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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structural Insights into the Mechanisms and Pharmacology of K 2P Potassium Channels

Leak currents, defined as voltage and time independent flows of ions across cell membranes, are central to cellular electrical excitability control. The K 2P (KCNK) potassium channel class comprises an ion channel family that produces potassium leak currents that oppose excitation and stabilize the resting membrane potential in cells in the brain, cardiovascular system, immune system, and sensory organs. Due to their widespread tissue distribution, K 2P s contribute to many physiological and pathophysiological processes including anesthesia, pain, arrythmias, ischemia, hypertension, migraine, intraocular pressure regulation, and lung injury responses. Structural studies of six homomeric K 2P s have established the basic architecture of this channel family, revealed key moving parts involved in K 2P function, uncovered the importance of asymmetric pinching and dilation motions in the K 2P selectivity filter (SF) C-type gate, and defined two K 2P structural classes based on the absence or presence of an intracellular gate. Further, a series of structures characterizing K 2P :modulator interactions have revealed a striking polysite pharmacology housed within a relatively modestly sized (~70 kDa) channel. Binding sites for small molecules or lipids that control channel function are found at every layer of the channel structure, starting from its extracellular side through the portion that interacts with the membrane bilayer inner leaflet. This framework provides the basis for understanding how gating cues sensed by different channel parts control function and how small molecules and lipids modulate K 2P activity. Such knowledge should catalyze development of new K 2P modulators to probe function and treat a wide range of disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multiscale modeling of solute diffusion in triblock copolymer membranes

We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent field theory (SCFT) to predict the structure of the self-assembled, solvated membrane and on-lattice kinetic Monte Carlo (kMC) simulations to model diffusion of solutes. Solvation is simulated in SCFT by constraining the glassy membrane matrix while relaxing the brush-like membrane pore coating against the solvent. The kMC simulations capture the resulting solute spatial distribution and concentration-dependent local diffusivity in the polymer-coated pores; we parameterize the latter using particle-based simulations. We apply our approach to simulate solute diffusion through nonequilibrium morphologies of a model triblock copolymer, and we correlate diffusivity with structural descriptors of the morphologies. We also compare the model’s predictions to alternative approaches based on simple lattice random walks and find our multiscale model to be more robust and systematic to parameterize. Furthermore, our multiscale modeling approach is general and can be readily extended in the future to other chemistries, morphologies, and models for the local solute diffusivity and interactions with the membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A biology-informed similarity metric for simulated patches of human cell membrane

Complex scientific inquiries rely increasingly upon large and autonomous multiscale simulation campaigns, which fundamentally require similarity metrics to quantify ‘sufficient’ changes among data and/or configurations. However, subject matter experts are often unable to articulate similarity precisely or in terms of well-formulated definitions, especially when new hypotheses are to be explored, making it challenging to design a meaningful metric. Furthermore, the key to practical usefulness of such metrics to enable autonomous simulations lies in in situ inference, which requires generalization to possibly substantial distributional shifts in unseen, future data. Here, we address these challenges in a cancer biology application and develop a meaningful similarity metric for ‘patches’—regions of simulated human cell membrane that express interactions between certain proteins of interest and relevant lipids. In the absence of well-defined conditions for similarity, we leverage several biology-informed notions about data and the underlying simulations to impose inductive biases on our metric learning framework, resulting in a suitable similarity metric that also generalizes well to significant distributional shifts encountered during the deployment. We combine these intuitions to organize the learned embedding space in a multiscale manner, which makes the metric robust to incomplete and even contradictory intuitions. Our approach delivers a metric that not only performs well on the conditions used for its development and other relevant criteria, but also learns key spatiotemporal relationships without ever being exposed to any such information during training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Specific ion effects on ion transport in charged polymer membranes

