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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Nonconventional NMR Spin-Coupling Constants in Oligosaccharide Conformational Modeling: Structural Dependencies Determined from Density Functional Theory Calculations

Nonconventional NMR spin-coupling constants were investigated to determine their potential as conformational constraints in MA’AT modeling of the O-glycosidic linkages of oligosaccharides. Four ( 1 J C1',H1' , 1 J C1',C2' , 2 J C1',H2' , and 2 J C2',H1' ) and eight ( 1 J C4,H4 , 1 J C3,C4 , 1 J C4,C5 , 2 J C3,H4 , 2 J C4,H3 , 2 J C5,H4 , 2 J C4,H5 , and 2 J C3,C5 ) spin-couplings in methyl β-d-galactopyranosyl-(1→4)-β-d-glucopyranoside (methyl β-lactoside) were calculated using density functional theory (DFT) to determine their dependencies on O-glycosidic linkage C–O torsion angles, $\phi$ and ψ, respectively. Long-range 4 J H1',H4 was also examined as a potential conformational constraint of either $\phi$ or ψ. Secondary effects of exocyclic (hydroxyl) C–O bond rotation within or proximal to these coupling pathways were investigated. Based on the findings of methyl β-lactoside, analogous J-couplings were studied in five additional two-bond O-glycosidic linkages [βGlcNAc-(1→4)-βMan, 2-deoxy-βGlc-(1→4)-βGlc, αMan-(1→3)-βMan, αMan-(1→2)-αMan, and βGlcNAc(1→2)-αMan] to determine whether the coupling behaviors observed in methyl β-lactoside were more broadly observed. Of the 13 nonconventional J-couplings studied, 7 exhibit properties that may be useful in future MA’AT modeling of O-glycosidic linkages, none of which involve coupling pathways that include the linkage C–O bonds. The findings also provide new insights into the general effects of exocyclic C–O bond conformation on the magnitude of experimental spin-couplings in saccharides and other hydroxyl-containing molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Precursor-Dependent Routing of Aromatic Amino Acids Determines Lignin Structure in Grasses by Sensitivity-Enhanced Solid-State NMR

Lignin biosynthesis in grasses exhibits unique metabolic flexibility, yet the precursor-specific routing of carbon into lignin polymers remains poorly resolved in planta. Here, we combine 13 C-isotope labeling with solid-state NMR under sensitivity-enhancement by dynamic nuclear polarization (DNP), to directly track phenylalanine- and tyrosine-derived carbon incorporation into the lignin polymer in Brachypodium distachyon. Precursor-specific 13 C labeling reveals that phenylalanine is the dominant contributor to canonical guaiacyl and syringyl lignins, whereas tyrosine preferentially enriches hydroxyphenyl lignin and hydroxycinnamates, including ferulates characteristic of grass cell walls. Two-dimensional 13 C− 13 C correlation NMR resolves distinct lignin moieties arising from each precursor. Disruption of pcoumarate 3-hydroxylase (C3H) selectively impairs phenylalanine-derived lignification, while tyrosine-derived lignin remains comparatively unchanged, maintaining polymer assembly through alternative metabolic routes. These findings show precursordependent control of lignin composition and reveal tyrosine-mediated lignification as a compensatory pathway in grasses. This work also establishes precursor-resolved solid-state NMR and DNP as a powerful framework for dissecting lignin biosynthesis and metabolic plasticity in plant cell walls.

Biopolymers↗

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.

