the direction of C—C bonds. The obtained values not only demonstrate variations in curvature but also show a correlation with the hybridization of the C atoms involved in the bond.

The activation of C—C bonds by transition-metal com­plexes is of continuing inter­est and aceto­nitrile (MeCN) has attracted attention as a cyanide source with com­paratively low toxicity for organic cyanation reactions. A di­iron end-on μ-η1:η1-CN-bridged com­plex was obtained from a crystallization experiment of an open-chain iron–NHC com­plex, namely, μ-cyanido-κ2C:N-bis­{[(aceto­nitrile-κN)[3,3'-bis­(pyridin-2-yl)-1,1'-(methyl­idene)bis­(benzimidazol-2-yl­idene)]iron(II)} tris­(hexa­fluoro­phos­phate), [Fe2(CN)(C2H3N)2(C25H18N6)2](PF6)3. The cyanide appears to originate from the MeCN solvent by C—C bond cleavage or through carbon–hy­dro­gen oxidation.

Three 2,4-di­aryl­pyrroles were synthesized starting from 4-nitro­butano­nes and the crystal structures of two derivatives were analysed. These are 4-(4-meth­oxy­phen­yl)-2-(thio­phen-2-yl)-1H-pyrrole, C15H13NOS, and 3-(4-bromo­phen­yl)-2-nitroso-5-phenyl-1H-pyrrole, C16H11BrN2O. Although pyrroles without sub­stituents at the α-position with respect to the N atom are very air sensitive and tend to polymerize, we succeeded in growing an adequate crystal for X-ray diffraction analysis. Further derivatization using sodium nitrite afforded a nitrosyl pyrrole derivative, which crystallized in the triclinic space group Poverline{1} with Z = 6. Thus, herein we report the first crystal structure of a nitrosyl pyrrole. Inter­estingly, the co-operative hydrogen bonds in this NO-substituted pyrrole lead to a trimeric structure with bifurcated halogen bonds at the ends, forming a two-dimensional (2D) layer with inter­stitial voids having a radius of 5 Å, similar to some reported macrocyclic porphyrins.

Herein we report the crystal structures of two ben­zo­di­az­e­pines obtained by reacting N,N'-(4,5-di­amino-1,2-phenyl­ene)bis­(4-methyl­ben­zene­sul­fon­am­ide) (1) or 4,5-(4-methyl­ben­zene­sul­fon­am­ido)­ben­zene-1,2-diaminium dichloride (1·2HCl) with acetone, giving 2,2,4-trimethyl-8,9-bis­(4-methyl­ben­zene­sul­fon­am­ido)-2,3-di­hydro-5H-1,5-ben­zo­di­az­e­pine, C26H30N4O4S2 (2), and 2,2,4-tri­methyl-8,9-bis­(4-methyl­ben­zene­sul­fon­am­ido)-2,3-di­hydro-5H-1,5-ben­zo­di­az­e­pin-1-ium chloride 0.3-hydrate, C26H31N4O4S2+·Cl−·0.3H2O (3). Compounds 2 and 3 were first obtained in attempts to recrystallize 1 and 1·2HCl using acetone as solvent. This solvent reacted with the vicinal di­amines present in the mol­ecular structures, forming a 5H-1,5-ben­zo­di­az­e­pine ring. In the crystal structure of 2, the seven-membered ring of ben­zo­di­az­e­pine adopts a boat-like conformation, while upon protonation, observed in the crystal structure of 3, it adopts an envelope-like conformation. In both crystalline com­pounds, the tosyl­amide N atoms are not in resonance with the arene ring, mainly due to hy­dro­gen bonds and steric hindrance caused by the large vicinal groups in the aromatic ring. At a supra­molecular level, the crystal structure is maintained by a combination of hy­dro­gen bonds and hydro­phobic inter­actions. In 2, amine-to-tosyl N—H⋯O and amide-to-imine N—H⋯N hy­dro­gen bonds can be observed. In contrast, in 3, the chloride counter-ion and water mol­ecule result in most of the hy­dro­gen bonds being of the amide-to-chloride and ammonium-to-chloride N—H⋯Cl types, while the amine inter­acts with the tosyl group, as seen in 2. In conclusion, we report the synthesis of 1, 1·2HCl and 2, as well as their chemical characterization. For 2, two synthetic methods are described, i.e. solvent-mediated crystallization and synthesis via a more efficient and cleaner route as a polycrystalline material. Salt 3 was only obtained as presented, with only a few crystals being formed.