Selective separation of like-charged ions is a central challenge in applications such as critical mineral recovery. Electrochemical membrane–based separations offer promising pathways to address this need, but a limited fundamental understanding of ion transport in charged polymer membranes hampers the development of highly selective materials. This study elucidates the role of specific ion effects (SIEs) in ion transport through charged polymer membranes by integrating experimental measurements of ion mobility and in situ ion/ion and ion/water interactions in model charged polymer membranes with results from molecular dynamics simulations on analogous systems. We demonstrate that solvent-mediated ion interactions drive pronounced SIEs within the studied membranes, with the ion softness, i.e., the malleability of ion hydration shells, from hard/soft acid/base (HSAB) theory emerging as a key predictor of transport properties. HSAB theory also explains the observed mechanism of solvent-mediated ion interactions. Our findings offer a mechanistic framework for designing membranes with tailored ion selectivity, potentially enabling efficient separations of chemically similar ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Free Energy and Flexibility Analysis of Autoinhibited Human BRAF

The RAF serine/threonine protein kinases function as direct effectors of RAS in the intracellular transmission of extracellular growth signals, and they are key targets for drug discovery, given the high incidence of oncogenic mutations in RAF and other components of this signaling pathway. In its inactive state, RAF is held in an autoinhibited conformation in the cytosol through a combination of intramolecular interactions and binding to a regulatory 14−3−3 protein dimer. Activation of RAF is initiated by its interaction with membrane-localized GTP-bound RAS, which induces conformational changes that release RAF from its autoinhibited state. However, the molecular mechanisms governing RAF activation remain incomplete, largely due to the challenges in experimentally capturing the intermediate conformational states in this process. To address this gap, we developed a comprehensive all-atom model of BRAF based on existing cryo-EM structures. Using this model, we performed extensive molecular dynamics simulations to evaluate the stability and free energy landscape of autoinhibited BRAF in solution. Our analysis reveals conformational flexibility within the autoinhibited complex, suggesting that this dynamic behavior may play a role in facilitating BRAF activation upon engagement with the membrane-bound RAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Challenges of conventional iterative all-atom and coarse-grained multiscale molecular dynamics

In this work, we evaluate the biomolecular dynamics behaviors when conventionally iterating between all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations over multiple cycles. We implemented the workflow to iterate between AA and CG in OpenMM, namely the iterative multiscale MD (iMMD) simulation workflow. In particular, we aim to identify practical applications for iterating between AA and CG simulations in a conventional manner without any constraints or model modifications. We evaluate the iMMD workflow on four representative systems, spanning folding of two soluble proteins and protein-protein as well as protein-lipid interactions of two membrane proteins. We observe that iteration between AA and CG representations could help the soluble proteins exit undesirable metastable states to fold, resulting from random protein structural distortions due to cycling. Consequently, the most reliable use of iterative AA and CG simulations appears to be to accelerating complex lipid mixing for membrane-bound protein systems rather than sampling protein conformational space. Our work explores the practical usages and limitations for iterative AA and CG simulations using readily available AA and CG force fields. The evaluated iMMD workflow in OpenMM is made available at https://github.com/lanl/iMMD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains

Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Primary biomolecular adsorption energetics of core–shell nanocomplexes: Implications for biological interactions

Molecular organization at the nano-bio interface governing the colloidal stability, reactivity, immune recognition, and drug delivery performance of nanoparticles remains difficult to predict. Quantifying the primary hydration energetics of biomolecule-coated nanomaterials can determine those interactions and provide a basis for engineered nanocarriers with tailored behavior in biological systems. Here, we measured the thermodynamics of water adsorption on patchy dry magnetite (Fe 3 O 4 ) nanoparticles coated with three model biomolecules, bovine serum albumin, potato starch, and lauric acid and compared these properties to the hydration energetics of the corresponding free dry biomolecules. The results demonstrate how the surface functionalization alters the hydrophilicity, the accessible hydrophilic surface, and the interaction potential of the nanocomplex surface with biological media. The protein coating increases the interaction potential of the surface of the nanocomplex. The weaker interaction potential of the polysaccharide coating and the relatively large hydrophilic surface area allow dynamic and reversible binding, while the fatty acid rearranges into a partial bilayer with very strong hydrophilicity. The findings establish the hydration enthalpy as a quantitative basis to determine and interpret nanoparticle interactions with proteins, membranes, and biological fluids, and provide a thermodynamic foundation for designing nanocarriers with predictable biological reactivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Interfacial interactions between polymers and selective adsorbents influence ion transport properties of boron scavenging ion-exchange membranes

