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Results for “integrative structural biology”

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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Role of shielding in modulating the effects of solar particle events: Monte Carlo calculation of absorbed dose and DNA complex lesions in different organs

Distributions of absorbed dose and DNA clustered damage yields in various organs and tissues following the October 1989 solar particle event (SPE) were calculated by coupling the FLUKA Monte Carlo transport code with two anthropomorphic phantoms (a mathematical model and a voxel model), with the main aim of quantifying the role of the shielding features in modulating organ doses. The phantoms, which were assumed to be in deep space, were inserted into a shielding box of variable thickness and material and were irradiated with the proton spectra of the October 1989 event. Average numbers of DNA lesions per cell in different organs were calculated by adopting a technique already tested in previous works, consisting of integrating into "condensed-history" Monte Carlo transport codes--such as FLUKA--yields of radiobiological damage, either calculated with "event-by-event" track structure simulations, or taken from experimental works available in the literature. More specifically, the yields of "Complex Lesions" (or "CL", defined and calculated as a clustered DNA damage in a previous work) per unit dose and DNA mass (CL Gy-1 Da-1) due to the various beam components, including those derived from nuclear interactions with the shielding and the human body, were integrated in FLUKA. This provided spatial distributions of CL/cell yields in different organs, as well as distributions of absorbed doses. The contributions of primary protons and secondary hadrons were calculated separately, and the simulations were repeated for values of Al shielding thickness ranging between 1 and 20 g/cm2. Slight differences were found between the two phantom types. Skin and eye lenses were found to receive larger doses with respect to internal organs; however, shielding was more effective for skin and lenses. Secondary particles arising from nuclear interactions were found to have a minor role, although their relative contribution was found to be larger for the Complex Lesions than for the absorbed dose, due to their higher LET and thus higher biological effectiveness. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Non-NASA Center↗
DOE OSTI2024

Integrating Machine Learning Potential and X-ray Absorption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon Nitrides

Precise determination of atomic structural information in functional materials holds transformative potential and broad implications for emerging technologies. Spectroscopic techniques, such as X-ray absorption near-edge structure (XANES), have been widely used for material characterization; however, extracting chemical information from experimental probes remains a significant challenge, particularly for disordered materials. We present an integrated approach that combines atomic simulations, data-driven techniques, and experimental measurements to investigate chemical speciation of amorphous carbon nitride systems as a case study. Here, we discuss the development of machine learning potentials that can efficiently explore the vast configuration space of amorphous carbon nitrides. By employing statistical methods, this structural database enables the elucidation of the most representative local structures and how they evolve with chemical compositions and density. Density functional theory simulations are used to establish a correlation between the local structure and spectroscopic signatures, which then serve as the basis for interpreting and extracting chemical content from experimental data. Although our framework is specifically demonstrated for XANES and carbon nitrides, the approach described herein is readily adaptable as applied to other experimental characterization probes and materials classes.

36 MATERIALS SCIENCE↗
NASA NTRS1996

Characterization of the proteins comprising the integral matrix of Strongylocentrotus purpuratus embryonic spicules

In the present study, we enumerate and characterize the proteins that comprise the integral spicule matrix of the Strongylocentrotus purpuratus embryo. Two-dimensional gel electrophoresis of [35S]methionine radiolabeled spicule matrix proteins reveals that there are 12 strongly radiolabeled spicule matrix proteins and approximately three dozen less strongly radiolabeled spicule matrix proteins. The majority of the proteins have acidic isoelectric points; however, there are several spicule matrix proteins that have more alkaline isoelectric points. Western blotting analysis indicates that SM50 is the spicule matrix protein with the most alkaline isoelectric point. In addition, two distinct SM30 proteins are identified in embryonic spicules, and they have apparent molecular masses of approximately 43 and 46 kDa. Comparisons between embryonic spicule matrix proteins and adult spine integral matrix proteins suggest that the embryonic 43-kDa SM30 protein is an embryonic isoform of SM30. An adult 49-kDa spine matrix protein is also identified as a possible adult isoform of SM30. Analysis of the SM30 amino acid sequences indicates that a portion of SM30 proteins is very similar to the carbohydrate recognition domain of C-type lectin proteins.

