Pollution from plastics is a global problem that threatens the biosphere for a host of reasons, including the time scale that it takes for most plastics to degrade. Biodegradation is an ideal solution for remediating bioplastic waste as it does not require the high temperatures necessary for thermal degradation and does not introduce additional pollutants into the environment. Numerous organisms can scavenge for bioplastics, such as polylactic acid (PLA) or poly-(R)-hydroxybutyrate (PHB), which they can use as an energy source. Recently, a promiscuous PHBase from the thermophilic soil bacterium Lihuaxuella thermophila (LtPHBase) was identified. LtPHBase can accommodate many substrates, including PHB granules and films and PHB block copolymers, as well as the unrelated polymers polylactic acid (PLA) and polycaprolactone (PCL). LtPHBase uses the expected Ser–His–Asp catalytic triad for hydrolysis at an optimal enzyme activity near 70°C. Here, the 1.75 Å resolution crystal structure of apo LtPHBase is presented and its chemical stability is profiled. Knowledge of its substrate preferences was extended to different-sized PHB granules. It is shown that LtPHBase is highly resistant to unfolding, with barriers typical for thermophilic enzymes, and shows a preference for low-molecular-mass PHB granules. These insights have implications for the long-term potential of LtPHBase as an industrial PHB hydrolase and shed light on the evolutionary role that this enzyme plays in bacterial metabolism.

For protein crystals in which more than two thirds of the volume is occupied by solvent, the featureless nature of the solvent region often generates a constraint that is powerful enough to allow direct phasing of X-ray diffraction data. Practical implementation relies on the use of iterative projection algorithms with good global convergence properties to solve the difficult nonconvex phase-retrieval problem. In this paper, some aspects of phase retrieval using iterative projection algorithms are systematically explored, where the diffraction data and density-value distributions in the protein and solvent regions provide the sole constraints. The analysis is based on the addition of random error to the phases of previously determined protein crystal structures, followed by evaluation of the ability to recover the correct phase set as the distance from the solution increases. The properties of the difference-map (DM), relaxed–reflect–reflect (RRR) and relaxed averaged alternating reflectors (RAAR) algorithms are compared. All of these algorithms prove to be effective for crystallographic phase retrieval, and the useful ranges of the adjustable parameter which controls their behavior are established. When these algorithms converge to the solution, the algorithm trajectory becomes stationary; however, the density function continues to fluctuate significantly around its mean position. It is shown that averaging over the algorithm trajectory in the stationary region, following convergence, improves the density estimate, with this procedure outperforming previous approaches for phase or density refinement.

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.

Serial electron diffraction (SerialED), which applies a snapshot data acquisition strategy for each crystal, was introduced to tackle the problem of radiation damage in the structure determination of beam-sensitive materials by three-dimensional electron diffraction (3DED). The snapshot data acquisition in SerialED can be realized using both transmission and scanning transmission electron microscopes (TEM/STEM). However, the current SerialED workflow based on STEM setups requires special external devices and software, which limits broader adoption. Here, we present a simplified experimental implementation of STEM-based SerialED on Thermo Fisher Scientific STEMs using common proprietary software interfaced through Python scripts to automate data collection. Specifically, we utilize TEM Imaging and Analysis (TIA) scripting and TEM scripting to access the STEM functionalities of the microscope, and DigitalMicrograph scripting to control the camera for snapshot data acquisition. Data analysis adapts the existing workflow using the software CrystFEL, which was developed for serial X-ray crystallography. Our workflow for STEM SerialED can be used on any Gatan or Thermo Fisher Scientific camera. We apply this workflow to collect high-resolution STEM SerialED data from two aluminosilicate zeolites, zeolite Y and ZSM-25. We demonstrate, for the first time, ab initio structure determination through direct methods using STEM SerialED data. Zeolite Y is relatively stable under the electron beam, and STEM SerialED data extend to 0.60 Å. We show that the structural model obtained using STEM SerialED data merged from 358 crystals is nearly identical to that using continuous rotation electron diffraction data from one crystal. This demonstrates that accurate structures can be obtained from STEM SerialED. Zeolite ZSM-25 is very beam-sensitive and has a complex structure. We show that STEM SerialED greatly improves the data resolution of ZSM-25, compared with serial rotation electron diffraction (SerialRED), from 1.50 to 0.90 Å. This allows, for the first time, the use of standard phasing methods, such as direct methods, for the ab initio structure determination of ZSM-25.

