Determining magnetic structures in GSAS-II using the Bilbao Crystallographic Server tool k-SUBGROUPSMAG.

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

The effect of the acceleration voltage on the quality of structure determination by 3D-electron diffraction.

Nowadays, 3D Electron Diffraction (3DED) is widely used for the structure determination of sub-micron-sized particles. In this work, we investigate the influence of the acceleration voltage on the quality of 3DED datasets acquired on BaTiO3 nanoparticles. Datasets were acquired using a wide range of beam energies, from common, high acceleration voltages (300 kV and 200 kV) to medium (120 kV and 80 kV) and low acceleration voltages (60 kV and 30 kV). It was observed that, in the integration process, Rint increases as the beam energy is reduced, which is mainly due to the increased dynamical scattering. Nevertheless, the structure was solved successfully in all cases. The structure refinement was comparable for all beam energies with small deficiencies such as negative atomic displacements for the heaviest atom in the structure, barium. Including extinction correction in the refinement noticeably improved the model for low acceleration voltages, probably due to higher beam absorption in these cases. Dynamical refinement, however, shows superior results for higher acceleration voltages, since the dynamical refinement calculations currently ignore inelastic scattering effects.

A solid solution to computational challenges presented by crystal structures exhibiting disorder.

Crystal structues exhibiting disorder still present a barrier for many computational methods. Dittrich et al. [(2024). IUCrJ, 11, 347-358] showcase a unified approach, tackling solid solutions, near symmetry and more.

DREAMweb: An online tool for graph-based modeling of NMR protein structure.

The value of accurate protein structural models closely conforming to the experimental data is indisputable. DREAMweb deploys an improved DREAM algorithm, DREAMv2, that incorporates a tighter bound in the constraint set of the underlying optimization approach. This reduces the artifacts while modeling the protein structure by solving the distance-geometry problem. DREAMv2 follows a bottom-up strategy of building smaller substructures for regions with a larger concentration of experimental bounds and consolidating them before modeling the rest of the protein structure. This improves secondary structure conformance in the final models consistent with experimental data. The proposed method efficiently models regions with sparse coverage of experimental data by reducing the possibility of artifacts compared to DREAM. To balance performance and accuracy, smaller substructures ( ∼ 200 $\sim 200$ atoms) are solved in this regime, allowing faster builds for the other parts under relaxed conditions. DREAMweb is accessible as an internet resource. The improvements in results are showcased through benchmarks on 10 structures. DREAMv2 can be used in tandem with any NMR-based protein structure determination workflow, including an iterative framework where the NMR assignment for the NOESY spectra is incomplete or ambiguous. DREAMweb is freely available for public use at http://pallab.cds.iisc.ac.in/DREAM/ and downloadable at https://github.com/niladriranjandas/DREAMv2.git.

The single-atom R1: a new optimization method to solve crystal structures.

A crystal structure with N atoms in its unit cell can be solved starting from a model with atoms 1 to j - 1 being located. To locate the next atom j, the method uses a modified definition of the traditional R1 factor where its dependencies on the locations of atoms j + 1 to N are removed. This modified R1 is called the single-atom R1 (sR1), because the locations of atoms 1 to j - 1 in sR1 are the known parameters, and only the location of atom j is unknown. Finding the correct position of atom j translates thus into the optimization of the sR1 function, with respect to its fractional coordinates, xj, yj, zj. Using experimental data, it has been verified that an sR1 has a hole near each missing atom. Further, it has been verified that an algorithm based on sR1, hereby called the sR1 method, can solve crystal structures (with up to 156 non-hydrogen atoms in the unit cell). The strategy to carry out this calculation has also been optimized. The main feature of the sR1 method is that, starting from a single arbitrarily positioned atom, the structure is gradually revealed. With the user's help to delete poorly determined parts of the structure, the sR1 method can build the model to a high final quality. Thus, sR1 is a viable and useful tool for solving crystal structures.

Crystal structure solution and high-temperature thermal expansion in NaZr2(PO4)3-type materials.

