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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mediation of Colloidal Encounter Dynamics by Surface Roughness

Rigorous understanding on the self-assembly of colloidal nanocrystals is crucial to develop tailored nanostructured materials for energy storage, sensing, and optical fields. Despite extensive studies on the self-assembly, a mechanistic understanding of self-assembly under an external field still remains an ongoing challenge. Here, in this work, we used optical tweezers that impose an external attractive force field, resulting in the self-assembly of alpha-phase sodium yttrium fluoride nanocrystals. The dynamic force that is strongly dependent on the surface roughness of the nanocrystals is shown to be a decisive factor for a direct contact between the nanocrystals, manifested by the roughness-dependent hydrodynamic resistivity and Langevin dynamic simulations. Our study provides direct evidence that the role of dynamics is equally important in understanding the self-assembly, which has been rarely observed in the self-assembly in contrast with many studies on the equilibrium forces. These results may have further impact in other fields, such as having explanatory power for the probability of nonclassical crystal growth or the structure of viral spike proteins that affect the probability of viruses binding with cells.

Felsted, Robert G. [Univ. of Washington, Seattle, ↗
NASA NTRS2003

The evolution of transcriptional regulation in eukaryotes

Gene expression is central to the genotype-phenotype relationship in all organisms, and it is an important component of the genetic basis for evolutionary change in diverse aspects of phenotype. However, the evolution of transcriptional regulation remains understudied and poorly understood. Here we review the evolutionary dynamics of promoter, or cis-regulatory, sequences and the evolutionary mechanisms that shape them. Existing evidence indicates that populations harbor extensive genetic variation in promoter sequences, that a substantial fraction of this variation has consequences for both biochemical and organismal phenotype, and that some of this functional variation is sorted by selection. As with protein-coding sequences, rates and patterns of promoter sequence evolution differ considerably among loci and among clades for reasons that are not well understood. Studying the evolution of transcriptional regulation poses empirical and conceptual challenges beyond those typically encountered in analyses of coding sequence evolution: promoter organization is much less regular than that of coding sequences, and sequences required for the transcription of each locus reside at multiple other loci in the genome. Because of the strong context-dependence of transcriptional regulation, sequence inspection alone provides limited information about promoter function. Understanding the functional consequences of sequence differences among promoters generally requires biochemical and in vivo functional assays. Despite these challenges, important insights have already been gained into the evolution of transcriptional regulation, and the pace of discovery is accelerating.

Review, Academic↗
DOE OSTI2021

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. Here, the framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2026

Tracking the protein conformational motions driving HIV-1 membrane fusion

HIV-1 Env (trimeric gp120/gp41) is the surface protein responsible for membrane fusion. The Env binds to the receptor proteins, which induces gp120 shedding leading to conformational changes of gp41 from the pre-fusion to post-fusion state, allowing its fusion peptide to embed in the host cell membrane and bringing the viral and host cell membranes together. The gp41 refolding is a target of several peptide inhibitors. Yet, the molecular mechanism of this dynamic process is still not well understood. In this study, we successfully simulate the conformational change of gp41 from pre-fusion to post-fusion state in atomistic resolution using all-atom structure-based models. We reveal that maintaining the directionality of protomer interactions in both pre-fusion and post-fusion states is crucial for gp41 refolding. Additionally, we find that HR1 inherently extends as a three-helical bundle toward the host-cell membrane without any bias. Importantly, we identify native contacts in the pre-fusion state that are critical for the proper refolding of gp41 towards the post-fusion state. Lastly, by incorporating the membrane-fusion inhibitors, T20 and SFT, we identify the most vulnerable stage in the fusion pathway that exhibits the greatest sensitivity to these drugs, which could aid in a better understanding of drug resistance mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Dynamic telerobotic control of crystallization experiments

A dynamically controlled system has been used to prepare crystals of lysozyme. The temperature of the crystallization chamber was adjusted based upon a scintillation signal used to detect the degree of nucleation and incipient crystal growth. Experiments conducted in one country were controlled and monitored by researchers in another, providing the first demonstration of telerobotic control of a protein crystallization experiment.

