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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Data-driven prediction of α IIb β 3 integrin activation paths using manifold learning and deep generative modeling

The integrin heterodimer is a transmembrane protein critical for driving cellular process and is a therapeutic target in the treatment of multiple diseases linked to its malfunction. Activation of integrin involves conformational transitions between bent and extended states. Some of the conformations that are intermediate between bent and extended states of the heterodimer have been experimentally characterized, but the full activation pathways remain unresolved both experimentally due to their transient nature and computationally due to the challenges in simulating rare barrier crossing events in these large molecular systems. An understanding of the activation pathways can provide new fundamental understanding of the biophysical processes associated with the dynamic interconversions between bent and extended states and unveil new putative therapeutic targets. In this work, we apply nonlinear manifold learning to coarse-grained molecular dynamics simulations of bent, extended, and two intermediate states of αI I b β3 integrin to learn a low-dimensional embedding of the configurational phase space. We then train deep generative models to learn an inverse mapping between the low-dimensional embedding and high-dimensional molecular space and use these models to interpolate the molecular configurations constituting the activation pathways between the experimentally characterized states. Furthermore, this work furnishes plausible predictions of integrin activation pathways and reports a generic and transferable multi-scale technique to predict transition pathways for biomolecular systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models including the fetal human brain and hiPSC-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders – the CUL3 E3 ubiquitin ligase, the DDX3X and YBX1 nucleic-acid binding proteins – by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to systematically and more comprehensively resolve the synaptic architecture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Ultrafast Carrier Self-Trapping Driven by Strong Exciton–Phonon Coupling in 2D MA 3 Bi 2 I 6 Cl 3 Perovskite

Two-dimensional (2D) hybrid bismuth halide perovskites have emerged as promising lead-free materials for optoelectronic applications due to their solution processability and tunable structures. Here, in this study, we investigate 2D layered hybrid perovskite MA 3 Bi 2 I 6 Cl 3 using temperature-dependent photoluminescence (PL) and femtosecond transient absorption spectroscopy. Our results reveal strong coupling between excitons and phonons, evidenced by giant Huang–Rhys factors, coherent phonon oscillations, and ultrafast carrier self-trapping into small-polaron and self-trapped exciton (STE) states. These processes appear as time-dependent ground-state bleach and photoinduced absorption features, highlighting the influence of the lattice in carrier dynamics. Wavelength- and time-resolved measurements reveal that PL emission is dominated by STEs, while free exciton emission is weak and short-lived. By comparing 2D MA 3 Bi 2 I 6 Cl 3 with 0D MA 3 Bi 2 I 9 , which contains molecularly isolated [BiI 6 ] 3− octahedra and 2D MA 3 Bi 2 Br 9 perovskites, we demonstrate how halide composition and structural dimensionality influence the balance between free exciton populations and carrier localization. These insights uncover the intrinsic kinetic landscape of photoexcited states in MA 3 Bi 2 I 6 Cl 3 . Overall, our study contributes to a mechanistic understanding of exciton–phonon interactions in lead-free 2D perovskites.

Pradeep, Kodimana Ramakrishnan [Northwestern Univ.↗
DOE OSTI2020

Mathematical Model of ATM Activation and Chromatin Relaxation by Ionizing Radiation

We propose a comprehensive mathematical model to study the dynamics of ionizing radiation induced Ataxia-telangiectasia mutated (ATM) activation that consists of ATM activation through dual mechanisms: the initiative activation pathway triggered by the DNA damage-induced local chromatin relaxation and the primary activation pathway consisting of a self-activation loop by interplay with chromatin relaxation. The model is expressed as a series of biochemical reactions, governed by a system of differential equations and analyzed by dynamical systems techniques. Radiation induced double strand breaks (DSBs) cause rapid local chromatin relaxation, which is independent of ATM but initiates ATM activation at damage sites. Key to the model description is how chromatin relaxation follows when active ATM phosphorylates KAP-1, which subsequently spreads throughout the chromatin and induces global chromatin relaxation. Additionally, the model describes how oxidative stress activation of ATM triggers a self-activation loop in which PP2A and ATF2 are released so that ATM can undergo autophosphorylation and acetylation for full activation in relaxed chromatin. In contrast, oxidative stress alone can partially activate ATM because phosphorylated ATM remains as a dimer. The model leads to predictions on ATM mediated responses to DSBs, oxidative stress, or both that can be tested by experiments.

