Search NASA⌕ Search

SEARCH · Search NASA

Results for “Library screening”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Directed evolution of an ultrastable carbonic anhydrase for highly efficient carbon capture from flue gas

Carbonic anhydrase (CA) is one of nature’s fastest enzymes and can dramatically improve the economics of carbon capture under demanding environments such as coal-fired power plants. The use of CA to accelerate carbon capture is limited by the enzyme’s sensitivity to the harsh process conditions. Using directed evolution, the properties of a β-class CA from Desulfovibrio vulgaris were dramatically enhanced. Iterative rounds of library design, library generation, and high-throughput screening identified highly stable CA variants that tolerate temperatures of up to 107 °C in the presence of 4.2 M alkaline amine solvent at pH >10.0. This increase in thermostability and alkali tolerance translates to a 4,000,000-fold improvement over the natural enzyme. In conclusion, at pilot scale, the evolved catalyst enhanced the rate of CO2 absorption 25-fold compared with the noncatalyzed reaction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

DNA-encoded chemistry technology yields expedient access to SARS-CoV-2 M pro inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed more than 4 million humans globally, but there is no bona fide Food and Drug Administration–approved drug-like molecule to impede the COVID-19 pandemic. The sluggish pace of traditional therapeutic discovery is poorly suited to producing targeted treatments against rapidly evolving viruses. Here, we used an affinity-based screen of 4 billion DNA-encoded molecules en masse to identify a potent class of virus-specific inhibitors of the SARS-CoV-2 main protease (M pro ) without extensive and time-consuming medicinal chemistry. CDD-1714, the initial three-building-block screening hit (molecular weight [MW] = 542.5 g/mol), was a potent inhibitor (inhibition constant [K i ] = 20 nM). CDD-1713, a smaller two-building-block analog (MW = 353.3 g/mol) of CDD-1714, is a reversible covalent inhibitor of M pro (K i = 45 nM) that binds in the protease pocket, has specificity over human proteases, and shows in vitro efficacy in a SARS-CoV-2 infectivity model. Subsequently, key regions of CDD-1713 that were necessary for inhibitory activity were identified and a potent (K i = 37 nM), smaller (MW = 323.4 g/mol), and metabolically more stable analog (CDD-1976) was generated. Thus, screening of DNA-encoded chemical libraries can accelerate the discovery of efficacious drug-like inhibitors of emerging viral disease targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Structural Insight into Allosteric Inhibition of Mycobacterium tuberculosis Tryptophan Synthase

The rise of antibiotic‐resistant pathogens requires redirecting drug discovery effort toward new cellular targets to provide new treatment options. Such alternative, yet unexplored opportunities exist in central metabolism, where many enzymes are only conditionally essential and thus their successful exploitation requires understanding of metabolic fluxes and pathway regulations under certain environmental conditions. In Mycobacterium tuberculosis , tryptophan biosynthesis represents one such promising pathway that could be targeted. In Mtb, the multistep L‐Trp synthesis involves several enzymes: TrpEG, TrpD, TrpC and TrpAB, which is validated as conditionally essential in vivo . The whole‐cell screening of a diversity‐oriented synthetic library identified a novel bactericidal azetidine derivative, BRD4592, that specifically inhibits TrpAB (tryptophan synthase). TrpAB is a heterotetrameric, PLP‐dependent complex catalyzing two last reactions in L‐Trp synthesis: the conversion of indole‐3‐glycerol phosphate to indole and glyceraldehyde 3‐phosphate (TrpA) followed by indole and L‐Ser condensation to yield L‐Trp (TrpB). During the catalytic cycle, indole is transferred from the TrpA to TrpB active site through 25 Å hydrophobic channel to react with the L‐Ser‐PLP adduct. The enzymatic activities and substrate channeling are coordinated by complex allosteric communication between the subunits. This regulation involves cycling between various conformational states, with both subunits adopting either an open (inactive) or closed (active) state. Detailed kinetic, biophysical and structural evidence reveals that BRD4592 is an allosteric, mixed‐type inhibitor, which binds specifically to a novel site within the intersubunit channel, at the TrpA‐TrpB interface. The molecule promotes closed, active state of the TrpB subunit and increases enzyme affinity for the L‐Ser substrate. BRD4592 acts on three levels: it limits flexibility of the interface potentially disrupting mutual activation of the subunits, prevents indole translocation, and increases product inhibition providing means to successfully inhibit both, TrpA and TrpB reactions. Our results indicate that allosteric binders may represent an effective tool to deactivate central metabolism enzymes, which often are allosterically regulated and might be predisposed for this type of inhibition. Support or Funding Information This work was supported by the Broad Institute Tuberculosis donor group, the Pershing Square Foundation, the Bill & Melinda Gates Foundation under grant OPP1032518, the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contracts HHSN272200700058C and HHSN272201200026C and the U. S. Department of Energy, Office of Biological and Environmental Research, under contract DE‐AC02‐06CH11357. For this work, University of Chicago is a subgrantee of Structural Genomics Consortium under a Bill & Melinda Gates Foundation grant for the Structure‐Guided Drug Discovery Coalition.

