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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Spontaneous rearrangement of acetylated xylan on hydrophilic cellulose surfaces

The interaction of xylan, an abundant plant polysaccharide, with cellulose microfibrils is essential for secondary cell wall strength. A deeper understanding of these interactions is crucial both to improve our understanding of plant cell wall architecture and to design alternate strategies to overcome cellulose recalcitrance for the production of biofuels and sustainable biomaterials. Naturally occurring acetate or glucuronic acid substitutions on xylan have been shown to influence xylan-cellulose interactions. In this work, we use unrestrained molecular dynamics simulations to determine the interactions with the (110) hydrophilic face of cellulose fibers of four different xylans. In the absence of cellulose, all xylans, independent of the substitution pattern, adopt a highly flexible threefold helical screw conformation. However, when xylan is spatially close to a cellulose surface 1,2 linked acetyl xylans (2AcX) adopt rigid twofold helical screw conformations. The 2AcX conformations are primarily stabilized by interactions between the acetylated oxygen and the glycosidic linkage with C-O6 of cellulose. In contrast, the glycosidic oxygens and acetyl decorations for 1,3 linked acetyl groups (3AcX) are oriented away from the cellulose surface and the 3AcX xylans maintain threefold helical screw conformations on the cellulose surface. Our results show that evenly spaced chemical functionalization (with acetyl groups) and the position of substitution (1,2) on xylan backbone play key roles in tuning the xylan-cellulose interactions to stabilize the twofold helical screw conformations of xylan on the cellulose surface. A comparison with previous experimental findings further suggests that 1,2 substitutions induce twofold helical screw conformations of xylan on the cellulose surface irrespective of the chemical nature of the substituent, while 1,3 substitutions primarily bind lignin in threefold helical screw conformations rather than cellulose in plant cell walls.

1,2 Ac↗
DOE OSTI2022

Structural characterization and biological activity of an α-glucan from the mollusk Marcia hiantina (Lamarck, 1818)

Marcia hiantina (Mollusca, Bivalvia) (Lamarck, 1818), is an edible clam mainly distributed along the tropical coastal regions. Recent researches have demonstrated that clams can possess compounds, including polysaccharides, with a wide range of biological actions including antioxidant, immunomodulatory and antitumor activities. Here an α-glucan was isolated from M. hiantina by hot water, purified by anion exchange chromatography, and its structure was characterized by a combination of multiple nuclear magnetic resonance (NMR) methods (1D 1 H, 1 H- 1 H COSY, 1 H- 1 H TOCSY, 1 H- 1 H NOESY, 1 H- 13 C HSQC and 1 H- 13 C HSQC-NOESY spectra), gas chromatography-mass spectrometry, and high performance size exclusion chromatography (HPSEC). The analysis from NMR, monosaccharide composition, methylation analyses and HPSEC combined with multi angle light scattering (MALS) of M. hiantina-derived α-glycan confirmed a branched polysaccharide exclusively composed of glucose (Glc), mostly 4-linked in its backbone, branched occasionally at 6-positions, and having a molecular weight of ~ 570 kDa. The mollusk α-glucan was subjected to four cell-based assays: (i) viability of three cell lines (RAW264.7, HaCaT, and HT-29), (ii) activity on lipopolysaccharide (LPS)-induced prostaglandin production in RAW264.7 cells, (iii) inhibitory activities of in H 2 O 2 - and LPS-induced reactive oxygen species (ROS) production in HMC3 cells, and (iv) HaCaT cell proliferation. Furthermore, results have indicated no cytotoxicity, potent inhibition of both H 2 O 2 - and LPS-induced ROS, and potent cell proliferative activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Peptide nucleic acid Hoogsteen strand linker design for major groove recognition of DNA thymine bases