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

Monatomic ions influence substrate permeation across bacterial microcompartment shells

Abstract Bacterial microcompartments (BMCs) are protein organelles consisting of an inner enzymatic core encased within a selectively permeable shell. BMC shells are modular, tractable architectures that can be repurposed with new interior enzymes for biomanufacturing purposes. The permeability of BMC shells is function-specific and regulated by biophysical properties of the shell subunits, especially its pores. We hypothesized that ions may interact with pore residues in a manner that influences the substrate permeation process. In vitro activity comparisons between native and broken BMCs demonstrated that increasing NaCl negatively affects permeation rates. Molecular dynamics simulations of the dominant shell protein (BMC-H) revealed that chloride ions preferentially occupy the positive pore, hindering substrate permeation, while sodium cations remain excluded. Overall, these results demonstrate that shell properties influence ion permeability and leverages the integration of experimental and computational techniques to improve our understanding of BMC shells towards their repurposing for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Structures of a synthetic antibody selected against and bound to the C‐terminal domain of Clostridium perfringens enterotoxin

Abstract Clostridium perfringensenterotoxin (CpE) causes cytotoxic gastrointestinal disease in mammalian epithelium by binding membrane protein receptors called claudins. Claudins direct the formation of cell/cell tight junctions through oligomerization and govern the transport of molecules between individual cells. CpE binds claudins through its C‐terminal domain (cCpE) and induces cytotoxicity through its N‐terminal domain. The non‐toxic cCpE is a useful tool to study claudins, tight junctions, and for translational applications, such as increasing the permeability of restrictive tissues like the blood–brain barrier or selective targeting of claudin overexpressing cancers. Conversely, there are no specialized molecular tools to study CpE or cCpE, or to modulate or inhibit their functions. We previously reported the development of synthetic antigen‐binding fragments (sFabs) that bind cCpE, and low‐resolution structures of them bound to claudin/cCpE complexes. Here, we determine high‐resolution structures of sFab COP‐2 bound to cCpE using X‐ray crystallography and cryogenic electron microscopy. The structures and biophysical findings provide the mechanism of COP‐2 binding to cCpE and the molecular determinants driving their interactions. These insights can advance the design of new antibody‐based tools from our COP‐2 scaffold to study or alter cCpE function and give rise to a “Trojan horse” strategy that exploits cCpE's tight junction barrier disrupting function to selectively deliver conjugated therapeutics through normally impermeable tissues.

Biochemistry & Molecular Biology↗
DOE OSTI2022

The allosteric mechanism leading to an open-groove lipid conductive state of the TMEM16F scramblase

TMEM16F is a Ca 2+ -activated phospholipid scramblase in the TMEM16 family of membrane proteins. Unlike other TMEM16s exhibiting a membrane-exposed hydrophilic groove that serves as a translocation pathway for lipids, the experimentally determined structures of TMEM16F shows the groove in a closed conformation even under conditions of maximal scramblase activity. It is currently unknown if/how TMEM16F groove can open for lipid scrambling. Here we describe the analysis of ~400 µs all-atom molecular dynamics (MD) simulations of the TMEM16F revealing an allosteric mechanism leading to an open-groove, lipid scrambling competent state of the protein. The groove opens into a continuous hydrophilic conduit that is highly similar in structure to that seen in other activated scramblases. The allosteric pathway connects this opening to an observed destabilization of the Ca 2+ ion bound at the distal site near the dimer interface, to the dynamics of specific protein regions that produces the open-groove state to scramble phospholipids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multivalent interactions between CsoS2 and Rubisco mediate α-carboxysome formation

Carboxysomes are bacterial microcompartments that function as the centerpiece of the bacterial CO 2 -concentrating mechanism by facilitating high CO 2 concentrations near the carboxylase Rubisco. The carboxysome self-assembles from thousands of individual proteins into icosahedral-like particles with a dense enzyme cargo encapsulated within a proteinaceous shell. In the case of the α-carboxysome, there is little molecular insight into protein–protein interactions that drive the assembly process. In this work, studies on the α-carboxysome from Halothiobacillus neapolitanus demonstrate that Rubisco interacts with the N terminus of CsoS2, a multivalent, intrinsically disordered protein. X-ray structural analysis of the CsoS2 interaction motif bound to Rubisco reveals a series of conserved electrostatic interactions that are only made with properly assembled hexadecameric Rubisco. Although biophysical measurements indicate that this single interaction is weak, its implicit multivalency induces high-affinity binding through avidity. Taken together, our results indicate that CsoS2 acts as an interaction hub to condense Rubisco and enable efficient α-carboxysome formation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Unveiling the nanoscale architectures and dynamics of protein assembly with in situ atomic force microscopy

Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Long-range structural defects by pathogenic mutations in most severe glucose-6-phosphate dehydrogenase deficiency

Glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common blood disorder, presenting multiple symptoms, including hemolytic anemia. It affects 400 million people worldwide, with more than 160 single mutations reported in G6PD. The most severe mutations (about 70) are classified as class I, leading to more than 90% loss of activity of the wild-type G6PD. The crystal structure of G6PD reveals these mutations are located away from the active site, concentrating around the noncatalytic NADP + -binding site and the dimer interface. However, the molecular mechanisms of class I mutant dysfunction have remained elusive, hindering the development of efficient therapies. To resolve this, we performed integral structural characterization of five G6PD mutants, including four class I mutants, associated with the noncatalytic NADP + and dimerization, using crystallography, small-angle X-ray scattering (SAXS), cryogenic electron microscopy (cryo-EM), and biophysical analyses. Comparisons with the structure and properties of the wild-type enzyme, together with molecular dynamics simulations, bring forward a universal mechanism for this severe G6PD deficiency due to the class I mutations. We highlight the role of the noncatalytic NADP + -binding site that is crucial for stabilization and ordering two β-strands in the dimer interface, which together communicate these distant structural aberrations to the active site through a network of additional interactions. This understanding elucidates potential paths for drug development targeting G6PD deficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structure and dynamics of SARS-CoV-2 proofreading exoribonuclease ExoN

High-fidelity replication of the large RNA genome of coronaviruses (CoVs) is mediated by a 3'-to-5' exoribonuclease (ExoN) in nonstructural protein 14 (nsp14), which excises nucleotides including antiviral drugs misincorporated by the low-fidelity viral RNA-dependent RNA polymerase (RdRp) and has also been implicated in viral RNA recombination and resistance to innate immunity. Here, we determined a 1.6-Å resolution crystal structure of severe acute respiratory syndrome CoV 2 (SARS-CoV-2) ExoN in complex with its essential cofactor, nsp10. The structure shows a highly basic and concave surface flanking the active site, comprising several Lys residues of nsp14 and the N-terminal amino group of nsp10. Modeling suggests that this basic patch binds to the template strand of double-stranded RNA substrates to position the 3' end of the nascent strand in the ExoN active site, which is corroborated by mutational and computational analyses. We also show that the ExoN activity can rescue a stalled RNA primer poisoned with sofosbuvir and allow RdRp to continue its extension in the presence of the chain-terminating drug, biochemically recapitulating proofreading in SARS-CoV-2 replication. Molecular dynamics simulations further show remarkable flexibility of multidomain nsp14 and suggest that nsp10 stabilizes ExoN for substrate RNA binding to support its exonuclease activity. Our high-resolution structure of the SARS-CoV-2 ExoN–nsp10 complex serves as a platform for future development of anticoronaviral drugs or strategies to attenuate the viral virulence.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

3D cell mapping↗
DOE OSTI2025

Cholesterol modulates membrane elasticity via unified biophysical laws

Cholesterol and lipid unsaturation underlie a balance of opposing forces that features prominently in adaptive cell responses to diet and environmental cues. These competing factors have resulted in contradictory observations of membrane elasticity across different measurement scales, requiring chemical specificity to explain incompatible structural and elastic effects. Here, we demonstrate that – unlike macroscopic observations – lipid membranes exhibit a unified elastic behavior in the mesoscopic regime between molecular and macroscopic dimensions. Using nuclear spin techniques and computational analysis, we find that mesoscopic bending moduli follow a universal dependence on the lipid packing density regardless of cholesterol content, lipid unsaturation, or temperature. Our observations reveal that compositional complexity can be explained by simple biophysical laws that directly map membrane elasticity to molecular packing associated with biological function, curvature transformations, and protein interactions. The obtained scaling laws closely align with theoretical predictions based on conformational chain entropy and elastic stress fields. These findings provide unique insights into the membrane design rules optimized by nature and unlock predictive capabilities for guiding the functional performance of lipid-based materials in synthetic biology and real-world applications.