Non-NASA Center↗
DOE OSTI2023

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge or artificial intelligence driven, and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary- structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models, which contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly, while refining them against the density maps. Here, we introduce such an adaptive decision making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, and the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two protein systems, Adenylate Kinase and Carbon Monoxide Dehydrogenase. For the test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2 - 3 Å, map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that is inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from Chimpanzee adenovirus. The overhead for decision making remaining low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install the R-MDFF on different computing environments, from local Linux based workstations to High Performance Computing (HPC) environments.

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

Sequential Inference of Hospitalization Electronic Health Records Using Probabilistic Models

In the dynamic hospital setting, decision support can be a valuable tool for improving patient outcomes. Data-driven inference of future outcomes is challenging in this dynamic setting, where long sequences such as laboratory tests and medications are updated frequently. This is due in part to heterogeneity of data types and mixed-sequence types contained in variable length sequences. In this work we design a probabilistic unsupervised model for multiple arbitrary-length sequences contained in hospitalization Electronic Health Record (EHR) data. The model uses a latent variable structure and captures complex relationships between medications, diagnoses, laboratory tests, neurological assessments, and medications. It can be trained on original data, without requiring any lossy transformations or time binning. Inference algorithms are derived that use partial data to infer properties of the complete sequences, including their length and presence of specific values. We train this model on data from subjects receiving medical care in the Kaiser Permanente Northern California integrated healthcare delivery system. The results are evaluated against held-out data for predicting the length of sequences and presence of Intensive Care Unit (ICU) in hospitalization bed sequences. Our method outperforms a baseline approach, showing that in these experiments the trained model captures information in the sequences that is informative of their future values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Magnetosome Protein, Mms6 from Magnetospirillum magneticum Strain AMB-1, Is a Lipid-Activated Ferric Reductase

Magnetosomes of magnetotactic bacteria consist of magnetic nanocrystals with defined morphologies enclosed in vesicles originated from cytoplasmic membrane invaginations. Although many proteins are involved in creating magnetosomes, a single magnetosome protein, Mms6 from Magnetospirillum magneticum strain AMB-1, can direct the crystallization of magnetite nanoparticles in vitro. The in vivo role of Mms6 in magnetosome formation is debated, and the observation that Mms6 binds Fe3+ more tightly than Fe2+ raises the question of how, in a magnetosome environment dominated by Fe3+, Mms6 promotes the crystallization of magnetite, which contains both Fe3+ and Fe2+. Here we show that Mms6 is a ferric reductase that reduces Fe3+ to Fe2+ using NADH and FAD as electron donor and cofactor, respectively. Reductase activity is elevated when Mms6 is integrated into either liposomes or bicelles. Analysis of Mms6 mutants suggests that the C-terminal domain binds iron and the N-terminal domain contains the catalytic site. Although Mms6 forms multimers that involve C-terminal and N-terminal domain interactions, a fusion protein with ubiquitin remains a monomer and displays reductase activity, which suggests that the catalytic site is fully in the monomer. However, the quaternary structure of Mms6 appears to alter the iron binding characteristics of the C-terminal domain. These results are consistent with a hypothesis that Mms6, a membrane protein, promotes the formation of magnetite in vivo by a mechanism that involves reducing iron.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Direct Write of 3D Nanoscale Mesh Objects with Platinum Precursor via Focused Helium Ion Beam Induced Deposition

The next generation optical, electronic, biological, and sensing devices as well as platforms will inevitably extend their architecture into the 3rd dimension to enhance functionality. In focused ion beam induced deposition (FIBID), a helium gas field ion source can be used with an organometallic precursor gas to fabricate nanoscale structures in 3D with high-precision and smaller critical dimensions than focused electron beam induced deposition (FEBID), traditional liquid metal source FIBID, or other additive manufacturing technology. In this work, we report the effect of beam current, dwell time, and pixel pitch on the resultant segment and angle growth for nanoscale 3D mesh objects. We note subtle beam heating effects, which impact the segment angle and the feature size. Additionally, we investigate the competition of material deposition and sputtering during the 3D FIBID process, with helium ion microscopy experiments and Monte Carlo simulations. Our results show complex 3D mesh structures measuring ~300 nm in the largest dimension, with individual features as small as 16 nm at full width half maximum (FWHM). These assemblies can be completed in minutes, with the underlying fabrication technology compatible with existing lithographic techniques, suggesting a higher-throughput pathway to integrating FIBID with established nanofabrication techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Integrating Viral Metagenomics into an Ecological Framework

