The Advantages of Flexibility: The Role of Entropy in Crystal Structures Containing C-H···F Interactions.

Molecular crystal structures are often interpreted in terms of strong, structure directing, intermolecular interactions, especially those with distinct geometric signatures such as H-bonds or π-stacking interactions. Other interactions can be overlooked, perhaps because they are weak or lack a characteristic geometry. We show that although the cumulative effect of weak interactions is significant, their deformability also leads to occupation of low energy vibrational energy levels, which provides an additional stabilizing entropic contribution. The entropies of five fluorobenzene derivatives have been calculated by periodic DFT calculations to assess the entropic influence of C-H···F interactions in stabilizing their crystal structures. Calculations reproduce inelastic neutron scattering data and experimental entropies from heat capacity measurements. C-H···F contacts are shown to have force constants which are around half of those of more familiar interactions such as hydrogen bonds, halogen bonds, and C-H···π interactions. This feature, in combination with the relatively high mass of F, means that the lowest energy vibrations in crystalline fluorobenzenes are dominated by C-H···F contributions. C-H···F contacts occur much more frequently than would be expected from their enthalpic contributions alone, but at 150 K, the stabilizing contribution of entropy provides, at -10 to -15 kJ mol-1, a similar level of stabilization to the N-H···N hydrogen bond in ammonia and O-H···O hydrogen bond in water.

Characterization of K562 cells: uncovering novel chromosomes, assessing transferrin receptor expression, and probing pharmacological therapies.

Human erythroleukemic K562 cells represent the prototypical cell culture model of chronic myeloid leukemia (CML). The cells are pseudo-triploid and positive for the Philadelphia chromosome. Therefore, K562 cells have been widely used for investigating the BCR/ABL1 oncogene and the tyrosine kinase inhibitor, imatinib-mesylate. Further, K562 cells overexpress transferrin receptors (TfR) and have been used as a model for targeting cytotoxic therapies, via receptor-mediated endocytosis. Here, we have characterized K562 cells focusing on the karyotype of cells in prolonged culture, regulation of expression of TfR in wildtype (WT) and doxorubicin-resistant cells, and responses to histone deacetylase inhibition (HDACi). Karyotype analysis indicates novel chromosomes and gene expression analysis suggests a shift of cultured K562 cells away from patient-derived leukemic cells. We confirm the high expression of TfR on K562 cells using immunofluorescence and cell-surface receptor binding radioassays. Importantly, high TfR expression is observed in patient-derived cells, and we highlight the persistent expression of TfR following doxorubicin acquired resistance. Epigenetic analysis indicates that permissive histone acetylation and methylation at the promoter region regulates the transcription of TfR in K562 cells. Finally, we show relatively high expression of HDAC enzymes in K562 cells and demonstrate the chemotoxic effects of HDACi, using the FDA-approved hydroxamic acid, vorinostat. Together with a description of morphology, infrared spectral analysis, and examination of metabolic properties, we provide a comprehensive characterization of K562 cells. Overall, K562 cell culture systems remain widely used for the investigation of novel therapeutics for CML, which is particularly important in cases of imatinib-mesylate resistance.

Behavior of Occupied and Void Space in Molecular Crystal Structures at High Pressure.

We report a Monte Carlo algorithm for calculation of occupied ("network") and unoccupied ("void") space in crystal structures. The variation of the volumes of the voids and the network of intermolecular contacts with pressure sensitively reveals discontinuities associated with first- and second-order phase transitions, providing insights into the effect of compression (and, in principle, other external stimuli) at a level between those observed in individual contact distances and the overall unit cell dimensions. The method is shown to be especially useful for the correlation of high-pressure crystallographic and spectroscopic data, illustrated for naphthalene, where a phase transition previously detected by vibrational spectroscopy, and debated in the literature for over 80 years, has been revealed unambiguously in crystallographic data for the first time. Premonitory behavior before a phase transition and crystal collapse at the end of a compression series has also been detected. The network and void volumes for 129 high-pressure studies taken from the Cambridge Structural Database (CSD) were fitted to equation of state to show that networks typically have bulk moduli between 40 and 150 GPa, while those of voids fall into a much smaller range, 2-5 GPa. These figures are shown to reproduce the narrow range of overall bulk moduli of molecular solids (ca. 5-20 GPa). The program, called CellVol, has been written in Python using the CSD Python API and can be run through the command line or through the Cambridge Crystallographic Data Centre's Mercury interface.

