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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Proteolytic dissection of Zab, the Z-DNA-binding domain of human ADAR1

Zalpha is a peptide motif that binds to Z-DNA with high affinity. This motif binds to alternating dC-dG sequences stabilized in the Z-conformation by means of bromination or supercoiling, but not to B-DNA. Zalpha is part of the N-terminal region of double-stranded RNA adenosine deaminase (ADAR1), a candidate enzyme for nuclear pre-mRNA editing in mammals. Zalpha is conserved in ADAR1 from many species; in each case, there is a second similar motif, Zbeta, separated from Zalpha by a more divergent linker. To investigate the structure-function relationship of Zalpha, its domain structure was studied by limited proteolysis. Proteolytic profiles indicated that Zalpha is part of a domain, Zab, of 229 amino acids (residues 133-361 in human ADAR1). This domain contains both Zalpha and Zbeta as well as a tandem repeat of a 49-amino acid linker module. Prolonged proteolysis revealed a minimal core domain of 77 amino acids (positions 133-209), containing only Zalpha, which is sufficient to bind left-handed Z-DNA; however, the substrate binding is strikingly different from that of Zab. The second motif, Zbeta, retains its structural integrity only in the context of Zab and does not bind Z-DNA as a separate entity. These results suggest that Zalpha and Zbeta act as a single bipartite domain. In the presence of substrate DNA, Zab becomes more resistant to proteases, suggesting that it adopts a more rigid structure when bound to its substrate, possibly with conformational changes in parts of the protein.

Non-NASA Center↗
DOE OSTI2020

Biochemical and structural basis for YTH domain of human YTHDC1 binding to methylated adenine in DNA

The recently characterized mammalian writer (methyltransferase) and eraser (demethylase) of the DNA N6-methyladenine (N6mA) methyl mark act on single-stranded (ss) and transiently-unpaired DNA. As YTH domain-containing proteins bind N6mA-containing RNA in mammalian cells, we investigated whether mammalian YTH domains are also methyl mark readers of N6mA DNA. Here, we show that the YTH domain of YTHDC1 (known to localize in the nucleus) binds ssDNA containing N6mA, with a 10 nM dissociation constant. This binding is stronger by a factor of 5 than in an RNA context, tested under the same conditions. However, the YTH domains of YTHDF2 and YTHDF1 (predominantly cytoplasmic) exhibited the opposite effect with ~1.5–2× stronger binding to ssRNA containing N6mA than to the corresponding DNA. We determined two structures of the YTH domain of YTHDC1 in complex with N6mA-containing ssDNA, which illustrated that YTHDC1 binds the methylated adenine in a single-stranded region flanked by duplexed DNA. We discuss the hypothesis that the writer-reader-eraser of N6mA-containining ssDNA is associated with maintaining genome stability. Structural comparison of YTH and SRA domains (the latter a DNA 5-methylcytosine reader) revealed them to be diverse members of a larger family of DNA/RNA modification readers, apparently having originated from bacterial modification-dependent restriction enzymes.

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

Epitopes recognition of SARS-CoV-2 nucleocapsid RNA binding domain by human monoclonal antibodies

Coronavirus nucleocapsid protein (NP) of SARS-CoV-2 plays a central role in many functions important for virus proliferation including packaging and protecting genomic RNA. The protein shares sequence, structure, and architecture with nucleocapsid proteins from betacoronaviruses. The N-terminal domain (NP RBD ) binds RNA and the C-terminal domain is responsible for dimerization. After infection, NP is highly expressed and triggers robust host immune response. The anti-NP antibodies are not protective and not neutralizing but can effectively detect viral proliferation soon after infection. Two structures of SARS-CoV-2 NP RBD were determined providing a continuous model from residue 48 to 173, including RNA binding region and key epitopes. Five structures of NP RBD complexes with human mAbs were isolated using an antigen-bait sorting. Complexes revealed a distinct complement-determining regions and unique sets of epitope recognition. This may assist in the early detection of pathogens and designing peptide-based vaccines. Mutations that significantly increase viral load were mapped on developed, full length NP model, likely impacting interactions with host proteins and viral RNA.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

Interactions of the SAP Domain of Human Ku70 with DNA Substrate: A Molecular Dynamics Study

NASA is developing a systems biology approach to improve the assessment of health risks associated with space radiation. The primary toxic and mutagenic lesion following radiation exposure is the DNA double strand break (DSB), thus a model incorporating proteins and pathways important in response and repair of this lesion is critical. One key protein heterodimer for systems models of radiation effects is the Ku70/80 complex. The Ku70/80 complex is important in the initial binding of DSB ends following DNA damage, and is a component of nonhomologous end joining repair, the primary pathway for DSB repair in mammalian cells. The SAP domain of Ku70 (residues 556-609), contains an a helix-extended strand-helix motif and similar motifs have been found in other nucleic acid-binding proteins critical for DNA repair. However, the exact mechanism of damage recognition and substrate specificity for the Ku heterodimer remains unclear in part due to the absence of a high-resolution structure of the SAP/DNA complex. We performed a series of molecular dynamics (MD) simulations on a system with the SAP domain of Ku70 and a 10 base pairs DNA duplex. Large-scale conformational changes were observed and some putative binding modes were suggested based on energetic analysis. These modes are consistent with previous experimental investigations. In addition, the results indicate that cooperation of SAP with other domains of Ku70/80 is necessary to explain the high affinity of binding as observed in experiments.