Michalska, Karolina↗
DOE OSTI2020

An ultrapotent synthetic nanobody neutralizes SARS-CoV-2 by stabilizing inactive Spike

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus enters host cells via an interaction between its Spike protein and the host cell receptor angiotensin-converting enzyme 2 (ACE2). By screening a yeast surface-displayed library of synthetic nanobody sequences, we developed nanobodies that disrupt the interaction between Spike and ACE2. Cryo–electron microscopy (cryo-EM) revealed that one nanobody, Nb6, binds Spike in a fully inactive conformation with its receptor binding domains locked into their inaccessible down state, incapable of binding ACE2. Affinity maturation and structure-guided design of multivalency yielded a trivalent nanobody, mNb6-tri, with femtomolar affinity for Spike and picomolar neutralization of SARS-CoV-2 infection. mNb6-tri retains function after aerosolization, lyophilization, and heat treatment, which enables aerosol-mediated delivery of this potent neutralizer directly to the airway epithelia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

An Amoebal Grazer of Cyanobacteria Requires Cobalamin Produced by Heterotrophic Bacteria

Amoebae are unicellular eukaryotes that consume microbial prey through phagocytosis, playing a role in shaping microbial food webs. Many amoebal species can be cultivated axenically in rich media or monoxenically with a single bacterial prey species. Here, we characterize heterolobosean amoeba LPG3, a recent natural isolate, which is unable to grow on unicellular cyanobacteria, its primary food source, in the absence of a heterotrophic bacterium, a Pseudomonas species coisolate. To investigate the molecular basis of this requirement for heterotrophic bacteria, we performed a screen using the defined nonredundant transposon library of Vibrio cholerae , which implicated genes in corrinoid uptake and biosynthesis. Furthermore, cobalamin synthase deletion mutations in V. cholerae and the Pseudomonas species coisolate do not support the growth of amoeba LPG3 on cyanobacteria. While cyanobacteria are robust producers of a corrinoid variant called pseudocobalamin, this variant does not support the growth of amoeba LPG3. Instead, we show that it requires cobalamin that is produced by the Pseudomonas species coisolate. The diversity of eukaryotes utilizing corrinoids is poorly understood, and this amoebal corrinoid auxotroph serves as a model for examining predator-prey interactions and micronutrient transfer in bacterivores underpinning microbial food webs.Cyanobacteria are important primary producers in aquatic environments, where they are grazed upon by a variety of phagotrophic protists and, hence, have an impact on nutrient flux at the base of microbial food webs. Here, we characterize amoebal isolate LPG3, which consumes cyanobacteria as its primary food source but also requires heterotrophic bacteria as a source of corrinoid vitamins. Amoeba LPG3 specifically requires the corrinoid variant produced by heterotrophic bacteria and cannot grow on cyanobacteria alone, as they produce a different corrinoid variant. This same corrinoid specificity is also exhibited by other eukaryotes, including humans and algae. This amoebal model system allows us to dissect predator-prey interactions to uncover factors that may shape microbial food webs while also providing insight into corrinoid specificity in eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Chemistry↗
DOE OSTI2025

