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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Physical chemistry and evolution of salt tolerance in halobacteria

The cellular constituents of extremely halophilic bacteria not only tolerate high salt concentration, but in many cases require it for optical functioning. The characteristics affected by salt include enzyme activity, stability, allosteric regulation, conformation and subunit association. The salt effects are of two major kinds: electrostatic shielding of negative charges by cations at low salt concentration, and hydrophobic stabilization by salting-out type salts at high salt concentration. The composition of halobacterial proteins shows an excess of acidic amino acids and a deficiency of nonpolar amino acids, which accounts for these effects. Since the cohesive forces are weaker and the repulsing forces are stronger in these proteins, preventing aggregation in salt, these structures are no longer suited for functioning in the absence of high salt concentrations. Unlike these nonspecific effects, ribosomes in halobacteria show marked preference for potassium over sodium ions. To ensure the proper intracellular ionic composition, powerful ion transport systems have evolved in the halobacteria, resulting in the extrusion of sodium ions and their replacement by potassium. It is likely that such membrane transport system for ionic movements is a necessary requisite for salt tolerance.

Lanyi, J. K.↗
DOE OSTI2023

The differing effects of a dual acting regulator on SIRT1

SIRT1 is an NAD + -dependent protein deacetylase that has been shown to play a significant role in many biological pathways, such as insulin secretion, tumor formation, lipid metabolism, and neurodegeneration. There is great interest in understanding the regulation of SIRT1 to better understand SIRT1-related diseases and to better design therapeutic approaches that target SIRT1. There are many known protein and small molecule activators and inhibitors of SIRT1. One well-studied SIRT1 regulator, resveratrol, has historically been regarded as a SIRT1 activator, however, recent studies have shown that it can also act as an inhibitor depending on the identity of the peptide substrate. The inhibitory nature of resveratrol has yet to be studied in detail. Understanding the mechanism behind this dual behavior is crucial for assessing the potential side effects of STAC-based therapeutics. Here, we investigate the detailed mechanism of substrate-dependent SIRT1 regulation by resveratrol. We demonstrate that resveratrol alters the substrate recognition of SIRT1 by affecting the K M values without significantly impacting the catalytic rate k cat ). Furthermore, resveratrol destabilizes SIRT1 and extends its conformation, but the conformational changes differ between the activation and inhibition scenarios. We propose that resveratrol renders SIRT1 more flexible in the activation scenario, leading to increased activity, while in the inhibition scenario, it unravels the SIRT1 structure, compromising substrate recognition. Our findings highlight the importance of substrate identity in resveratrol-mediated SIRT1 regulation and provide insights into the allosteric control of SIRT1. This knowledge can guide the development of targeted therapeutics for diseases associated with dysregulated SIRT1 activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Allosteric prediction via convolutional neural networks and protein structural and dynamical features

Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changing a protein’s functional state. As such, it is a ubiquitous aspect of protein functional regulation. Computationally predicting allosteric states is important as part of the broader challenge of functional annotation, but it also has practical implications for drug development, as targeting an allosteric site often affords greater specificity compared with targeting an orthosteric site. This study introduces a machine learning approach to predict the allosteric functional state using the small G-protein KRas as the model system, due to its implication in many types of cancer and being well studied as a result with many x-ray crystallographic structures of KRas available with different mutations and ligands bound. Using structural and dynamical features that can be cast as images, namely interatomic distances, contact maps, covariance, and mutual information, supervised learning was performed using convolutional neural networks. Two pretrained convolutional neural network architectures, GoogLeNet and ResNet18, were fine-tuned to classify KRas into active or inactive states based on these features. Across training regimes, atomic contact maps emerged as the most effective structural feature, whereas linearized mutual information outperformed covariance in capturing dynamical correlations relevant to allostery. Models achieved significant validation accuracy, with atomic contact maps yielding up to 90% accuracy. In conclusion, the findings suggest that integrating global structural rearrangements and correlated motion patterns with deep learning can reliably predict protein allosteric states, offering a promising framework for understanding allosteric regulation and developing targeted therapeutics.