Single-particle imaging using X-ray free-electron lasers (XFELs) is a promising technique for observing nanoscale biological samples under near-physiological conditions. However, as the sample's orientation in each diffraction pattern is unknown, advanced algorithms are required to reconstruct the 3D diffraction intensity volume and subsequently the sample's density model. While most approaches perform 3D reconstruction via determining the orientation of each diffraction pattern, a correlation-based approach utilizes the averaged spatial correlations of diffraction intensities over all patterns, making it well suited for processing experimental data with a poor signal-to-noise ratio of individual patterns. Here, a method is proposed to determine the 3D structure of a sample by analyzing the double, triple and quadruple spatial correlations in diffraction patterns. This ab initio method can reconstruct the basic shape of an irregular unsymmetric 3D sample without requiring any prior knowledge of the sample. The impact of background and noise on correlations is investigated and corrected to ensure the success of reconstruction under simulated experimental conditions. Additionally, the feasibility of using the correlation-based approach to process incomplete partial diffraction patterns is demonstrated. The proposed method is a variable addition to existing algorithms for 3D reconstruction and will further promote the development and adoption of XFEL single-particle imaging techniques.

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.

The structures of the simplest symmetric primary ethers [(CnH2n+1)2O, n = 1–3] determined under high pressure revealed their conformational preferences and intermolecular interactions. In three new polymorphs of di­ethyl ether (C2H5)2O, high pressure promotes intermolecular CH⋯O contacts and enforces a conversion from the trans–trans conformer present in the α, β and γ phases to the trans–gauche conformer, which is higher in energy by 6.4 kJ mol−1, in the δ phase. Two new polymorphs of di­methyl ether (CH3)2O display analogous transformations of the CH⋯O bonds. The crystal structure of di-n-propyl ether (C3H7)2O, determined for the first time, is remarkably stable over the whole pressure range investigated from 1.70 up to 5.30 GPa.

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.

Our study compares short-range order parameters refined from the diffuse scattering in single-crystal X-ray and single-crystal electron diffraction data. Nb0.84CoSb was chosen as a reference material. The correlations between neighbouring vacancies and the displacements of Sb and Co atoms were refined from the diffuse scattering using a Monte Carlo refinement in DISCUS. The difference between the Sb and Co displacements refined from the diffuse scattering and the Sb and Co displacements refined from the Bragg reflections in single-crystal X-ray diffraction data is 0.012 (7) Å for the refinement on diffuse scattering in single-crystal X-ray diffraction data and 0.03 (2) Å for the refinement on the diffuse scattering in single-crystal electron diffraction data. As electron diffraction requires much smaller crystals than X-ray diffraction, this opens up the possibility of refining short-range order parameters in many technologically relevant materials for which no crystals large enough for single-crystal X-ray diffraction are available.

Molecular structures can be determined in vitro and in situ with cryo-electron microscopy (cryo-EM). Specimen preparation is a major obstacle in cryo-EM. Typical sample preparation is orders of magnitude slower than biological processes. Time-resolved cryo-EM (TR-cryo-EM) can capture short-lived states. Here, Cryo-EM sample preparation with light-activated molecules (C-SPAM) is presented, an open-source, photochemistry-coupled device for TR-cryo-EM that enables millisecond resolution and tunable timescales across broad biological applications.

Highly accurate protein structure prediction can generate accurate models of protein and protein–protein complexes in X-ray crystallography. However, the question of how to make more effective use of predicted models for completing structure analysis, and which strategies should be employed for the more challenging cases such as multi-helical structures, multimeric structures and extremely large structures, both in the model preparation and in the completion steps, remains open for discussion. In this paper, a new strategy is proposed based on the framework of direct methods and dual-space iteration, which can greatly simplify the pre-processing steps of predicted models both in normal and in challenging cases. Following this strategy, full-length models or the conservative structural domains could be used directly as the starting model, and the phase error and the model bias between the starting model and the real structure would be modified in the direct-methods-based dual-space iteration. Many challenging cases (from CASP14) have been tested for the general applicability of this constructive strategy, and almost complete models have been generated with reasonable statistics. The hybrid strategy therefore provides a meaningful scheme for X-ray structure determination using a predicted model as the starting point.