The recent emergence of adsorptive ion-exchange membranes (IEMs), designed by the synergistic integration of highly selective porous aromatic frameworks (PAFs) with ion-exchange polymers, has enabled simultaneous desalination and targeted removal of specific solutes (e.g., mercury, iron, boron, etc.). While the addition of highly selective PAFs to IEMs yields membranes with entirely new functions, PAF-polymer interactions, and the effects of such interactions on ion transport properties of the membranes, are not well understood. In this study, we developed cross-linked adsorptive cation- and anion-exchange membranes (CEMs and AEMs) for simultaneous desalination and boron removal via in-situ formation of the cross-linked polymer network around the boron selective PAF particles. Here we systematically investigated the influence of PAF loading level on PAF-polymer interactions as well as the equilibrium and transport properties of the adsorptive IEMs. The interactions between the PAF and the ion-exchange polymer matrix differed for the CEMs and AEMs due to differences in the fixed charge group chemistry. Notably, the sulfonate groups of the CEMs can form hydrogen bonds with the hydroxyl groups of the PAF, while the quaternary ammonium groups in the AEMs cannot. These differences in interfacial interactions did not significantly impact counter-ion transport across the adsorptive IEMs but had a significant influence on co-ion transport, which affected the counter-ion/co-ion selectivity of the membranes. The selectivity of the adsorptive CEMs decreased while that of the adsorptive AEMs increased with PAF loading level. The results of this study underscore the importance of controlling interfacial interactions when designing adsorptive IEMs for simultaneous water desalination and solute capture and recovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular design and fabrication of PIM-1/polyphosphazene blend membranes with high performance for CO 2 /N 2 separation

New polymeric blend membranes for CO 2 separation were synthesized based on insights from molecular dynamics simulation. A molecular-level structure-property relationship in polymers of intrinsic microporosity (PIM) based blend membranes, was investigated in detail computationally. Calculated local density profiles and energy of interaction of the blend membranes, composed of PIM-1 and various polyphosphazenes, showed that using the polyphosphazene with a higher concentration of ether side chains can improve the compatibility with PIM-1. Furthermore, based on the findings of computational studies, blend membranes were experimentally fabricated from PIM-1 and polyphosphazenes with various polyether side chain concentrations. Polyether concentration in polyphosphazenes was correlated with the film properties and gas transport performance of the blend membranes. Blend membranes showed very high CO 2 permeability (3100-5300 barrer) and improved CO 2 /N 2 selectivity (24-28), outperforming all other PIM-based blend membranes reported to date. Moreover, the CO 2 permeability performance of the blend membranes was tested 566 hours under real post-combustion flue gas from a coal-fired power plant, including CO 2 , N 2 , H 2 O, O 2 , SO x and NO x .

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

Molecular Dynamics Investigation of Lipid-Specific Interactions with a Fusion Peptide

The HIV-1 fusion peptide, which is a short hydrophobic peptide from the gp41 coat glycoprotein that participates in the infection of a cell, interacts with model lipid bilayer membranes in a concentration-dependent manner. The interaction of the peptide with the bilayer also strongly depends on the lipid composition. Here, molecular dynamics simulations were performed to investigate lipid-specific interactions that arise shortly after the binding of a less-fusogenic variant of the HIV-1 fusion peptide to a lipid bilayer composed of a mixture of dimyristoyl phosphatidylcholine and dimyristoyl phosphatidylglycerol. The impact of peptide concentration was also studied. An improved understanding was gained of the lipid-specific interactions experienced by the FP. New insight was also gained into how the peptide concentration changes these interactions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Biophysical analysis of the plant-specific GIPC sphingolipids reveals multiple modes of membrane regulation

