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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structural basis underlying the synergism of NADase and SLO during group A Streptococcus infection

Group A Streptococcus (GAS) is a strict human pathogen possessing a unique pathogenic trait that utilizes the cooperative activity of NAD + -glycohydrolase (NADase) and Streptolysin O (SLO) to enhance its virulence. How NADase interacts with SLO to synergistically promote GAS cytotoxicity and intracellular survival is a long-standing question. Here, the structure and dynamic nature of the NADase/SLO complex are elucidated by X-ray crystallography and small-angle scattering, illustrating atomic details of the complex interface and functionally relevant conformations. Structure-guided studies reveal a salt-bridge interaction between NADase and SLO is important to cytotoxicity and resistance to phagocytic killing during GAS infection. Furthermore, the biological significance of the NADase/SLO complex in GAS virulence is demonstrated in a murine infection model. Overall, this work delivers the structure-functional relationship of the NADase/SLO complex and pinpoints the key interacting residues that are central to the coordinated actions of NADase and SLO in the pathogenesis of GAS infection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Expanding and quantifying the crystal chemistry of the flexible ligand 15aneN5

Tetraazamacrocycles have been very extensively exploited as transition metal ligands for a variety of purposes, including catalysis, medical imaging, pharmaceuticals, etc. However, the pentaazamacrocycles are much less commonly used for similar purposes because of poor availability, difficulties in their synthesis, and less well-known metal coordination properties. 1,4,7,10,13-pentaazacyclopentadane (15aneN5) was initially synthesized by a published synthetic route, which we simplified and shortened with minimal drop in yield. Eight different transition metal complexes were made using typical complexation methods. X-ray crystallography of multiple novel complexes yielded insight into the flexibility in coordination geometry of this interesting macrocycle as well as the first crystal structures of 15aneN5 with Cr 3+ , Mn 3+ , Fe 3+ , Co 3+ , Cu 2+ , and Ru 2+ . A parameter to quantify the coordination geometry adopted by the ligand was devised and applied to all known crystal structures of its metal complexes. Lastly, oxidation of 15aneN5 to a novel diimine macrocycle was observed during complexation with ruthenium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Critical role of structural order in bipolar redox-active molecules for organic redox flow batteries

Bipolar redox-active molecules (BRMs) have been suggested as a means to address crossover related issues in all-organic redox flow batteries (RFBs). In such species, electron donors (anolytes) and electron acceptors (catholytes) are linked by a chain, and the same chemical composition is used in both anode and cathode compartments to reduce chemical gradients and unbalanced ion transport. The resultant RFBs resemble the aqueous vanadium RFBs, but offer greater design flexibility and potentially more favorable electrochemical and physicochemical properties. Yet the complex trade-offs in these properties have been a complication. Here we developed a fundamental rubric to uncover the likely origins in the performance metrics of these BRMs that are salient for their use in RFBs. Methylene linked phenothiazine and phthalimide moieties were employed as model BRMs and variations in their properties and molecular conformations were evaluated by systematically varying the methylene linker. Our results revealed that even minimalistic changes in the linker length resulted in dramatic oscillations in the solubility and stability. Using crystallography, quantum chemistry, and molecular dynamics, we clarify that the seemingly fluctuating behavior is due to (1) the inter- and intra-molecular charge transfer between the donor and acceptor through bond or/and through space; (2) the formation of distinctive packing/clustering motifs. Both interactions are strongly dependent on the molecular conformation. As these structural factors modify the electronic structure of both electroactive functional groups and do not change monotonically, the structure–property response in BRMs is often complex. Finally, accordingly, these behaviors need to be taken into account in developing BRMs and knowledge of these structural factors will allow the more rational design of BRMs for grid-scale energy storage.

25 ENERGY STORAGE↗
DOE OSTI2023

Synthesis of zirconium-based metal–organic frameworks with iron( ii ) clathrochelate ligands

Zirconium-based metal organic frameworks (MOFs) are of great significance in supramolecular coordination chemistry, mainly as catalysts, due to their chemical stability and structural diversity. We report the synthesis of zirconium-clathrochelate based crystalline MOFs (Zr-GU-1to -4) made from hexanuclear zirconium inorganic nodes and iron(II) clathrochelate-based ditopic carboxylic acid ligands bearing various lateral moieties, namely, butyl, cyclohexyl, phenyl and methyl groups. Among the various iron(II) clathrochelate linkers, the one with butyl side chains, i.e., Zr-GU-1, forms stable crystalline MOFs as confirmed by single-crystal X-ray crystallography and exhibits a promising porosity with a BET surface area of ~650 m 2 g -1 after its activation with supercritical CO 2 (ScCO 2 ) from acetonitrile.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quantification of Dynamic Scattering Effects in Molecular Crystals using Large Angle Rocking Beam Electron Diffraction

