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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Effects of oxidants and reductants on the efficiency of excitation transfer in green photosynthetic bacteria

The efficiency of energy transfer in chlorosome antennas in the green sulfur bacteria Chlorobium vibrioforme and Chlorobium limicola was found to be highly sensitive to the redox potential of the suspension. Energy transfer efficiencies were measured by comparing the absorption spectrum of the bacteriochlorophyll c or d pigments in the chlorosome to the excitation spectrum for fluorescence arising from the chlorosome baseplate and membrane-bound antenna complexes. The efficiency of energy transfer approaches 100% at low redox potentials induced by addition of sodium dithionite or other strong reductants, and is lowered to 10-20% under aerobic conditions or after addition of a variety of membrane-permeable oxidizing agents. The redox effect on energy transfer is observed in whole cells, isolated membranes and purified chlorosomes, indicating that the modulation of energy transfer efficiency arises within the antenna complexes and is not directly mediated by the redox state of the reaction center. It is proposed that chlorosomes contain a component that acts as a highly quenching center in its oxidized state, but is an inefficient quencher when reduced by endogenous or exogenous reductants. This effect may be a control mechanism that prevents cellular damage resulting from reaction of oxygen with reduced low-potential electron acceptors found in the green sulfur bacteria. The redox modulation effect is not observed in the green gliding bacterium Chloroflexus aurantiacus, which contains chlorosomes but does not contain low-potential electron acceptors.

NASA Discipline Exobiology↗
DOE OSTI2024

Elucidating mechanisms of Photosystem I assembly and repair (Final Technical Report)

Oxygenic photosynthesis generates the carbohydrates and oxygen that support life on earth. Central to this process are photosystems I and II (PSI and PSII), large protein-pigment complexes that are among the most complex macromolecular structures in nature. Impressive advances have been made in understanding the structure and photochemical mechanisms of PSI and PSII. However, less is known about the mechanisms underlying their biogenesis. The overarching goal of this project was to elucidate mechanisms of photosystem assembly. Several proteins that are not found in mature PSI or PSII are essential for their assembly, but the assembly pathways and the role of each assembly factor are just starting to emerge. During the course of this project, we advanced understanding of this problem in several ways. First, we addressed the spatial organization of photosystem assembly by localizing many known assembly factors to specific subdomains of thylakoid membranes in plant chloroplasts. This work revealed that the "curvature" domain - the highly curved periphery of stacked granal membrane disks - is a center of photosystem assembly. However, whereas some PSI assembly factors localized exclusively to the curvature domain, another was found exclusively in granal margins and unstacked membranes. This spatial partitioning suggests an assembly line along which different assembly intermediates are physically segregated. Most assembly factors localized similarly in dark-adapted and illuminated plants, but one PSII assembly factor shifted from the curvature domain to unstacked membranes upon illumination, suggesting an unanticipated role in the repair of light-induced PSII damage. Whereas most PSII subunits were found primarily in grana stacks (as expected), one PSII subunit, PsbP, was prominent also in the curvature fraction, suggesting that PsbP has functions beyond its role in mature PSII, possibly in biogenesis or repair.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Molecular principles of Piwi-mediated cotranscriptional silencing through the dimeric SFiNX complex

Nuclear Argonaute proteins, guided by their bound small RNAs to nascent target transcripts, mediate cotranscriptional silencing of transposons and repetitive genomic loci through heterochromatin formation. The molecular mechanisms involved in this process are incompletely understood. Here, we show that the SFiNX complex, a silencing mediator downstream from nuclear Piwi-piRNA complexes in Drosophila, facilitates cotranscriptional silencing as a homodimer. The dynein light chain protein Cut up/LC8 mediates SFiNX dimerization, and its function can be bypassed by a heterologous dimerization domain, arguing for a constitutive SFiNX dimer. Dimeric, but not monomeric SFiNX, is capable of forming molecular condensates in a nucleic acid-stimulated manner. Mutations that prevent SFiNX dimerization result in loss of condensate formation in vitro and the inability of Piwi to initiate heterochromatin formation and silence transposons in vivo. We propose that multivalent SFiNX-nucleic acid interactions are critical for heterochromatin establishment at piRNA target loci in a cotranscriptional manner.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-throughput native mass spectrometry as experimental validation for in silico drug design