Rajeshwar T., Rajitha [Oak Ridge National Laborato↗
DOE OSTI2022

The role of filamentation in activation and DNA sequence specificity of the sequence-specific endonuclease SgrAI

Filament formation by metabolic, biosynthetic, and other enzymes has recently come into focus as a mechanism to fine-tune enzyme activity in the cell. Filamentation is key to the function of SgrAI, a sequence-specific DNA endonuclease that has served as a model system to provide some of the deepest insights into the biophysical characteristics of filamentation and its functional consequences. Structure-function analyses reveal that, in the filamentous state, SgrAI stabilizes an activated enzyme conformation that leads to accelerated DNA cleavage activity and expanded DNA sequence specificity. The latter is thought to be mediated by sequence-specific DNA structure, protein–DNA interactions, and a disorder-to-order transition in the protein, which collectively affect the relative stabilities of the inactive, non-filamentous conformation and the active, filamentous conformation of SgrAI bound to DNA. Full global kinetic modeling of the DNA cleavage pathway reveals a slow, rate-limiting, second-order association rate constant for filament assembly, and simulations of in vivo activity predict that filamentation is superior to non-filamenting mechanisms in ensuring rapid activation and sequestration of SgrAI's DNA cleavage activity on phage DNA and away from the host chromosome. In vivo studies demonstrate the critical requirement for accelerated DNA cleavage by SgrAI in its biological role to safeguard the bacterial host. Collectively, these data have advanced our understanding of how filamentation can regulate enzyme structure and function, while the experimental strategies used for SgrAI can be applied to other enzymatic systems to identify novel functional roles for filamentation.

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

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13 C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Combining Random Mutagenesis and Metabolic Engineering for Enhanced Tryptophan Production in Synechocystis sp. Strain PCC 6803

Tryptophan (Trp) is an essential aromatic amino acid that has value as an animal feed supplement, as the amount found in plant-based sources is insufficient. An alternative to production by engineered microbial fermentation is to have tryptophan biosynthesized by a photosynthetic microorganism that could replace or supplement both the plant and industrially used microbes. We selected Synechocystis sp. strain PCC 6803, a model cyanobacterium, as the host and studied metabolic engineering and random mutagenesis approaches. Previous work on engineering heterotrophic microbes for improved Trp titers has targeted allosteric feedback regulation in enzymes 3-deoxy-d-arabinoheptulosonate 7-phosphate synthase (DAHPS) and anthranilate synthase (AS) as major bottlenecks in the shikimate pathway. In this work, the genes encoding feedback-resistant enzymes from Escherichia coli, aroG fbr and trpE fbr , were overexpressed in the host wild-type (WT) strain. Separately, the WT strain was subjected to random mutagenesis and selection using an amino acid analog to isolate tryptophan-overproducing strains. The randomly mutagenized strains were sequenced in order to identify the mutations that resulted in the desirable phenotypes. Interestingly, the tryptophan overproducers had mutations in the gene encoding chorismate mutase (CM), which catalyzes the conversion of chorismate to prephenate. The best tryptophan overproducer from random mutagenesis was selected as a host for metabolic engineering where aroG fbr and trpE fbr were overexpressed. The best strain developed produced 212 ± 23 mg/liter of tryptophan after 10 days of photoautotrophic growth under 3% (vol/vol) CO2. We demonstrated that a combination of random mutagenesis and metabolic engineering was superior to either individual approach.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Inhibition of Pyruvate Kinase From Thermoanaerobacterium saccharolyticum by IMP Is Independent of the Extra-C Domain

The pyruvate kinase (PYK) isozyme from Thermoanaerobacterium saccharolyticum (TsPYK) has previously been used in metabolic engineering for improved ethanol production. This isozyme belongs to a subclass of PYK isozymes that include an extra C-domain. Like other isozymes that include this extra C-domain, we found that TsPYK is activated by AMP and ribose-5-phosphate (R5P). Our use of sugar-phosphate analogs generated a surprising result in that IMP and GMP are allosteric inhibitors (rather than activators) of TsPYK. We believe this to be the first report of any PYK isozyme being inhibited by IMP and GMP. A truncated protein that lacks the extra C-domain is also inhibited by IMP. A screen of several other bacterial PYK enzymes (include several that have the extra-C domain) indicates that the inhibition by IMP is specific to only a subset of those isozymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Microbial spies and bloggers: programming cells to convert environmental information into discernible signals