Automated tracking of emergency department abdominal CT findings during the COVID-19 pandemic using natural language processing.

PURPOSE: During the COVID-19 pandemic, emergency department (ED) volumes have fluctuated. We hypothesized that natural language processing (NLP) models could quantify changes in detection of acute abdominal pathology (acute appendicitis (AA), acute diverticulitis (AD), or bowel obstruction (BO)) on CT reports. METHODS: This retrospective study included 22,182 radiology reports from CT abdomen/pelvis studies performed at an urban ED between January 1, 2018 to August 14, 2020. Using a subset of 2448 manually annotated reports, we trained random forest NLP models to classify the presence of AA, AD, and BO in report impressions. Performance was assessed using 5-fold cross validation. The NLP classifiers were then applied to all reports. RESULTS: The NLP classifiers for AA, AD, and BO demonstrated cross-validation classification accuracies between 0.97 and 0.99 and F1-scores between 0.86 and 0.91. When applied to all CT reports, the estimated numbers of AA, AD, and BO cases decreased 43-57% in April 2020 (first regional peak of COVID-19 cases) compared to 2018-2019. However, the number of abdominal pathologies detected rebounded in May-July 2020, with increases above historical averages for AD. The proportions of CT studies with these pathologies did not significantly increase during the pandemic period. CONCLUSION: Dramatic decreases in numbers of acute abdominal pathologies detected by ED CT studies were observed early on during the COVID-19 pandemic, though these numbers rapidly rebounded. The proportions of CT cases with these pathologies did not increase, which suggests patients deferred care during the first pandemic peak. NLP can help automatically track findings in ED radiology reporting.

MrPIXEL: automated execution of Pixel calculations via the Mercury interface.

The interpretation of crystal structures in terms of intermolecular interaction energies enables phase stability and polymorphism to be rationalized in terms of quantitative thermodynamic models, while also providing insight into the origin of physical and chemical properties including solubility, compressibility and host-guest formation. The Pixel method is a semi-empirical procedure for the calculation of intermolecular interactions and lattice energies based only on crystal structure information. Molecules are represented as blocks of undistorted ab initio molecular electron and nuclear densities subdivided into small volume elements called pixels. Electrostatic, polarization, dispersion and Pauli repulsion terms are calculated between pairs of pixels and nuclei in different molecules, with the accumulated sum equating to the intermolecular interaction energy, which is broken down into physically meaningful component terms. The MrPIXEL procedure enables Pixel calculations to be carried out with minimal user intervention from the graphical interface of Mercury, which is part of the software distributed with the Cambridge Structural Database (CSD). Following initial setup of a crystallographic model, one module assigns atom types and writes necessary input files. A second module then submits the required electron-density calculation either locally or to a remote server, downloads the results, and submits the Pixel calculation itself. Full lattice energy calculations can be performed for structures with up to two molecules in the crystallographic asymmetric unit. For more complex cases, only molecule-molecule energies are calculated. The program makes use of the CSD Python API, which is also distributed with the CSD.

σ-Hole interactions in small-molecule compounds containing divalent sulfur groups R1-S-R2.

Hydrogen bonds, aromatic stacking contacts and σ-hole interactions are all noncovalent interactions commonly observed in biological systems. Structural data derived from the Protein Data Bank showed that methionine residues can interact with oxygen atoms through directional S...O contacts in the protein core. In the present work, the Cambridge Structural Database (CSD) was used in conjunction with ab initio calculations to explore the σ-hole interaction properties of small-molecule compounds containing divalent sulfur. CSD surveys showed that 7095 structures contained R1-S-R2 groups that interact with electronegative atoms like N, O, S and Cl. Frequencies of occurrence and geometries of the interaction were dependent on the nature of R1 and R2, and the hybridization of carbon atoms in C,C-S, and C,S-S fragments. The most common interactions in terms of frequency of occurrence were C,C-S...O, C,C-S...N and C,C-S...S with predominance of Csp2. The strength of the chalcogen interaction increased when enhancing the electron-withdrawing character of the substituents. The most positive electrostatic potentials (VS,max; illustrating positive σ-holes) calculated on R1-S-R2 groups were located on the S atom, in the S-R1 and S-R2 extensions, and increased with electron-withdrawing R1 and R2 substituents like the interaction strength did. As with geometric data derived from the CSD, interaction geometries calculated for some model systems and representative CSD compounds suggested that the interactions were directed in the extensions of S-R1 and S-R2 bonds. The values of complexation energies supported attractive interactions between σ-hole bond donors and acceptors, enhanced by dispersion. The interactions of R1-S-R2 with large VS,max and nucleophiles with large negative VS,min coherently provided more negative energies. According to NBO analysis, chalcogen interactions consisted of charge transfer from a nucleophile lone pair to an S-R1 or S-R2 antibonding orbital. The directional σ-hole interactions at R1-S-R2 can be useful in crystal engineering and the area of supramolecular biochemistry.