The application of grazing-incidence total X-ray scattering (GITXS) for pair distribution function (PDF) analysis using >50 keV X-rays from synchrotron light sources has created new opportunities for structural characterization of supported thin films with high resolution. Compared with grazing-incidence wide-angle X-ray scattering, which is only useful for highly ordered materials, GITXS/PDFs expand such analysis to largely disordered or nanostructured materials by examining the atomic pair correlations dependent on the direction relative to the surface of the supporting substrate. A characterization of nanocrystalline In2O3-derived thin films is presented here with in-plane-isotropic and out-of-plane-anisotropic orientational ordering of the atomic structure, each synthesized using different techniques. The atomic orientations of such films are known to vary based on the synthetic conditions. Here, an azimuthal orientational analysis of these films using GITXS with a single incident angle is shown to resolve the markedly different orientations of the atomic structures with respect to the planar support and the different degrees of long-range order, and hence, the terminal surface chemistries. It is anticipated that orientational analysis of GITXS/PDF data will offer opportunities to extend structural analyses of thin films by providing a means to qualitatively determine the major atomic orientation within nanocrystalline and, eventually, non-crystalline films.

Interoperability of crystallographic data with other disciplines is essential for the smooth and rapid progress of structure-based science in the computer age. Within crystallography and closely related subject areas, there is already a high level of conformance to the generally accepted FAIR principles (that data be findable, accessible, interoperable and reusable) through the adoption of common information exchange protocols by databases, publishers, instrument vendors, experimental facilities and software authors. Driven by the success within these domains, the IUCr has worked closely with CODATA (the Committee on Data of the International Science Council) to help develop the latter's commitment to cross-domain integration of discipline-specific data. The IUCr has, in particular, emphasized the need for standards relating to data quality and completeness as an adjunct to the FAIR data landscape. This can ensure definitive reusable data, which in turn can aid interoperability across domains. A microsymposium at the IUCr 2023 Congress provided an up-to-date survey of data interoperability within and outside of crystallography, expounded using a broad range of examples.

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

Vancomycin is a glycopeptide antibiotic that for decades has been a mainstay of treatment for persistent bacterial infections. However, the spread of antibiotic resistance threatens its continued utility. In particular, vancomycin-resistant enterococci (VRE) have become a pressing clinical challenge. Vancomycin acts by binding and sequestering the intermediate Lipid II in cell-wall biosynthesis, specifically recognizing a d-alanine-d-alanine dipeptide motif within the Lipid II molecule. VRE achieve resistance by remodeling this motif to either d-alanine-d-lactate or d-alanine-d-serine; the former substitution essentially abolishes recognition by vancomycin of Lipid II, whereas the latter reduces the affinity of the antibiotic by roughly one order of magnitude. The complex of vancomycin bound to d-alanine-d-serine has been crystallized, and its 1.20 Å X-ray crystal structure is presented here. This structure reveals that the d-alanine-d-serine ligand is bound in essentially the same position and same pose as the native d-alanine-d-alanine ligand. The serine-containing ligand appears to be slightly too large to be comfortably accommodated in this way, suggesting one possible contribution to the reduced binding affinity. In addition, two flexible hydroxyl groups – one from the serine side chain of the ligand, and the other from a glucose sugar on the antibiotic – are locked into single conformations in the complex, which is likely to contribute an unfavorable entropic component to the recognition of the serine-containing ligand.

In the search for new active pharmaceutical ingredients, the precise control of the chemistry of cocrystals becomes essential. One crucial step within this chemistry is proton migration between cocrystal coformers to form a salt, usually anticipated by the empirical ΔpKa rule. Due to the effective role it plays in modifying intermolecular distances and interactions, pressure adds a new dimension to the ΔpKa rule. Still, this variable has been scarcely applied to induce proton-transfer reactions within these systems. In our study, high-pressure X-ray diffraction and Raman spectroscopy experiments, supported by DFT calculations, reveal modifications to the protonation states of the 4,4'-bi­pyridine (BIPY) and malonic acid (MA) cocrystal (BIPYMA) that allow the conversion of the cocrystal phase into ionic salt polymorphs. On compression, neutral BIPYMA and monoprotonated (BIPYH+MA−) species coexist up to 3.1 GPa, where a phase transition to a structure of P21/c symmetry occurs, induced by a double proton-transfer reaction forming BIPYH22+MA2−. The low-pressure C2/c phase is recovered at 2.4 GPa on decompression, leading to a 0.7 GPa hysteresis pressure range. This is one of a few studies on proton transfer in multicomponent crystals that shows how susceptible the interconversion between differently charged species is to even slight pressure changes, and how the proton transfer can be a triggering factor leading to changes in the crystal symmetry. These new data, coupled with information from previous reports on proton-transfer reactions between coformers, extend the applicability of the ΔpKa rule incorporating the pressure required to induce salt formation.