In this project, we developed automated workflows for both experimental validation and computational prediction of protein-ligand interactions. The ultimate goal is to establish an integrated pipeline for high throughput design of inhibitors to enzymes relevant to all areas of biological research. Our experimental approach is based on native mass spectrometry (native MS), which measures accurate masses and quantify the relative abundance of protein-ligand complexes to define binding affinity. We set up an in-house built autosampler with highly flexible configurations to minimize the manual steps for high throughput native MS. In parallel, we also performed manual native MS to characterize the binding of substrates and inhibitors of SARS-Cov-2 nonstructural protein nsp10/16 in order to optimize the experimental parameters for future automation. On the computational side, we streamlined the pipeline to achieve minimal manual intervention for predicting enzyme inhibitors via simulation, using the same nsp10/16 system as an example. Using the native MS method we examined 8 top-ranked designed compounds, 2 of which showed weak binding of ~50 µM. The information from native MS experiment provided critical insights and the foundation for a fully integrated workflow for enzyme inhibitor design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world’s largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid “fingerprints” imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Carpenter, Timothy S. [Lawrence Livermore National↗
DOE OSTI2024

Hydrogen–Deuterium Exchange Mass Spectrometry Identifies Local and Long-Distance Interactions within the Multicomponent Radical SAM Enzyme, PqqE

Interactions among proteins and peptides are essential for many biological activities including the tailoring of peptide substrates to produce natural products. The first step in the production of the bacterial redox cofactor pyrroloquinoline quinone (PQQ) from its peptide precursor is catalyzed by a radical SAM (rSAM) enzyme, PqqE. We describe the use of hydrogen–deuterium exchange mass spectrometry (HDX-MS) to characterize the structure and conformational dynamics in the protein–protein and protein–peptide complexes necessary for PqqE function. HDX-MS-identified hotspots can be discerned in binary and ternary complex structures composed of the peptide PqqA, the peptide-binding chaperone PqqD, and PqqE. Structural conclusions are supported by size-exclusion chromatography coupled to small-angle X-ray scattering (SEC-SAXS). HDX-MS further identifies reciprocal changes upon the binding of substrate peptide and S-adenosylmethionine (SAM) to the PqqE/PqqD complex: long-range conformational alterations have been detected upon the formation of a quaternary complex composed of PqqA/PqqD/PqqE and SAM, spanning nearly 40 Å, from the PqqA binding site in PqqD to the PqqE active site Fe 4 S 4 . Interactions among the various regions are concluded to arise from both direct contact and distal communication. The described experimental approach can be readily applied to the investigation of protein conformational communication among a large family of peptide-modifying rSAM enzymes.

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

Improving Protein–Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge

Elucidating protein–ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery and design. The problem of protein–ligand interaction is traditionally tackled by molecular docking and simulation, which is based on physical forces and statistical potentials and cannot effectively leverage cryo-EM data and existing protein structural information in the protein–ligand modeling process. In this work, we developed a deep learning bioinformatics pipeline (DeepProLigand) to predict protein–ligand interactions from cryo-EM density maps of proteins and ligands. DeepProLigand first uses a deep learning method to predict the structure of proteins from cryo-EM maps, which is averaged with a reference (template) structure of the proteins to produce a combined structure to add ligands. The ligands are then identified and added into the structure to generate a protein–ligand complex structure, which is further refined. The method based on the deep learning prediction and template-based modeling was blindly tested in the 2021 EMDataResource Ligand Challenge and was ranked first in fitting ligands to cryo-EM density maps. These results demonstrate that the deep learning bioinformatics approach is a promising direction for modeling protein–ligand interactions on cryo-EM data using prior structural information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mining Thermophile Photosynthesis Genes: A Synthetic Operon Expressing Chloroflexota Species Reaction Center Genes in Rhodobacter sphaeroides

Photosynthesis is the foundation of the vast majority of life systems, and is therefore the most important bioenergetic process on earth. The greatest diversity of photosynthetic systems is found in microorganisms. However, our understanding of the biophysical and biochemical processes that transduce light into chemical energy is derived from a relatively small subset of proteins from microbes that are amenable to cultivation, in contrast to the huge number of predicted proteins that catalyze the initial photochemical reactions deposited in databases, such as from metagenomics. We describe the use of a Rhodobacter sphaeroides laboratory strain for the expression of heterologous photosynthesis genes to demonstrate the feasibility of mining this resource, focusing on hot spring Chloroflexota gene sequences. Using a synthetic operon of genes, we produced a photochemically active complex of reaction center proteins in our biological system. We also present bioinformatic analyses of anoxygenic type II reaction center sequences from metagenomic samples collected from hot (42–90 °C) springs available through the JGI IMG database, to generate a resource of diverse sequences that are potentially adapted to photosynthesis at such temperatures. These data provide a view into the natural diversity of anoxygenic photosynthesis, through a lens focused on high-temperature environments. The approach we took to express such genes can be applied for potential biotechnology purposes as well as for studies of fundamental catalytic properties of these heretofore inaccessible protein complexes.