Hu, Shaowen↗
NASA NTRS2007

Interactions of the C-terminal Domain of Human Ku70 with DNA Substrate: A Molecular Dynamics Study

NASA is developing a systems biology approach to improve the assessment of health risks associated with space radiation. The primary toxic and mutagenic lesion following radiation exposure is the DNA double strand break (DSB), thus a model incorporating proteins and pathways important in response and repair of this lesion is critical. One key protein heterodimer for systems models of radiation effects is the Ku(sub 70/80) complex. The Ku70/80 complex is important in the initial binding of DSB ends following DNA damage, and is a component of nonhomologous end joining repair, the primary pathway for DSB repair in mammalian cells. The C-terminal domain of Ku70 (Ku70c, residues 559-609), contains an helix-extended strand-helix motif and similar motifs have been found in other nucleic acid-binding proteins critical for DNA repair. However, the exact mechanism of damage recognition and substrate specificity for the Ku heterodimer remains unclear in part due to the absence of a high-resolution structure of the Ku70c/DNA complex. We performed a series of molecular dynamics (MD) simulations on a system with the subunit Ku70c and a 14 base pairs DNA duplex, whose starting structures are designed to be variable so as to mimic their different binding modes. By analyzing conformational changes and energetic properties of the complex during MD simulations, we found that interactions are preferred at DNA ends, and within the major groove, which is consistent with previous experimental investigations. In addition, the results indicate that cooperation of Ku70c with other subunits of Ku(sub 70/80) is necessary to explain the high affinity of binding as observed in experiments.

Hu, Shaowen↗
NASA NTRS2015

Preliminary Work Domain Analysis for Human Extravehicular Activity

A work domain analysis (WDA) of human extravehicular activity (EVA) is presented in this study. A formative methodology such as Cognitive Work Analysis (CWA) offers a new perspective to the knowledge gained from the past 50 years of living and working in space for the development of future EVA support systems. EVA is a vital component of human spaceflight and provides a case study example of applying a work domain analysis (WDA) to a complex sociotechnical system. The WDA presented here illustrates how the physical characteristics of the environment, hardware, and life support systems of the domain guide the potential avenues and functional needs of future EVA decision support system development.

McGuire, Kerry↗
DOE OSTI2024

A ligand discovery toolbox for the WWE domain family of human E3 ligases

The WWE domain is a relatively under-researched domain found in twelve human proteins and characterized by a conserved tryptophan-tryptophan-glutamate (WWE) sequence motif. Six of these WWE domain-containing proteins also contain domains with E3 ubiquitin ligase activity. The general recognition of poly-ADP-ribosylated substrates by WWE domains suggests a potential avenue for development of Proteolysis-Targeting Chimeras (PROTACs). Here, we present novel crystal structures of the HUWE1, TRIP12, and DTX1 WWE domains in complex with PAR building blocks and their analogs, thus enabling a comprehensive analysis of the PAR binding site structural diversity. Furthermore, we introduce a versatile toolbox of biophysical and biochemical assays for the discovery and characterization of novel WWE domain binders, including fluorescence polarization-based PAR binding and displacement assays, 15 N-NMR-based binding affinity assays and 19 F-NMR-based competition assays. Through these assays, we have characterized the binding of monomeric iso -ADP-ribose ( iso -ADPr) and its nucleotide analogs with the aforementioned WWE proteins. Finally, we have utilized the assay toolbox to screen a small molecule fragment library leading to the successful discovery of novel ligands targeting the HUWE1 WWE domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Ground Truth Program: Simulations as Test Beds for Social Science Research Methods.

Social systems are uniquely complex and difficult to study, but understanding them is vital to solving the world’s problems. The Ground Truth program developed a new way of testing the research methods that attempt to understand and leverage the Human Domain and its associated complexities. The program developed simulations of social systems as virtual world test beds. Not only were these simulations able to produce data on future states of the system under various circumstances and scenarios, but their causal ground truth was also explicitly known. Research teams studied these virtual worlds, facilitating deep validation of causal inference, prediction, and prescription methods. The Ground Truth program model provides a way to test and validate research methods to an extent previously impossible, and to study the intricacies and interactions of different components of research.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Development of a Human Systems Integration Plan

NASA defines Human Systems Integration (HSI) as part of the overall systems engineering and acquisition strategy for space systems. The HSI Plan defines how HSI activities will be implemented across the lifecycle of the mission, as required by NPR 7123.1C, NASA Systems Engineering Processes and Requirements, and NPR 8705.2C Human-Rating Requirements for Space Systems. The goal of this presentation is to share with government and industry how an HSI Plan can be implemented. The presentation will cover HSI implementation for flight systems, vehicle processing, and interfaces. These are divided into six NASA HSI Domains: human factors engineering, operations resources, safety, training, maintainability and supportability, habitability and environment. HSI activities go across the mission’s lifecycle from pre-formulation and acquisition through design, development, operations, maintenance, and decommissioning. The HSI Plan includes a description of the HSI activities and products that are essential for human rating, operability, maintainability, supportability, and affordability of the mission systems. It also describes the role of the HSI Team required as part of the Human Rating process. The HSI Plan utilizes the operational expertise within NASA to ensure designs and testing are successful, leading to acceptable human spaceflight vehicles.