Serial crystallography (SX) has become an established technique for protein structure determination, especially when dealing with small or radiation-sensitive crystals and investigating fast or irreversible protein dynamics. The advent of newly developed multi-megapixel X-ray area detectors, capable of capturing over 1000 images per second, has brought about substantial benefits. However, this advancement also entails a notable increase in the volume of collected data. Today, up to 2 PB of data per experiment could be easily obtained under efficient operating conditions. The combined costs associated with storing data from multiple experiments provide a compelling incentive to develop strategies that effectively reduce the amount of data stored on disk while maintaining the quality of scientific outcomes. Lossless data-compression methods are designed to preserve the information content of the data but often struggle to achieve a high compression ratio when applied to experimental data that contain noise. Conversely, lossy compression methods offer the potential to greatly reduce the data volume. Nonetheless, it is vital to thoroughly assess the impact of data quality and scientific outcomes when employing lossy compression, as it inherently involves discarding information. The evaluation of lossy compression effects on data requires proper data quality metrics. In our research, we assess various approaches for both lossless and lossy compression techniques applied to SX data, and equally importantly, we describe metrics suitable for evaluating SX data quality.

This paper uses deep learning to present a proof-of-concept for data-driven chemistry in single-molecule magnets (SMMs). Previous discussions within SMM research have proposed links between molecular structures (crystal structures) and single-molecule magnetic properties; however, these have only interpreted the results. Therefore, this study introduces a data-driven approach to predict the properties of SMM structures using deep learning. The deep-learning model learns the structural features of the SMM molecules by extracting the single-molecule magnetic properties from the 3D coordinates presented in this paper. The model accurately determined whether a molecule was a single-molecule magnet, with an accuracy rate of approximately 70% in predicting the SMM properties. The deep-learning model found SMMs from 20 000 metal complexes extracted from the Cambridge Structural Database. Using deep-learning models for predicting SMM properties and guiding the design of novel molecules is promising.

Evidence that the electronic structure of atoms persists in molecules to a much greater extent than has been usually admitted is presented. This is achieved by resorting to N-electron real-space descriptors instead of one- or at most two-particle projections like the electron or exchange-correlation densities. Here, the 3N-dimensional maxima of the square of the wavefunction, the so-called Born maxima, are used. Since this technique is relatively unknown to the crystallographic community, a case-based approach is taken, revisiting first the Born maxima of atoms in their ground state and then some of their excited states. It is shown how they survive in molecules and that, beyond any doubt, the distribution of electrons around an atom in a molecule can be recognized as that of its isolated, in many cases excited, counterpart, relating this fact with the concept of energetic promotion. Several other cases that exemplify the applicability of the technique to solve chemical bonding conflicts and to introduce predictability in real-space analyses are also examined.

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

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

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

Leishmaniasis is a neglected parasitic tropical disease with numerous clinical manifestations. One of the causative agents of cutaneous leishmaniasis (CL) is Leishmania tropica (L. tropica) known for causing ulcerative lesions on the skin. The adverse effects of the recommended available drugs, such as amphotericin B and pentavalent antimonial, and the emergence of drug resistance in parasites, mean the search for new safe and effective anti-leishmanial agents is crucial. Miltefosine (MIL) was the first recommended oral medication, but its use is now limited because of the rapid emergence of resistance. Pharmaceutical cocrystallization is an effective method to improve the physicochemical and biological properties of active pharmaceutical ingredients (APIs). Herein, we describe the cocrystallization of coumarin-3-carb­oxy­lic acid (CU, 1a; 2-oxobenzo­pyrane-3-carb­oxy­lic acid, C10H6O4) with five coformers [2-amino-3-bromo­pyridine (1b), 2-amino-5-(tri­fluoro­methyl)-pyridine (1c), 2-amino-6-methyl­pyridine (1d), p-amino­benzoic acid (1e) and amitrole (1f)] in a 1:1 stoichiometric ratio via the neat grinding method. The cocrystals 2–6 obtained were characterized via single-crystal X-ray diffraction, powder X-ray diffraction, differential scanning calorimetry and thermogravimetric analysis, as well as Fourier transform infrared spectroscopy. Non-covalent interactions, such as van der Waals, hydrogen bonding, C—H⋯π and π⋯π interactions contribute significantly towards the packing of a crystal structure and alter the physicochemical and biological activity of CU. In this research, newly synthesized cocrystals were evaluated for their anti-leishmanial activity against the MIL-resistant L. tropica and cytotoxicity against the 3T3 (normal fibroblast) cell line. Among the non-cytotoxic cocrystals synthesized (2–6), CU:1b (2, IC50 = 61.83 ± 0.59 µM), CU:1c (3, 125.7 ± 1.15 µM) and CU:1d (4, 48.71 ± 0.75 µM) appeared to be potent anti-leishmanial agents and showed several-fold more anti-leishmanial potential than the tested standard drug (MIL, IC50 = 169.55 ± 0.078 µM). The results indicate that cocrystals 2–4 are promising anti-leishmanial agents which require further exploration.