Sequence-specific targeting of double-stranded DNA and non-coding RNA via triple-helix-forming peptide nucleic acids (PNAs) has attracted considerable attention in therapeutic, diagnostic and nanotechnological fields. An E-base (3-oxo-2,3-dihydropyridazine), attached to the polyamide backbone of a PNA Hoogsteen strand by a side-chain linker molecule, is typically used in the hydrogen bond recognition of the 4-oxo group of thymine and uracil nucleic acid bases in the major groove. We report on the application of quantum chemical computational methods, in conjunction with spatial constraints derived from the experimental structure of a homopyrimidine PNA·DNA-PNA hetero-triplex, to investigate the influence of linker flexibility on binding interactions of the E-base with thymine and uracil bases in geometry-optimised model systems. Hydrogen bond formation between the N2 E-base atom and target pyrimidine base 4-oxo groups in model systems containing a β-alanine linker (J Am Chem Soc 119:11116, 1997) was found to incur significant internal strain energy and the potential disruption of intra-stand aromatic base stacking interactions in an oligomeric context. Additionally, in geometry-optimised model systems containing a 3-trans olefin linker (Bioorg Med Chem Lett 14:1551, 2004) the E-base swung out away from the target pyrimidine bases into the solvent. These findings are in qualitative agreement with calorimetric measurements in hybridisation experiments at T–A and U–A inversion sites. In contrast, calculations on a novel 2-cis olefin linker design indicate that it could permit simultaneous E-base hydrogen bonding with the thymine 4-oxo group, circumvention and solvent screening of the thymine 5-methyl group, and maintenance of triplex intra-stand base stacking interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Characterizing Reactive Transport Behavior in a Three-Dimensional Discrete Fracture Network

While several studies have linked network and in-fracture scale properties to conservative transport behavior in subsurface fractured media, studies on reactive transport cases remain relatively underdeveloped. In this study, we explore the behavior of an irreversible kinetic reaction during the interaction of two solute plumes, one consisting of species A and the other species B. When the plumes converge, these species react kinetically to form a new species C via A+B→kC. This reactive system is studied using a three-dimensional discrete fracture network (DFN) model coupled with reactive Lagrangian particle tracking. We find that the interplay of network topology and chemical properties of the reactive solutes controls reactive transport processes. The network topology drives species A and B together, and the chemical properties dictate whether and how quickly a reaction occurs. Results demonstrate that reactions are most likely to occur in high-velocity fractures that make up the network backbone. The interplay between species’ chemical properties and transport is characterized by a non-dimensional Damköhler (Da) number. We show that the spatial distribution of reactions is sensitive to Da, which subsequently influences late-time tailing behavior in outlet breakthrough time distributions. The results of this study provide initial insights into how an irreversible reaction occurs during transport in a fracture network, using a methodology that can be applied to study reactive transport in a wide range of fractured media environments and contexts.

58 GEOSCIENCES↗
DOE OSTI2021

Machine-Learning-based Algorithms for Automated Image Segmentation Techniques of Transmission X-ray Microscopy (TXM)

Four state-of-the-art Deep Learning-based Convolutional Neural Networks (DCNN) were applied to automate the semantic segmentation of a 3D Transmission x-ray Microscopy (TXM) nanotomography image data. The standard U-Net architecture as baseline along with UNet++, PSPNet, and DeepLab v3+ networks were trained to segment the microstructural features of an AA7075 micropillar. A workflow was established to evaluate and compare the DCNN prediction dataset with the manually segmented features using the Intersection of Union (IoU) scores, time of training, confusion matrix, and visual assessment. Comparing all model segmentation accuracy metrics, it was found that using pre-trained models as a backbone along with appropriate training encoder-decoder architecture of the Unet++ can robustly handle large volumes of x-ray radiographic images in a reasonable amount of time. This opens a new window for handling accurate and efficient image segmentation of in situ time-dependent 4D x-ray microscopy experimental datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Wafer-scale quasi-layered tungstate-doped polypyrrole film with high volumetric capacitance