36 MATERIALS SCIENCE↗

RCSB Protein Data Bank: visualizing groups of experimentally determined PDB structures alongside computed structure models of proteins

Recent advances in Artificial Intelligence and Machine Learning (e.g., AlphaFold, RosettaFold, and ESMFold) enable prediction of three-dimensional (3D) protein structures from amino acid sequences alone at accuracies comparable to lower-resolution experimental methods. These tools have been employed to predict structures across entire proteomes and the results of large-scale metagenomic sequence studies, yielding an exponential increase in available biomolecular 3D structural information. Given the enormous volume of this newly computed biostructure data, there is an urgent need for robust tools to manage, search, cluster, and visualize large collections of structures. Equally important is the capability to efficiently summarize and visualize metadata, biological/biochemical annotations, and structural features, particularly when working with vast numbers of protein structures of both experimental origin from the Protein Data Bank (PDB) and computationally-predicted models. Moreover, researchers require advanced visualization techniques that support interactive exploration of multiple sequences and structural alignments. This paper introduces a suite of tools provided on the RCSB PDB research-focused web portal RCSB. org, tailor-made for efficient management, search, organization, and visualization of this burgeoning corpus of 3D macromolecular structure data.

3D visualization↗

Determining the Structure of Rotating Massive Stellar Cores with Gravitational Waves

The gravitational wave (GW) signal resulting from stellar core collapse encodes a wealth of information about the physical parameters of the progenitor star and the resulting core-collapse supernova (CCSN). We present a novel approach to constrain CCSN progenitor properties at collapse using two of the most detectable parts of the GW signal: the core-bounce signal and evolution of the dominant frequency mode from the protoneutron star. We focus on the period after core bounce but before explosion and investigate the predictive power of GWs from rotating CCSNe to constrain properties of the progenitor star. We analyze 34 2D and four 3D neutrino-radiation-hydrodynamic simulations of stellar core collapse in progenitors of varied initial mass and rotation rate. Extending previous work, we verify the compactness of the progenitor at collapse to correlate with the early ramp-up slope, and in rotating cases, also with the core angular momentum. Combining this information with the bounce signal, we present a new analysis method to constrain the pre-collapse core compactness of the progenitor. Because these GW features occur less than a second after core bounce, this analysis could allow astronomers to predict electromagnetic properties of a resulting CCSN even before shock breakout.

Astronomy & Astrophysics↗

Analysis of OSO data to determine the structure and energy balance of the solar chromosphere

A detailed reexamination of the temperature-density structure of the photosphere and low chromosphere shows that the middle and upper chromosphere, which directly emits most of the OSO spectrum, is sensitive to conditions in this underlying region of the atmosphere. A model of this region is based on a unified compilation of all recently published broadband flux and central intensity observations of the solar spectrum from 500 microns in the far infrared to 1220 A in the far ultraviolet. This extensive compilation includes the OSO 4 and 6 observations in the wavelength range 1400 to 1220 A. A model is presented of the quiet solar atmosphere in the height range between the temperature minimum and the upper part of the chromosphere-corona transition region. This model is based on statistical equilibrium calculations of H, He 1, He 2, Si 1, C 1, and other ions.

Avrett, E. H.↗

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗

Multinuclear Solid-State NMR and NMR Crystallography of Solid Forms of Creatine and Creatinine

Creatine is a performance-enhancing supplement with two widely available commercial solid forms, namely, creatine monohydrate (creatine·H 2 O) and creatine HCl, the latter of which does not have a reported crystal structure. Moreover, commercial formulations of creatine may contain creatinine, an undesired impurity phase resulting from the self-cyclization of creatine during manufacturing. Therefore, reliable methods for characterizing the different solid forms of creatine and detecting the presence of creatinine are essential. Herein, we address these challenges using 13 C, 15 N, and 35 Cl solid-state NMR (SSNMR) spectroscopy to obtain distinct spectral fingerprints for creatine·H 2 O and creatine HCl, along with creatinine and creatinine HCl. The acquisition of these SSNMR spectra offers a robust approach for both the rapid characterization of each solid form and the detection of the impurity phases. Additionally, quadrupolar NMR crystallography-guided crystal structure prediction (QNMRX-CSP) was applied for the de novo crystal structure determination of creatine HCl, which was validated by the subsequently determined single-crystal X-ray diffraction (SCXRD) structure. Finally, to investigate the relationship between NMR parameters and structural features, 13 C and 15 N chemical shifts and 35 Cl electric field gradient (EFG) tensors were computed from geometry-optimized structures of the four solid forms by using dispersion-corrected DFT-D2* methods. Finally, this integrative approach offers a powerful framework for advancing the structural understanding and quality control of creatine-based supplements and next-generation formulations, as well as a wide range of other solid pharmaceuticals and nutraceuticals.