Ward, K. B.↗
DOE OSTI2023

Mathematical modeling of plus-strand RNA virus replication to identify broad-spectrum antiviral treatment strategies

Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called “replication factories”), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and showed that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency, which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, such as polyprotein cleavage and viral RNA synthesis, may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the in vitro viral replication early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Chickpea NCR13 disulfide cross-linking variants exhibit profound differences in antifungal activity and modes of action

Small cysteine-rich antifungal peptides with multi-site modes of action (MoA) have potential for development as biofungicides. In particular, legumes of the inverted repeat-lacking clade express a large family of nodule-specific cysteine-rich (NCR) peptides that orchestrate differentiation of nitrogen-fixing bacteria into bacteroids. These NCRs can form two or three intramolecular disulfide bonds and a subset of these peptides with high cationicity exhibits antifungal activity. However, the importance of intramolecular disulfide pairing and MoA against fungal pathogens for most of these plant peptides remains to be elucidated. Our study focused on a highly cationic chickpea NCR13, which has a net charge of +8 and contains six cysteines capable of forming three disulfide bonds. NCR13 expression in Pichia pastoris resulted in formation of two peptide folding variants, NCR13_PFV1 and NCR13_PFV2, that differed in the pairing of two out of three disulfide bonds despite having an identical amino acid sequence. The NMR structure of each PFV revealed a unique three-dimensional fold with the PFV1 structure being more compact but less dynamic. Surprisingly, PFV1 and PFV2 differed profoundly in the potency of antifungal activity against several fungal plant pathogens and their multi-faceted MoA. PFV1 showed significantly faster fungal cell-permeabilizing and cell entry capabilities as well as greater stability once inside the fungal cells. Additionally, PFV1 was more effective in binding fungal ribosomal RNA and inhibiting protein translation in vitro. Furthermore, when sprayed on pepper and tomato plants, PFV1 was more effective in reducing disease symptoms caused by Botrytis cinerea, causal agent of gray mold disease in fruits, vegetables, and flowers. In conclusion, our work highlights the significant impact of disulfide pairing on the antifungal activity and MoA of NCR13 and provides a structural framework for design of novel, potent antifungal peptides for agricultural use.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

ESnet Requirements Review Program Through the IRI Lens: A Meta-Analysis of Workflow Patterns Across DOE Office of Science Programs (Final Report)

The Department of Energy (DOE) ensures America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. The DOE’s Office of Science (SC) delivers groundbreaking scientific discoveries and major scientific tools that transform our understanding of nature and advance the energy, economic, and national security of the United States. The SC’s programs advance DOE mission science across a wide range of disciplines and have developed the research infrastructure needed to remain at the forefront of scientific discovery. The DOE SC’s world-class research infrastructure — exemplified by the 28 SC scientific user facilities — provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. A hallmark of many facilities is the large population of students, postdoctoral researchers, and early-career scientists who contribute as full-fledged users. These facility staff and users collaborate over years to devise new approaches to utilizing the user facility’s core capabilities. The history of the SC user facilities has many examples of wildly inventive researchers challenging operational orthodoxy to pioneer new vistas of discovery; for example, the use of the synchrotron X-ray light sources for study of proteins and other large biological molecules. This continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high performance data, networking, and computing solutions. The DOE SC’s three HPC user facilities and the Energy Sciences Network (ESnet) high-performance research network serve all of the SC’s programs as well as the global research community. Argonne Leadership Computing Facility (ALCF), the National Energy Research Scientific Computing Center (NERSC), and Oak Ridge Leadership Computing Facility (OLCF) conceive, build, and provide access to a range of supercomputing, advanced computing, and large-scale data-infrastructure platforms, while ESnet interconnects DOE SC research infrastructure and enables seamless exchange of scientific data. All four facilities operate testbeds to expand the frontiers of computing and networking research. Together, the ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements reviews (RRs) methodology. In recent years, the research communities around the SC user facilities have begun experimenting with and demanding solutions integrated with HPC and data infrastructure. This rise of integrated-science approaches is documented in many community and high-level government reports. At the dawn of the era of exascale science and the acceleration of artificial intelligence (AI) innovation, there is a broad need for integrated computational, data, and networking solutions. In response to these drivers, DOE has developed a vision for an Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation.