Form factors based on aspherical models of atomic electron density have brought great improvement in the accuracies of hydrogen atom parameters derived from X-ray crystal structure refinement. Today, two main groups of such models are available, the banks of transferable atomic densities parametrized using the Hansen–Coppens multipole model which allows for rapid evaluation of atomic form factors and Hirshfeld atom refinement (HAR)-related methods which are usually more accurate but also slower. In this work, a model that combines the ideas utilized in the two approaches is tested. It uses atomic electron densities based on Hirshfeld partitions of electron densities, which are precalculated and stored in a databank. This model was also applied during the refinement of the structures of five small molecules. A comparison of the resulting hydrogen atom parameters with those derived from neutron diffraction data indicates that they are more accurate than those obtained with the Hansen–Coppens based databank, and only slightly less accurate than those obtained with a version of HAR that neglects the crystal environment. The advantage of using HAR becomes more noticeable when the effects of the environment are included. To speed up calculations, atomic densities were represented by multipole expansion with spherical harmonics up to l = 7, which used numerical radial functions (a different approach to that applied in the Hansen–Coppens model). Calculations of atomic form factors for the small protein crambin (at 0.73 Å resolution) took only 68 s using 12 CPU cores.

Dynamical refinement is a well established method for refining crystal structures against 3D electron diffraction (ED) data and its benefits have been discussed in the literature [Palatinus, Petříček & Corrêa, (2015). Acta Cryst. A71, 235–244; Palatinus, Corrêa et al. (2015). Acta Cryst. B71, 740–751]. However, until now, dynamical refinements have only been conducted using the independent atom model (IAM). Recent research has shown that a more accurate description can be achieved by applying the transferable aspherical atom model (TAAM), but this has been limited only to kinematical refinements [Gruza et al. (2020). Acta Cryst. A76, 92–109; Jha et al. (2021). J. Appl. Cryst. 54, 1234–1243]. In this study, we combine dynamical refinement with TAAM for the crystal structure of 1-methyl­uracil, using data from precession ED. Our results show that this approach improves the residual Fourier electrostatic potential and refinement figures of merit. Furthermore, it leads to systematic changes in the atomic displacement parameters of all atoms and the positions of hydrogen atoms. We found that the refinement results are sensitive to the parameters used in the TAAM modelling process. Though our results show that TAAM offers superior performance compared with IAM in all cases, they also show that TAAM parameters obtained by periodic DFT calculations on the refined structure are superior to the TAAM parameters from the UBDB/MATTS database. It appears that multipolar parameters transferred from the database may not be sufficiently accurate to provide a satisfactory description of all details of the electrostatic potential probed by the 3D ED experiment.

Serial crystallography requires large numbers of microcrystals and robust strategies to rapidly apply substrates to initiate reactions in time-resolved studies. Here, we report the use of droplet miniaturization for the controlled production of uniform crystals, providing an avenue for controlled substrate addition and synchronous reaction initiation. The approach was evaluated using two enzymatic systems, yielding 3 µm crystals of lysozyme and 2 µm crystals of Pdx1, an Arabidopsis enzyme involved in vitamin B6 biosynthesis. A seeding strategy was used to overcome the improbability of Pdx1 nucleation occurring with diminishing droplet volumes. Convection within droplets was exploited for rapid crystal mixing with ligands. Mixing times of <2 ms were achieved. Droplet microfluidics for crystal size engineering and rapid micromixing can be utilized to advance time-resolved serial crystallography.