Treating the amide acetanilide (N-phenyl­acetamide, C8H9NO) with aqueous strong acids allowed the structures of five hemi-protonated salt forms of acetanilide to be elucidated. N-(1-Hy­droxy­ethyl­idene)anilinium chloride–N-phenyl­acetamide (1/1), [(C8H9NO)2H][Cl], and the bromide, [(C8H9NO)2H][Br], triiodide, [(C8H9NO)2H][I3], tetra­fluoro­borate, [(C8H9NO)2H][BF4], and di­iodo­bromide hemi(diiodine), [(C8H9NO)2H][I2Br]·0.5I2, analogues all feature centrosymmetric dimeric units linked by O—H⋯O hy­dro­gen bonds that extend into one-dimensional hy­dro­gen-bonded chains through N—H⋯X inter­actions, where X is the halide atom of the anion. Protonation occurs at the amide O atom and results in systematic lengthening of the C=O bond and a corresponding shortening of the C—N bond. The size of these geometric changes is similar to those found for hemi-protonated paracetamol structures, but less than those in fully protonated paracetamol structures. The bond angles of the amide fragments are also found to change on protonation, but these angular changes are also influenced by conformation, namely, whether the amide group is coplanar with the phenyl ring or twisted out of plane.

Three structurally diverse 5-phenyl­tetra­zolato (Tz) Ti, Zr, and Ta com­plexes, namely, (C2H8N)[Ti2(C7H5N4)5(C2H6N)4]·1.45C6H6 or (Me2NH2)[Ti2(NMe2)4(2,3-μ-Tz)3(2-η1-Tz)2]·1.45C6H6, (1·1.45C6H6), [Zr2(C7H5N4)6(C2H6N)2(C2H7N)2]·1.12C6H6·0.382CH2Cl2 or [Zr2(Me2NH)2(NMe2)2(2,3-μ-Tz)3(2-η1-Tz)2(1,2-η2-Tz)]·1.12C6H6·0.38CH2Cl2 (2·1.12C6H6·0.38CH2Cl2), and (C2H8N)2[Ta2(C7H5N4)8(C2H6N)2O]·0.25C7H8 or (Me2NH2)2[Ta2(NMe2)2(2,3-μ-Tz)2(2-η1-Tz)6O]·0.25C7H8 (3·0.25C7H8), where TzH is 5-phenyl-1H-tetra­zole, have been synthesized and structurally characterized. All three com­plexes are dinuclear; the Ti center in 1 is six-coordinate, whereas the Zr and Ta atoms in 2 and 3 are seven-coordinate. The coordination environments of the Ti centers in 1 are similar, and so are the ligations of the Ta centers in 3. In contrast, the two Zr centers in 2 bear a different number of ligands, one of which is a bidentate η2-5-phenyl­tetra­zolato ligand that has not been observed previously for d-block elements. The di­methyl­amido ligand, present in the starting materials, remained un­changed, or was converted to di­methyl­amine and di­methyl­ammonium during the synthesis. Di­methyl­amine coordinates as a neutral ligand, whereas di­methyl­ammonium is retained as a hy­dro­gen-bonded entity bridging Tz ligands.

The crystal structures of two coordination com­pounds, (acetato-κO)(2,2'-bi­py­ri­dine-κ2N,N')(1,10-phenanthroline-κ2N,N')copper(II) acetate hexa­hydrate, [Cu(C2H3O2)(C10H8N2)(C12H8N2)](C2H3O2)·6H2O or [Cu(bipy)(phen)Ac]Ac·6H2O, and (acetato-κO)bis­(2,2'-bi­py­ri­dine-κ2N,N')copper(II) acetate–acetic acid–water (1/1/3), [Cu(C2H3O2)(C10H8N2)2](C2H3O2)·C2H4O2·3H2O or [Cu(bipy)2Ac]Ac·HAc·3H2O, are reported and com­pared with the previously published structure of [Cu(phen)2Ac]Ac·7H2O (phen is 1,10-phenanthroline, bipy for 2,2'-bi­py­ri­dine, ac is acetate and Hac is acetic acid). The geometry around the metal centre is penta­coordinated, but highly distorted in all three cases. The coordination number and the geometric distortion are both discussed in detail, and all com­plexes belong to the space group Poverline{1}. The analysis of the geometric parameters and the Hirshfeld surface properties dnorm and curvedness provide information about the metal–ligand inter­actions in these com­plexes and allow com­parison with similar systems.