Layered materials are particularly attractive for supercapacitors because of their unique physical, electrical and chemical properties. In this work, we demonstrate a facile and scalable electrochemical deposition method for wafer-scale synthesis of quasi-layered tungstate-doped polypyrrole films (named TALPy) with controllable thickness and size. The as-prepared TALPy film exhibits a high gravimetric density and excellent volumetric capacitance, exceeding many high-performing carbon- and polymer-based film electrodes. Based on combined results of ex-situ X-ray diffraction (XRD), Raman and X-ray photoelectron spectroscopy (XPS), it is determined that TALPy stores charge through an ion intercalation process accompanied by change in oxidation states of polypyrrole backbone, which is referred as intercalation pseudocapacitance. All these results suggest the great promise of electrochemical deposition as a scalable and controllable bottom-up approach for synthesizing quasi-layered conductive organic-inorganic hybrid films for electrochemical energy storage applications with high volumetric performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing

Abstract The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence conducted on relatively small scales. This poses problems for typically data-hungry machine learning tools which could otherwise expedite the development cycle. We build upon prior work by applying conditional generative adversarial networks (GANs) to scanning electron microscope (SEM) imagery from an emerging advanced manufacturing process, shear-assisted processing and extrusion (ShAPE). We generate realistic images conditioned on temper and either experimental parameters or material properties. In doing so, we are able to integrate machine learning into the development cycle, by allowing a user to immediately visualize the microstructure that would arise from particular process parameters or properties. This work forms a technical backbone for a fundamentally new approach for understanding manufacturing processes in the absence of first-principle models. By characterizing microstructure from a topological perspective, we are able to evaluate our models’ ability to capture the breadth and diversity of experimental scanning electron microscope (SEM) samples. Our method is successful in capturing the visual and general microstructural features arising from the considered process, with analysis highlighting directions to further improve the topological realism of our synthetic imagery.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-performance n-Type Polymers Based on Multiple Electron-withdrawing Groups Decorated ( E )-1,2-Di(thiophen-2-yl)ethene Building Blocks

The performance of n-type conjugated polymers lags far behind that of p-type polymers, which significantly restricts the development of organic electronics. The (E)-1,2-di(thiophen-2-yl)ethene (TVT) unit, owing to its unique advantages, has been widely applied in the design of p-type polymer semiconductors. Previous studies have demonstrated that introducing electron-withdrawing groups can lower the frontier orbital energy levels of polymers and enhance electron injection/transporting capabilities. Based on this, we proposed incorporating multiple electronwithdrawing groups, such as amide groups, fluorine atoms, and cyano groups, into the polymer backbones of TVT-based polymer to facilitate the electron transport. Here, we successfully designed and synthesized the polymers TVTDA-4FTVT and TVTDA-2F2CNTVT. Both polymers exhibited low frontier orbital energy levels. Due to its significantly higher crystallization tendency and favorable intermolecular packing structure, the organic field-effect transistor (OFET) device based on TVTDA-4FTVT demonstrated an electron mobility one order of magnitude higher than that of TVTDA-2F2CNTVT. TVTDA-4FTVT showed the highest electron mobility of 0.87 cm 2 ·V −1 ·s −1 , while TVTDA-2F2CNTVT exhibited the highest electron mobility of 0.049 cm 2 ·V −1 ·s −1 . Owing to its deeper lowest unoccupied molecular orbital (LUMO) level, the OFET devices based on TVTDA-2F2CNTVT showed good air stability after being placed in a natural environment for 15 d.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Validation of a Tapered Impact Damper for Traffic Signal Structure Vibrations Using the Method of Harmonic Balance

Significant vibration amplitudes and cycles can be produced when traffic signal structures with low inherent damping are excited near one of their natural frequencies. For the mitigation of wind-induced vibrations, dynamic vibration absorbers coupled to the structure are often used. Here, this research investigates the performance of a tapered impact damper, consisting of a hanging spring-mass oscillator inside a housing capable of reducing vibration amplitude over a broader frequency range than the conventional tuned mass damper. A nonlinear, two degree-of-freedom model is developed with coordinates representing the traffic structure and the tapered impact damper. This research focuses on the application of the harmonic balance method to approximate the periodic solutions of the nonlinear equations to compute the nonlinear dynamics of the damped traffic signal structure. After designing and manufacturing a tapered impact damper, the traffic signal structure is tested with and without the damper using free vibration snapback tests. The experimental frequency and damping backbone curves are used to validate the analytical model, and the effectiveness of the damper is discussed.