The NaZr2P3O12 family of materials have shown low and tailorable thermal expansion properties. In this study, SrZr4P6O24 (SrO·4ZrO2·3P2O5), CaZr4P6O24 (CaO·4ZrO2·3P2O5), MgZr4P6O24 (MgO·4ZrO2·3P2O5), NaTi2P3O12 [½(Na2O·4TiO2·3P2O5)], NaZr2P3O12 [½(Na2O·4ZrO2·3P2O5)], and related solid solutions were synthesized using the organic-inorganic steric entrapment method. The samples were characterized by in-situ high-temperature X-ray diffraction from 25 to 1500°C at the Advanced Photon Source and National Synchrotron Light Source II. The average linear thermal expansion of SrZr4P6O24 and CaZr4P6O24 was between -1 × 10-6 per °C and 6 × 10-6 per °C from 25 to 1500°C. The crystal structures of the high-temperature polymorphs of CaZr4P6O24 and SrZr4P6O24 with R3c symmetry were solved by Fourier difference mapping and Rietveld refinement. This polymorph is present above ∼1250°C. This work measured thermal expansion coefficients to 1500°C for all samples and investigated the differences in thermal expansion mechanisms between polymorphs and between compositions.

Structure solution and refinement of beam-sensitive nano-crystals.

Radiation sensitive materials are among the most difficult materials to study, even more so if they exist only as nanometer-sized particles, where their size is either intentional because of enhanced properties at the nano-scale or it is unintentional because it is impossible to obtain bigger particles of the same structure. In both cases characterization methods need to be optimized to get the most information out of these particles before the radiation damages them to a point where their structure is altered. When the particles are crystallized, both characteristics, the small size and the beam sensitivity, call for electron diffraction as a privileged investigation tool. The strong interaction of electrons (as compared to X-rays) with matter allows single crystal diffraction experiments on nanometer-sized crystals and for the same amount of beam damage, electron diffraction yields more information than X-rays. These inherent advantages of electron diffraction are optimized in the recently developed low-dose electron diffraction tomography (LD-EDT) by minimizing the necessary dose for a complete data collection. In this contribution we show that in some cases even doses as low as 2 e-/Ų can induce damage in crystal structures that inhibit a correct structure refinement. However, by LD-EDT we can obtain data using extremely low doses that don't alter the structure which make it then possible not only to solve crystal structures but also to refine them using dynamical diffraction theory. Here a synthetic oxide containing volatile Na and a metal-organic framework are given as examples. A dynamical refinement of the structures is possible with data sets requiring a dose of less than 0.15 e-/Ų.

Praziquantel meets Niclosamide: A dual-drug Antiparasitic Cocrystal.

In this paper we report a successful example of combining drugs through cocrystallization. Specifically, the novel solid is formed by two anthelminthic drugs, namely praziquantel (PZQ) and niclosamide (NCM) in a 1:3 molar ratio, and it can be obtained through a sustainable one-step mechanochemical process in the presence of micromolar amounts of methanol. The novel solid phase crystallizes in the monoclinic space group of P21/c, showing one PZQ and three NCM molecules linked through homo- and heteromolecular hydrogen bonds in the asymmetric unit, as also attested by SSNMR and FT-IR results. A plate-like habitus is evident from scanning electron microscopy analysis with a melting point of 202.89 °C, which is intermediate to those of the parent compounds. The supramolecular interactions confer favorable properties to the cocrystal, preventing NCM transformation into the insoluble monohydrate both in the solid state and in aqueous solution. Remarkably, the PZQ - NCM cocrystal exhibits higher anthelmintic activity against in vitro S. mansoni models than corresponding physical mixture of the APIs. Finally, due to in vitro promising results, in vivo preliminary tests on mice were also performed through the administration of minicapsules size M.

The crystal structure of the killer fibre erionite from Tuzköy (Cappadocia, Turkey).