Viral metagenomics has expanded our knowledge of the ecology of uncultured viruses, within both environmental (e.g., terrestrial and aquatic) and host-associated (e.g., plants and animals, including humans) contexts. Here, we emphasize the implementation of an ecological framework in viral metagenomic studies to address questions in virology rarely considered ecological, which can change our perception of viruses and how they interact with their surroundings. Additionally, an ecological framework explicitly considers diverse variants of viruses in populations that make up communities of interacting viruses, with ecosystem-level effects. It provides a structure for the study of the diversity, distributions, dynamics, and interactions of viruses with one another, hosts, and the ecosystem, including interactions with abiotic factors. An ecological framework in viral metagenomics stands poised to broadly expand our knowledge in basic and applied virology. We highlight specific fundamental research needs to capitalize on its potential and advance the field.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Regulation of translation by ribosomal RNA pseudouridylation

Pseudouridine is enriched in ribosomal, spliceosomal, transfer, and messenger RNA and thus integral to the central dogma. The chemical basis for how pseudouridine affects the molecular apparatus such as ribosome, however, remains elusive owing to the lack of structures without this natural modification. Here, we studied the translation of a hypopseudouridylated ribosome initiated by the internal ribosome entry site (IRES) elements. We analyzed eight cryo–electron microscopy structures of the ribosome bound with the Taura syndrome virus IRES in multiple functional states. We found widespread loss of pseudouridine-mediated interactions through water and long-range base pairings. In the presence of the translocase, eukaryotic elongation factor 2, and guanosine 5'-triphosphate hydrolysis, the hypopseudouridylated ribosome favors a rare unconducive conformation for decoding that is partially recouped in the ribosome population that remains modified at the P-site uridine. The structural principles learned establish the link between functional defects and modification loss and are likely applicable to other pseudouridine-associated processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural basis for enzymatic terminal C–H bond functionalization of alkanes

Alkane monooxygenase (AlkB) is a widely occurring integral membrane metalloenzyme that catalyzes the initial step in the functionalization of recalcitrant alkanes with high terminal selectivity. AlkB enables diverse microorganisms to use alkanes as their sole carbon and energy source. Here we present the 48.6-kDa cryo-electron microscopy structure of a natural fusion from Fontimonas thermophila between AlkB and its electron donor AlkG at 2.76 Å resolution. The AlkB portion contains six transmembrane helices with an alkane entry tunnel within its transmembrane domain. A dodecane substrate is oriented by hydrophobic tunnel-lining residues to present a terminal C–H bond toward a diiron active site. AlkG, an [Fe–4S] rubredoxin, docks via electrostatic interactions and sequentially transfers electrons to the diiron center. The archetypal structural complex presented reveals the basis for terminal C–H selectivity and functionalization within this broadly distributed evolutionary class of enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

The endomembrane sheath: a key structure for understanding the plant cell?

Recent evidence suggests that integrin is abundant in endomembranes of plant cells, and the endomembranes are clad by a sheath of cytoskeleton including F-actin. A role for endomembrane integrin and the endomembrane sheath is proposed: this system might orchestrate metabolic regulation by providing and modulating loci for channelling, and might accelerate channeling as needed by dragging the endoplasmic reticulum (ER) and organelles through the cytoplasm. To accomplish this "streaming", F-actin might lever against the rest of the endomembrane sheath and the ER might also lever against adhesion sites (i.e., plasmodesmata and plasmalemmal control centers). As an important agent in the control of cellular activities, according to this model, the endomembrane sheath would play a major part in responses to diverse signals and stresses, and under extreme stress cell survival would depend on the ability of the system to maintain enough integrity to direct critical syntheses and degradations.

