Search

The Independent Atom Model (IAM) of electron density is used in routine X-ray data analysis. However, this model does not give a quantitative description of the electron-density distribution. A better model that allows for modelling of aspherical charge density deformations is introduced by the Hansen–Coppens variant of the multipole model of electron density. However, the application of this model requires crystals of excellent quality and high-resolution XRD data which are quite often difficult criteria to fulfil. Therefore, Mo Kα and Cu Kα data of three model compounds (tricyclic imide, xylitol and methyluracil) were refined using IAM and new methods which enabled the refinement and reconstruction of charge density based on the Cu Kα data. These methods were the Bond-Oriented Deformation Density (BODD) model, Hirshfeld Atom Refinement (HAR) and the Transferable Aspherical Atom Model (TAAM). The final results were compared to the model obtained from neutron diffraction experiments. Our results demonstrated not only that Cu Kα data may be refined using BODD, HAR and TAAM methods, but also revealed systematic errors arising from the use of Cu Kα data. These errors were a result of the limited information in the low-resolution data set that manifested as higher values for the anisotropic displacement parameters (ADPs) and smaller maxima and minima of the residual electron density for the Cu Kα data compared to the Mo Kα data. Notably, these systematic errors were much less significant than those found for the IAM. Therefore, the application of BODD, HAR and TAAM on Cu Kα data has a more significant influence on the final results of refinement than for the Mo Kα data.

The performance of a model is dependent on the quality and information content of the data used to build it. By applying machine learning approaches to a standard chemical dataset, we developed a 4-class classification algorithm that is able to predict the hydrogen bond network dimensionality that a molecule would adopt in its crystal form with an accuracy of 59% (in comparison to a 25% random threshold), exclusively from two and lower dimensional molecular descriptors. Although better than random, the performance level achieved by the model did not meet the standards for its reliable application. The practical value of our model was improved by wrapping the model around a confidence tool that increases model robustness, quantifies prediction trust, and allows one to operate a classifier virtually up to any accuracy level. Using this tool, the performance of the model could be improved up to 73% or 89% with the compromise that only 34% and 8% of the total set of test examples could be predicted. We anticipate that the ability to adjust the performance of reliable 2D based models to the requirements of its different applications may increase their practical value, making them suitable to tasks that range from initial virtual library filtering to profile specific compound identification.

CREBBP (CBP/KAT3A) and its paralogue EP300 (KAT3B) are lysine acetyltransferases (KATs) that are essential for human development. They each comprise 10 domains through which they interact with >400 proteins, making them important transcriptional co-activators and key nodes in the human protein-protein interactome. The bromodomains of CREBBP and EP300 enable the binding of acetylated lysine residues from histones and a number of other important proteins, including p53, p73, E2F, and GATA1. Here, we report a work to develop a high-affinity, small-molecule ligand for the CREBBP and EP300 bromodomains [(-)-OXFBD05] that shows >100-fold selectivity over a representative member of the BET bromodomains, BRD4(1). Cellular studies using this ligand demonstrate that the inhibition of the CREBBP/EP300 bromodomain in HCT116 colon cancer cells results in lowered levels of c-Myc and a reduction in H3K18 and H3K27 acetylation. In hypoxia (

Transition-metal complexes are widely used in the physical and biological sciences. They have essential roles in catalysis, synthesis, materials science, photophysics and bioinorganic chemistry. Our understanding of transition-metal complexes originates from Alfred Werner’s realization that their three-dimensional shape influences their properties and reactivity1, and the intrinsic link between shape and electronic structure is now firmly underpinned by molecular-orbital theory2–5. Despite more than a century of advances in this field, the geometries of transition-metal complexes remain limited to a few well-understood examples. The archetypal geometries of six-coordinate transition metals are octahedral and trigonal prismatic, and although deviations from ideal bond angles and bond lengths are frequent6, alternative parent geometries are extremely rare7. The hexagonal planar coordination environment is known, but it is restricted to condensed metallic phases8, the hexagonal pores of coordination polymers9, or clusters that contain more than one transition metal in close proximity10,11. Such a geometry had been considered12,13 for [Ni(PtBu)6]; however, an analysis of the molecular orbitals suggested that this complex is best described as a 16-electron species with a trigonal planar geometry14. Here we report the isolation and structural characterization of a simple coordination complex in which six ligands form bonds with a central transition metal in a hexagonal planar arrangement. The structure contains a central palladium atom surrounded by three hydride and three magnesium-based ligands. This finding has the potential to introduce additional design principles for transition-metal complexes, with implications for several scientific fields. A six-coordinate transition-metal complex with a hexagonal planar geometry is isolated and characterized.