Next-generation sequencing dataset of genome-scale CRISPRi in Synechococcus sp. PCC 7002 across seven conditions

A 33,298-member sgRNA library developed for Synechococus sp. PCC 7002 was screened with two replicates across seven growth conditions and sequenced with Illumina NextSeq (paired end, 2x150 bp) for a total of ~700M reads. The original plasmid library and the library after transformation into a dCas9-containing and dCas9-absent strain were also sequenced as a reference for initial sgRNA abundance.

genome- wide screens environmental acclimation spe↗
DOE OSTI2018

Discovery of Selective RNA-Binding Small Molecules by Affinity-Selection Mass Spectrometry

Recent advances in understanding the relevance of noncoding RNA (ncRNA) to disease have increased interest in drugging ncRNA with small molecules. The recent discovery of ribocil, a structurally distinct synthetic mimic of the natural ligand of the flavin mononucleotide (FMN) riboswitch, has revealed the potential chemical diversity of small molecules that target ncRNA. Affinity-selection mass spectrometry (AS-MS) is theoretically applicable to high-throughput screening (HTS) of small molecules binding to ncRNA. In this paper, we report the first application of the Automated Ligand Detection System (ALIS), an indirect AS-MS technique, for the selective detection of small molecule–ncRNA interactions, high-throughput screening against large unbiased small-molecule libraries, and identification and characterization of novel compounds (structurally distinct from both FMN and ribocil) that target the FMN riboswitch. Crystal structures reveal that different compounds induce various conformations of the FMN riboswitch, leading to different activity profiles. Our findings validate the ALIS platform for HTS screening for RNA-binding small molecules and further demonstrate that ncRNA can be broadly targeted by chemically diverse yet selective small molecules as therapeutics.

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

Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows

Synthetic polymers are highly customizable with tailored structures and functionality, yet this versatility generates challenges in the design of advanced materials due to the size and complexity of the design space. Thus, exploration and optimization of polymer properties using combinatorial libraries has become increasingly common, which requires careful selection of synthetic strategies, characterization techniques, and rapid processing workflows to obtain fundamental principles from these large data sets. Herein, we provide guidelines for strategic design of macromolecule libraries and workflows to efficiently navigate these high-dimensional design spaces. We describe synthetic methods for multiple library sizes and structures as well as characterization methods to rapidly generate data sets, including tools that can be adapted from biological workflows. We further highlight relevant insights from statistics and machine learning to aid in data featurization, representation, and analysis. This Perspective acts as a “user guide” for researchers interested in leveraging high-throughput screening toward the design of multifunctional polymers and predictive modeling of structure–property relationships in soft materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways

The ability to fine tune gene expression has created the field of metabolic pathway optimization and balancing where a variety of factors affecting flux balance are carefully modulated to improve product titers, yields and productivity. Using a library of isopropyl β-D- 1 -thiogalactopyranoside (IPTG)-inducible mutant T 7 promoters of varied strength a combinatorial method was developed for transcriptional balancing of the violacein pathway. Violacein biosynthesis involves a complex five-gene pathway that is an excellent model for exploratory metabolic engineering efforts into pathway regulation and control due to many colorful intermediates and side products allowing for easy analysis and strain comparison. Upon screening approximately 4% of the total initial library, several high-titer mutants were discovered that resulted in up to a 63-fold improvement over the control strain. With further fermentation optimization, titers were improved to 1829 ± 46 mg/L; a 2.6-fold improvement in titer and a 30-fold improvement in productivity from previous literature reports.