42 ENGINEERING↗
DOE OSTI2025

CFD Simulation of Aerobic Gas Fermentation to Enable Commercial Conversion of CO 2 into Aquaculture and Animal Feed: Cooperative Research and Development (Final Report)

NovoNutrients’ fermentation technology uses energy from hydrogen to transform industrial CO2 emissions into premium animal feed ingredients and other valuable products. A single NovoNutrients’ commercial manufacturing plant will capture and convert over 200,000 tons/yr of CO2 into over 100,000 tons/yr of high-protein feed. Key to the rapid and widespread deployment of the technology is maximization of its productivity and energy efficiency. Robust, physically based computational models of the technology will significantly increase productivity and efficiency, accelerating NovoNutrients’ technology to manufacturing scale. NREL has unique capabilities for creating and running such computational models. NREL's existing aerobic bioreaction computational fluid dynamics (CFD) models will be adapted to NovoNutrients’ gas fermentation (CO2, H2, O2) technology. The multiphysics CFD simulations require thousands of high-performance computing (HPC) node hours to simulate the complex geometries and contents of NovoNutrients’ industrial bioreactors. The experimentally validated CFD models were used to identify optimally efficient and productive bioreactor designs and operating conditions.

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

Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro

As temperatures decrease in autumn, vegetation of temperate and boreal ecosystems increases its tolerance to freezing. This process, known as hardening, results in a set of physiological changes at the molecular level that initiate modifications of cell membrane composition and the synthesis of anti-freeze proteins. Together with the freezing of extracellular water, anti-freeze proteins reduce plant water potentials and xylem conductivity. To represent the responses of vegetation to climate change, land surface schemes increasingly employ “hydrodynamic” models that represent the explicit fluxes of water from soil and through plants. The functioning of such schemes under frozen soil conditions, however, is poorly understood. Nonetheless, hydraulic processes are of major importance in the dynamics of these systems, which can suffer from, e.g., winter “frost drought” events. In this study, we implement a scheme that represents hardening into CLM5.0-FATES-Hydro. FATES-Hydro is a plant hydrodynamics module in FATES, a cohort model of vegetation physiology, growth, and dynamics hosted in CLM5.0. We find that, in frozen systems, it is necessary to introduce reductions in plant water loss associated with hardening to prevent winter desiccation. This work makes it possible to use CLM5.0-FATES-Hydro to model realistic impacts from frost droughts on vegetation growth and photosynthesis, leading to more reliable projections of how northern ecosystems respond to climate change.

58 GEOSCIENCES↗
NASA NTRS1982

The possible role of soluble salts in chemical evolution

A model for a prebiotic environment in which concentration, condensation, and chemical evolution of biomolecules could have occurred is proposed. The principal reactions expected of proteins, nucleic acids, lipids, and some of their precursors in this environment are discussed. The model is based on the concept of a fluctuating system in which hydration and dehydration processes occur in a cyclic manner, with allowance for high concentrations of soluble salts, such as chlorides and sulfates. It is concluded that the proposed prebiotic environment with its dynamical characteristics is a plausible model for the chemical evolution from biomonomers through random oligomers toward self-replicating chemical systems.

Lahav, N.↗
NASA NTRS1994

Convective flow effects on protein crystal growth

The long-term stability of the interferometric setup for the monitoring of protein morphologies has been improved. Growth or dissolution of a crystal on a 100 A scale can now be clearly distinguished from dimensional changes occurring within the optical path of the interferometer. This capability of simultaneously monitoring the local interfacial displacement at several widely-spaced positions on the crystal surface with high local depth resolution, has already yielded novel results. We found with lysozyme that (1) the normal growth rate is oscillatory, and (2) the mean growth step density is greater at the periphery of a facet than in its center. The repartitioning of Na(+) and Cl(-) ions between lysozyme solutions and crystals was studied for a wide range of crystallization conditions. A nucleation-growth-repartitioning model was developed to interpret the large body of data in a unified way. The results strongly suggests that (1) the ion to lysozyme ratio in the crystal depends mostly on kinetic rather than crystallographic parameters, and (2) lysozyme crystals possess a salt-rich core with a diameter on the order of 10 microns. The computational model for diffusive-convective transport in protein crystallization (see the First Report) has been applied to a realistic growth cell geometry, taking into account the findings of the above repartitioning studies. These results show that some elements of a moving boundary problem must be incorporated into the model in order to obtain a more realistic description. Our experimental setup for light scattering investigations of aggregation and nucleation in protein solutions has been extensively tested. Scattering intensity measurements with a true Rayleigh scatterer produced systematically increased forward scattering, indicating problems with glare. These have been resolved. Preliminary measurements with supersaturated lysozyme solutions revealed that the scatterers grow with time. Work has begun on a computer program for the unified evaluation of simultaneously obtained, multi-angle static and dynamic light scattering data.