Crystal structure refinement and analysis is a powerful method for determination of crystal structures and finds widespread application in determination of structures of crystals of small molecules and frameworks at atomic resolution. The independent atom model is used to describe atomic scattering for routine use, while more accurate aspherical scattering factors are increasingly available. The structure factor is presented as the Fourier transform of convolutions of scattering and probability densities in the crystal structure to clarify how aspherical scattering factors and alternative displacement probabilities can be introduced into refinement methods. Non-linear least squares fitting of the crystal structure parameters in the structure factor equations is described using matrix algebra notation which enables simple derivation of the extensions required for discussion of crystallographic restraints and leverage analysis. Finally, combined analysis of multiple single-crystal experiments is discussed highlighting the potential of refinement tools to extract useful information from joint X-ray and neutron data and from mixed ground-state and excited-state X-ray data from pump-probe experiments.

The reactions of a series of β-diketiminate stabilised aluminium dihydrides with ruthenium bis(phosphine), palladium bis(phosphine) and palladium cyclopentadienyl complexes is reported., The reactions of a series of β-diketiminate stabilised aluminium dihydrides with ruthenium bis(phosphine), palladium bis(phosphine) and palladium cyclopentadienyl complexes is reported. In the case of ruthenium, alane coordination occurs with no evidence for hydrogen loss resulting in the formation of ruthenium complexes with a pseudo–octahedral geometry and cis-relation of phosphine ligands. These new ruthenium complexes have been characterised by multinuclear and variable temperature NMR spectroscopy, IR spectroscopy and single crystal X-ray diffraction. In the case of palladium, a series of structural snapshots of alane dehydrogenation have been isolated and crystallographically characterised. Variation of the palladium precursor and ligand on aluminium allows kinetic control over reactivity and isolation of intermetallic complexes that contain new Pd–Al and Pd–Pd interactions. These complexes differ by the ratio of H : Al (2 : 1, 1.5 : 1 and 1 : 1) with lower hydride content species forming with dihydrogen loss. A combination of X-ray and neutron diffraction studies have been used to interrogate the structures and provide confidence in the assignment of the number and position of hydride ligands. 27Al MAS NMR spectroscopy and calculations (DFT, QTAIM) have been used to gain an understanding of the dehydrogenation processes. The latter provide evidence for dehydrogenation being accompanied by metal–metal bond formation and an increased negative charge on Al due to the covalency of the new metal–metal bonds. To the best of our knowledge, we present the first structural information for intermediate species in alane dehydrogenation including a rare neutron diffraction study of a palladium–aluminium hydride complex. Furthermore, as part of these studies we have obtained the first SS 27Al NMR data on an aluminium(i) complex. Our findings are relevant to hydrogen storage, materials chemistry and catalysis.

Transition-metal complexes are widely used in the physical and biological sciences. They have essential roles in catalysis, synthesis, materials science, photophysics and bioinorganic chemistry. Our understanding of transition-metal complexes originates from Alfred Werner's realization that their three-dimensional shape influences their properties and reactivity