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.

In this study, we report the results of continuous rotation electron diffraction studies of single DyPO4·nH2O (rhabdophane) nanocrystals. The diffraction patterns can be fit to a trigonal lattice (P3121) with lattice parameters a = 7.019 (5) and c = 6.417 (5) Å. However, there is also a set of diffuse background scattering features present that are associated with a disordered superstructure that is double these lattice parameters and fits with an arrangement of water mol­ecules present in the structure pore. Pair distribution function (PDF) maps based on the diffuse background allowed the extent of the water correlation to be estimated, with 2–3 nm correlation along the c axis and ∼5 nm along the a/b axis.

Historically, knowledge of the mol­ecular packing within the crystal structures of organic semi­con­duc­tors has been instrumental in understanding their solid-state electronic properties. Nowadays, crystal structures are thus becoming increasingly important for enabling engineering properties, understanding poly­mor­phism in bulk and in thin films, exploring dynamics and elucidating phase-transition mech­a­nisms. This review article introduces the most salient and recent results of the field.

The technique of time-resolved macromolecular crystallography (TR-MX) has recently been rejuvenated at synchrotrons, resulting in the design of dedicated beamlines. Using pump–probe schemes, this should make the mechanistic study of photoactive proteins and other suitable systems possible with time resolutions down to microseconds. In order to identify relevant time delays, time-resolved spectroscopic experiments directly performed on protein crystals are often desirable. To this end, an instrument has been built at the icOS Lab (in crystallo Optical Spectroscopy Laboratory) at the European Synchrotron Radiation Facility using reflective focusing objectives with a tuneable nanosecond laser as a pump and a microsecond xenon flash lamp as a probe, called the TR-icOS (time-resolved icOS) setup. Using this instrument, pump–probe spectra can rapidly be recorded from single crystals with time delays ranging from a few microseconds to seconds and beyond. This can be repeated at various laser pulse energies to track the potential presence of artefacts arising from two-photon absorption, which amounts to a power titration of a photoreaction. This approach has been applied to monitor the rise and decay of the M state in the photocycle of crystallized bacteriorhodopsin and showed that the photocycle is increasingly altered with laser pulses of peak fluence greater than 100 mJ cm−2, providing experimental laser and delay parameters for a successful TR-MX experiment.

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.

Cryo-electron microscopy (cryo-EM) has witnessed radical progress in the past decade, driven by developments in hardware and software. While current software packages include processing pipelines that simplify the image-processing workflow, they do not prioritize the in-depth analysis of crucial metadata, limiting troubleshooting for challenging data sets. The widely used RELION software package lacks a graphical native representation of the underlying metadata. Here, two web-based tools are introduced: relion_live.py, which offers real-time feedback on data collection, aiding swift decision-making during data acquisition, and relion_analyse.py, a graphical interface to represent RELION projects by plotting essential metadata including interactive data filtration and analysis. A useful script for estimating ice thickness and data quality during movie pre-processing is also presented. These tools empower researchers to analyse data efficiently and allow informed decisions during data collection and processing.

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

Catalase is an antioxidant enzyme that breaks down hydrogen peroxide (H2O2) into molecular oxygen and water. In all monofunctional catalases the pathway that H2O2 takes to the catalytic centre is via the `main channel'. However, the structure of this channel differs in large-subunit and small-subunit catalases. In large-subunit catalases the channel is 15 Å longer and consists of two distinct parts, including a hydrophobic lower region near the heme and a hydrophilic upper region where multiple H2O2 routes are possible. Conserved glutamic acid and threonine residues are located near the intersection of these two regions. Mutations of these two residues in the Scytalidium thermophilum catalase had no significant effect on catalase activity. However, the secondary phenol oxidase activity was markedly altered, with kcat and kcat/Km values that were significantly increased in the five variants E484A, E484I, T188D, T188I and T188F. These variants also showed a lower affinity for inhibitors of oxidase activity than the wild-type enzyme and a higher affinity for phenolic substrates. Oxidation of heme b to heme d did not occur in most of the studied variants. Structural changes in solvent-chain integrity and channel architecture were also observed. In summary, modification of the main-channel gate glutamic acid and threonine residues has a greater influence on the secondary activity of the catalase enzyme, and the oxidation of heme b to heme d is predominantly inhibited by their conversion to aliphatic and aromatic residues.