Microbes regulate their dynamic behaviors using the chemical and physical characteristics of their environment. The ability of microbes to continuously convert this physicochemical information into biochemical information and to use organic matter in the environment as a power source makes these organisms attractive as chassis for building sensors. However, most biosensors have severe limitations when considering applications in hard-to-image settings like soils, sediments, and wastewater. Emerging technologies at the interface of biomolecular design, microbiome engineering, and synthetic biology offer new tools to program cells and communities as biosensors for these settings. Here, in this review, we describe innovations in biosensor outputs that are enabling new applications in complex environments, including reporters that are read out using electrochemical, gas chromatography, hyperspectral imaging, and next-generation sequencing methods. We also discuss computational advances that are accelerating the diversification of sensing components by mining metagenomics data for new transcriptional regulators and by designing allosteric protein switches that directly regulate reporter outputs using analytes. We highlight emerging opportunities for programming undomesticated microbes in communities to function as distributed sensors in the environment. Finally, we discuss the need for responsible biosensor development and to modernize regulatory frameworks to support evidence-based assessment of environmental biosensors.

analyte↗
DOE OSTI2021

A lipoprotein allosterically activates the CwlD amidase during Clostridioides difficile spore formation

Spore-forming pathogens like Clostridioides difficile depend on germination to initiate infection. During gemination, spores must degrade their cortex layer, which is a thick, protective layer of modified peptidoglycan. Cortex degradation depends on the presence of the spore-specific peptidoglycan modification, muramic-∂-lactam (MAL), which is specifically recognized by cortex lytic enzymes. In C . difficile , MAL production depends on the CwlD amidase and its binding partner, the GerS lipoprotein. To gain insight into how GerS regulates CwlD activity, we solved the crystal structure of the CwlD:GerS complex. In this structure, a GerS homodimer is bound to two CwlD monomers such that the CwlD active sites are exposed. Although CwlD structurally resembles amidase_3 family members, we found that CwlD does not bind Zn 2+ stably on its own, unlike previously characterized amidase_3 enzymes. Instead, GerS binding to CwlD promotes CwlD binding to Zn 2+ , which is required for its catalytic mechanism. Thus, in determining the first structure of an amidase bound to its regulator, we reveal stabilization of Zn 2+ co-factor binding as a novel mechanism for regulating bacterial amidase activity. Our results further suggest that allosteric regulation by binding partners may be a more widespread mode for regulating bacterial amidase activity than previously thought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An Activity-Based Oxaziridine Platform for Identifying and Developing Covalent Ligands for Functional Allosteric Methionine Sites: Redox-Dependent Inhibition of Cyclin-Dependent Kinase 4

Activity-based protein profiling (ABPP) is a versatile strategy for identifying and characterizing functional protein sites and compounds for therapeutic development. However, the vast majority of ABPP methods for covalent drug discovery target highly nucleophilic amino acids such as cysteine or lysine. Here, we report a methionine-directed ABPP platform using Redox-Activated Chemical Tagging (ReACT), which leverages a biomimetic oxidative ligation strategy for selective methionine modification. Application of ReACT to oncoprotein cyclin-dependent kinase 4 (CDK4) as a representative high-value drug target identified three new ligandable methionine sites. We then synthesized a methionine-targeting covalent ligand library bearing a diverse array of heterocyclic, heteroatom, and stereochemically rich substituents. ABPP screening of this focused library identified 1oxF11 as a covalent modifier of CDK4 at an allosteric M169 site. This compound inhibited kinase activity in a dose-dependent manner on purified protein and in breast cancer cells. Further investigation of 1oxF11 found prominent cation-π and H-bonding interactions stabilizing the binding of this fragment at the M169 site. Quantitative mass-spectrometry studies validated 1oxF11 ligation of CDK4 in breast cancer cell lysates. Further biochemical analyses revealed cross-talk between M169 oxidation and T172 phosphorylation, where M169 oxidation prevented phosphorylation of the activating T172 site on CDK4 and blocked cell cycle progression. Finally, by identifying a new mechanism for allosteric methionine redox regulation on CDK4 and developing a unique modality for its therapeutic intervention, this work showcases a generalizable platform that provides a starting point for engaging in broader chemoproteomics and protein ligand discovery efforts to find and target previously undruggable methionine sites.

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

Molecular characterization of ebselen binding activity to SARS-CoV-2 main protease

There is an urgent need to repurpose drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recent computational-experimental screenings have identified several existing drugs that could serve as effective inhibitors of the virus’ main protease, M pro , which is involved in gene expression and replication. Among these, ebselen (2-phenyl-1,2-benzoselenazol-3-one) appears to be particularly promising. Here, we examine, at a molecular level, the potential of ebselen to decrease Mpro activity. We find that it exhibits a distinct affinity for the catalytic region. Our results reveal a higher-affinity, previously unknown binding site localized between the II and III domains of the protein. A detailed strain analysis indicates that, on such a site, ebselen exerts a pronounced allosteric effect that regulates catalytic site access through surface-loop interactions, thereby inducing a reconfiguration of water hotspots. Together, these findings highlight the promise of ebselen as a repurposed drug against SARS-CoV-2.