NASA Discipline Plant Biology↗
DOE OSTI2021

ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Abstract Machine learning has been increasingly used for protein engineering. However, because the general sequence contexts they capture are not specific to the protein being engineered, the accuracy of existing machine learning algorithms is rather limited. Here, we report ECNet (evolutionary context-integrated neural network), a deep-learning algorithm that exploits evolutionary contexts to predict functional fitness for protein engineering. This algorithm integrates local evolutionary context from homologous sequences that explicitly model residue-residue epistasis for the protein of interest with the global evolutionary context that encodes rich semantic and structural features from the enormous protein sequence universe. As such, it enables accurate mapping from sequence to function and provides generalization from low-order mutants to higher-order mutants. We show that ECNet predicts the sequence-function relationship more accurately as compared to existing machine learning algorithms by using ~50 deep mutational scanning and random mutagenesis datasets. Moreover, we used ECNet to guide the engineering of TEM-1 β-lactamase and identified variants with improved ampicillin resistance with high success rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers

Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Tensegrity: the architectural basis of cellular mechanotransduction

Physical forces of gravity, hemodynamic stresses, and movement play a critical role in tissue development. Yet, little is known about how cells convert these mechanical signals into a chemical response. This review attempts to place the potential molecular mediators of mechanotransduction (e.g. stretch-sensitive ion channels, signaling molecules, cytoskeleton, integrins) within the context of the structural complexity of living cells. The model presented relies on recent experimental findings, which suggests that cells use tensegrity architecture for their organization. Tensegrity predicts that cells are hard-wired to respond immediately to mechanical stresses transmitted over cell surface receptors that physically couple the cytoskeleton to extracellular matrix (e.g. integrins) or to other cells (cadherins, selectins, CAMs). Many signal transducing molecules that are activated by cell binding to growth factors and extracellular matrix associate with cytoskeletal scaffolds within focal adhesion complexes. Mechanical signals, therefore, may be integrated with other environmental signals and transduced into a biochemical response through force-dependent changes in scaffold geometry or molecular mechanics. Tensegrity also provides a mechanism to focus mechanical energy on molecular transducers and to orchestrate and tune the cellular response.

Review↗
DOE OSTI2026

Forest residue harvest optimization: spanning the bridge between plant biology and biorefinery performance

Forestry residues have immense potential as alternative feedstocks to petroleum, yet their inherent complexity remains a major challenge to widespread use. Pairing the temporal rhythms of plant biology with biorefinery performance is critical to industrial-scale biorefinery development. Here, we provide the first report of a techno-economic analysis (TEA) and life cycle assessment (LCA) for a model integrated reductive catalytic fractionation (RCF)–molten salt hydrolysis process for forestry residues varying in tree part, species, and phenophase. All forestry residues resulted in net-negative greenhouse gas (GHG) emissions vs. comparable petroleum feedstocks, with GHG emissions potentially reduced >4.0× through composition-based feedstock selection (e.g., harvesting American beech bark in spring vs. summer). Moreover, American beech twigs/branchlets and bark in leafed and emergence phenophases, respectively, had 7.9× lower predicted phenolic minimum selling prices (MSPs) vs. other feedstocks and MSPs within the current global phenolic market range. Hemicellulose content and RCF yield emerged as key parameters impacting GHG emissions and biorefinery revenue, identifying hardwood twigs/branchlets in the leafed phenophase as optimal biofeedstocks. Biorefinery expenses were dominated by purchased equipment, raw materials, and utility costs, highlighting essential areas for future study. Notably, RCF reactor pressures drove 85–90% of equipment costs, but sensitivity analysis revealed that decreasing the pressure 20% could reduce the phenol MSP 4-fold. Structural carbohydrate dynamics were also investigated using a two-step acid hydrolysis method to resolve tissue- and species-level patterns in biomass composition throughout the year to enable harvest optimization based on TEA/LCA findings. Ultimately, elucidating the impact of biofeedstock dynamics on biorefinery performance enables harvest optimization, informed engineering design, and progress towards an expanded bioeconomy.