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.

The validation of structural models obtained by macromolecular X-ray crystallography against experimental diffraction data, whether before deposition into the PDB or after, is typically carried out exclusively against the merged data that are eventually archived along with the atomic coordinates. It is shown here that the availability of unmerged reflection data enables valuable additional analyses to be performed that yield improvements in the final models, and tools are presented to implement them, together with examples of the results to which they give access. The first example is the automatic identification and removal of image ranges affected by loss of crystal centering or by excessive decay of the diffraction pattern as a result of radiation damage. The second example is the `reflection-auditing' process, whereby individual merged data items showing especially poor agreement with model predictions during refinement are investigated thanks to the specific metadata (such as image number and detector position) that are available for the corresponding unmerged data, potentially revealing previously undiagnosed instrumental, experimental or processing problems. The third example is the calculation of so-called F(early) − F(late) maps from carefully selected subsets of unmerged amplitude data, which can not only highlight the location and extent of radiation damage but can also provide guidance towards suitable fine-grained parametrizations to model the localized effects of such damage.

The widespread adoption of cryoEM technologies for structural biology has pushed the discipline to new frontiers. A significant worldwide effort has refined the single-particle analysis (SPA) workflow into a reasonably standardized procedure. Significant investments of development time have been made, particularly in sample preparation, microscope data-collection efficiency, pipeline analyses and data archiving. The widespread adoption of specific commercial microscopes, software for controlling them and best practices developed at facilities worldwide has also begun to establish a degree of standardization to data structures coming from the SPA workflow. There is opportunity to capitalize on this moment in the maturation of the field, to capture metadata from SPA experiments and correlate the metadata with experimental outcomes, which is presented here in a set of programs called EMinsight. This tool aims to prototype the framework and types of analyses that could lead to new insights into optimal microscope configurations as well as to define methods for metadata capture to assist with the archiving of cryoEM SPA data. It is also envisaged that this tool will be useful to microscope operators and facilities looking to rapidly generate reports on SPA data-collection and screening sessions.

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.

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.

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

Lanthanide ions have ideal chemical properties for catalysis, such as hard Lewis acidity, fast ligand-exchange kinetics, high coordination-number preferences and low geometric requirements for coordination. As a result, many small-molecule lanthanide catalysts have been described in the literature. Yet, despite the ability of enzymes to catalyse highly stereoselective reactions under gentle conditions, very few lanthanoenzymes have been investigated. In this work, the mononuclear binding of europium(III) and gadolinium(III) to the active site of a mutant of the model enzyme phosphotriesterase are described using X-ray crystallography at 1.78 and 1.61 Å resolution, respectively. It is also shown that despite coordinating a single non-natural metal cation, the PTE-R18 mutant is still able to maintain esterase activity.

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.

Metalloproteins are ubiquitous in all living organisms and take part in a very wide range of biological processes. For this reason, their experimental characterization is crucial to obtain improved knowledge of their structure and biological functions. The three-dimensional structure represents highly relevant information since it provides insight into the interaction between the metal ion(s) and the protein fold. Such interactions determine the chemical reactivity of the bound metal. The available PDB structures can contain errors due to experimental factors such as poor resolution and radiation damage. A lack of use of distance restraints during the refinement and validation process also impacts the structure quality. Here, the aim was to obtain a thorough overview of the distribution of the distances between metal ions and their donor atoms through the statistical analysis of a data set based on more than 115 000 metal-binding sites in proteins. This analysis not only produced reference data that can be used by experimentalists to support the structure-determination process, for example as refinement restraints, but also resulted in an improved insight into how protein coordination occurs for different metals and the nature of their binding interactions. In particular, the features of carboxylate coordination were inspected, which is the only type of interaction that is commonly present for nearly all metals.