Jackelynne Silva-Martinez↗
NASA NTRSDate not supplied

Implementation of Human Systems Integration Technical and Management Process for the Lunar Gateway Program

NASA recognizes Human Systems Integration (HSI) as part of the overall systems engineering and acquisition strategy for space systems. The Lunar Gateway Program is implementing HSI technical and management process across the lifecycle of the mission, as required by NPR 7123.1C NASA Systems Engineering Processes and Requirements, and led by the Gateway HSI team as required by NPR 8705.2C Human-Rating Requirements for Space Systems, now HEOMD-003 Crewed Deep Space Systems Human Rating Certification Requirements and Standards for NASA Missions. NASA has been using HSI principles for many years and has applied them to many of its previous human spaceflight Programs. As NASA returns to the Moon in a more sustainable manner, the Gateway Program is maturing the application of HSI by implementing it more visibly as part of Artemis, with guidance from the NASA/SP-20210010952 NASA HSI Handbook. This paper discusses how HSI is being implemented in the Gateway Program, challenges faced with its implementation during the development phase, and strategies/approaches used to overcome those. The paper also covers HSI implementation for flight systems, vehicle processing, and interfaces across the six identified NASA HSI Domains: human factors engineering, operations, safety, training, maintainability and supportability, habitability and environment. The goal is to provide an overview of the implementation process of HSI in the Gateway Program as an example for other Programs/Projects/Missionsthat are looking to implement HSI.

Jackelynne Silva-Martinez↗
DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development of a Framework for Data Integration, Assimilation, and Learning for Geological Carbon Sequestration (DIAL-GCS) (Final Report)

This project aimed to develop and demonstrate a Data Integration, Assimilation, and Learning framework for geologic carbon sequestration projects (DIAL-GCS). DIAL-GCS is an intelligence monitoring system (IMS) for automating GCS closed-loop management by leveraging recent developments in machine learning technologies, complex event processing (CEP), and reduced-order modeling. The safe and efficient operation of GCS repositories requires integrated monitoring to track the injected CO¬2 as it moves within a storage reservoir. GCS projects are data intensive, as a result of proliferation of digital instrumentation and smart-sensing technologies. GCS projects are also resource intensive, often requiring multidisciplinary teams performing different monitoring, verification, accounting (MVA) tasks throughout the lifecycle of a project to ensure secure containment of injected CO2. The success of GCS thus depends in a large part on our ability to access, assimilate, and analyze heterogeneous data and information sources in a timely manner. This project included a number of meaningful and necessary tasks to transform the human domain knowledge into machine-interpretable rules for automating knowledge extraction and discovery in GCS. The specific technical objectives of the proposed DIAL-GCS project were to develop an ontology-driven GCS data management module for storing, querying, and exchanging GCS data (both historic and live sensor data) from multiple sources and in heterogeneous formats. Incorporate a CEP engine for detecting abnormal situations by seamlessly combining expert knowledge, rule-based reasoning, and machine learning. Enable uncertainty quantification and predictive analytics using a combination of coupled-process modeling, AI/ML methods, and reduced-order modeling, and integrate and demonstrate the system’s capabilities with both real and simulated data. As far as we know, this is one of the first projects aimed to develop intelligent monitoring systems (IMS) targeting the GCS. Under this project, the team had developed a large number of web applications and scientific algorithms that contribute the main theme of intelligent monitoring. The team has published more than a dozen peer reviewed papers and disseminated the research results at multiple technical meetings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2014

Overview of the Contributing Factor Map and How it can Support your Research

The Contributing Factor Map (CFM) is a visual representation of a taxonomy of factors influencing human health and performance in space. This presentation will give an overview of its development and its structure. It will describe various uses of the CFM that can support researchers working within the Human Research Program (HRP) Architecture of Evidence-Risk-Gap-Task-Deliverable. For example, during the Risk phase, the CFM can be used as a "menu" to help formulate a qualitative model of the factors contributing to specific consequences of concern. It provides a reference set of factors from across the operational, vehicle design, and human domains that otherwise might not be considered if approaching a risk from a specific domain perspective. Using the CFM as a reference can increase awareness of potential cross-disciplinary collaborations for overall risk mitigation. The CFM can also be used as a framework for identifying gaps in knowledge about a risk. This identification can support the subsequent development of gaps and tasks comprising the research plan aimed at risk mitigation. Examples of these types of applications of the CFM will be discussed and information on the support available to researchers in using it will be provided.

Mindock, Jennifer A.↗