Electron crystallography provides a pathway to solve structure of small crystals (< 1um) in size, and thus overcomes difficult synthesis constraints involved in growing large crystals. Generally, electron diffraction data is collected in the form of integrated intensity using continuous rotation or by precession. The measured intensities in 3D are utilized for structure solution. Using this approach, structure solution of difficult crystals, such as small crystals of zeolites, metal-organic frameworks, molecular crystals, and proteins , can be solved by electron diffraction. However, electron structure solutions are regularly reported with higher Rvalues than x-ray or neutron diffraction. While similar structures are found despite the high R-values, the differences in the measure intensity and theory calculated intensity limit information that can be extracted by electron diffraction. Previous work demonstrated that including multiple-scattering effects significantly reduce the R-values . Thus, it is critical to be able to quantify the dynamical diffraction effects in molecular crystals.

Crystallography↗
DOE OSTI2021

Reproducibility of protein x-ray diffuse scattering and potential utility for modeling atomic displacement parameters

Protein structure and dynamics can be probed using x-ray crystallography. Whereas the Bragg peaks are only sensitive to the average unit-cell electron density, the signal between the Bragg peaks—diffuse scattering—is sensitive to spatial correlations in electron-density variations. Although diffuse scattering contains valuable information about protein dynamics, the diffuse signal is more difficult to isolate from the background compared to the Bragg signal, and the reproducibility of diffuse signal is not yet well understood. We present a systematic study of the reproducibility of diffuse scattering from isocyanide hydratase in three different protein forms. Both replicate diffuse datasets and datasets obtained from different mutants were similar in pairwise comparisons (Pearson correlation coefficient ≥0.8). The data were processed in a manner inspired by previously published methods using custom software with modular design, enabling us to perform an analysis of various data processing choices to determine how to obtain the highest quality data as assessed using unbiased measures of symmetry and reproducibility. The diffuse data were then used to characterize atomic mobility using a liquid-like motions (LLM) model. This characterization was able to discriminate between distinct anisotropic atomic displacement parameter (ADP) models arising from different anisotropic scaling choices that agreed comparably with the Bragg data. Our results emphasize the importance of data reproducibility as a model-free measure of diffuse data quality, illustrate the ability of LLM analysis of diffuse scattering to select among alternative ADP models, and offer insights into the design of successful diffuse scattering experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Dynamics retrieval from stochastically weighted incomplete data by low-pass spectral analysis

Time-resolved serial femtosecond crystallography (TR-SFX) provides access to protein dynamics on sub-picosecond timescales, and with atomic resolution. Due to the nature of the experiment, these datasets are often highly incomplete and the measured diffracted intensities are affected by partiality. To tackle these issues, one established procedure is that of splitting the data into time bins, and averaging the multiple measurements of equivalent reflections within each bin. This binning and averaging often involve a loss of information. Here, we propose an alternative approach, which we call low-pass spectral analysis (LPSA). In this method, the data are projected onto the subspace defined by a set of trigonometric functions, with frequencies up to a certain cutoff. This approach attenuates undesirable high-frequency features and facilitates retrieving the underlying dynamics. A time-lagged embedding step can be included prior to subspace projection to improve the stability of the results with respect to the parameters involved. Subsequent modal decomposition allows to produce a low-rank description of the system's evolution. Using a synthetic time-evolving model with incomplete and partial observations, we analyze the LPSA results in terms of quality of the retrieved signal, as a function of the parameters involved. We compare the performance of LPSA to that of a range of other sophisticated data analysis techniques. We show that LPSA allows to achieve excellent dynamics reconstruction at modest computational cost. Finally, we demonstrate the superiority of dynamics retrieval by LPSA compared to time binning and merging, which is, to date, the most commonly used method to extract dynamical information from TR-SFX data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Deconvolution of dynamic heterogeneity in protein structure

Heterogeneity is intrinsic to the dynamic process of a chemical reaction. As reactants are converted to products via intermediates, the nature and extent of heterogeneity vary temporally throughout the duration of the reaction and spatially across the molecular ensemble. The goal of many biophysical techniques, including crystallography and spectroscopy, is to establish a reaction trajectory that follows an experimentally provoked dynamic process. It is essential to properly analyze and resolve heterogeneity inevitably embedded in experimental datasets. We have developed a deconvolution technique based on singular value decomposition (SVD), which we have rigorously practiced in diverse research projects. In this review, we recapitulate the motivation and challenges in addressing the heterogeneity problem and lay out the mathematical foundation of our methodology that enables isolation of chemically sensible structural signals. We also present a few case studies to demonstrate the concept and outcome of the SVD-based deconvolution. Finally, we highlight a few recent studies with mechanistic insights made possible by heterogeneity deconvolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Scaling and merging time-resolved pink-beam diffraction with variational inference