59 BASIC BIOLOGICAL SCIENCES↗
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↗
DOE OSTI2023

Coupling High-Throughput and Targeted Screening for Identification of Nonobvious Metabolic Engineering Targets

Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving p-coumaric acid (p-CA) and L -DOPA production from two large 4k gRNA libraries each deregulating 1000 metabolic genes in the yeast Saccharomyces cerevisiae. We initially screened yeast cells transformed with gRNA library plasmids for individual regulatory targets improving the production of l-tyrosine-derived betaxanthins, identifying 30 targets that increased intracellular betaxanthin content 3.5–5.7 fold. Hereafter, we screened the targets individually in a high-producing p-CA strain, narrowing down the targets to six that increased the secreted titer by up to 15%. To investigate whether any of the six targets could be additively combined to improve p-CA production further, we created a gRNA multiplexing library and subjected it to our proposed coupled workflow. The combination of regulating PYC1 and NTH2 simultaneously resulted in the highest (threefold) improvement of the betaxanthin content, and an additive trend was also observed in the p-CA strain. Lastly, we tested the initial 30 targets in a L -DOPA producing strain, identifying 10 targets that increased the secreted titer by up to 89%, further validating our screening by proxy workflow. This coupled approach is useful for strain development in the absence of direct HTP screening assays for products of interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Inferior Vena Cava Filters in Hemodynamically Unstable Patients with Acute Pulmonary Embolism: How Often are They Used? Data from Multicenter Prospective Registries on Acute Pulmonary Embolism

The use of inferior vena cava (IVC) filters is recommended in patients with acute pulmonary embolism (PE) who have absolute contraindications to anticoagulant drugs and/or in those subjects with recurrent PE despite treated with an adequate anticoagulant regimen. During the last 2 decades, some investigations have demonstrated that the use of IVC filters in high-risk PE patients, treated or not with systemic thrombolysis, was able to reduce the short-term mortality rate if inserted early after the acute event. The aim of the present review is to analyze the use of IVC filters in high-risk PE patients enrolled in prospective multicenter registries between 1990 and 2018. After screening 3542 article in PubMed, Scopus, Cochrane library and Goggle Scholar databases, we identified four registry studies meeting the inclusion criteria. In a prospective cohort of 39,056 patients, 1387 (3.5%) were hemodynamically unstable at admission. Among them, IVC filters were used only in 2.7% of cases. Conversely, IVC filters were inserted in 3.8% of hemodynamically stable patients. Over the years, a fluctuating trend in the use of IVC filters was observed. In the absence of randomized controlled trial on this issue, which would be difficult, if not impossible to realize, data obtained from the medical literature seem to suggest that IVC filters could represent a valid adjunctive therapy in hemodynamically unstable PE patients, able to prevent further hemodynamic deterioration. Further and larger subgroup analyses, obtained both by prospective and retrospective studies, are necessary to clarify this therapeutic approach.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Biophysical Screens Identify Fragments That Bind to the Viral DNA-Binding Proteins EBNA1 and LANA

The human gamma-herpesviruses Epstein–Barr virus (EBV) (HHV-4) and Kaposi’s sarcoma-associated herpesvirus (KSHV) (HHV-8) are responsible for a number of diseases, including various types of cancer. Epstein–Barr nuclear antigen 1 (EBNA1) from EBV and latency-associated nuclear antigen (LANA) from KSHV are viral-encoded DNA-binding proteins that are essential for the replication and maintenance of their respective viral genomes during latent, oncogenic infection. As such, EBNA1 and LANA are attractive targets for the development of small-molecule inhibitors. To this end, we performed a biophysical screen of EBNA1 and LANA using a fragment library by saturation transfer difference (STD)–NMR spectroscopy and surface plasmon resonance (SPR). We identified and validated a number of unique fragment hits that bind to EBNA1 or LANA. We also determined the high-resolution crystal structure of one fragment bound to EBNA1. Results from this screening cascade provide new chemical starting points for the further development of potent inhibitors for this class of viral proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Diverse Bacterial Groups Contribute to the Alkane Degradation Potential of Chronically Polluted Subantarctic Coastal Sediments