Radiation damage remains one of the major impediments to accurate structure solution in macromolecular crystallography. The artefacts of radiation damage can manifest as structural changes that result in incorrect biological interpretations being drawn from a model, they can reduce the resolution to which data can be collected and they can even prevent structure solution entirely. In this article, we discuss how to identify and mitigate against the effects of radiation damage at each stage in the macromolecular crystal structure-solution pipeline.

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.

The detection of specific biological macromolecules in cryogenic electron tomography data is frequently approached by applying cross-correlation-based 3D template matching. To reduce computational cost and noise, high binning is used to aggregate voxels before template matching. This remains a prevalent practice in both practical applications and methods development. Here, the relation between template size, shape and angular sampling is systematically evaluated to identify ribosomes in a ground-truth annotated data set. It is shown that at the commonly used binning, a detailed subtomogram average, a sphere and a heart emoji result in near-identical performance. These findings indicate that with current template-matching practices macromolecules can only be detected with high precision if their shape and size are sufficiently different from the background. Using theoretical considerations, the experimental results are rationalized and it is discussed why primarily low-frequency information remains at high binning and that template matching fails to be accurate because similarly shaped and sized macromolecules have similar low-frequency spectra. These challenges are discussed and potential enhancements for future template-matching methodologies are proposed.

Fragment-based drug design using X-ray crystallography is a powerful technique to enable the development of new lead compounds, or probe molecules, against biological targets. This study addresses the need to determine fragment binding orientations for low-occupancy fragments with incomplete electron density, an essential step before further development of the molecule. Halogen atoms play multiple roles in drug discovery due to their unique combination of electronegativity, steric effects and hydrophobic properties. Fragments incorporating halogen atoms serve as promising starting points in hit-to-lead development as they often establish halogen bonds with target proteins, potentially enhancing binding affinity and selectivity, as well as counteracting drug resistance. Here, the aim was to unambiguously identify the binding orientations of fragment hits for SARS-CoV-2 nonstructural protein 1 (nsp1) which contain a combination of sulfur and/or chlorine, bromine and iodine substituents. The binding orientations of carefully selected nsp1 analogue hits were focused on by employing their anomalous scattering combined with Pan-Dataset Density Analysis (PanDDA). Anomalous difference Fourier maps derived from the diffraction data collected at both standard and long-wavelength X-rays were compared. The discrepancies observed in the maps of iodine-containing fragments collected at different energies were attributed to site-specific radiation-damage stemming from the strong X-ray absorption of I atoms, which is likely to cause cleavage of the C—I bond. A reliable and effective data-collection strategy to unambiguously determine the binding orientations of low-occupancy fragments containing sulfur and/or halogen atoms while mitigating radiation damage is presented.

For cryo-electron tomography (cryo-ET) of beam-sensitive biological specimens, a planar sample geometry is typically used. As the sample is tilted, the effective thickness of the sample along the direction of the electron beam increases and the signal-to-noise ratio concomitantly decreases, limiting the transfer of information at high tilt angles. In addition, the tilt range where data can be collected is limited by a combination of various sample-environment constraints, including the limited space in the objective lens pole piece and the possible use of fixed conductive braids to cool the specimen. Consequently, most tilt series are limited to a maximum of ±70°, leading to the presence of a missing wedge in Fourier space. The acquisition of cryo-ET data without a missing wedge, for example using a cylindrical sample geometry, is hence attractive for volumetric analysis of low-symmetry structures such as organelles or vesicles, lysis events, pore formation or filaments for which the missing information cannot be compensated by averaging techniques. Irrespective of the geometry, electron-beam damage to the specimen is an issue and the first images acquired will transfer more high-resolution information than those acquired last. There is also an inherent trade-off between higher sampling in Fourier space and avoiding beam damage to the sample. Finally, the necessity of using a sufficient electron fluence to align the tilt images means that this fluence needs to be fractionated across a small number of images; therefore, the order of data acquisition is also a factor to consider. Here, an n-helix tilt scheme is described and simulated which uses overlapping and interleaved tilt series to maximize the use of a pillar geometry, allowing the entire pillar volume to be reconstructed as a single unit. Three related tilt schemes are also evaluated that extend the continuous and classic dose-symmetric tilt schemes for cryo-ET to pillar samples to enable the collection of isotropic information across all spatial frequencies. A fourfold dose-symmetric scheme is proposed which provides a practical compromise between uniform information transfer and complexity of data acquisition.