We probe the effect of heteroatom substitution on the spin crossover (SCO) properties of dinuclear materials of the type [Fe2(NCX)4(R-trz)5]·S (X = S, Se; S = solvent; R-trz = (E)-N-(furan-2-ylmethylene)- 4H-1,2,4-triazol-4-amine (furtrz); (E)-N-(thiophen-2-ylmethylene)-4H-1,2,4-triazole-4-amine (thtrz)). For the furtrz family ([Fe2(NCX)4(furtrz)5]·furtrz·MeOH; X = S (furtrz-S) and X = Se (furtrz-Se)) gradual and incomplete one-step SCO transitions are observed (furtrz-S (T1/2 = 172 K) and furtrz-Se (T1/2 = 205 K)) and a structural evolution from [HS-HS] to [HS-LS] per dinuclear species. Contrasting this, within the thtrz family ([Fe2(NCX)4(thtrz)5]·4MeOH; X = S (thtrz-S) and X = Se (thtrz-Se)) more varied SCO transitions are observed, with thtrz-S being SCO-inactive (high spin) and thtrz-Se showing a rare complete two-step SCO transition (T1/2(1,2) = 170, 200 K) in which the FeII sites transition from [HS-HS] to [HS-LS] to [LS-LS] per dinuclear unit with no long range ordering of spin-states at the intermediate plateau. Detailed structure- function analyses have been conducted within this growing dinuclear family to rationalise these diverse spin-switching properties.

A study of post-refinement absolute structure determination using previously published data was carried out using theCRYSTALSsoftware package. We show that absolute structure determination may be carried out optimally using the analyses available inCRYSTALS, and that it is not necessary to have the separate proceduresabsolute structure determinationandno interest in absolute structureas proposed by Flack [Chimia(2014),68, 26–30].

Crystallographic restraints are widely used during refinement of small-molecule and macromolecular crystal structures. They can be especially useful for introducing additional observations and information into structure refinements against low-quality or low-resolution data (e.g. data obtained at high pressure) or to retain physically meaningful parameter values in disordered or unstable refinements. However, despite the fact that the anisotropic displacement parameters (ADPs) often constitute more than half of the total model parameters determined in a structure analysis, there are relatively few useful restraints for them, examples being Hirshfeld rigid-bond restraints, direct equivalence of parameters and SHELXL RIGU-type restraints. Conversely, geometric parameters can be subject to a multitude of restraints (e.g. absolute or relative distance, angle, planarity, chiral volume, and geometric similarity). This article presents a series of new ADP restraints implemented in CRYSTALS [Parois, Cooper & Thompson (2015), Chem. Cent. J. 9, 30] to give more control over ADPs by restraining, in a variety of ways, the directions and magnitudes of the principal axes of the ellipsoids in locally defined coordinate systems. The use of these new ADPs results in more realistic models, as well as a better user experience, through restraints that are more efficient and faster to set up. The use of these restraints is recommended to preserve physically meaningful relationships between displacement parameters in a structural model for rigid bodies, rotationally disordered groups and low-completeness data.

We present here the crystallisation outcomes for 319 publicly available compounds in up to 18 different solvents spread over 5,710 individual single solvent evaporation trials. The recorded data is part of a much larger, corresponding in-house data base and includes both positive as well as negative crystallisation outcomes. Such data can be used for statistical analyses of solvent performances, machine learning approaches or to investigate the crystallisation behaviour in structurally similar compound classes. The presented data suggests that crystallisation behaviour in different solvents is not correlated to chemical similarity among clusters of highly similar compounds. Further, our machine learning models can be used to guide the solvent choice when crystallising a compound. In a retrospective evaluation, these models proved potent to reduce the workload to a third of our initial protocol, while still guaranteeing crystallisation success rates >92%.