An X-ray absorption spectroscopy (XAS) electrochemical cell was used to collect high-quality XAS measurements of N-truncated Cu:amyloid-β (Cu:Aβ) samples under near-physiological conditions. N-truncated Cu:Aβ peptide complexes contribute to oxidative stress and neurotoxicity in Alzheimer's patients' brains. However, the redox properties of copper in different Aβ peptide sequences are inconsistent. Therefore, the geometry of binding sites for the copper binding in Aβ4–8/12/16 was determined using novel advanced extended X-ray absorption fine structure (EXAFS) analysis. This enables these peptides to perform redox cycles in a manner that might produce toxicity in human brains. Fluorescence XAS measurements were corrected for systematic errors including defective-pixel data, monochromator glitches and dispersion of pixel spectra. Experimental uncertainties at each data point were measured explicitly from the point-wise variance of corrected pixel measurements. The copper-binding environments of Aβ4–8/12/16 were precisely determined by fitting XAS measurements with propagated experimental uncertainties, advanced analysis and hypothesis testing, providing a mechanism to pursue many similarly complex questions in bioscience. The low-temperature XAS measurements here determine that CuII is bound to the first amino acids in the high-affinity amino-terminal copper and nickel (ATCUN) binding motif with an oxygen in a tetragonal pyramid geometry in the Aβ4–8/12/16 peptides. Room-temperature XAS electrochemical-cell measurements observe metal reduction in the Aβ4–16 peptide. Robust investigations of XAS provide structural details of CuII binding with a very different bis-His motif and a water oxygen in a quasi-tetrahedral geometry. Oxidized XAS measurements of Aβ4–12/16 imply that both CuII and CuIII are accommodated in an ATCUN-like binding site. Hypotheses for these CuI, CuII and CuIII geometries were proven and disproven using the novel data and statistical analysis including F tests. Structural parameters were determined with an accuracy some tenfold better than literature claims of past work. A new protocol was also developed using EXAFS data analysis for monitoring radiation damage. This gives a template for advanced analysis of complex biosystems.

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.

Human peptidylarginine deiminase isoform VI (PAD6), which is predominantly limited to cytoplasmic lattices in the mammalian oocytes in ovarian tissue, is essential for female fertility. It belongs to the peptidylarginine deiminase (PAD) enzyme family that catalyzes the conversion of arginine residues to citrulline in proteins. In contrast to other members of the family, recombinant PAD6 was previously found to be catalytically inactive. We sought to provide structural insight into the human homologue to shed light on this observation. We report here the first crystal structure of PAD6, determined at 1.7 Å resolution. PAD6 follows the same domain organization as other structurally known PAD isoenzymes. Further structural analysis and size-exclusion chromatography show that PAD6 behaves as a homodimer similar to PAD4. Differential scanning fluorimetry suggests that PAD6 does not coordinate Ca2+ which agrees with acidic residues found to coordinate Ca2+ in other PAD homologs not being conserved in PAD6. The crystal structure of PAD6 shows similarities with the inactive state of apo PAD2, in which the active site conformation is unsuitable for catalytic citrullination. The putative active site of PAD6 adopts a non-productive conformation that would not allow protein–substrate binding due to steric hindrance with rigid secondary structure elements. This observation is further supported by the lack of activity on the histone H3 and cytokeratin 5 substrates. These findings suggest a different mechanism for enzymatic activation compared with other PADs; alternatively, PAD6 may exert a non-enzymatic function in the cytoplasmic lattice of oocytes and early embryos.

Metal-based complexes with their unique chemical properties, including multiple oxidation states, radio-nuclear capabilities and various coordination geometries yield value as potential pharmaceuticals. Understanding the interactions between metals and biological systems will prove key for site-specific coordination of new metal-based lead compounds. This study merges the concepts of target coordination with fragment-based drug methodologies, supported by varying the anomalous scattering of rhenium along with infrared spectroscopy, and has identified rhenium metal sites bound covalently with two amino acid types within the model protein. A time-based series of lysozyme-rhenium-imidazole (HEWL-Re-Imi) crystals was analysed systematically over a span of 38 weeks. The main rhenium covalent coordination is observed at His15, Asp101 and Asp119. Weak (i.e. noncovalent) interactions are observed at other aspartic, asparagine, proline, tyrosine and tryptophan side chains. Detailed bond distance comparisons, including precision estimates, are reported, utilizing the diffraction precision index supplemented with small-molecule data from the Cambridge Structural Database. Key findings include changes in the protein structure induced at the rhenium metal binding site, not observed in similar metal-free structures. The binding sites are typically found along the solvent-channel-accessible protein surface. The three primary covalent metal binding sites are consistent throughout the time series, whereas binding to neighbouring amino acid residues changes through the time series. Co-crystallization was used, consistently yielding crystals four days after setup. After crystal formation, soaking of the compound into the crystal over 38 weeks is continued and explains these structural adjustments. It is the covalent bond stability at the three sites, their proximity to the solvent channel and the movement of residues to accommodate the metal that are important, and may prove useful for future radiopharmaceutical development including target modification.

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.

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

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

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.

