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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 OSTI2022

Computing diffraction patterns of microstructures from phase-field simulations

The diffraction pattern of a material contains information not only on the crystal structures of its constituting phases, but also on its mesoscale spatial distributions of phases, grains, and ferroelastic, ferroelectric, and ferromagnetic domains. While diffraction patterns from experiments such as X-ray diffraction are presented in the reciprocal or Fourier space, mesoscale microstructure models such as the phase-field method naturally produce real-space images of spatial distribution of chemical composition, structural, and ferroic domains. Although one could rather readily compute the Fourier amplitudes of chemical and structural domain distributions generated by mesoscale simulations, they only contain information about the length scale and alignment of the real-space chemical and structure domains. Therefore, a direct comparison between diffraction experiments and mesoscale microstructure simulations is not possible. Here, we develop a theoretical approach to directly compute the crystal diffraction patterns of microstructures predicted by phase-field simulations. In particular, we consider five representative examples of microstructure patterns involving purely compositional domains, a single pair of tetragonal twin structures, multiple twin variants in a hexagonal system, ferroelectric polar vortices, and polycrystalline grains. The results are compared with previous experimental observations as well as X-ray diffraction experiments performed in the present study. Furthermore, the theoretical framework allows one to directly connect material microstructures and diffraction patterns predicted from phase-field simulations and the corresponding diffraction patterns from experiments, and thus providing guidance to experimental diffraction characterization and interpretation of microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structure-based discovery of potent WD repeat domain 5 inhibitors that demonstrate efficacy and safety in preclinical animal models

WD repeat domain 5 (WDR5) is a core scaffolding component of many multiprotein complexes that perform a variety of critical chromatin-centric processes in the nucleus. WDR5 is a component of the mixed lineage leukemia MLL/SET complex and localizes MYC to chromatin at tumor-critical target genes. As a part of these complexes, WDR5 plays a role in sustaining oncogenesis in a variety of human cancers that are often associated with poor prognoses. Thus, WDR5 has been recognized as an attractive therapeutic target for treating both solid and hematological tumors. Previously, small-molecule inhibitors of the WDR5-interaction (WIN) site and WDR5 degraders have demonstrated robust in vitro cellular efficacy in cancer cell lines and established the therapeutic potential of WDR5. However, these agents have not demonstrated significant in vivo efficacy at pharmacologically relevant doses by oral administration in animal disease models. We have discovered WDR5 WIN-site inhibitors that feature bicyclic heteroaryl P 7 units through structure-based design and address the limitations of our previous series of small-molecule inhibitors. Importantly, our lead compounds exhibit enhanced on-target potency, excellent oral pharmacokinetic (PK) profiles, and potent dose-dependent in vivo efficacy in a mouse MV4:11 subcutaneous xenograft model by oral dosing. Furthermore, these in vivo probes show excellent tolerability under a repeated high-dose regimen in rodents to demonstrate the safety of the WDR5 WIN-site inhibition mechanism. Collectively, our results provide strong support for WDR5 WIN-site inhibitors to be utilized as potential anticancer therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here, we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation, and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The Neighboring Subunit Is Engaged to Stabilize the Substrate in the Active Site of Plant Arginases