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.

When solving a structure of a protein from single-wavelength anomalous diffraction X-ray data, the initial phases obtained by phasing from an anomalously scattering substructure usually need to be improved by an iterated electron-density modification. In this manuscript, the use of convolutional neural networks (CNNs) for segmentation of the initial experimental phasing electron-density maps is proposed. The results reported demonstrate that a CNN with U-net architecture, trained on several thousands of electron-density maps generated mainly using X-ray data from the Protein Data Bank in a supervised learning, can improve current density-modification methods.

The formation of a vitrified thin film embedded with randomly oriented macromolecules is an essential prerequisite for cryogenic sample electron microscopy. Most commonly, this is achieved using the plunge-freeze method first described nearly 40 years ago. Although this is a robust method, the behaviour of different macromolecules shows great variation upon freezing and often needs to be optimized to obtain an isotropic, high-resolution reconstruction. For a macromolecule in such a film, the probability of encountering the air–water interface in the time between blotting and freezing and adopting preferred orientations is very high. 3D reconstruction using preferentially oriented particles often leads to anisotropic and uninterpretable maps. Currently, there are no general solutions to this prevalent issue, but several approaches largely focusing on sample preparation with the use of additives and novel grid modifications have been attempted. In this study, the effect of physical and chemical factors on the orientations of macromolecules was investigated through an analysis of selected well studied macromolecules, and important parameters that determine the behaviour of proteins on cryo-EM grids were revealed. These insights highlight the nature of the interactions that cause preferred orientations and can be utilized to systematically address orientation bias for any given macromolecule and to provide a framework to design small-molecule additives to enhance sample stability and behaviour.

The determination of the atomic resolution structure of biomacromolecules is essential for understanding details of their function. Traditionally, such a structure determination has been performed with crystallographic or nuclear resonance methods, but during the last decade, cryogenic transmission electron microscopy (cryo-TEM) has become an equally important tool. As the blotting and flash-freezing of the samples can induce conformational changes, external validation tools are required to ensure that the vitrified samples are representative of the solution. Although many validation tools have already been developed, most of them rely on fully resolved atomic models, which prevents early screening of the cryo-TEM maps. Here, a novel and automated method for performing such a validation utilizing small-angle X-ray scattering measurements, publicly available through the new software package AUSAXS, is introduced and implemented. The method has been tested on both simulated and experimental data, where it was shown to work remarkably well as a validation tool. The method provides a dummy atomic model derived from the EM map which best represents the solution structure.

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.

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

Protein crystallography is an established method to study the atomic structures of macromolecules and their complexes. A prerequisite for successful structure determination is diffraction-quality crystals, which may require extensive optimization of both the protein and the conditions, and hence projects can stretch over an extended period, with multiple users being involved. The workflow from crystallization and crystal treatment to deposition and publication is well defined, and therefore an electronic laboratory information management system (LIMS) is well suited to management of the data. Completion of the project requires key information on all the steps being available and this information should also be made available according to the FAIR principles. As crystallized samples are typically shipped between facilities, a key feature to be captured in the LIMS is the exchange of metadata between the crystallization facility of the home laboratory and, for example, synchrotron facilities. On completion, structures are deposited in the Protein Data Bank (PDB) and the LIMS can include the PDB code in its database, completing the chain of custody from crystallization to structure deposition and publication. A LIMS designed for macromolecular crystallography, IceBear, is available as a standalone installation and as a hosted service, and the implementation of key features for the capture of metadata in IceBear is discussed as an example.

Histidine can be protonated on either or both of the two N atoms of the imidazole moiety. Each of the three possible forms occurs as a result of the stereochemical environment of the histidine side chain. In an atomic model, comparing the possible protonation states in situ, looking at possible hydrogen bonding and metal coordination, it is possible to predict which is most likely to be correct. A more direct method is described that uses quantum-mechanical methods to calculate, also in situ, the minimum geometry and energy for comparison, and therefore to more accurately identify the most likely proton­ation state.