A new polymorph of 1,3-diacetylpyrene has been obtained from its melt and thoroughly characterized using single-crystal X-ray diffraction, steady-state UV–Vis spectroscopy and periodic density functional theory calculations. Experimental studies covered the temperature range from 90 to 390 K and the pressure range from atmospheric to 4.08 GPa. Optimal sample placement in a diamond anvil cell according to our previously presented methodology ensured over 80% data coverage up to 0.8 Å for a monoclinic sample. Unrestrained Hirshfeld atom refinement of the high-pressure crystal structures was successful and anharmonic behavior of carbonyl oxygen atoms was observed. Unlike the previously characterized polymorph, the structure of 2°AP-β is based on infinite π-stacks of antiparallel 2°AP molecules. 2°AP-β displays piezochromism and piezofluorochromism which are directly related to the variation in interplanar distances within the π-stacking. The importance of weak intermolecular interactions is reflected in the substantial negative thermal expansion coefficient of −55.8 (57) MK−1 in the direction of C—H⋯O interactions.

Platinum(II) complexes of square-planar geometry are interesting from a crystal engineering viewpoint because they exhibit strong luminescence based on the self-assembly of molecular units. The luminescence color changes in response to gentle stimuli, such as vapor exposure or weak mechanical forces. Both the molecular and the crystal designs for soft crystals are critical to effectively generate the chromic luminescence phenomenon of Pt(II) complexes. In this topical review, strategies for fabricating chromic luminescent Pt(II) complexes are described from a crystal design perspective, focusing on the structural regulation of Pt(II) complexes that exhibit assembly-induced luminescence via metal–metal interactions and structural control of anionic Pt(II) complexes using cations. The research progress on the evolution of various chromic luminescence properties of Pt(II) complexes, including the studies conducted by our group, are presented here along with the latest research outcomes, and an overview of the frontiers and future potential of this research field is provided.

Although COF-300 is often used as an example to study the synthesis and structure of (3D) covalent organic frameworks (COFs), knowledge of the underlying synthetic processes is still fragmented. Here, an optimized synthetic procedure based on a combination of linker protection and modulation was applied. Using this approach, the influence of time and temperature on the synthesis of COF-300 was studied. Synthesis times that were too short produced materials with limited crystallinity and porosity, lacking the typical pore flexibility associated with COF-300. On the other hand, synthesis times that were too long could be characterized by loss of crystallinity and pore order by degradation of the tetrakis(4-aminophenyl)methane (TAM) linker used. The presence of the degradation product was confirmed by visual inspection, Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). As TAM is by far the most popular linker for the synthesis of 3D COFs, this degradation process might be one of the reasons why the development of 3D COFs is still lagging compared with 2D COFs. However, COF crystals obtained via an optimized procedure could be structurally probed using 3D electron diffraction (3DED). The 3DED analysis resulted in a full structure determination of COF-300 at atomic resolution with satisfying data parameters. Comparison of our 3DED-derived structural model with previously reported single-crystal X-ray diffraction data for this material, as well as parameters derived from the Cambridge Structural Database, demonstrates the high accuracy of the 3DED method for structure determination. This validation might accelerate the exploitation of 3DED as a structure determination technique for COFs and other porous materials.

In this work, regenerated cellulose textile fibers, Ioncell-F, dry-wet spun with different draw ratios, have been investigated by scanning wide-angle X-ray scattering (WAXS) using a mesoscopic X-ray beam. The fibers were found to be homogeneous on the 500 nm length scale. Analysis of the azimuthal angular dependence of a crystalline Bragg spot intensity revealed a radial dependence of the degree of orientation of crystallites that was found to increase with the distance from the center of the fiber. We attribute this to radial velocity gradients during the extrusion of the spin dope and the early stage of drawing. On the other hand, the fiber crystallinity was found to be essentially homogeneous over the fiber cross section.

Crystallography is a quintessential method for determining the atomic structure of crystals. The most common implementation of crystallography uses single crystals that must be of sufficient size, typically tens of micrometres or larger, depending on the complexity of the crystal structure. The emergence of serial data-collection methods in crystallography, particularly for time-resolved experiments, opens up opportunities to develop new routes to structure determination for nanocrystals and ensembles of crystals. Fluctuation X-ray scattering is a correlation-based approach for single-particle imaging from ensembles of identical particles, but has yet to be applied to crystal structure determination. Here, an iterative algorithm is presented that recovers crystal structure-factor intensities from fluctuation X-ray scattering correlations. The capabilities of this algorithm are demonstrated by recovering the structure of three small-molecule crystals and a protein crystal from simulated fluctuation X-ray scattering correlations. This method could facilitate the recovery of structure-factor intensities from crystals in serial crystallography experiments and relax sample requirements for crystallography experiments.