A new molecular descriptor, nConf20, based on chemical connectivity, is presented which captures the accessible conformational space of a molecule. Currently the best available two-dimensional descriptors for quantifying the flexibility of a particular molecule are the rotatable bond count (RBC) and the Kier flexibility index. We present a descriptor which captures this information by sampling the conformational space of a molecule using the RDKit conformer generator. Flexibility has previously been identified as a key feature in determining whether a molecule is likely to crystallize or not. For this application, nConf20 significantly outperforms previously reported single-variable classifiers and also assists rule-based analysis of black-box machine learning classification algorithms.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices´ for performing CSP calculations. All of the targets, apart from a single potentially disordered Z?? = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms. Fil: Reilly, Anthony M.. Cambridge Crystallographic Data Centre; Fil: Cooper, Richard I.. Chemistry Research Laboratory; Fil: Adjiman, Claire S.. Imperial College London; Reino Unido Fil: Bhattacharya, Saswata. Fritz Haber Institute Of The Max Planck Society; Fil: Boese, A. Daniel. Karl-franzens-universitat Graz; Austria Fil: Brandenburg, Jan Gerit. Colegio Universitario de Londres; Reino Unido. Universitat Bonn; Alemania Fil: Bygrave, Peter J.. University of Southampton; Reino Unido Fil: Bylsma, Rita. Radboud Universiteit Nijmegen; Países Bajos Fil: Campbell, Josh E.. University of Southampton; Reino Unido Fil: Car, Roberto. University of Princeton; Estados Unidos Fil: Case, David H.. University of Southampton; Reino Unido Fil: Chadha, Renu. University Institute Of Pharmaceutical Sciences India; India Fil: Cole, Jason C.. Cambridge Crystallographic Data Centre; Fil: Cosburn, Katherine. University of Tulane; Estados Unidos. University of Toronto; Canadá Fil: Cuppen, Herma M.. Radboud Universiteit Nijmegen; Países Bajos Fil: Curtis, Farren. University of Tulane; Estados Unidos. University of Carnegie Mellon; Estados Unidos Fil: Day, Graeme M.. University of Southampton; Reino Unido Fil: DiStasio, Robert A.. University of Princeton; Estados Unidos. Cornell University; Estados Unidos Fil: Dzyabchenko, Alexander. Karpov Institute Of Physical Chemistry; Fil: Van Eijck, Bouke P.. University of Utrecht; Países Bajos. Utrecht University; Países Bajos Fil: Elking, Dennis M.. Openeye Scientific Software, Inc; Fil: Van Den Ende, Joost A.. Radboud Universiteit Nijmegen; Países Bajos Fil: Facelli, Julio C.. University of Utah; Estados Unidos Fil: Ferraro, Marta B.. Universidad de Buenos Aires; Argentina Fil: Fusti-Molnar, Laszlo. Openeye Scientific Software, Inc; Fil: Gatsiou, Christina-Anna. Imperial College London; Reino Unido Fil: Gee, Thomas S.. University of Southampton; Reino Unido Fil: De Gelder, René. Radboud Universiteit Nijmegen; Países Bajos Fil: Ghiringhelli, Luca M.. Fritz Haber Institute Of The Max Planck Society; Fil: Goto, Hitoshi. Toyohashi University Of Technology; Fil: Grimme, Stefan. Universitat Bonn; Alemania Fil: Guo, Rui. Colegio Universitario de Londres; Reino Unido Fil: Hofmann, Detlef W. M.. Flexcryst; . Polaris; Fil: Hoja, Johannes. Fritz Haber Institute Of The Max Planck Society; Fil: Hylton, Rebecca K.. Colegio Universitario de Londres; Reino Unido Fil: Iuzzolino, Luca. Colegio Universitario de Londres; Reino Unido Fil: Jankiewicz, Wojciech. University Of Silesia In Katowice; Fil: De Jong, Daniël T.. Radboud Universiteit Nijmegen; Países Bajos Fil: Kendrick, John. University Of Bradford; Fil: De Klerk, Niek J. J.. Radboud