Arginine acts as a precursor of polyamines in plants in two known pathways, agmatine and ornithine routes. It is decarboxylated to agmatine by arginine decarboxylase, and then transformed to putrescine by the consecutive action of agmatine iminohydrolase and N-carbamoylputrescine amidohydrolase. Alternatively, it can be hydrolyzed to ornithine by arginase and then decarboxylated by ornithine decarboxylase to putrescine. Some plants lack a functional ornithine pathway, but all have one or two arginases that can have dual cellular localization, in mitochondria and plastids. It was recently shown that arginases from Arabidopsis thaliana and soybean act also as agmatinases, thus they can produce putrescine directly from agmatine. Therefore, arginase (together with arginine decarboxylase) can complement putrescine production in plastids, providing a third polyamine biosynthesis pathway in plants. Phylogenetic analysis suggests that arginases, highly conserved in the plant kingdom, create the only group of enzymes recognized in the family of ureohydrolases in plants. Arginases are metalloenzymes with binuclear manganese cluster in the active site. In this work, two arginases from A. thaliana and Medicago truncatula are structurally characterized and their binding properties are discussed. Crystal structures with bound ornithine show that plant hexameric arginases engage a long loop from the neighboring subunit to stabilize α-amino and carboxyl groups of the ligand. This unique ligand binding mode is unobserved in arginases from other domains of life. Structural analysis shows that substrate binding by residues from two neighboring subunits might also characterize some prokaryotic agmatinases. This feature of plant arginases is most likely the determinant of their ability to recognize not only arginine but also agmatine as their substrates, thus, to act as arginase and agmatinase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Autonomous Multistate Nanoencoding Using Combinatorial Ferroelectric Closure Domains in BiFeO 3

Recent advances in ferroic materials have identified topological defects as promising candidates for enabling additional functionalities in future electronic systems. The generation of stable and customizable polar topologies is needed to achieve multistates that enable beyond-binary device architectures. Here, in this study, we show how to autonomously pattern on-demand highly tunable striped closure domains in pristine rhombohedral-phase BiFeO 3 thin films through precise scanning of a biased atomic force microscopy tip along carefully designed paths. By employing this strategy, we generate and manipulate closed-loop structures with high spatial resolution in an automated manner, allowing the creation of highly tunable and intricate topological domain structures that exhibit distinct polarization configurations without the need for electrode deposition or complex heterostructure growth. As a proof-of-concept for ferroelectric beyond-binary memory devices, we use such topological domains as multistates, engineering an alphabet and automating the symbolic writing/reading process using autonomous microscopy. The resulting information density is compared with that of current commercially available memory devices, demonstrating the potential of ferroelectric topological domains for multistate information storage applications.

BiFeO3↗
DOE OSTI2025

Structural and functional analyses of SARS-CoV-2 Nsp3 and its specific interactions with the 5’ UTR of the viral genome

ABSTRACT Non-structural protein 3 (Nsp3) is the largest open reading frame encoded in the SARS-CoV-2 genome, essential for the formation of double-membrane vesicles (DMV) wherein viral RNA replication occurs. We conducted an extensive structure-function analysis of Nsp3 and determined the crystal structures of the ubiquitin-like 1 (Ubl1), nucleic acid binding (NAB), β-coronavirus-specific marker (βSM) domains, and a sub-region of the Y domain of this protein. We show that the Ubl1, ADP-ribose phosphatase (ADRP), human SARS Unique (HSUD), NAB, and Y domains of Nsp3 bind the 5’ UTR of the viral genome and that the Ubl1 and Y domains possess affinity for recognition of this region, suggesting high specificity. The Ubl1-Nucleocapsid (N) protein complex binds the 5’ UTR with greater affinity than the individual proteins alone. Our results suggest that multiple domains of Nsp3, particularly Ubl1 and Y, shepherd the 5’ UTR of the viral genome during translocation through the DMV membrane, priming the Ubl1 domain to load the genome onto N protein. IMPORTANCE The largest protein encoded by the SARS-CoV-2 genome is Nsp3. In infected cells, this multi-domain protein forms a pore structure in the virus-induced double-membrane vesicles (DMV). We have incomplete data on Nsp3 molecular structure, and here, we describe crystal structures for multiple domains of Nsp3. It is thought that newly replicated viral RNA transits through the DMV pore; however, we possess incomplete data on which regions of Nsp3 actually interact with RNA. Here, we present data showing that five domains of Nsp3 interact with the 5’ UTR of the SARS-CoV-2 RNA, including the Y domain for which no function has ever been discovered. These data suggest that the pore structure plays an active role in recognizing the terminal end of the genome, transiting and loading the viral RNA onto the cytoplasmic nucleocapsid protein. These data help expand our knowledge of Nsp3 structure and function and the SARS-CoV-2 replication cycle.

Microbiology↗