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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

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↗

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↗

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↗

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↗

Efficient derivative computation for unsteady fatigue-constrained nonlinear aero-structural wind turbine blade optimization

Gradient-based optimization offers significant efficiency advantages for wind turbine blade design, but its application has often been limited by the cost and accuracy of finite-difference derivative calculations, especially when fatigue constraints are considered. In this work, we systematically compare and evaluate four differentiation techniques, namely algorithmic differentiation, implicit differentiation, sparsity exploitation, and parallelization, to determine their effectiveness in computing accurate gradients through time-domain aero-structural simulations. By integrating these techniques with unsteady nonlinear aerodynamic and structural models, we develop software designed for accurate gradient computation. We show that combining these techniques addresses memory and runtime challenges associated with long simulations required by design load cases. Specifically, the most effective combination reduces derivative computation wall time by over an order of magnitude compared to finite differencing while maintaining superior accuracy. We demonstrate this approach in a proof-of-concept aero-structural optimization of a wind turbine blade that improves the cost of energy by 12.78 %. This comparative study establishes a viable approach for fatigue-aware blade design that balances computational efficiency with modeling accuracy.

17 WIND ENERGY↗