Shapiro, Alison J. [University of Delaware, Newark↗
DOE OSTI2025

Electrical signaling in fungi: past and present challenges

Abstract Electrical signaling is a fundamental mechanism for integrating environmental stimuli and coordinating responses in living organisms. While extensively studied in animals and plants, the role of electrical signaling in fungi remains a largely underexplored field. Early studies suggested that filamentous fungi generate action potential-like signals and electrical currents at hyphal tips, yet their function in intracellular communication remained unclear. Renewed interest in fungal electrical activity has fueled developments such as the hypothesis that mycorrhizal networks facilitate electrical communication between plants and the emerging field of fungal-based electronic materials. Given their continuous plasma membrane, specialized septal pores, and insulating cell wall structures, filamentous fungi possess architectural features that could support electrical signaling over long distances. However, studying electrical phenomena in fungal networks presents unique challenges due to the microscopic dimensions of hyphae, the structural complexity of highly modular mycelial networks, and the limitations of traditional electrophysiological methods. This review synthesizes current evidence for electrical signaling in filamentous fungi, evaluates methodological approaches, and highlights experimental challenges. By addressing these challenges and identifying best practices, we aim to advance research in this field and provide a foundation for future studies exploring the role of electrical signaling in fungal biology.

Buffi, Matteo↗
DOE OSTI2024

SISGR: The regulation of carbon fixation in plant and green algae: Rubisco activase and the origin of heat inactivation of CO 2 assimilation

Rubisco activase (Rca) is a critical AAA+ ATPase protein complex that remodels and promotes the Rubisco enzyme, a key player in photosynthetic performance and carbon fixation. The assembly and function of the Rca protein complex are regulated by a range of factors, including subunit concentration, nucleotide-binding states, thermal conditions, metal-ion coordination, and post-translational modifications, such as phosphorylation. Despite its importance in photosynthesis, the detailed molecular mechanisms underlying the regulation of plant Rca and how it activates Rubisco remain elusive. This project aims to bridge this knowledge gap by integrating sophisticated enzymology tools with single-molecule methods and high-resolution electron microscopy to elucidate the structure and function of plant Rca. Through these multiple approaches, we have systematically investigated how the activity of plant Rca is impacted by various factors, such as phosphorylation and metal-ion coordination. The Rca complex assembly/disassembly dynamics were captured using anti-Brownian electrokinetic (ABEL) trap-based measurements, providing unprecedented insight into its structural flexibility and diverse assembly states. Furthermore, the structural analysis of Rca through electron crystallography and single-particle cryogenic electron microscopy (cryo-EM) reveals novel assembly states of the spinach Rca, providing insight into the mechanistic action for Rubisco remodeling. By combining cutting-edge tools and approaches, this work uncovers critical aspects of Rca’s regulation and assembly, paving the way for a deeper understanding of its role in photosynthetic efficiency and the potential for enhancing carbon fixation in crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Type IV-like pili facilitate transformation in naturally competent archaea

Naturally competent organisms are capable of DNA uptake directly from the environment through the process of transformation. Despite the importance of transformation to microbial evolution, DNA uptake remains poorly characterized outside the bacterial domain. Here, we identify the pilus as a necessary component of the transformation machinery in archaea. We describe two naturally competent organisms: Methanococcus maripaludis and Methanoculleus thermophilus. In M. maripaludis, replicative vectors were transferred with an average efficiency of 2.4 x 10 3 transformants μg -1 DNA. In M. thermophilus, integrative vectors were transferred with an average efficiency of 2.7 x 10 3 transformants μg -1 DNA. Additionally, natural transformation of M. thermophilus could be used to introduce chromosomal mutations. To our knowledge, this is the first demonstration of a method to introduce targeted mutations in a member of the order Methanomicrobiales. For both organisms, mutants lacking structural components of the type IV-like pilus filament were defective for DNA uptake, demonstrating the importance of pili for natural transformation. Interestingly, competence could be induced in a non-competent strain of M. maripaludis by expressing pilin genes from a replicative vector. Furthermore, these results expand the known natural competence pili to include examples from the archaeal domain and highlight the importance of pili for DNA uptake in diverse microbial organisms.

59 BASIC BIOLOGICAL SCIENCES↗