Universiteit Nijmegen; Países Bajos Fil: Ko, Hsin-Yu. University of Princeton; Estados Unidos Fil: Kuleshova, Liudmila N.. Flexcryst; Fil: Li, Xiayue. University of Tulane; Estados Unidos. Argonne National Laboratory; Estados Unidos Fil: Lohani, Sanjaya. University of Tulane; Estados Unidos Fil: Leusen, Frank J. J.. University Of Bradford; Fil: Lund, Albert M.. University of Utah; Estados Unidos. Openeye Scientific Software, Inc; Fil: Lv, Jian. Jilin University; China Fil: Ma, Yanming. Jilin University; China Fil: Marom, Noa. University of Carnegie Mellon; Estados Unidos. University of Tulane; Estados Unidos Fil: Masunov, Artëm E.. University Of Central Florida; . National Research Nuclear University Mephi; Fil: McCabe, Patrick. Cambridge Crystallographic Data Centre; Fil: McMahon, David P.. University of Southampton; Reino Unido Fil: Meekes, Hugo. Radboud Universiteit Nijmegen; Países Bajos Fil: Metz, Michael P.. University Of Delaware; Fil: Misquitta, Alston J.. Queen Mary, University Of London; Fil: Mohamed, Sharmarke. Khalifa University Of Science And Technology; Fil: Monserrat, Bartomeu. Rutgers, The State University Of New Jersey; . University of Cambridge; Estados Unidos Fil: Needs, Richard J.. University of Cambridge; Estados Unidos Fil: Neumann, Marcus A.. No especifica; Fil: Nyman, Jonas. University of Southampton; Reino Unido Fil: Obata, Shigeaki. Toyohashi University Of Technology; Fil: Oberhofer, Harald. Universitat Technical Zu Munich; Alemania Fil: Oganov, Artem R.. Northwestern Polytechnical University; China. Skolkovo Institute Of Science And Technology; . Moscow Institute Of Physics And Technology; . Stony Brook University; Fil: Orendt, Anita M.. University of Utah; Estados Unidos Fil: Pagola, Gabriel Ignacio. Universidad de Buenos Aires; Argentina Fil: Pantelides, Constantinos C.. Imperial College London; Reino Unido Fil: Pickard, Chris J.. University of Cambridge; Estados Unidos. Colegio Universitario de Londres; Reino Unido Fil: Podeszwa, Rafal. University Of Silesia In Katowice; Fil: Price, Louise S.. Colegio Universitario de Londres; Reino Unido Fil: Price, Sarah L.. Colegio Universitario de Londres; Reino Unido Fil: Pulido, Angeles. University of Southampton; Reino Unido Fil: Read, Murray G.. Cambridge Crystallographic Data Centre; Fil: Reuter, Karsten. Universitat Technical Zu Munich; Alemania Fil: Schneider, Elia. University of New York; Estados Unidos Fil: Schober, Christoph. Universitat Technical Zu Munich; Alemania Fil: Shields, Gregory P.. Cambridge Crystallographic Data Centre; Fil: Singh, Pawanpreet. University Institute Of Pharmaceutical Sciences India; India Fil: Sugden, Isaac J.. Imperial College London; Reino Unido Fil: Szalewicz, Krzysztof. University Of Delaware; Fil: Taylor, Christopher R.. University of Southampton; Reino Unido Fil: Tkatchenko, Alexandre. University Of Luxembourg; . Fritz Haber Institute Of The Max Planck Society; Fil: Tuckerman, Mark E.. University of New York; Estados Unidos. New York University Shanghai; China. Courant Institute Of Mathematical Sciences; Fil: Vacarro, Francesca. University of Tulane; Estados Unidos. Loyola University New Orleans; Fil: Vasileiadis, Manolis. Imperial College London; Reino Unido Fil: Vazquez-Mayagoitia, Alvaro. Argonne National Laboratory; Estados Unidos Fil: Vogt, Leslie. University of New York; Estados Unidos Fil: Wang, Yanchao. Jilin University; China Fil: Watson, Rona E.. Colegio Universitario de Londres; Reino Unido Fil: De Wijs, Gilles A.. Radboud Universiteit Nijmegen; Países Bajos Fil: Yang, Jack. University of Southampton; Reino Unido Fil: Zhu, Qiang. Stony Brook University; Fil: Groom, Colin R.. Cambridge Crystallographic Data Centre