42 ENGINEERING↗
DOE OSTI2023

Green-Solvent Processed Blade-Coating Organic Solar Cells with an Efficiency Approaching 19% Enabled by Alkyl-Tailored Acceptors

Power-conversion-efficiencies (PCEs) of organic solar cells (OSCs) in laboratory, normally processed by spin-coating technology with toxic halogenated solvents, have reached over 19%. However, there is usually a marked PCE drop when the blade-coating and/or green-solvents toward large-scale printing are used instead, which hampers the practical development of OSCs. Here, a new series of N-alkyl-tailored small molecule acceptors named YR-SeNF with a same molecular main backbone are developed by combining selenium-fused central-core and naphthalene-fused end-group. Thanks to the N-alkyl engineering, NIR-absorbing YR-SeNF series show different crystallinity, packing patterns, and miscibility with polymeric donor. The studies exhibit that the molecular packing, crystallinity, and vertical distribution of active layer morphologies are well optimized by introducing newly designed guest acceptor associated with tailored N-alkyl chains, providing the improved charge transfer dynamics and stability for the PM6:L8-BO:YR-SeNF-based OSCs. As a result, a record-high PCE approaching 19% is achieved in the blade-coating OSCs fabricated from a green-solvent o-xylene with high-boiling point. Notably, ternary OSCs offer robust operating stability under maximum-power-point tracking and well-keep > 80% of the initial PCEs for even over 400 h. Our alkyl-tailored guest acceptor strategy provides a unique approach to develop green-solvent and blade-coating processed high-efficiency and operating stable OSCs, which paves a way for industrial development.

14 SOLAR ENERGY↗
DOE OSTI2025

60 years of science in ICF: from conception to scientific breakeven on the National Ignition Facility

The recent achievements of a burning plasma, fusion ignition, and scientific energy gain with deuterium-tritium (DT) fuel at Lawrence Livermore National Laboratory’s National Ignition Facility (NIF) represents a major milestone in the development of inertial confinement fusion (ICF) and all of fusion research. In these experiments, fuel pressures well in excess of hundreds of GBars were achieved in the compressed fuel, and robust alpha heating of the fuel, far in excess of the energy provided by the implosion, were demonstrated for the first time. These achievements occurred 60 years after the inception of ICF and the first laser demonstration, and were made possible by more than five decades of research at laser facilities around the world. Advances in laser technology both in wavelength and precision, motivated by improved understanding of laser-plasma interaction physics and the demands of targets; improvements in target fabrication inspired by the need to control and minimize hydrodynamic instabilities in the implosion; and multi-dimensional simulations and diagnostics have been critical to this achievement. This paper will summarize the scientific and technical advances, the surprises, and the challenges that had to be overcome to achieve these goals.

fusion↗
DOE OSTI2025

Application of Atmospheric Gases and Particulate Matter to the Assessment of Urban Heat Island

Background: Urban heat island (UHI), where built areas are warmer compared to non-urban regions, increases human related diseases and mortality. A key challenge in UHI analysis is the designation of sites as urban or suburban/rural; however, the growing complexity of green spaces in urban areas and the predominance of the transportation sector in nonurban areas creates a dilemma for distinct delineation. Objectives: This study aims to utilize the variability of atmospheric components such as particulate matter (PM), inorganic gases, and volatile organic compounds (VOCs) as direct tracers of the degree of urbanization for ground-based measurements to fully comprehend UHI in convoluted regions with indistinct delineation of urban and nonurban environments. Methods: Atmospheric gases and aerosols were used as direct tracers of urbanization for UHI analysis. Inorganic gases and particulate matter were monitored in two sites in a southeastern US city with varying degrees of urbanization. VOCs were analyzed using a proton transfer reaction time-of-flight mass spectrometer. Results: The more-urbanized site exhibited warmer night conditions and elevated total oxidant levels, leading to the formation of nanometer-sized particles. Machine learning analysis revealed similar atmospheric pollutant profiles for both sites, suggesting comparable sources and variability. Biogenic VOCs were enhanced at the less-urbanized site; however, levels of anthropogenic aromatic VOCs were comparable for both sites. A comprehensive mass spectra analysis revealed distinct molecular backbones per site that further affirmed the applicability of VOCs as indicators of urbanization. Conclusion: This study concludes that VOCs provide more direct and accurate information than typical inorganic gases and PM parameters for characterizing the degree of urbanization. Further exploration of VOCs can enhance our understanding of UHI dynamics and its interaction with vegetation in urban green spaces.

