Journal of Applied Crystallography最新文献

For membrane proteins, ab initio modelling based on a single curve of small-angle X-ray scattering (SAXS) is precluded by the presence of detergent molecules bound to the hydrophobic region of the protein. MEMPROT was developed for the modelling of protein–detergent complexes based on the SAXS curve of the complex, and on an a priori representation of the detergent corona by an elliptical semi-torus surrounding the protein. In previous studies, MEMPROT has succeeded in modelling several membrane proteins solubilized in n-dodecyl-β-maltopyranoside (DDM). However, it has never been tested on proteins solubilized in other detergents. To understand whether the geometrical shape currently parametrized in MEMPROT could be applied to a broader catalogue of protein–detergent complexes, here, MEMPROT was used to model the detergent corona around the multi-hydrophobic substrate transporter from Bacillus halodurans solubilized in four different detergents, namely DDM, n-decyl-β-maltopyranoside (DM), 4-cyclohexyl-1-butyl-β-d-maltoside (Cymal4) and decyl-maltose-neopentyl-glycol (DMNG). The study indicates a significant variation in detergent shapes, depending on the type of detergent. The modelling results suggest that the elliptical semi-torus with a circular closure is an excellent approximation for long-tailed detergents (DDM and DM) but leads to a slightly poorer agreement with the data for DMNG and Cymal4, which have a shorter hydrophobic tail, smaller than the half-width of the protein hydrophobic region. Here, for the latter, it is hypothesized that a corona with a flatter closure would be a better shape descriptor.

A multi-technique analysis was used to investigate how the orientation of single-crystal Si wafer surfaces affects the size, shape and orientation of NiSi₂ nanocrystals grown within the wafers through the thermal diffusion of Ni atoms from a nickel-doped thin film deposited on the surface. Nickel-doped thin films were prepared on silicon wafers with three distinct crystallographic orientations, [001], [110] and [111]. Three sets of samples were then annealed at 500, 600 and 700°C for 2 h. Regardless of crystallographic orientation or annealing temperature, NiSi₂ nanoplates with a nearly hexagonal shape grew close to the external surface of the wafers, aligning their larger surfaces parallel to one of the planes of the Si{111} crystallographic form. The crystallographic orientation and annealing temperature in the 500–700°C range did not significantly affect the final values of the average diameter and thickness of the nanoplates. However, significant differences were noted in the number of nanoplates formed in Si wafers with different crystallographic orientations. The results indicate that these observed differences are correlated with the number of pre-existing defects in the wafers that influence the heterogeneous nucleation process. In addition, the average size and size dispersion were determined for pores at the surface of the Si wafers formed due to the etching process used for native oxide removal.

The workshop titled `X-ray-based technologies in emerging fuel cell research', organized by Vivian Stojanoff from Brookhaven National Laboratory (BNL) and Narayanasami Sukumar from Cornell University/Advanced Photon Source-Northeastern Collaborative Access Team, was a notable segment of the National Synchrotron Light Source II and Center for Functional Nanomaterials Users' Meeting held 13–17 May 2024. This one-day event, on 13 May 2024, at BNL in New York, aimed to bring together researchers, beamline scientists, management and developers to propel fuel cell technology forward using model systems inspired by natural photosynthesis and redox enzymes. This summary encapsulates the key discussions, advancements and future implications of the workshop.

Flow cells are ubiquitous in laboratories and automated instrumentation, and are crucial for ease of sample preparation, analyte addition and buffer exchange. The assumption that the fluids have exchanged completely in a flow cell is often critical to data interpretation. This article describes the buoyancy effects on the exchange of fluids with differing densities or viscosities in thin, circular flow cells. Depending on the flow direction, fluid exchange varies from highly efficient to drastically incomplete, even after a large excess of exchange volume. Numerical solutions to the Navier–Stokes and Cahn–Hilliard equations match well with experimental observations. This leads to quantitative predictions of the conditions where buoyancy forces in thin flow cells are significant. A novel method is introduced for exchanging fluid cells by accounting for and utilizing buoyancy effects that can be essential to obtain accurate results from measurements performed within closed-volume fluid environments.

The objective of crystal structure prediction (CSP) is to predict computationally the thermodynamically stable crystal structure of a compound from its stoichiometry or its molecular diagram. Crystal similarity indices measure the degree of similarity between two crystal structures and are essential in CSP because they are used to identify duplicates. Powder-based indices, which are based on comparing X-ray diffraction patterns, allow the use of experimental X-ray powder diffraction data to inform the CSP search. Powder-assisted CSP presents two unique difficulties: (i) the experimental and computational structures are not entirely comparable because the former is subject to thermal expansion from lattice vibrations, and (ii) experimental patterns present features (noise, background contribution, varying peak shapes etc.) that are not easily predictable computationally. This work presents a powder-based similarity index (GPWDF) based on a modification of the index introduced by de Gelder, Wehrens & Hageman [J. Comput. Chem. (2001), 22, 273–289] using cross-correlation functions that can be calculated analytically. Based on GPWDF, a variable-cell similarity index (VC-GPWDF) is also proposed that assigns a high similarity score to structures that differ only by a lattice deformation and which takes advantage of the analytical derivatives of GPWDF with respect to the lattice parameters. VC-GPWDF can be used to identify similarity between two computational structures generated using different methods, between a computational and an experimental structure, and between two experimental structures measured under different conditions (e.g. different temperature and pressure). VC-GPWDF can also be used to compare crystal structures with experimental patterns in combination with an automatic pre-processing step. The proposed similarity indices are simple, efficient and fully automatic. They do not require indexing of the experimental pattern or a guess of the space group, they account for deformations caused by varying experimental conditions, they give meaningful results even when the experimental pattern is of very poor quality, and their computational cost does not increase with the flexibility of the molecular motif.