A sizeable proportion of structures withZ′ = 2 are thought to exhibit pseudosymmetry, but establishing the extent of the deviation from true symmetry is problematic. By considering both the conformational similarity between the independent molecules and the way in which they are related in space, assessment of the pseudosymmetry of a structure becomes possible. A method of matching two groups of atoms where both these factors are quantified usingCRYSTALS[Betteridge, Carruthers, Cooper, Prout & Watkin (2003).J. Appl. Cryst.36, 1487] is described.

Overlapping absorption edges will occur when an element is present in multiple oxidation states within a material.DetOxis a program for partitioning overlapping X-ray absorption spectra into contributions from individual atomic species and computing the dependence of the anomalous scattering factors on X-ray energy. It is demonstrated how these results can be used in combination with X-ray diffraction data to determine the oxidation state of ions at specific sites in a mixed-valance material, GaCl2.

Although non-merohedrally twinned crystal structures can normally be solved without difficulty, problems usually arise during refinement. Careful analysis of poorly fitting data reveals that they belong predominantly to certain distinct zones in which |Fo|2is systematically larger than |Fc|2. In the computer programROTAX, a set of data with the largest values of (|F_{o}^{\,2}| − |F_{c}^{\,2}|)/u(|F_{o}^{\,2}|) is identified and their indices transformed by rotations or roto-inversions about possible direct- and reciprocal-lattice directions. Matrices that transform the indices of the poorly fitting data to integers are identified as possible twin laws.

The programCRYSTALS[Betteridge, Carruthers, Cooper, Prout & Watkin (2003).J. Appl. Cryst.36, 1487] has been extended to include an option for the refinement of a continuous electron density distribution lying along a line, a ring or on the surface of a sphere. These additional non-atomic electron distributions can be refined in any combination with traditional anisotropically distributed spherical atoms, including the refinement of `partial' atoms overlapping with the special electron distributions.

Leverages measure the influence that observations (intensity data and restraints) have on the fit obtained in crystal structure refinement. Further analysis enables the influence that observations have on specific parameters to be measured. The results of leverage analyses are discussed in the context of the amino acid alanine and an incomplete high-pressure data set of the complex bis(salicylaldoximato)copper(II). Leverage analysis can reveal situations where weak data are influential and allows an assessment of the influence of restraints. Analysis of the high-pressure refinement of the copper complex shows that the influence of the highest-leverage intensity observations increases when completeness is reduced, but low leverages stay low. The influence of restraints, notably those applying the Hirshfeld rigid-bond criterion, also increases dramatically. In alanine the precision of the Flack parameter is determined by medium-resolution data with moderate intensities. The results of a leverage analysis can be incorporated into a weighting scheme designed to optimize the precision of a selected parameter. This was applied to absolute structure refinement of light-atom crystal structures. The standard uncertainty of the Flack parameter could be reduced to around 0.1 even for a hydrocarbon.

A new polymorph of 2,4-dihydroxybenzoic acid is reported. The structure was characterized by multiple-temperature X-ray diffraction and solid-state DFT computations. The material shows a geometric pattern of hydrogen bonding consistent with cooperativity between the intermolecular carboxylic acid dimer and intramolecular hydrogen bonds. The presence of proton disorder within this hydrogen-bond system, which would support such a cooperative model, was not fully ruled out by the initial X-ray studies. However, solid-state calculations on the three possible end-point tautomers indicate that the dominant crystallographically observed configuration is substantially lower in energy than the other tautomers (by at least 9 kJ mol−1), indicating that no disorder should be expected. It is therefore concluded that no disorder is observed either in the intra- or intermolecular hydrogen bonds of the title compound and that the cooperativity between the hydrogen bonds is not present within the temperature range studied.

A modern industrial route for the manufacture of methyl methacrylate involves the reaction of methyl propanoate and formaldehyde over a silica-supported Cs catalyst. Although the process has been successfully commercialised, little is known about the surface interactions responsible for the forward chemistry. This work concentrates upon the interaction of methyl propanoate over a representative silica. A combination of infrared spectroscopy, inelastic neutron scattering, DFT calculations, X-ray diffraction and temperature-programmed desorption is used to deduce how the ester interacts with the silica surface.

Predicting and controlling crystallinity of molecular materials has applications in a crystal engineering context, as well as process control and formulation in the pharmaceutical industry. Here, we present a machine learning approach to this problem which uses a large input training set which is classified on a single measurable outcome: does a substance have a reasonable probability of forming good quality crystals. While the related problem of crystal structure prediction requires reliable calculation of three dimensional molecular conformations, the method employed here for predicting crystallisation propensity uses only "two dimensional" information consisting of atom types and connectivity. We show that an error rate lower than 10% can be achieved against unseen test data. The predictive model was also tested in a blind screen of a set of compounds which do not have crystal structures reported in the literature, and we found it to have a 79% classification accuracy. Analysis of the most significant descriptors used in the classification shows that the number of rotatable bonds and a molecular connectivity index are key in determining crystallisation propensity and using these two measures alone can give 80% accurate classification of unseen test data.