Mercury 4.0: from visualization to analysis, design and prediction.

The program Mercury, developed at the Cambridge Crystallographic Data Centre, was originally designed primarily as a crystal structure visualization tool. Over the years the fields and scientific communities of chemical crystallography and crystal engineering have developed to require more advanced structural analysis software. Mercury has evolved alongside these scientific communities and is now a powerful analysis, design and prediction platform which goes a lot further than simple structure visualization.

Mapping the cooperativity pathways in spin crossover complexes.

Crystal packing energy calculations are applied to the [Fe(PM-L)2(NCS)2] family of spin crossover (SCO) complexes (PM-L = 4-substituted derivatives of the N-(2-pyridylmethylene)-4-aminobiphenyl ligand) with the aim of relating quantitatively the cooperativity of observed SCO transitions to intermolecular interactions in the crystal structures. This approach reveals a linear variation of the transition abruptness with the sum of the magnitudes of the interaction energy changes within the first molecular coordination sphere in the crystal structure. Abrupt transitions are associated with the presence of significant stabilising and destabilising changes in intermolecular interaction energies. While the numerical trend established for the PM-L family does not directly extend to other classes of SCO complex in which the intermolecular interactions may be very different, a plot of transition abruptness against the range of interaction energy changes normalised by the largest change shows a clustering of complexes with similar transition abruptness. The changes in intermolecular interactions are conveniently visualised using energy difference frameworks, which illustrate the cooperativity pathways of an SCO transition.

One class classification as a practical approach for accelerating π-π co-crystal discovery.

The implementation of machine learning models has brought major changes in the decision-making process for materials design. One matter of concern for the data-driven approaches is the lack of negative data from unsuccessful synthetic attempts, which might generate inherently imbalanced datasets. We propose the application of the one-class classification methodology as an effective tool for tackling these limitations on the materials design problems. This is a concept of learning based only on a well-defined class without counter examples. An extensive study on the different one-class classification algorithms is performed until the most appropriate workflow is identified for guiding the discovery of emerging materials belonging to a relatively small class, that being the weakly bound polyaromatic hydrocarbon co-crystals. The two-step approach presented in this study first trains the model using all the known molecular combinations that form this class of co-crystals extracted from the Cambridge Structural Database (1722 molecular combinations), followed by scoring possible yet unknown pairs from the ZINC15 database (21 736 possible molecular combinations). Focusing on the highest-ranking pairs predicted to have higher probability of forming co-crystals, materials discovery can be accelerated by reducing the vast molecular space and directing the synthetic efforts of chemists. Further on, using interpretability techniques a more detailed understanding of the molecular properties causing co-crystallization is sought after. The applicability of the current methodology is demonstrated with the discovery of two novel co-crystals, namely pyrene-6H-benzo[c]chromen-6-one (1) and pyrene-9,10-dicyanoanthracene (2).

Targeted classification of metal-organic frameworks in the Cambridge structural database (CSD).

Large-scale targeted exploration of metal-organic frameworks (MOFs) with characteristics such as specific surface chemistry or metal-cluster family has not been investigated so far. These definitions are particularly important because they can define the way MOFs interact with specific molecules (e.g. their hydrophilic/phobic character) or their physicochemical stability. We report here the development of algorithms to break down the overarching family of MOFs into a number of subgroups according to some of their key chemical and physical features. Available within the Cambridge Crystallographic Data Centre's (CCDC) software, we introduce new approaches to allow researchers to browse and efficiently look for targeted MOF families based on some of the most well-known secondary building units. We then classify them in terms of their crystalline properties: metal-cluster, network and pore dimensionality, surface chemistry (i.e. functional groups) and chirality. This dynamic database and family of algorithms allow experimentalists and computational users to benefit from the developed criteria to look for specific classes of MOFs but also enable users - and encourage them - to develop additional MOF queries based on desired chemistries. These tools are backed-up by an interactive web-based data explorer containing all the data obtained. We also demonstrate the usefulness of these tools with a high-throughput screening for hydrogen storage at room temperature. This toolbox, integrated in the CCDC software, will guide future exploration of MOFs and similar materials, as well as their design and development for an ever-increasing range of potential applications.