Kumarage, Teshani [Virginia Polytechnic Inst. and ↗
DOE OSTI2023

Homo- and hetero-dimeric subunit interactions set affinity and efficacy in metabotropic glutamate receptors

Metabotropic glutamate receptors (mGluRs) are dimeric class C G-protein–coupled receptors that operate in glia and neurons. Glutamate affinity and efficacy vary greatly between the eight mGluRs. The molecular basis of this diversity is not understood. We used single-molecule fluorescence energy transfer to monitor the structural rearrangements of activation in the mGluR ligand binding domain (LBD). In saturating glutamate, group II homodimers fully occupy the activated LBD conformation (full efficacy) but homodimers of group III mGluRs do not. Strikingly, the reduced efficacy of Group III homodimers does not arise from differences in the glutamate binding pocket but, instead, from interactions within the extracellular dimerization interface that impede active state occupancy. By contrast, the functionally boosted mGluR II/III heterodimers lack these interface ‘brakes’ to activation and heterodimer asymmetry in the flexibility of a disulfide loop connecting LBDs greatly favors occupancy of the activated conformation. Our results suggest that dimerization interface interactions generate substantial functional diversity by differentially stabilizing the activated conformation. This diversity may optimize mGluR responsiveness for the distinct spatio-temporal profiles of synaptic versus extrasynaptic glutamate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fe protein docking transduces conformational changes to MoFe nitrogenase active site in a nucleotide-dependent manner

The reduction of dinitrogen to ammonia catalyzed by nitrogenase involves a complex series of events, including ATP hydrolysis, electron transfer, and activation of metal clusters for N 2 reduction. Early evidence shows that an essential part of the mechanism involves transducing information between the nitrogenase component proteins through conformational dynamics. Here, millisecond time-resolved hydrogen-deuterium exchange mass spectrometry was used to unravel peptide-level protein motion on the time scale of catalysis of Mo-dependent nitrogenase from Azotobacter vinelandii. Normal mode analysis calculations complemented this data, providing insights into the specific signal transduction pathways that relay information across protein interfaces at distances spanning 100 Å. Together, these results show that conformational changes induced by protein docking are rapidly transduced to the active site, suggesting a specific mechanism for activating the metal cofactor in the enzyme active site.

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

HDBind: encoding of molecular structure with hyperdimensional binary representations

Traditional methods for identifying “hit” molecules from a large collection of potential drug-like candidates rely on biophysical theory to compute approximations to the Gibbs free energy of the binding interaction between the drug and its protein target. These approaches have a significant limitation in that they require exceptional computing capabilities for even relatively small collections of molecules. Increasingly large and complex state-of-the-art deep learning approaches have gained popularity with the promise to improve the productivity of drug design, notorious for its numerous failures. However, as deep learning models increase in their size and complexity, their acceleration at the hardware level becomes more challenging. Hyperdimensional Computing (HDC) has recently gained attention in the computer hardware community due to its algorithmic simplicity relative to deep learning approaches. The HDC learning paradigm, which represents data with high-dimension binary vectors, allows the use of low-precision binary vector arithmetic to create models of the data that can be learned without the need for the gradient-based optimization required in many conventional machine learning and deep learning methods. This algorithmic simplicity allows for acceleration in hardware that has been previously demonstrated in a range of application areas (computer vision, bioinformatics, mass spectrometery, remote sensing, edge devices, etc.). To the best of our knowledge, our work is the first to consider HDC for the task of fast and efficient screening of modern drug-like compound libraries. We also propose the first HDC graph-based encoding methods for molecular data, demonstrating consistent and substantial improvement over previous work. We compare our approaches to alternative approaches on the well-studied MoleculeNet dataset and the recently proposed LIT-PCBA dataset derived from high quality PubChem assays. We demonstrate our methods on multiple target hardware platforms, including Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs), showing at least an order of magnitude improvement in energy efficiency versus even our smallest neural network baseline model with a single hidden layer. Our work thus motivates further investigation into molecular representation learning to develop ultra-efficient pre-screening tools. We make our code publicly available at https://github.com/LLNL/hdbind.

59 BASIC BIOLOGICAL SCIENCES↗