Erionite is a non-asbestos fibrous zeolite classified by the International Agency for Research on Cancer (IARC) as a Group 1 carcinogen and is considered today similar to or even more carcinogenic than the six regulated asbestos minerals. Exposure to fibrous erionite has been unequivocally linked to cases of malignant mesothelioma (MM) and this killer fibre is assumed to be directly responsible for more than 50% of all deaths in the population of the villages of Karain and Tuzköy in central Anatolia (Turkey). Erionite usually occurs in bundles of thin fibres and very rarely as single acicular or needle-like fibres. For this reason, a crystal structure of this fibre has not been attempted to date although an accurate characterization of its crystal structure is of paramount importance for our understanding of the toxicity and carcinogenicity. In this work, we report on a combined approach of microscopic (SEM, TEM, electron diffraction), spectroscopic (micro-Raman) and chemical techniques with synchrotron nano-single-crystal diffraction that allowed us to obtain the first reliable ab initio crystal structure of this killer zeolite. The refined structure showed regular T-O distances (in the range 1.61-1.65 Å) and extra-framework content in line with the chemical formula (K2.63Ca1.57Mg0.76Na0.13Ba0.01)[Si28.62Al7.35]O72·28.3H2O. The synchrotron nano-diffraction data combined with three-dimensional electron diffraction (3DED) allowed us to unequivocally rule out the presence of offretite. These results are of paramount importance for understanding the mechanisms by which erionite induces toxic damage and for confirming the physical similarities with asbestos fibres.

Buccaneer model building with neural network fragment selection.

Tracing the backbone is a critical step in protein model building, as incorrect tracing leads to poor protein models. Here, a neural network trained to identify unfavourable fragments and remove them from the model-building process in order to improve backbone tracing is presented. Moreover, a decision tree was trained to select an optimal threshold to eliminate unfavourable fragments. The neural network was tested on experimental phasing data sets from the Joint Center for Structural Genomics (JCSG), recently deposited experimental phasing data sets (from 2015 to 2021) and molecular-replacement data sets. The experimental results show that using the neural network in the Buccaneer protein-model-building software can produce significantly more complete protein models than those built using Buccaneer alone. In particular, Buccaneer with the neural network built protein models with a completeness that was at least 5% higher for 25% and 50% of the original and truncated resolution JCSG experimental phasing data sets, respectively, for 28% of the recently collected experimental phasing data sets and for 43% of the molecular-replacement data sets.

Zwitterionic or Not? Fast and Reliable Structure Determination by Combining Crystal Structure Prediction and Solid-State NMR.

When it comes to crystal structure determination, computational approaches such as Crystal Structure Prediction (CSP) have gained more and more attention since they offer some insight on how atoms and molecules are packed in the solid state, starting from only very basic information without diffraction data. Furthermore, it is well known that the coupling of CSP with solid-state NMR (SSNMR) greatly enhances the performance and the accuracy of the predictive method, leading to the so-called CSP-NMR crystallography (CSP-NMRX). In this paper, we present the successful application of CSP-NMRX to determine the crystal structure of three structural isomers of pyridine dicarboxylic acid, namely quinolinic, dipicolinic and dinicotinic acids, which can be in a zwitterionic form, or not, in the solid state. In a first step, mono- and bidimensional SSNMR spectra, i.e., 1H Magic-Angle Spinning (MAS), 13C and 15N Cross Polarisation Magic-Angle Spinning (CPMAS), 1H Double Quantum (DQ) MAS, 1H-13C HETeronuclear CORrelation (HETCOR), were used to determine the correct molecular structure (i.e., zwitterionic or not) and the local molecular arrangement; at the end, the RMSEs between experimental and computed 1H and 13C chemical shifts allowed the selection of the correct predicted structure for each system. Interestingly, while quinolinic and dipicolinic acids are zwitterionic and non-zwitterionic, respectively, in the solid state, dinicotinic acid exhibits in its crystal structure a "zwitterionic-non-zwitterionic continuum state" in which the proton is shared between the carboxylic moiety and the pyridinic nitrogen. Very refined SSNMR experiments were carried out, i.e., 14N-1H Phase-Modulated (PM) pulse and Rotational-Echo Saturation-Pulse Double-Resonance (RESPDOR), to provide an accurate N-H distance value confirming the hybrid nature of the molecule. The CSP-NMRX method showed a remarkable match between the selected structures and the experimental ones. The correct molecular input provided by SSNMR reduced the number of CSP calculations to be performed, leading to different predicted structures, while RMSEs provided an independent parameter with respect to the computed energy for the selection of the best candidate.