Rosenberger, Franz↗
NASA NTRS1996

Formation of Ordered Arrays of Proteins on Surfaces

Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. While the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models, with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation and crystal growth.

Lenhoff, A. M.↗
NASA NTRS1996

Van der Waals Interactions Involving Proteins

Van der Waals (dispersion) forces contribute to interactions of proteins with other molecules or with surfaces, but because of the structural complexity of protein molecules, the magnitude of these effects is usually estimated based on idealized models of the molecular geometry, e.g., spheres or spheroids. The calculations reported here seek to account for both the geometric irregularity of protein molecules and the material properties of the interacting media. Whereas the latter are found to fall in the generally accepted range, the molecular shape is shown to cause the magnitudes of the interactions to differ significantly from those calculated using idealized models. with important consequences. First, the roughness of the molecular surface leads to much lower average interaction energies for both protein-protein and protein-surface cases relative to calculations in which the protein molecule is approximated as a sphere. These results indicate that a form of steric stabilization may be an important effect in protein solutions. Underlying this behavior is appreciable orientational dependence, one reflection of which is that molecules of complementary shape are found to exhibit very strong attractive dispersion interactions. Although this has been widely discussed previously in the context of molecular recognition processes, the broader implications of these phenomena may also be important at larger molecular separations, e.g., in the dynamics of aggregation, precipitation, and crystal growth.

Roth, Charles M.↗
NASA NTRS1982

Dynamics of weight loss during prolonged spaceflight

Data from three Skylab flights lasting 28, 59, and 84 days are used to study changes in body composition occurring during extended spaceflight. The analysis includes pre- and postflight measurements used to compute lean body mass and body fat losses for an entire mission using previously accepted methods based on total body water, potassium, and density, and also includes the daily metabolic balances in order to provide an estimate of the time course of the changes in water, protein, and fat. The analytical approach is explained and the results presented, including a summary of changes in lean body mass and changes in weight loss and tissue components. It is concluded that little more than half of the weight loss observed during the missions can be attributed to loss in lean body mass, the remainder being derived from fat stores.

Leach, C. S.↗
DOE OSTI2021

A conserved epitope III on hepatitis C virus E2 protein has alternate conformations facilitating cell binding or virus neutralization

Epitope III, a highly conserved amino acid motif of 524 APTYSW 529 on the hepatitis C virus (HCV) E2 glycoprotein, resides in the critical loop that binds to the host receptor CD81, thus making it one of the most important antibody targets for blocking HCV infections. Here, we have determined the X-ray crystal structure of epitope III at a 2.0-Å resolution when it was captured by a site-specific neutralizing antibody, monoclonal antibody 1H8 (mAb1H8). The snapshot of this complex revealed that epitope III has a relatively rigid structure when confined in the binding grooves of mAb1H8, which confers the residue specificity at both ends of the epitope. Such a high shape complementarity is reminiscent of the “lock and key” mode of action, which is reinforced by the incompatibility of an antibody binding with an epitope bearing specific mutations. By subtly positioning the side chains on the three residues of Tyr 527 , Ser 528 , and Trp 529 while preserving the spatial rigidity of the rest, epitope III in this cocrystal complex adopts a unique conformation that is different from previously described E2 structures. With further analyses of molecular docking and phage display–based peptide interactions, we recognized that it is the arrangements of two separate sets of residues within epitope III that create these discrete conformations for the epitope to interact selectively with either mAb1H8 or CD81. These observations thus raise the possibility that local epitope III conformational dynamics, in conjunction with sequence variations, may act as a regulatory mechanism to coordinate “mAb1H8-like” antibody-mediated immune defenses with CD81-initiated HCV infections.

59 BASIC BIOLOGICAL SCIENCES↗