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.

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.

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.

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.

During the automatic processing of crystallographic diffraction experiments, beamstop shadows are often unaccounted for or only partially masked. As a result of this, outlier reflection intensities are integrated, which is a known issue. Traditional statistical diagnostics have only limited effectiveness in identifying these outliers, here termed Not-Excluded-unMasked-Outliers (NEMOs). The diagnostic tool AUSPEX allows visual inspection of NEMOs, where they form a typical pattern: clusters at the low-resolution end of the AUSPEX plots of intensities or amplitudes versus resolution. To automate NEMO detection, a new algorithm was developed by combining data statistics with a density-based clustering method. This approach demonstrates a promising performance in detecting NEMOs in merged data sets without disrupting existing data-reduction pipelines. Re-refinement results indicate that excluding the identified NEMOs can effectively enhance the quality of subsequent structure-determination steps. This method offers a prospective automated means to assess the efficacy of a beamstop mask, as well as highlighting the potential of modern pattern-recognition techniques for automating outlier exclusion during data processing, facilitating future adaptation to evolving experimental strategies.

AlphaFold2 has revolutionized structural biology by offering unparalleled accuracy in predicting protein structures. Traditional methods for determining protein structures, such as X-ray crystallography and cryo-electron microscopy, are often time-consuming and resource-intensive. AlphaFold2 provides models that are valuable for molecular replacement, aiding in model building and docking into electron density or potential maps. However, despite its capabilities, models from AlphaFold2 do not consistently match the accuracy of experimentally determined structures, need to be validated experimentally and currently miss some crucial information, such as post-translational modifications, ligands and bound ions. In this paper, the advantages are explored of collecting X-ray anomalous data to identify chemical elements, such as metal ions, which are key to understanding certain structures and functions of proteins. This is achieved through methods such as calculating anomalous difference Fourier maps or refining the imaginary component of the anomalous scattering factor f''. Anomalous data can serve as a valuable complement to the information provided by AlphaFold2 models and this is particularly significant in elucidating the roles of metal ions.

A group of three deep-learning tools, referred to collectively as CHiMP (Crystal Hits in My Plate), were created for analysis of micrographs of protein crystallization experiments at the Diamond Light Source (DLS) synchrotron, UK. The first tool, a classification network, assigns images into categories relating to experimental outcomes. The other two tools are networks that perform both object detection and instance segmentation, resulting in masks of individual crystals in the first case and masks of crystallization droplets in addition to crystals in the second case, allowing the positions and sizes of these entities to be recorded. The creation of these tools used transfer learning, where weights from a pre-trained deep-learning network were used as a starting point and repurposed by further training on a relatively small set of data. Two of the tools are now integrated at the VMXi macromolecular crystallography beamline at DLS, where they have the potential to absolve the need for any user input, both for monitoring crystallization experiments and for triggering in situ data collections. The third is being integrated into the XChem fragment-based drug-discovery screening platform, also at DLS, to allow the automatic targeting of acoustic compound dispensing into crystallization droplets.

The availability of highly accurate protein structure predictions from AlphaFold2 (AF2) and similar tools has hugely expanded the applicability of molecular replacement (MR) for crystal structure solution. Many structures can be solved routinely using raw models, structures processed to remove unreliable parts or models split into distinct structural units. There is therefore an open question around how many and which cases still require experimental phasing methods such as single-wavelength anomalous diffraction (SAD). Here, this question is addressed using a large set of PDB depositions that were solved by SAD. A large majority (87%) could be solved using unedited or minimally edited AF2 predictions. A further 18 (4%) yield straightforwardly to MR after splitting of the AF2 prediction using Slice'N'Dice, although different splitting methods succeeded on slightly different sets of cases. It is also found that further unique targets can be solved by alternative modelling approaches such as ESMFold (four cases), alternative MR approaches such as ARCIMBOLDO and AMPLE (two cases each), and multimeric model building with AlphaFold-Multimer or UniFold (three cases). Ultimately, only 12 cases, or 3% of the SAD-phased set, did not yield to any form of MR tested here, offering valuable hints as to the number and the characteristics of cases where experimental phasing remains essential for macromolecular structure solution.