β-U4O9 is a superlattice structure based on the fluorite arrangement of UO2. The U atoms occupy positions close to those in UO2 and the additional O atoms are accommodated in cuboctahedral clusters of \bar43m symmetry, which are centred on the special 12-fold sites of the cubic space group I\bar43d. The structure has been refined from single-crystal neutron data in accordance with the procedure described in the previous paper [Popa & Willis (2004). Acta Cryst. A60, 318–321].

The traditional Waser distance restraint, the rigid-bond restraint and atomic displacement parameter (ADP) similarity restraints have an equal influence on both atoms involved in the restraint. This may be inappropriate in cases where it can reasonably be expected that the precision of the determination of the positional parameters and ADPs is not equal,e.g.towards the extremities of a librating structure or where one atom is a significantly stronger scatterer than the other. In these cases, the traditional restraint feeds information from the poorly defined atom to the better defined atom, with the possibility that its characteristics become degraded. The modified restraint described here feeds information from the better defined atom to the more poorly defined atom with minimal feedback.

Direct determination of the Flack parameter as part of the structure refinement procedure usually gives different, though similar, values to post-refinement methods. The source of this discrepancy has been probed by analysing a range of data sets taken from the recent literature. Most significantly, it was observed that the directly refined Flack (x) parameter and its standard uncertainty are usually not much influenced by changes in the refinement weighting schemes, but if they are then there are probably problems with the data or model. Post-refinement analyses give Flack parameters strongly influenced by the choice of weights. Weights derived from those used in the main least squares lead to post-refinement estimates of the Flack parameters and their standard uncertainties very similar to those obtained by direct refinement. Weights derived from the variances of the observed structure amplitudes are more appropriate and often yield post-refinement Flack parameters similar to those from direct refinement, but always with lower standard uncertainties. Substantial disagreement between direct and post-refinement determinations are strongly indicative of problems with the data, which may be difficult to identify. Examples drawn from 28 structure determinations are provided showing a range of different underlying problems. It seems likely that post-refinement methods taking into account the slope of the normal probability plot are currently the most robust estimators of absolute structure and should be reported along with the directly refined values.

The compositional dependence of thermal expansion behaviour in 19 different perovskite-like metal-organic frameworks (MOFs) of composition [AI][MII(HCOO)3] (A = alkylammonium cation; M = octahedrally-coordinated divalent metal) is studied using variable-temperature X-ray powder diffraction measurements. While all systems show essentially the same type of thermomechanical response-irrespective of their particular structural details-the magnitude of this response is shown to be a function of AI and MII cation radii, as well as the molecular anisotropy of AI. Flexibility is maximised for large MII and small AI, while the shape of AI has implications for the direction of framework hingeing., 11 pages, 7 figures, 2 tables

The structure of the title compound, C9H9N 3O5, was determined as one of a group of five related compounds in order to assess its suitability as a test material for the 2004 Cambridge Crystallographic Data Centre 'Blind Structure Prediction Test'. The structure consists of hydrogen-bonded ribbons of molecules stacked along the a axis with the benzene rings parallel by unit-cell translations. © 2005 International Union of Crystallography Printed in Great Britain - all rights reserved.

The title compound, [Pd(C2H3O2)(C18H15P)(C12H11N2O)]·CH2Cl2, crystallizes readily from a mixture of di­chloro­methane and light petroleum. The structure is one of few examples of palladacycles that incorporate the N-substituent in five-membered-ring heterocycles [Nonoyama & Nakajima (1998). Polyhedron, 18, 533–543].

Epimeric azidoesters containing a glucofuranosyl moiety are readily prepared from glucoheptonolactone and may be reduced to corresponding aminoesters; such compounds may be useful intermediates for the generation of combinatorial libraries of glucofuranose mimics and of spiroderivatives of glucofuranose at the anomeric position. The X-ray crystal structure of methyl 2-amino-2-deoxy-3,4-di- O - tert -butyldimethylsilyl-6,7- O -isopropylidene- β -D- gluco -2-heptulofuranosonate is reported.