This paper was motivated by the articles `Same or different – that is the question' in CrystEngComm (July 2020) and `Change to the definition of a crystal' in the IUCr Newsletter (June 2021). Experimental approaches to crystal comparisons require rigorously defined classifications in crystallography and beyond. Since crystal structures are determined in a rigid form, their strongest equivalence in practice is rigid motion, which is a composition of translations and rotations in 3D space. Conventional representations based on reduced cells and standardizations theoretically distinguish all periodic crystals. However, all cell-based representations are inherently discontinuous under almost any atomic displacement that can arbitrarily scale up a reduced cell. Hence, comparison of millions of known structures in materials databases requires continuous distance metrics.

The functionality and efficiency of proteins within a biological membrane are highly dependent on both the membrane lipid composition and the physiochemical properties of the solution. Lipid mesophases are directly influenced by changes in temperature, pH, water content or due to individual properties of single lipids such as photoswitchability. In this work, we were able to induce light- and temperature-driven mesophase transitions in a model membrane system containing a mixture of 1,2-dipalmitoyl-phosphatidylcholine phospho­lipids and azo­benzene amphiphiles. We observed reversible and reproducible transitions between the lamellar and Pn3m cubic phase after illuminating the sample for 5 min with light of 365 and 455 nm wavelengths, respectively, to switch between the cis and trans states of the azo­benzene N=N double bond. These light-controlled mesophase transitions were found for mixed complexes with up to 20% content of the photosensitive molecule and at temperatures below the gel-to-liquid crystalline phase transition temperature of 33°C. Our results demonstrate the potential to design bespoke model systems to study the response of membrane lipids and proteins upon changes in mesophase without altering the environment and thus provide a possible basis for drug delivery systems.

The hardware for data archiving has expanded capacities for digital storage enormously in the past decade or more. The IUCr evaluated the costs and benefits of this within an official working group which advised that raw data archiving would allow ground truth reproducibility in published studies. Consultations of the IUCr's Commissions ensued via a newly constituted standing advisory committee, the Committee on Data. At all stages, the IUCr financed workshops to facilitate community discussions and possible methods of raw data archiving implementation. The recent launch of the IUCrData journal's Raw Data Letters is a milestone in the implementation of raw data archiving beyond the currently published studies: it includes diffraction patterns that have not been fully interpreted, if at all. The IUCr 75th Congress in Melbourne included a workshop on raw data reuse, discussing the successes and ongoing challenges of raw data reuse. This article charts the efforts of the IUCr to facilitate discussions and plans relating to raw data archiving and reuse within the various communities of crystallography, diffraction and scattering.

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

Carbonic anhydrase (CA) was among the first proteins whose X-ray crystal structure was solved to atomic resolution. CA proteins have essentially the same fold and similar active centers that differ in only several amino acids. Primary sulfonamides are well defined, strong and specific binders of CA. However, minor variations in chemical structure can significantly alter their binding properties. Over 1000 sulfonamides have been designed, synthesized and evaluated to understand the correlations between the structure and thermodynamics of their binding to the human CA isozyme family. Compound binding was determined by several binding assays: fluorescence-based thermal shift assay, stopped-flow enzyme activity inhibition assay, isothermal titration calorimetry and competition assay for enzyme expressed on cancer cell surfaces. All assays have advantages and limitations but are necessary for deeper characterization of these protein–ligand interactions. Here, the concept and importance of intrinsic binding thermodynamics is emphasized and the role of structure–thermodynamics correlations for the novel inhibitors of CA IX is discussed – an isozyme that is overexpressed in solid hypoxic tumors, and thus these inhibitors may serve as anticancer drugs. The abundant structural and thermodynamic data are assembled into the Protein–Ligand Binding Database to understand general protein–ligand recognition principles that could be used in drug discovery.

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.

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

The success of experimental phasing in macromolecular crystallography relies primarily on the accurate locations of heavy atoms bound to the target crystal. To improve the process of substructure determination, a modified phase-retrieval algorithm built on the framework of the relaxed alternating averaged reflection (RAAR) algorithm has been developed. Importantly, the proposed algorithm features a combination of the π-half phase perturbation for weak reflections and enforces the direct-method-based tangent formula for strong reflections in reciprocal space. The proposed algorithm is extensively demonstrated on a total of 100 single-wavelength anomalous diffraction (SAD) experimental datasets, comprising both protein and nucleic acid structures of different qualities. Compared with the standard RAAR algorithm, the modified phase-retrieval algorithm exhibits significantly improved effectiveness and accuracy in SAD substructure determination, highlighting the importance of additional constraints for algorithmic performance. Furthermore, the proposed algorithm can be performed without human intervention under most conditions owing to the self-adaptive property of the input parameters, thus making it convenient to be integrated into the structural determination pipeline. In conjunction with the IPCAS software suite, we demonstrated experimentally that automatic de novo structure determination is possible on the basis of our proposed algorithm.

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.