The plant plasma membrane (PM) is an essential barrier between the cell and the external environment, controlling signal perception and transmission. It consists of an asymmetrical lipid bilayer made up of three different lipid classes: sphingolipids, sterols, and phospholipids. The glycosyl inositol phosphoryl ceramides (GIPCs), representing up to 40% of total sphingolipids, are assumed to be almost exclusively in the outer leaflet of the PM. However, their biological role and properties are poorly defined. In this study, we investigated the role of GIPCs in membrane organization. Because GIPCs are not commercially available, we developed a protocol to extract and isolate GIPC-enriched fractions from eudicots (cauliflower and tobacco) and monocots (leek and rice). Lipidomic analysis confirmed the presence of trihydroxylated long chain bases and 2-hydroxylated very long-chain fatty acids up to 26 carbon atoms. The glycan head groups of the GIPCs from monocots and dicots were analyzed by gas chromatograph-mass spectrometry, revealing different sugar moieties. Multiple biophysics tools, namely Langmuir monolayer, ζ-Potential, light scattering, neutron reflectivity, solid state 2H-NMR, and molecular modeling, were used to investigate the physical properties of the GIPCs, as well as their interaction with free and conjugated phytosterols. We showed that GIPCs increase the thickness and electronegativity of model membranes, interact differentially with the different phytosterols species, and regulate the gel-to-fluid phase transition during temperature variations. These results unveil the multiple roles played by GIPCs in the plant PM.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Impact of Organic and Volatile Compounds in Produced Water from Unconventional Reservoirs on Direct Contact Membrane Distillation Permeate Quality

The expansion of oil and gas extraction from unconventional reservoirs has led to an increase in the amount of produced water that has to be managed by this industry. Direct contact membrane distillation (DCMD) is a promising technology for treatment of produced water to enable water recovery and reduce the environmental footprint of this industry. The feasibility of DCMD for the treatment of highly saline produced water from the Permian Basin in TX with commercially available polyethylene and polytetrafluoroethylene membranes was evaluated in this study. An increase in water recovery by a DCMD system operated in the batch (concentrating) mode led to an increase in permeate conductivity. Partial removal of organic compounds from the produced water by biodegradation, chemical oxidation, and/or activated carbon adsorption could not resolve deterioration in permeate quality, and none of the organics observed in the permeate contributed to its conductivity. The observed increase in permeate conductivity was attributed to the passage of ammonia vapor from the feed side followed by protonation on the permeate side. Furthermore, this study revealed that permeate conductivity may not always be a reliable indicator of membrane wetting and underscores the importance of understanding the interactions between specific solutes and membrane materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Surface Functional Groups Affect Iron (Hydr)oxide Heterogeneous Nucleation: Implications for Membrane Scaling

Because of its favorable thermodynamics and fast kinetics, heterogeneous solid nucleation on membranes triggers early-stage mineral scaling. Iron (hydr)oxide, a typical membrane scale, initially forms as nanoparticles that interact with surface functional groups on membranes, but these nanoscale phenomena are difficult to observe in real time. In this study, we utilized in situ grazing incidence small angle X-ray scattering and ex situ atomic force microscopy to examine the heterogeneous nucleation of iron (hydr)oxide on surface functional groups commonly used in membranes, including hydroxyl (OH), carboxyl (COOH), and fluoro (F) groups. We found that, compared to nucleation on hydrophilic OH- and COOH-surfaces, the high hydrophobicity of an F-modified surface significantly reduced the extents of both heterogeneously and homogeneously formed iron (hydr)oxide nucleation. Moreover, on the OH-surface, the high functional group density of 0.76 nmol/cm 2 caused faster heterogeneous nucleation than that on a COOH-surface, with a density of 0.28 ± 0.04 nmol/cm 2 . The F-surface also had the highest heterogeneous nucleation energy barrier (26 ± 0.6 kJ/mol), followed by COOH- (23 ±0.8 kJ/mol) and OH- (20 ± 0.9 kJ/mol) surfaces. The kinetic and thermodynamic information provided here will help us better predict the rates and extents of early-stage scaling of iron (hydr)oxide nanoparticles in membrane processes. Finally, this work provides both kinetic and thermodynamic information about iron (hydr)oxide nucleation controlled by membrane-related functional groups (OH, COOH, and F).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