Chloroflexota↗
DOE OSTI2020

Theoretical, Solid‐State, and Solution Quantification of the Hydrogen Bond‐Enhanced Halogen Bond

Abstract Proximal noncovalent forces are commonplace in natural systems and understanding the consequences of their juxtaposition is critical. This paper experimentally quantifies for the first time a Hydrogen Bond‐Enhanced Halogen Bond (HBeXB) without the complexities of protein structure or preorganization. An HBeXB is a halogen bond that has been strengthened when the halogen donor simultaneously accepts a hydrogen bond. Our theoretical studies suggest that electron‐rich halogen bond donors are strengthened most by an adjacent hydrogen bond. Furthermore, stronger hydrogen bond donors enhance the halogen bond the most. X‐ray crystal structures of halide complexes (X − =Br − , I − ) reveal that HBeXBs produce shorter halogen bonds than non‐hydrogen bond analogues. 19 F NMR titrations with chloride highlight that the HBeXB analogue exhibits stronger binding. Together, these results form the foundation for future studies concerning hydrogen bonds and halogen bonds in close proximity.

Decato, Daniel A.↗
DOE OSTI2023

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Theoretical, Solid-State, and Solution Quantification of the Hydrogen Bond-Enhanced Halogen Bond

Proximal noncovalent forces are commonplace in natural systems and understanding the consequences of their juxtaposition is critical. This paper experimentally quantifies for the first time a Hydrogen Bond-Enhanced Halogen Bond (HBeXB) without the complexities of protein structure or preorganization. An HBeXB is a halogen bond that has been strengthened when the halogen donor simultaneously accepts a hydrogen bond. In this work, our theoretical studies suggest that electron-rich halogen bond donors are strengthened most by an adjacent hydrogen bond. Furthermore, stronger hydrogen bond donors enhance the halogen bond the most. X-ray crystal structures of halide complexes (X - =Br - , I - ) reveal that HBeXBs produce shorter halogen bonds than non-hydrogen bond analogues. 19 F NMR titrations with chloride highlight that the HBeXB analogue exhibits stronger binding. Together, these results form the foundation for future studies concerning hydrogen bonds and halogen bonds in close proximity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Mechanism of efficient double-strand break repair by a long non-coding RNA

Mechanistic studies in DNA repair have focused on roles of multi-protein DNA complexes, so how long non-coding RNAs (lncRNAs) regulate DNA repair is less well understood. Yet, lncRNA LINP1 is over-expressed in multiple cancers and confers resistance to ionizing radiation and chemotherapeutic drugs. Here, we unveil structural and mechanistic insights into LINP1’s ability to facilitate non-homologous end joining (NHEJ). We characterized LINP1 structure and flexibility and analyzed interactions with the NHEJ factor Ku70/Ku80 (Ku) and Ku complexes that direct NHEJ. LINP1 self-assembles into phase-separated condensates via RNA–RNA interactions that reorganize to form filamentous Ku-containing aggregates. Structured motifs in LINP1 bind Ku, promoting Ku multimerization and stabilization of the initial synaptic event for NHEJ. Significantly, LINP1 acts as an effective proxy for PAXX. Collective results reveal how lncRNA effectively replaces a DNA repair protein for efficient NHEJ with implications for development of resistance to cancer therapy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Graph identification of proteins in tomograms ( GRIP‐Tomo )

Abstract In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three‐dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo‐multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single‐domain protein native topologies as well as distinct single‐domain proteins from multimeric complexes within noisy volumes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Role of Protein-Water Interface in the Stacking Interactions of Granum Thylakoid Membranes—As Revealed by the Effects of Hofmeister Salts