Air quality sensor↗
DOE OSTI2022

GW-PINN: A deep learning algorithm for solving groundwater flow equations

Machine learning methods provide new perspective for more convenient and efficient prediction of groundwater flow. In this study, a deep learning method “GW-PINN” without labeled data for solving groundwater flow equations with wells was proposed. GW-PINN takes the physics inform neural network (PINN) as the backbone and uses either the hard or soft constraint in the loss function for training. A locally refined sampling strategy (LRS) is adopted to generate the consistent spatial sampling points for problems with strong hydraulic head change, and then combined with an appropriate temporal sampling scheme to obtain the final spatial-temporal sampling points. A snowball-style two-stage training strategy by dividing the temporal domain into two subdomains is designed to decrease the sampling points. Five cases were designed to test the training performance of GW-PINN under different sampling strategies and two constraints. The predicted results of GW-PINN were compared with MODFLOW and the analytical solution. The results demonstrate that GW-PINN possesses strong ability in capturing the hydraulic head change for both confined and un-confined aquifers. The hard constraint owns more robust learning ability than the soft constraint. The LRS strategy can generate more accurate results with much fewer sampling points than traditional sampling strategies, and the snowball-style two-stage training strategy is significantly efficient for problems with the drastic change of hydraulic head. Additionally, the application of GW-PINN as a surrogate model for parameterized groundwater flow equations is illustrated. This study provides an option tool for efficient groundwater flow simulation, especially for those with local refinements are needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Structure of the polysaccharide sheath from the B race of the green microalga Botryococcus braunii

The green microalga Botryococcus braunii forms a colony of cells held together by an intricate extracellular matrix. This extracellular matrix also acts as a storage location for liquid hydrocarbons initially produced inside the cells. These hydrocarbons can be used as feedstocks to produce transportation fuels. In the B race of B. braunii, the extracellular matrix is composed of several elements: a cross-linked hydrocarbon network filled with the liquid hydrocarbons, a retaining wall to hold the hydrocarbons in the extracellular matrix, an arabinogalactan polysaccharide fibrillar sheath that extends outward from the retaining wall, and a single protein known as polysaccharide associated protein is found at the base of the polysaccharide fibers where they connect to the retaining wall. During growth, colonies of the B race of B. braunii shed fragments of the retaining wall with polysaccharide fibrils attached into the media. Here we describe the isolation and structural analysis of these polysaccharides using a series of chemical degradations in combination with glycosyl residue composition and linkage analysis, as well as 2-dimensional nuclear magnetic resonance spectroscopy. The results demonstrate that the polysaccharide is highly branched, consisting of a galactan backbone with short branches comprised of Dgalactopyranose, L-arabinofuranose, 4-O-methyl-D-glucopyranuronic acid, and 6-deoxy-D-altropyranose. To our knowledge, this is the first description of 6-deoxyaltrose in algae or plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