We aimed to gain insight into the alkane degradation potential of microbial communities from chronically polluted sediments of a subantarctic coastal environment using a combination of metagenomic approaches. A total of 6178 sequences annotated as alkane-1-monooxygenases (EC 1.14.15.3) were retrieved from a shotgun metagenomic dataset that included two sites analyzed in triplicate. The majority of the sequences binned with AlkB described in Bacteroidetes (32 ± 13 %) or Proteobacteria (29 ± 7 %), although a large proportion remained unclassified at the phylum level. Operational taxonomic unit (OTU)-based analyses showed small differences in AlkB distribution among samples that could be correlated with alkane concentrations, as well as with site-specific variations in pH and salinity. A number of low-abundance OTUs, mostly affiliated with Actinobacterial sequences, were found to be only present in the most contaminated samples. On the other hand, the molecular screening of a large-insert metagenomic library of intertidal sediments from one of the sampling sites identified two genomic fragments containing novel alkB gene sequences, as well as various contiguous genes related to lipid metabolism. Both genomic fragments were affiliated with the phylum Planctomycetes, and one could be further assigned to the genus Rhodopirellula due to the presence of a partial sequence of the 23S ribosomal RNA (rRNA) gene. This work highlights the diversity of bacterial groups contributing to the alkane degradation potential and reveals patterns of functional diversity in relation with environmental stressors in a chronically polluted, high-latitude coastal environment. In addition, alkane biodegradation genes are described for the first time in members of Planctomycetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Kinetic characterization of ebselen, chelerythrine and apomorphine as glutaminase inhibitors

Highlights: •Ebselen, chelerythrine and apomorphine were identified as glutaminase inhibitors. •These had greater affinities and efficiency of inhibition than known prototypes. •Their previously reported biological activity could be due to glutaminase inhibition. -- Abstract: Glutaminase catalyzes the hydrolysis of glutamine to glutamate and plays a central role in the proliferation of neoplastic cells via glutaminolysis, as well as in the generation of excitotoxic glutamate in central nervous system disorders such as HIV-associated dementia (HAD) and multiple sclerosis. Both glutaminase siRNA and glutaminase inhibition have been shown to be effective in in vitro models of cancer and HAD, suggesting a potential role for small molecule glutaminase inhibitors. However, there are no potent, selective inhibitors of glutaminase currently available. The two prototypical glutaminase inhibitors, BPTES and DON, are either insoluble or non-specific. In a search for more drug-like glutaminase inhibitors, we conducted a screen of 1280 in vivo active drugs (Library of Pharmacologically Active Compounds (LOPAC{sup 1280})) and identified ebselen, chelerythrine and (R)-apomorphine. The newly identified inhibitors exhibited 10 to 1500-fold greater affinities than DON and BPTES and over 100-fold increased efficiency of inhibition. Although non-selective, it is noteworthy that the affinity of ebselen for glutaminase is more potent than any other activity yet described. It is possible that the previously reported biological activity seen with these compounds is due, in part, to glutaminase inhibition. Ebselen, chelerythrine and apomorphine complement the armamentarium of compounds to explore the role of glutaminase in disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Identification of FAM96B as a novel prelamin A binding partner

Highlights: •We screen the binding protein of prelamin A by yeast two-hybrid screen. •FAM96B colocalizes with prelamin A in HEK-293 cells. •FAM96B physically interacts with prelamin A. -- Abstract: Prelamin A accumulation causes nuclear abnormalities, impairs nuclear functions, and eventually promotes cellular senescence. However, the underlying mechanism of how prelamin A promotes cellular senescence is still poorly understood. Here we carried out a yeast two-hybrid screen using a human skeletal muscle cDNA library to search for prelamin A binding partners, and identified FAM96B as a prelamin A binding partner. The interaction of FAM96B with prelamin A was confirmed by GST pull-down and co-immunoprecipitation experiments. Furthermore, co-localization experiments by fluorescent confocal microscopy revealed that FAM96B colocalized with prelamin A in HEK-293 cells. Taken together, our data demonstrated the physical interaction between FAM96B and prelamin A, which may provide some clues to the mechanisms of prelamin A in premature aging.

60 APPLIED LIFE SCIENCES↗