NMR↗

Molecular mechanism of biased signaling at the kappa opioid receptor

The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.

59 BASIC BIOLOGICAL SCIENCES↗

X-ray crystal structure of a designed rigidified imaging scaffold in the ligand-free conformation

Imaging scaffolds composed of designed protein cages fused to designed ankyrin repeat proteins (DARPins) have enabled the structure determination of small proteins by cryogenic electron microscopy (cryo-EM). One particularly well characterized scaffold type is a symmetric tetrahedral assembly composed of 24 subunits, 12 A and 12 B, which has three cargo-binding DARPins positioned on each vertex. Here, the X-ray crystal structure of a representative tetrahedral scaffold in the apo state is reported at 3.8 Å resolution. The X-ray crystal structure complements recent cryo-EM findings on a closely related scaffold, while also suggesting potential utility for crystallographic investigations. As observed in this crystal structure, one of the three DARPins, which serve as modular adaptors for binding diverse `cargo' proteins, present on each of the vertices is oriented towards a large solvent channel. The crystal lattice is unusually porous, suggesting that it may be possible to soak crystals of the scaffold with small (≤30 kDa) protein cargo ligands and subsequently determine cage–cargo structures via X-ray crystallography. The results suggest the possibility that cryo-EM scaffolds may be repurposed for structure determination by X-ray crystallography, thus extending the utility of electron-microscopy scaffold designs for alternative structural biology applications.

59 BASIC BIOLOGICAL SCIENCES↗

In crystallo observation of three metal ion promoted DNA polymerase misincorporation

Error-free replication of DNA is essential for life. Despite the proofreading capability of several polymerases, intrinsic polymerase fidelity is in general much higher than what base-pairing energies can provide. Although researchers have investigated this long-standing question with kinetics, structural determination, and computational simulations, the structural factors that dictate polymerase fidelity are not fully resolved. Time-resolved crystallography has elucidated correct nucleotide incorporation and established a three-metal-ion-dependent catalytic mechanism for polymerases. Using X-ray time-resolved crystallography, we visualize the complete DNA misincorporation process catalyzed by DNA polymerase η. The resulting molecular snapshots suggest primer 3´-OH alignment mediated by A-site metal ion binding is the key step in substrate discrimination. Moreover, we observe that C-site metal ion binding preceded the nucleotidyl transfer reaction and demonstrate that the C-site metal ion is strictly required for misincorporation. Our results highlight the essential but separate roles of the three metal ions in DNA synthesis.

59 BASIC BIOLOGICAL SCIENCES↗

Cell invasion during competitive growth of polycrystalline solidification patterns

Abstract Spatially extended cellular and dendritic array structures forming during solidification processes such as casting, welding, or additive manufacturing are generally polycrystalline. Both the array structure within each grain and the larger scale grain structure determine the performance of many structural alloys. How those two structures coevolve during solidification remains poorly understood. By in situ observations of microgravity alloy solidification experiments onboard the International Space Station, we have discovered that individual cells from one grain can unexpectedly invade a nearby grain of different misorientation, either as a solitary cell or as rows of cells. This invasion process causes grains to interpenetrate each other and hence grain boundaries to adopt highly convoluted shapes. Those observations are reproduced by phase-field simulations further demonstrating that invasion occurs for a wide range of misorientations. Those results fundamentally change the traditional conceptualization of grains as distinct regions embedded in three-dimensional space.

36 MATERIALS SCIENCE↗