A Million Crystal Structures: The Whole Is Greater than the Sum of Its Parts.

The founding in 1965 of what is now called the Cambridge Structural Database (CSD) has reaped dividends in numerous and diverse areas of chemical research. Each of the million or so crystal structures in the database was solved for its own particular reason, but collected together, the structures can be reused to address a multitude of new problems. In this Review, which is focused mainly on the last 10 years, we chronicle the contribution of the CSD to research into molecular geometries, molecular interactions, and molecular assemblies and demonstrate its value in the design of biologically active molecules and the solid forms in which they are delivered. Its potential in other commercially relevant areas is described, including gas storage and delivery, thin films, and (opto)electronics. The CSD also aids the solution of new crystal structures. Because no scientific instrument is without shortcomings, the limitations of CSD research are assessed. We emphasize the importance of maintaining database quality: notwithstanding the arrival of big data and machine learning, it remains perilous to ignore the principle of garbage in, garbage out. Finally, we explain why the CSD must evolve with the world around it to ensure it remains fit for purpose in the years ahead.

Automated oxidation-state assignment for metal sites in coordination complexes in the Cambridge Structural Database.

The Cambridge Structural Database (CSD) currently contains over 400 000 transition-metal-containing entries, however many entries still lack curated oxidation-state assignments. Surveying and editing the remaining entries would be far too resource- and time-intensive to be carried out manually. Here, a highly reliable automated workflow for oxidation-state assignment in transition-metal coordination complexes via CSD Python API (application programming interface) scripts is presented. The strengths and limitations of the bond-valence sum (BVS) method are discussed and the use of complementary methods for improved assignment confidence is explored. In total, four complementary techniques have been implemented in this study. The resulting workflow overcomes the limitations of the BVS approach, widening the applicability of an automated procedure to more CSD entries. Assignments are successful for 99% of the cases where a high consensus between different methodologies is observed. Out of a total number of 54 999 unique metal atoms in a test dataset, the procedure yielded the correct oxidation state in 47 072 (86%) of cases.

Capturing neon - the first experimental structure of neon trapped within a metal-organic environment.

Despite being the fifth most abundant element in the atmosphere, neon has never been observed in an organic or metal-organic environment. This study shows the adsorption of this highly unreactive element within such an environment and reveals the first crystallographic observation of an interaction between neon and a transition metal.

Use of the PIXEL method to investigate gas adsorption in metal-organic frameworks.

PIXEL has been used to perform calculations of adsorbate-adsorbent interaction energies between a range of metal-organic frameworks (MOFs) and simple guest molecules. Interactions have been calculated for adsorption between MOF-5 and Ar, H2, and N2; Zn2(BDC)2(TED) (BDC = 1,4-benzenedicarboxylic acid, TED = triethylenediamine) and H2; and HKUST-1 and CO2. The locations of the adsorption sites and the calculated energies, which show differences in the Coulombic or dispersion characteristic of the interaction, compare favourably to experimental data and literature energy values calculated using density functional theory.

Hydrogen-bond coordination in organic crystal structures: statistics, predictions and applications.

Statistical models to predict the number of hydrogen bonds that might be formed by any donor or acceptor atom in a crystal structure have been derived using organic structures in the Cambridge Structural Database. This hydrogen-bond coordination behaviour has been uniquely defined for more than 70 unique atom types, and has led to the development of a methodology to construct hypothetical hydrogen-bond arrangements. Comparing the constructed hydrogen-bond arrangements with known crystal structures shows promise in the assessment of structural stability, and some initial examples of industrially relevant polymorphs, co-crystals and hydrates are described.

Hydrogen-bond landscapes, geometry and energetics of squaric acid and its mono- and dianions: a Cambridge Structural Database, IsoStar and computational study.