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

Ancient origins of allosteric activation in a Ser-Thr kinase

A myriad of cellular events are regulated by allostery; therefore, evolution of this process is of fundamental interest. Here, we use ancestral sequence reconstruction to resurrect ancestors of two colocalizing proteins, Aurora A kinase and its allosteric activator TPX2 (targeting protein for Xklp2), to experimentally characterize the evolutionary path of allosteric activation. Autophosphorylation of the activation loop is the most ancient activation mechanism; it is fully developed in the oldest kinase ancestor and has remained stable over 1 billion years of evolution. As the microtubule-associated protein TPX2 appeared, efficient kinase binding to TPX2 evolved, likely owing to increased fitness by virtue of colocalization. Subsequently, TPX2-mediated allosteric kinase regulation gradually evolved. Surprisingly, evolution of this regulation is encoded in the kinase and did not arise by a dominating mechanism of coevolution.

Science & Technology - Other Topics↗
DOE OSTI2024

Highly multiplexed design of an allosteric transcription factor to sense new ligands

Allosteric transcription factors (aTF) regulate gene expression through conformational changes induced by small molecule binding. Although widely used as biosensors, aTFs have proven challenging to design for detecting new molecules because mutation of ligand-binding residues often disrupts allostery. Here, we develop Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screen a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures – four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone – as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identifies biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design shows shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we develop cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid and scalable design of new biosensors, overcoming constraints of natural biosensors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MEP pathway products allosterically promote monomerization of deoxy-D-xylulose-5-phosphate synthase to feedback-regulate their supply

Isoprenoids are a very large and diverse family of metabolites required by all living organisms. All isoprenoids derive from the double-bond isomers isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP), which are produced by the methylerythritol 4-phosphate (MEP) pathway in bacteria and plant plastids. It has been reported that IPP and DMAPP feedback-regulate the activity of deoxyxylulose 5-phosphate synthase (DXS), a dimeric enzyme that catalyzes the main flux-controlling step of the MEP pathway. Here we provide experimental insights into the underlying mechanism. Isothermal titration calorimetry and dynamic light scattering approaches showed that IPP and DMAPP can allosterically bind to DXS in vitro, causing a size shift. In silico ligand binding site analysis and docking calculations identified a potential allosteric site in the contact region between the two monomers of the active DXS dimer. Modulation of IPP and DMAPP contents in vivo followed by immunoblot analyses confirmed that high IPP/DMAPP levels resulted in monomerization and eventual aggregation of the enzyme in bacterial and plant cells. Loss of the enzymatically active dimeric conformation allows a fast and reversible reduction of DXS activity in response to a sudden increase or decrease in IPP/DMAPP supply, whereas aggregation and subsequent removal of monomers that would otherwise be available for dimerization appears to be a more drastic response in the case of persistent IPP/DMAPP overabundance (e.g., by a blockage in their conversion to downstream isoprenoids). Our results represent an important step toward understanding the regulation of the MEP pathway and rational design of biotechnological endeavors aimed at increasing isoprenoid contents in microbial and plant systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Casein kinase 1 dynamics underlie substrate selectivity and the PER2 circadian phosphoswitch

Post-translational control of PERIOD stability by Casein Kinase 1δ and ε (CK1) plays a key regulatory role in metazoan circadian rhythms. Despite the deep evolutionary conservation of CK1 in eukaryotes, little is known about its regulation and the factors that influence substrate selectivity on functionally antagonistic sites in PERIOD that directly control circadian period. Here we describe a molecular switch involving a highly conserved anion binding site in CK1. This switch controls conformation of the kinase activation loop and determines which sites on mammalian PER2 are preferentially phosphorylated, thereby directly regulating PER2 stability. Integrated experimental and computational studies shed light on the allosteric linkage between two anion binding sites that dynamically regulate kinase activity. We show that period-altering kinase mutations from humans to Drosophila differentially modulate this activation loop switch to elicit predictable changes in PER2 stability, providing a foundation to understand and further manipulate CK1 regulation of circadian rhythms.

59 BASIC BIOLOGICAL SCIENCES↗