We use variable-temperature (150--300\,K) single-crystal X-ray diffraction to re-examine the interplay between structure and dynamics in the ambient phase of the isotropic negative thermal expansion (NTE) material Cd(CN)$_2$. We find strong experimental evidence for the existence of low-energy vibrational modes that involve off-centering of Cd$^{2+}$ ions. These modes have the effect of increasing network packing density---suggesting a mechanism for NTE that is different to the generally-accepted picture of correlated Cd(C/N)$_4$ rotation modes. Strong local correlations in the displacement directions of neighbouring cadmium centres are evident in the existence of highly-structured diffuse scattering in the experimental X-ray diffraction patterns. Monte Carlo simulations suggest these patterns might be interpreted in terms of a basic set of `ice-rules' that establish a mapping between the dynamics of Cd(CN)$_2$ and proton ordering in cubic ice VII., Comment: 5 pages, 5 figures, submitted to PRB

Because they scatter X-rays weakly, H atoms are often abused or neglected during structure refinement. The reasons why the H atoms should be included in the refinement and some of the consequences of mistreatment are discussed along with selected real examples demonstrating some of the features for hydrogen treatment that can be found in the software suite CRYSTALS. © 2010 International Union of Crystallography Printed in Singapore-all rights reserved.

We present ElectroShape, a novel ligand-based virtual screening method, that combines shape and electrostatic information into a single, unified framework. Building on the ultra-fast shape recognition (USR) approach for fast non-superpositional shape-based virtual screening, it extends the method by representing partial charge information as a fourth dimension. It also incorporates the chiral shape recognition (CSR) method, which distinguishes enantiomers. It has been validated using release 2 of the Directory of useful decoys (DUD), and shows a near doubling in enrichment ratio at 1% over USR and CSR, and improvements as measured by Receiver Operating Characteristic curves. These improvements persisted even after taking into account the chemotype redundancy in the sets of active ligands in DUD. During the course of its development, ElectroShape revealed a difference in the charge allocation of the DUD ligand and decoy sets, leading to several new versions of DUD being generated as a result. ElectroShape provides a significant addition to the family of ultra-fast ligand-based virtual screening methods, and its higher-dimensional shape recognition approach has great potential for extension and generalisation.

X-ray crystallographic analysis of the title hydrobromide salt, C10H20N+·Br−, of (1R,2S,3R,5R,8aR)-3-hydroxymethyl-5-methyloctahydroindolizine-1,2-diol defines the absolute and relative stereochemistry at the five chiral centres in steviamine, a new class of polyhydroxylated indolizidine alkaloid isolated from Stevia rebaudiana (Asteraceae) leaves. In the crystal structure, molecules are linked by intermolecular O—H...Br and N—H...Br hydrogen bonds, forming double chains around the twofold screw axes along the b-axis direction. Intramolecular O—H...O interactions occur.

The structure of the title compound, C7H5IN 2O4, was determined as one of a group of five related compounds, in order to assess its suitability as a test material for the 2004 Cambridge Crystallographic Data Centre 'Blind Structure Prediction Test'. The crystal structure consists of columns of nearly planar molecules stacked parallel to the a axis, with an interplanar spacing of 3.478 (3) Å. © 2005 International Union of Crystallography Printed in Great Britain - all rights reserved.

The structure of the title compound, C9H10O 3, was determined as one of a group of five related compounds in order to assess its suitability as a test material for the 2004 Cambridge Crystallographic Data Centre 'Blind Structure Prediction Test'. The molecules are almost planar except for the acetamide group, which is involved in hydrogen bonding. The structure consists of columns of molecules hudrogen bonded into chains parallel to the c axis. © 2005 International Union of Crystallography Printed in Great Britain - all rights reserved.

CIF2CRYis a program for converting structural data and reflection data contained in a CIF into instructions to be read by theCRYSTALSprogram [Betteridge, Carruthers, Cooper, Prout & Watkin (2003).J. Appl. Cryst.36, 1487]. The program can be used, for example, to read in CIFs that are archived by crystallographic journals, allowing users to study and re-refine published structures. Multiple data blocks in one CIF can be converted into a continuous file ofCRYSTALSinstructions, including an instruction for running user-specified calculations after each structure has been input. The program uses the CIFtbx Fortran library.