OR-AGENT framework – Architecting electrified heavy-duty drayage applications

The widespread adoption of zero-emission vehicles in heavy-duty (HD) commercial freight transportation faces considerable technoeconomic challenges. For heavy-duty trucks, ensuring high uptime, cost parity with diesel, and safety standards is especially critical as these vehicles operate over long distances with heavy loads, where any downtime or off-nominal behaviors significantly impacts logistics, productivity, and the total cost of ownership. Unlike traditional diesel refueling, BEV charging infrastructure must be co-optimized with vehicle deployment, operational demands, and grid capacity to ensure cost-effective and reliable freight operations. However, the lack of a standardized ownership and service model has led to a fragmented approach—where commercial vehicle operators may invest in, own, and maintain both vehicle/batteries and charging/energy infrastructure. This disconnect may exclude energy service providers from the equation, forcing fleet operators to explore ‘behind-the-fence’ energy solutions that increase capital investment, operational downtime, overhead costs, and, in some cases, net carbon emissions. To address these issues, this study introduces OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport), a comprehensive modeling framework that integrates powertrain architectures, charging infrastructures, and energy backbone systems into a cohesive strategy. In this paper, OR-AGENT is applied to develop an interconnected systems architecture for energy efficiency and resiliency enhancement of heavy-duty drayage vehicles at the Port of Savannah, GA. This framework showcases an interconnected systems approach to electrifying heavy-duty drayage vehicles at the Port of Savannah, GA. The study assessed BEVs with 400–1200 kWh battery capacities, accounting for seasonal variations in weather and freight routing. A diverse charging mix (150 kW–1250 kW) was evaluated alongside grid capacity constraints, cost, and carbon intensity analysis, leading to the development of a strategic microgrid/Distributed Energy Resources (DER) deployment architecture to ensure a reliable and sustainable transition. However, the findings also highlight the need for alternative zero-emission solutions for remaining trips, such as larger batteries, electrified roadways, hydrogen powertrains, or net-zero emission fuels. In conclusion, the findings are incorporated into a Total Cost of Ownership (TCO) model to identify optimal architectures for an interconnected electrified ecosystem.

Commercial vehicles↗
DOE OSTI2025

Carbon nanotube coated metal mesh: Bridging nanoscale and macroscale

A novel hybrid structure has been developed by growing carbon nanotubes (CNTs) on a metal mesh that functions as a literally unlimitedly extendable backbone. This hybrid material structure provides a new approach of extending CNTs’ advantageous properties such as ultrahigh thermal and electrical conductivities, high sensitivity to gases, and distinctive wettability for different liquids with chemical inertness to macroscale—otherwise available only in nano- and microscales. In this feasibility work, CNTs were grown on a Type 316 stainless steel (SS) mesh by self-catalytical chemical vapor deposition (CVD) without the need of an externally added catalyst or catalyst support. For the radially aligned and entangled CNT forest on the SS mesh, the average CNT diameter is around 50 nm, while the length varies from 20 to 25 µm. High-resolution transmission electron microscopy analysis revealed the multiwall structure of the CNTs with >30 rolled-up graphitic sheets. Raman spectra of the CNTs showed a dominant G band, indicating a well-ordered graphitic nanostructure. Being highly hydrophobic with a water contact angle of ∼145° and oleophilic, the CNT-coated SS mesh could be used in fluid separation and organic contaminant removal from water. Moreover, CNTs are recognized for their exceptional thermal conductivity and the CNT-coated mesh offers a supportive structure with directly connected CNTs for efficient heat transfer. Proof of concept has been achieved for the CNT-coated mesh’s potentials as a liquid filter and an thermal interface material (TIM). Specifically, the CNT-coated mesh demonstrated the capability of capturing water from a water-organic mixture with a 100 % efficiency while allowing organic liquids to pass through the filter. Furthermore, when used as a TIM, the CNT-coated mesh reduced the interfacial thermal impedance by >30 %.

Carbon nanotubes (CNTS)↗
DOE OSTI2023

Evaluation of darunavir-derived HIV-1 protease inhibitors incorporating P2' amide-derivatives: Synthesis, biological evaluation and structural studies

Here, we report here the synthesis and biological evaluation of darunavir derived HIV-1 protease inhibitors and their functional effect on enzyme inhibition and antiviral activity in MT-2 cell lines. The P2' 4-amino functionality was modified to make a number of amide derivatives to interact with residues in the S2' subsite of the HIV-1 protease active site. Several compounds exhibited picomolar enzyme inhibitory and low nanomolar antiviral activity. The X-ray crystal structure of the chloroacetate derivative bound to HIV-1 protease was determined. Interestingly, the active chloroacetate group converted to the acetate functionality during X-ray exposure. The structure revealed that the P2' carboxamide functionality makes enhanced hydrogen bonding interactions with the backbone atoms in the S2'-subsite.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion

NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a “sample and select” method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls ( 1 H, 15 N, and 13 C'). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