Structure of the regulatory hyaluronan binding domain in the inflammatory leukocyte homing receptor CD44

Adhesive interactions involving CD44, the cell surface receptor for hyaluronan, underlie fundamental processes such as inflammatory leukocyte homing and tumor metastasis. Regulation of such events is critical and appears to be effected by changes in CD44 N-glycosylation that switch the receptor "on" or "off" under appropriate circumstances. How altered glycosylation influences binding of hyaluronan to the lectin-like Link module in CD44 is unclear, although evidence suggests additional flanking sequences peculiar to CD44 may be involved. Here we show using X-ray crystallography and NMR spectroscopy that these sequences form a lobular extension to the Link module, creating an enlarged HA binding domain and a formerly unidentified protein fold. Moreover, the disposition of key N-glycosylation sites reveals how specific sugar chains could alter both the affinity and avidity of CD44 HA binding. Our results provide the necessary structural framework for understanding the diverse functions of CD44 and developing novel therapeutic strategies

Relativistic many-body calculations of electric-dipole matrix elements, lifetimes and polarizabilities in rubidium

Electric-dipole matrix elements for ns-n'p, nd-n'p, and 6d-4f transitions in Rb are calculated using a relativistic all-order method. A third-order calculation is also carried out for these matrix elements to evaluate the importance of the high-order many-body perturbation theory contributions. The all-order matrix elements are used to evaluate lifetimes of ns and np levels with n=6, 7, 8 and nd levels with n=4, 5, 6 for comparison with experiment and to provide benchmark values for these lifetimes. The dynamic polarizabilities are calculated for ns states of rubidium. The resulting lifetime and polarizability values are compared with available theory and experiment.Comment: 8 pages, 2 figure

Pushing the limits of molecular crystal structure determination from powder diffraction data in high-throughput chemical environments

Crystal structure determination from powder diffraction data (SDPD) using the DASH software package is evaluated for data recorded using transmission capillary, transmission flat plate and reflection flat plate geometries on a selection of pharmaceutical compounds. We show that transmission capillary geometry remains the best option when crystal structure determination is the primary consideration and, as expected, reflection flat plate geometry is not recommended for SDPD due to preferred orientation effects. However, the quality of crystal structures obtained from transmission plate instruments can be excellent and the convenience factor for sample preparation, throughput and retrieval is higher than that of transmission capillary instruments. Indeed, it is possible to solve crystal structures within an hour of a polycrystalline sample arriving in the laboratory, which has clear implications for making small molecule crystal structures more routinely available to the practising laboratory medicinal chemist. With appropriate modifications to crystal structure determination software, it can be imagined that SDPD could become a rapid turn-around walk-up analytical service in high-throughput chemical environments

Accurate measurement of long range proton-carbon scalar coupling constants

The accuracy and ease-of-use of various experimental NMR methods for measuringnJCHvalues is assessed.</p

SDPD-SX: combining a single crystal X-ray diffraction setup with advanced powder data structure determination for use in early stage drug discovery

We report a method for routine crystal structure determination on very small (typically 0.1 mg or less) amounts of crystalline material using powder X-ray diffraction data from a laboratory-based single-crystal diffractometer. The solved structures span a wide range of molecular and crystallographic complexity

Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

DEM L241, a Supernova Remnant containing a High-Mass X-ray Binary

A Chandra observation of the Large Magellanic Cloud supernova remnant DEM L241 reveals an interior unresolved source which is probably an accretion-powered binary. The optical counterpart is an O5III(f) star making this a High-Mass X-ray Binary (HMXB) with orbital period likely to be of order tens of days. Emission from the remnant interior is thermal and spectral information is used to derive density and mass of the hot material. Elongation of the remnant is unusual and possible causes of this are discussed. The precursor star probably had mass > 25 solar masse

Polymorph identification for flexible molecules : linear regression analysis of experimental and calculated solution- and solid-state NMR data

The Δδ regression approach of Blade et al. [ J. Phys. Chem. A 2020, 124(43), 8959–8977] for accurately discriminating between solid forms using a combination of experimental solution- and solid-state NMR data with density functional theory (DFT) calculation is here extended to molecules with multiple conformational degrees of freedom, using furosemide polymorphs as an exemplar. As before, the differences in measured 1H and 13C chemical shifts between solution-state NMR and solid-state magic-angle spinning (MAS) NMR (Δδexperimental) are compared to those determined by gauge-including projector augmented wave (GIPAW) calculations (Δδcalculated) by regression analysis and a t-test, allowing the correct furosemide polymorph to be precisely identified. Monte Carlo random sampling is used to calculate solution-state NMR chemical shifts, reducing computation times by avoiding the need to systematically sample the multidimensional conformational landscape that furosemide occupies in solution. The solvent conditions should be chosen to match the molecule’s charge state between the solution and solid states. The Δδ regression approach indicates whether or not correlations between Δδexperimental and Δδcalculated are statistically significant; the approach is differently sensitive to the popular root mean squared error (RMSE) method, being shown to exhibit a much greater dynamic range. An alternative method for estimating solution-state NMR chemical shifts by approximating the measured solution-state dynamic 3D behavior with an ensemble of 54 furosemide crystal structures (polymorphs and cocrystals) from the Cambridge Structural Database (CSD) was also successful in this case, suggesting new avenues for this method that may overcome its current dependency on the prior determination of solution dynamic 3D structures