As part of a programme of work to extend central-group coverage in the Cambridge Crystallographic Data Centre's (CCDC) IsoStar knowledge base of intermolecular interactions, we have studied the hydrogen-bonding abilities of squaric acid (H2SQ) and its mono- and dianions (HSQ(-) and SQ(2-)) using the Cambridge Structural Database (CSD) along with dispersion-corrected density functional theory (DFT-D) calculations for a range of hydrogen-bonded dimers. The -OH and -C=O groups of H2SQ, HSQ(-) and SQ(2-) are potent donors and acceptors, as indicated by their hydrogen-bond geometries in available crystal structures in the CSD, and by the attractive energies calculated for their dimers with acetone and methanol, which were used as model acceptors and donors. The two anions have sufficient examples in the CSD for their addition as new central groups in IsoStar. It is also shown that charge- and resonance-assisted hydrogen bonds involving H2SQ and HSQ(-) are similar in strength to those made by carboxylate COO(-) acceptors, while hydrogen bonds made by the dianion SQ(2-) are somewhat stronger. The study reinforces the value of squaric acid and its anions as cocrystal formers and their actual and potential importance as isosteric replacements for carboxylic acid and carboxylate functions.

Role of chloroform and dichloromethane solvent molecules in crystal packing: an interaction propensity study.

Using the Cambridge Structural Database (CSD), it is shown that the acidic C-H donors of chloroform and dichloromethane, respectively, form hydrogen bonds with N, O, S, halides or carbon-bound halogens in 82% and 77% of structures in which such interactions can occur. This hydrogen-bond potency is retained to a significant degree even in the presence of the more conventional O-H and N-H donors. The hydrogen-bond propensities exhibited by the C-H protons in CHCl3 and CH2Cl2 are similar to those of the acetylenic C-C≡C-H proton. However, involvement of the Cl atoms of CHCl3 and CH2Cl2 in non-bonded interactions is rather limited: the propensities for formation of (O or N)-H...Cl bonds are only 6% in both cases, while the propensities for the formation of halogen-halogen bonds is generally < 15%, with only Cl...Br interactions having slightly higher values. While C(phenyl)-H...Cl interactions are commonly observed, they are of low propensity and have distances at the upper end of the van der Waals limit. We conclude that the acidic C-H protons in chloroform and dichloromethane solvent molecules play a clear role in the involvement of these molecules in molecular aggregation in crystal structures, and this is exemplified by hydrogen-bond predictions made using the statistical propensity tool which is now part of the CSD system.

The versatile role of the ethynyl group in crystal packing: an interaction propensity study.

It is well documented that the ethynyl group can act as a hydrogen-bond donor via its acidic C-H, and as a hydrogen-bond acceptor via the triple-bond π-density. Using the Cambridge Structural Database (CSD), it is shown that C-C≡C-H forms hydrogen bonds to N, O, S or halogens in 74% of structures in which these bonds can form. Additionally, the ethynyl group forms C-H···π interactions with itself or with phenyl groups in 23% of structures and accepts hydrogen bonds from O-H, N-H or C(aromatic)-H in 47% of structures where such bonds are possible. Overall, C-C≡C-H acts as a donor or acceptor in 87% of structures in which it occurs. These propensities for hydrogen-bond formation have been determined using quite tight geometrical constraints, and many more ethynyl groups form interactions with only slight relaxations of these constraints. We conclude that the ethynyl group makes crucial contributions to molecular aggregation in crystal structures, and this is exemplified by hydrogen-bond predictions for specific structures made using the statistical propensity tool now available in CSD system software.

The hydrogen bond environments of 1H-tetrazole and tetrazolate rings: the structural basis for tetrazole-carboxylic acid bioisosterism.

Bioisosterism involving replacement of a carboxylic acid substituent by 1H-tetrazole, yielding deprotonated carboxylate and tetrazolate under physiological conditions, is a well-known synthetic strategy in medicinal chemistry. To improve our overall understanding of bioisosterism, we have used this example to study the geometrical and energetic aspects of the functional group replacement. Specifically, we use crystal structure informatics and high-level ab initio calculations to study the hydrogen bond (H-bond) energy landscapes of the protonated and deprotonated bioisosteric pairs. Each pair exhibits very similar H-bond environments in crystal structures retrieved from the CSD, and the attractive energies of these H-bonds are also very similar. However, by comparison with -COOH and -COO(-), the H-bond environments around 1H-tetrazole and tetrazolate substituents extend further, by about 1.2 Å, from the core of the connected molecule. Analysis of pairs of PDB structures containing ligands which differ only in having a tetrazole or a carboxyl substituent and which are bound to the same protein indicates that the protein binding site must flex sufficiently to form strong H-bonds to either substituent. A survey of DrugBank shows a rather small number of tetrazole-containing drugs in the 'approved' and 'experimental' drug sections of that database.