Improved NMR-data-compliant protein structure modeling captures context-dependent variations and expands the scope of functional inference.

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state-of-the-art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph-based modeling approach, where we first build substructures from NMR-derived distance-geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance-geometry constraints. One-shot structure building is rarely undertaken for large and sparse data systems, but our data-driven bottom-up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state-of-art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein-folds covering 38-282 length structures shows minimal experimental-constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state-of-art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure-function. Our work is thus useful in building enhanced NMR-evidence-based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference.

Extending the novel |ρ|-based phasing algorithm to the solution of anomalous scattering substructures from SAD data of protein crystals.

Owing to the importance of the single-wavelength anomalous diffraction (SAD) technique, the recently developed |ρ|-based phasing algorithm (SM,|ρ|) incorporating the inner-pixel preservation (ipp) procedure [Rius & Torrelles (2021). Acta Cryst A77, 339-347] has been adapted to the determination of anomalous scattering substructures and its applicability tested on a series of 12 representative experimental data sets, mostly retrieved from the Protein Data Bank. To give an idea of the suitability of the data sets, the main indicators measuring their quality are also given. The dominant anomalous scatterers are either SeMet or S atoms, or metals/clusters incorporated by soaking. The resulting SAD-adapted algorithm solves the substructures of the test protein crystals quite efficiently.

ModelCraft: an advanced automated model-building pipeline using Buccaneer.

Interactive model building can be a difficult and time-consuming step in the structure-solution process. Automated model-building programs such as Buccaneer often make it quicker and easier by completing most of the model in advance. However, they may fail to do so with low-resolution data or a poor initial model or map. The Buccaneer pipeline is a relatively simple program that iterates Buccaneer with REFMAC to refine the model and update the map. A new pipeline called ModelCraft has been developed that expands on this to include shift-field refinement, machine-learned pruning of incorrect residues, classical density modification, addition of water and dummy atoms, building of nucleic acids and final rebuilding of side chains. Testing was performed on 1180 structures solved by experimental phasing, 1338 structures solved by molecular replacement using homologues and 2030 structures solved by molecular replacement using predicted AlphaFold models. Compared with the previous Buccaneer pipeline, ModelCraft increased the mean completeness of the protein models in the experimental phasing cases from 91% to 95%, the molecular-replacement cases from 50% to 78% and the AlphaFold cases from 82% to 91%.

Solving molecular compounds from powder diffraction data: are results always reliable?

Commentary is given on a paper [Schlesinger et al. (2022). IUCrJ, 9, 406-424.] reporting on ambiguous structure determination from powder data using four different structural models of 4,11-difluoroquinacridone with similar X-ray powder patterns.

3D electron diffraction for structure determination of small-molecule nanocrystals: A possible breakthrough for the pharmaceutical industry.

Nanomedicine is among the most fascinating areas of research. Most of the newly discovered pharmaceutical polymorphs, as well as many new synthesized or isolated natural products, appear only in form of nanocrystals. The development of techniques that allow investigating the atomic structure of nanocrystalline materials is therefore one of the most important frontiers of crystallography. Some unique features of electrons, like their non-neutral charge and their strong interaction with matter, make this radiation suitable for imaging and detecting individual atoms, molecules, or nanoscale objects down to sub-angstrom resolution. In the recent years the development of three-dimensional (3D) electron diffraction (3D ED) has shown that electron diffraction can be successfully used to solve the crystal structure of nanocrystals and most of its limiting factors like dynamical scattering or limited completeness can be easily overcome. This article is a review of the state of the art of this method with a specific focus on how it can be applied to beam sensitive samples like small-molecule organic nanocrystals. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Predicting the performance of automated crystallographic model-building pipelines.