The thylakoid membranes of vascular plants are differentiated into stacked granum and unstacked stroma regions. The formation of grana is triggered by the macrodomain formation of photosystem II and light-harvesting complex II (PSII-LHCII) and thus their lateral segregation from the photosystem I—light-harvesting complex I (PSI-LHCI) super-complexes and the ATP-synthase; which is then stabilized by stacking interactions of the adjacent PSII-LHCII enriched regions of the thylakoid membranes. The self-assembly and dynamics of this highly organized membrane system and the nature of forces acting between the PSII-LHCII macrodomains are not well understood. By using circular dichroism (CD) spectroscopy, small-angle neutron scattering (SANS) and transmission electron microscopy (TEM), we investigated the effects of Hofmeister salts on the organization of pigment-protein complexes and on the ultrastructure of thylakoid membranes. We found that the kosmotropic agent (NH 4 ) 2 SO 4 and the Hofmeister-neutral NaCl, up to 2 M concentrations, hardly affected the macro-organization of the protein complexes and the membrane ultrastructure. In contrast, chaotropic salts, NaClO 4 , and NaSCN destroyed the mesoscopic structures, the multilamellar organization of the thylakoid membranes and the chiral macrodomains of the protein complexes but without noticeably affecting the short-range, pigment-pigment excitonic interactions. Comparison of the concentration- and time-dependences of SANS, TEM and CD parameters revealed the main steps of the disassembly of grana in the presence of chaotropes. It begins with a rapid diminishment of the long-range periodic order of the grana membranes, apparently due to an increased stacking disorder of the thylakoid membranes, as reflected by SANS experiments. SANS measurements also allowed discrimination between the cationic and anionic effects—in stacking and disorder, respectively. This step is followed by a somewhat slower disorganization of the TEM ultrastructure, due to the gradual loss of stacked membrane pairs. Occurring last is the stepwise decrease and disappearance of the long-range chiral order of the protein complexes, the rate of which was faster in LHCII-deficient membranes. These data are interpreted in terms of a theory, from our laboratory, according to which Hofmeister salts primarily affect the hydrophylic-hydrophobic interactions of proteins, and the stroma-exposed regions of the intrinsic membrane proteins, in particular—pointing to the role of protein-water interface in the stacking interactions of granum thylakoid membranes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures

We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Transparent window 2D IR spectroscopy of proteins

Proteins are complex, heterogeneous macromolecules that exist as ensembles of interconverting states on a complex energy landscape. A complete, molecular-level understanding of their function requires experimental tools to characterize them with high spatial and temporal precision. Infrared (IR) spectroscopy has an inherently fast time scale that can capture all states and their dynamics with, in principle, bond-specific spatial resolution. Two-dimensional (2D) IR methods that provide richer information are becoming more routine but remain challenging to apply to proteins. Spectral congestion typically prevents selective investigation of native vibrations; however, the problem can be overcome by site-specific introduction of amino acid side chains that have vibrational groups with frequencies in the “transparent window” of protein spectra. This Perspective provides an overview of the history and recent progress in the development of transparent window 2D IR of proteins.

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

Decoding Cancer Variants of Unknown Significance for Helicase–Nuclease–RPA Complexes Orchestrating DNA Repair During Transcription and Replication

All tumors have DNA mutations, and a predictive understanding of those mutations could inform clinical treatments. However, 40% of the mutations are variants of unknown significance (VUS), with the challenge being to objectively predict whether a VUS is pathogenic and supports the tumor or whether it is benign. To objectively decode VUS, we mapped cancer sequence data and evolutionary trace (ET) scores onto crystallography and cryo-electron microscopy structures with variant impacts quantitated by evolutionary action (EA) measures. As tumors depend on helicases and nucleases to deal with transcription/replication stress, we targeted helicase–nuclease–RPA complexes: (1) XPB-XPD (within TFIIH), XPF-ERCC1, XPG, and RPA for transcription and nucleotide excision repair pathways and (2) BLM, EXO5, and RPA plus DNA2 for stalled replication fork restart. As validation, EA scoring predicts severe effects for most disease mutations, but disease mutants with low ET scores not only are likely destabilizing but also disrupt sophisticated allosteric mechanisms. For sites of disease mutations and VUS predicted to be severe, we found strong co-localization to ordered regions. Rare discrepancies highlighted the different survival requirements between disease and tumor mutations, as well as the value of examining proteins within complexes. In a genome-wide analysis of 33 cancer types, we found correlation between the number of mutations in each tumor and which pathways or functional processes in which the mutations occur, revealing different mutagenic routes to tumorigenesis. We also found upregulation of ancient genes including BLM, which supports a non-random and concerted cancer process: reversion to a unicellular, proliferation-uncontrolled, status by breaking multicellular constraints on cell division. Together, these genes and global analyses challenge the binary “driver” and “passenger” mutation paradigm, support a gradient impact as revealed by EA scoring from moderate to severe at a single gene level, and indicate reduced regulation as well as activity. The objective quantitative assessment of VUS scoring and gene overexpression in the context of functional interactions and pathways provides insights for biology, oncology, and precision medicine.

59 BASIC BIOLOGICAL SCIENCES↗