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

EWALD: A macromolecular diffractometer for the second target station

Revealing the positions of all the atoms in large macromolecules is powerful but only possible with neutron macromolecular crystallography (NMC). Neutrons provide a sensitive and gentle probe for the direct detection of protonation states at near-physiological temperatures and clean of artifacts caused by x rays or electrons. Currently, NMC use is restricted by the requirement for large crystal volumes even at state-of-the-art instruments such as the macromolecular neutron diffractometer at the Spallation Neutron Source. EWALD’s design will break the crystal volume barrier and, thus, open the door for new types of experiments, the study of grand challenge systems, and the more routine use of NMC in biology. EWALD is a single crystal diffractometer capable of collecting data from macromolecular crystals on orders of magnitude smaller than what is currently feasible. The construction of EWALD at the Second Target Station will cause a revolution in NMC by enabling key discoveries in the biological, biomedical, and bioenergy sciences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Structure of the cell-binding component of the Clostridium difficile binary toxin reveals a di-heptamer macromolecular assembly

Targeting Clostridium difficile infection is challenging because treatment options are limited, and high recurrence rates are common. One reason for this is that hypervirulent C. difficile strains often have a binary toxin termed the C. difficile toxin, in addition to the enterotoxins TsdA and TsdB. The C. difficile toxin has an enzymatic component, termed CDTa, and a pore-forming or delivery subunit termed CDTb. CDTb was characterized here using a combination of single-particle cryoelectron microscopy, X-ray crystallography, NMR, and other biophysical methods. In the absence of CDTa, 2 di-heptamer structures for activated CDTb (1.0 MDa) were solved at atomic resolution, including a symmetric ( Sym CDTb; 3.14 Å) and an asymmetric form ( Asym CDTb; 2.84 Å). Roles played by 2 receptor-binding domains of activated CDTb were of particular interest since the receptor-binding domain 1 lacks sequence homology to any other known toxin, and the receptor-binding domain 2 is completely absent in other well-studied heptameric toxins (i.e., anthrax). For Asym CDTb, a Ca 2+ binding site was discovered in the first receptor-binding domain that is important for its stability, and the second receptor-binding domain was found to be critical for host cell toxicity and the di-heptamer fold for both forms of activated CDTb. Together, these studies represent a starting point for developing structure-based drug-design strategies to target the most severe strains of C. difficile .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Human XPG nuclease structure, assembly, and activities with insights for neurodegeneration and cancer from pathogenic mutations

Xeroderma pigmentosum group G (XPG) protein is both a functional partner in multiple DNA damage responses (DDR) and a pathway coordinator and structure-specific endonuclease in nucleotide excision repair (NER). Different mutations in the XPG gene ERCC5 lead to either of two distinct human diseases: Cancer-prone xeroderma pigmentosum (XP-G) or the fatal neurodevelopmental disorder Cockayne syndrome (XP-G/CS). To address the enigmatic structural mechanism for these differing disease phenotypes and for XPG’s role in multiple DDRs, here we determined the crystal structure of human XPG catalytic domain (XPGcat), revealing XPG-specific features for its activities and regulation. Furthermore, XPG DNA binding elements conserved with FEN1 superfamily members enable insights on DNA interactions. Notably, all but one of the known pathogenic point mutations map to XPGcat, and both XP-G and XP-G/CS mutations destabilize XPG and reduce its cellular protein levels. Mapping the distinct mutation classes provides structure-based predictions for disease phenotypes: Residues mutated in XP-G are positioned to reduce local stability and NER activity, whereas residues mutated in XP-G/CS have implied long-range structural defects that would likely disrupt stability of the whole protein, and thus interfere with its functional interactions. Combined data from crystallography, biochemistry, small angle X-ray scattering, and electron microscopy unveil an XPG homodimer that binds, unstacks, and sculpts duplex DNA at internal unpaired regions (bubbles) into strongly bent structures, and suggest how XPG complexes may bind both NER bubble junctions and replication forks. Collective results support XPG scaffolding and DNA sculpting functions in multiple DDR processes to maintain genome stability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Assessment of enzyme active site positioning and tests of catalytic mechanisms through X-ray–derived conformational ensembles