Proteins are macromolecules that perform essential biological functions which depend on their three-dimensional structure. Determining this structure involves complex laboratory and computational work. For the computational work, multiple software pipelines have been developed to build models of the protein structure from crystallographic data. Each of these pipelines performs differently depending on the characteristics of the electron-density map received as input. Identifying the best pipeline to use for a protein structure is difficult, as the pipeline performance differs significantly from one protein structure to another. As such, researchers often select pipelines that do not produce the best possible protein models from the available data. Here, a software tool is introduced which predicts key quality measures of the protein structures that a range of pipelines would generate if supplied with a given crystallographic data set. These measures are crystallographic quality-of-fit indicators based on included and withheld observations, and structure completeness. Extensive experiments carried out using over 2500 data sets show that the tool yields accurate predictions for both experimental phasing data sets (at resolutions between 1.2 and 4.0 Å) and molecular-replacement data sets (at resolutions between 1.0 and 3.5 Å). The tool can therefore provide a recommendation to the user concerning the pipelines that should be run in order to proceed most efficiently to a depositable model.

Crystal Engineering of Supramolecular 1,4-Benzene Bisamides by Side-Chain Modification - Towards Tuneable Anisotropic Morphologies and Surfaces.

Benzene bisamides are promising building blocks for supramolecular nano-objects. Their functionality depends on morphology and surface properties. However, a direct link between surface properties and molecular structure itself is missing for this material class. Here, we investigate this interplay for two series of 1,4-benzene bisamides with symmetric and asymmetric peripheral substitution. We elucidated the crystal structures, determined the nano-object morphologies and derived the wetting behaviour of the preferentially exposed surfaces. The crystal structures were solved by combining single-crystal and powder X-ray diffraction, solid-state NMR spectroscopy and computational modelling. Bulky side groups, here t-butyl groups, serve as a structure-directing motif into a packing pattern, which favours the formation of thin platelets. The use of slim peripheral groups on both sides, in our case linear perfluorinated, alkyl chains, self-assemble the benzene bisamides into a second packing pattern which leads to ribbon-like nano-objects. For both packing types, the preferentially exposed surfaces consist of the ends of the peripheral groups. Asymmetric substitution with bulky and slim groups leads to an ordered alternating arrangement of the groups exposed to the surface. This allows the hydrophobicity of the surfaces to be gradually altered. We thus identified two leitmotifs for molecular packings of benzene bisamides providing the missing link between the molecular structure, the anisotropic morphologies and adjustable surface properties of the supramolecular nano-objects.

A new density-modification procedure extending the application of the recent |ρ|-based phasing algorithm to larger crystal structures.

The incorporation of the new peakness-enhancing fast Fourier transform compatible ipp procedure (ipp = inner-pixel preservation) into the recently published SM algorithm based on |ρ| [Rius (2020). Acta Cryst A76, 489-493] improves its phasing efficiency for larger crystal structures with atomic resolution data. Its effectiveness is clearly demonstrated via a collection of test crystal structures (taken from the Protein Data Bank) either starting from random phase values or by using the randomly shifted modulus function (a Patterson-type synthesis) as initial ρ estimate. It has been found that in the presence of medium scatterers (e.g. S or Cl atoms) crystal structures with 1500 × c atoms in the unit cell (c = number of centerings) can be routinely solved. In the presence of strong scatterers like Fe, Cu or Zn atoms this number increases to around 5000 × c atoms. The implementation of this strengthened SM algorithm is simple, since it only includes a few easy-to-adjust parameters.

HPM-16, a Stable Interrupted Zeolite with a Multidimensional Mixed Medium-Large Pore System Containing Supercages.

HPM-16 is a highly porous germanosilicate zeolite with an interrupted framework that contains a three-dimensional system of 12+10×10(12)×12+10-membered ring (MR) pores. The 10(12) MR pore in the b direction is a 10 MR pore with long 12 MR stretches forming 30 Šlong tubular supercages. Along one direction the 10 MR pores are fused, meaning that the separation between adjacent pores consists of a single tetrahedron that is, additionally, connected to only three additional tetrahedra (a Q3 ). These fused pores are thus decorated by T-OH groups along the whole diffusion path, creating a hydrophilic region embedded in an otherwise essentially hydrophobic environment. The structure is built from highly porous 12×12×12 MR uninterrupted layers that are connected to each other through Q3 producing a second system of 10×10×10 MR pores. This zeolite can be extensively degermanated yielding a material with high thermal stability, despite its interrupted nature.