How enzymes achieve their enormous rate enhancements remains a central question in biology, and our understanding to date has impacted drug development, influenced enzyme design, and deepened our appreciation of evolutionary processes. While enzymes position catalytic and reactant groups in active sites, physics requires that atoms undergo constant motion. Numerous proposals have invoked positioning or motions as central for enzyme function, but a scarcity of experimental data has limited our understanding of positioning and motion, their relative importance, and their changes through the enzyme’s reaction cycle. To examine positioning and motions and test catalytic proposals, we collected “room temperature” X-ray crystallography data for Pseudomonas putida ketosteroid isomerase (KSI), and we obtained conformational ensembles for this and a homologous KSI from multiple PDB crystal structures. Here, ensemble analyses indicated limited change through KSI’s reaction cycle. Active site positioning was on the 1- to 1.5-Å scale, and was not exceptional compared to noncatalytic groups. The KSI ensembles provided evidence against catalytic proposals invoking oxyanion hole geometric discrimination between the ground state and transition state or highly precise general base positioning. Instead, increasing or decreasing positioning of KSI’s general base reduced catalysis, suggesting optimized Ångstrom-scale conformational heterogeneity that allows KSI to efficiently catalyze multiple reaction steps. Ensemble analyses of surrounding groups for WT and mutant KSIs provided insights into the forces and interactions that allow and limit active-site motions. Most generally, this ensemble perspective extends traditional structure–function relationships, providing the basis for a new era of “ensemble–function” interrogation of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Structure of SARS-CoV-2 ORF8, a rapidly evolving immune evasion protein

The molecular basis for the severity and rapid spread of the COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely unknown. ORF8 is a rapidly evolving accessory protein that has been proposed to interfere with immune responses. The crystal structure of SARS-CoV-2 ORF8 was determined at 2.04-Å resolution by X-ray crystallography. The structure reveals a ~60-residue core similar to SARS-CoV-2 ORF7a, with the addition of two dimerization interfaces unique to SARS-CoV-2 ORF8. A covalent disulfide-linked dimer is formed through an N-terminal sequence specific to SARS-CoV-2, while a separate noncovalent interface is formed by another SARS-CoV-2-specific sequence, 73 YIDI 76 . Together, the presence of these interfaces shows how SARS-CoV-2 ORF8 can form unique large-scale assemblies not possible for SARS-CoV, potentially mediating unique immune suppression and evasion activities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Molecular basis of hemoglobin binding and heme removal in Corynebacterium diphtheriae

To successfully mount infections, nearly all bacterial pathogens must acquire iron, a key metal cofactor that primarily resides within human hemoglobin. Corynebacterium diphtheriae causes the life-threatening respiratory disease diphtheria and captures hemoglobin for iron scavenging using the surface-displayed receptor HbpA. Here, we show using X-ray crystallography, NMR, and in situ binding measurements that C. diphtheriae selectively captures iron-loaded hemoglobin by partially ensconcing the heme molecules of its α subunits. Quantitative growth and heme release measurements are compatible with C. diphtheriae acquiring heme passively released from hemoglobin’s β subunits. We propose a model in which HbpA and heme-binding receptors collectively function on the C. diphtheriae surface to capture hemoglobin and its spontaneously released heme. Acquisition mechanisms that exploit the propensity of hemoglobin’s β subunit to release heme likely represent a common strategy used by bacterial pathogens to obtain iron during infections.

NMR↗
DOE OSTI2026

Kramers nodal line in the charge density wave state of YTe 3 and the influence of twin domains

Recent studies have focused on the relationship between charge density wave (CDW) collective electronic ground states and nontrivial topological states. YTe 3 , a nonmagnetic quasi-two-dimensional chalcogenide, has been reported to exhibit a CDW state below 334 K. Using angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT), we establish that YTe 3 is a CDW-induced Kramers nodal line (KNL) metal, a recently proposed topological state of matter. Scanning tunneling microscopy and low energy electron diffraction reveal two orthogonal domains, each with a unidirectional CDW and a similar wave vector (𝐪 CDW ). When the influence of twin domains is considered, the effective band structure (EBS) computations that utilize DFT-calculated bands using a noncentrosymmetric structure determined by x-ray crystallography, show excellent agreement with ARPES. The noncentrosymmetry of YTe 3 is established by Raman spectroscopy. The Fermi surface and ARPES intensity plots show weak shadow bands displaced by 𝐪 CDW from the main bands. Furthermore, these are linked to CDW modulation, as the EBS calculation confirms. Bilayer split main and shadow bands suggest the existence of crossings, according to theory and experiment. DFT bands, including spin-orbit coupling, indicate existence of a KNL along the Σ direction from multiple crossings of bands dispersing perpendicular to it. Additionally, doubly degenerate bands are only found along the KNL at all energies, with some bands dispersing through the Fermi level.

Angle-resolved photoemission spectroscopy↗
DOE OSTI2020

PyMDA : microcrystal data assembly using Python

The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. A multi-stage data assembly method has previously been designed for microcrystal synchrotron crystallography. Here the strategy has been implemented as a Python program for microcrystal data assembly ( PyMDA ). PyMDA optimizes microcrystal data quality including weak anomalous signals through iterative crystal and frame rejections. Beyond microcrystals, PyMDA may be applicable for assembling data sets from larger crystals for improved data quality.

36 MATERIALS SCIENCE↗