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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Principles of paralog-specific targeted protein degradation engaging the C-degron E3 KLHDC2

Abstract PROTAC® (proteolysis-targeting chimera) molecules induce proximity between an E3 ligase and protein-of-interest (POI) to target the POI for ubiquitin-mediated degradation. Cooperative E3-PROTAC-POI complexes have potential to achieve neo-substrate selectivity beyond that established by POI binding to the ligand alone. Here, we extend the collection of ubiquitin ligases employable for cooperative ternary complex formation to include the C-degron E3 KLHDC2. Ligands were identified that engage the C-degron binding site in KLHDC2, subjected to structure-based improvement, and linked to JQ1 for BET-family neo-substrate recruitment. Consideration of the exit vector emanating from the ligand engaged in KLHDC2’s U-shaped degron-binding pocket enabled generation of SJ46421, which drives formation of a remarkably cooperative, paralog-selective ternary complex with BRD3 BD2 . Meanwhile, screening pro-drug variants enabled surmounting cell permeability limitations imposed by acidic moieties resembling the KLHDC2-binding C-degron. Selectivity for BRD3 compared to other BET-family members is further manifested in ubiquitylation in vitro, and prodrug version SJ46420-mediated degradation in cells. Selectivity is also achieved for the ubiquitin ligase, overcoming E3 auto-inhibition to engage KLHDC2, but not the related KLHDC1, KLHDC3, or KLHDC10 E3s. In sum, our study establishes neo-substrate-specific targeted protein degradation via KLHDC2, and provides a framework for developing selective PROTAC protein degraders employing C-degron E3 ligases.

Science & Technology - Other Topics↗
NASA NTRS1999

Induction of Three-Dimensional Growth of Human Liver Cells in Simulated Microgravity

We previously reported that a NASA-developed bioreactor that simulates microgravity environment and creates the unique environment of low shear force and high-mass transfer is conducive for maintaining long term 3-D cell cultures of functional hepatocytes (60 days). However, significant further expansion of liver mass, or the remodeling of liver in vitro was jeopardized by the appearance of apoptotic zones in the center of large cell aggregates. To optimize oxygenation and nutritional uptake within growing cellular aggregates we cultured primary human liver cells (HLC) in a bioreactor in the presence or absence of microcarriers and biodegradable scaffolds. Also, to promote angiogenesis, HLC were cultured with or without microvascular endothelial cells. HLC were harvested from human livers by collagenase perfusion. While microcarriers did not affect cell growth, HLC cultured with biodegradable scaffolds made from polyglycolic acid (PGA) formed aggregates up to 3 cm in length. Culturing cells with PGA scaffolds increased the efficiency of cell self-assembly and the formation of larger cell aggregates. Based on histological evaluation it appears that the degree of apoptotic cells was diminished as compared to cultures without scaffolds. Histology of HLC with PGA-scaffolds revealed cell distribution between the fibers of the scaffolds, and cell-cell and cell-fiber interactions. Analyses of HLC spheroids revealed tissue-like structures comprised of hepatocytes, biliary epithelial cells and/or progenitor liver cells that were arranged as bile duct-like structures along nascent vascular sprouts. Electron microscopy revealed groups of cohesive hepatocytes and bile canaliculi with multiple microvilli and tight cellular junctions. Hepatocytes were further organized into tight clusters surrounded by complex stromal structures and reticulin fibers. Also, we observed higher levels of albumin mRNA expression when hepatocytes were co-cultured with endothelial cells. To evaluate viability and microsomal deethylation activity of hepatocytes we assessed the metabolism of midazolam by gas chromatography. Samples that were collected from HLC cultured in the bioreactor contained higher levels of midazolam metabolites (1-OH-midazolam and 4-OH-midazolam) than samples collected from conventional cultures. In summary, we have shown that co-culture of HLC with endothelial cells and/or culturing in the presence of PGA scaffolds provides additional advantages in maintaining functional activity of 3-D hepatocyte cultures that resemble liver tissue. This cell culture system may facilitate studies of liver regeneration and cell-to-cell interactions that occur in vivo and suggest the feasibility of using this approach for pre-clinical metabolic screening of novel drug candidates.

Pellis, Neal R.↗
NASA NTRS2002

Dynamic Light-Scattering Probe Used for the Very Early Detection of Cataracts and to Measure Response to Therapy (or Treatment)

Half of all blindness worldwide is due to cataracts, and 34 million Americans over the age of 65 have cataracts. This figure is expected to rise to 70 million by the year 2030. Currently, no medical treatment is available to prevent or halt the progression of a cataract; nor is there any way to reverse a cataract once it has been detected by conventional methods. The only known treatment is surgical removal of the lens. It is estimated that over $5 billion will be spent this year for the treatment of cataract patients in the United States alone. According to Carl Kupfer, M.D., former Director of the National Eye Institute at the National Institutes of Health, "A delay in cataract formation of about 10 years would reduce the prevalence of visually disabling cataracts by about 45 percent." However, this vision remains a dream because of the lack of objective methods that can be used to detect cataracts very early and, hence, can be used for screening potential anticataract drugs. This is about to change. The National Eye Institute and NASA entered into a formal interagency agreement in late 1996 to develop and test a dynamic light-scattering (DLS) device to detect the earliest changes due to cataract formation. The new DLS probe developed by Dr. Ansari at the NASA Glenn Research Center is several orders of magnitude more sensitive than conventional clinical systems. This ultrahigh sensitivity enables the probe to detect the onset of a cataract before it has any effect on vision and allows researchers to test the effectiveness of anticataract drugs in reversing cataracts. This device (see the following illustration) was originally designed to study transport phenomena in microgravity fluid physics experiments onboard the space shuttle orbiters and space station. It will be very useful in testing anticataract drugs to halt or reverse the progression of cataracts during longitudinal clinical trials.

Ansari,Rafat R.↗
NASA NTRS2011

Improved Devices for Collecting Sweat for Chemical Analysis

Improved devices have been proposed for collecting sweat for biochemical analysis - especially for determination of the concentration of Ca2+ ions in sweat as a measure of loss of Ca from bones. Unlike commercially available sweat-collection patches used previously in monitoring osteoporosis and in qualitative screening for some drugs, the proposed devices would not allow evaporation of the volatile chemical components (mostly water) of sweat. Moreover, the proposed devices would be designed to enable determination of the volumes of collected sweat. From these volumes and the quantities of Ca(2+) and/or other analytes as determined by other means summarized below, one could determine the concentrations of the analytes in sweat. A device according to the proposal would be flexible and would be worn like a commercial sweat-collection patch. It would be made of molded polydimethylsiloxane (silicone rubber) or other suitable material having properties that, for the purpose of analyzing sweat, are similar to those of glass. The die for molding the silicone rubber would be fabricated by a combination of lithography and electroplating. The die would reproducibly form, in the silicone rubber, a precisely defined number of capillary channels per unit area, each channel having a precisely defined volume. Optionally, electrodes for measuring the Ca(2+) content of the sweat could be incorporated into the device. The volume of sweat collected in the capillary channels of the device would be determined from (1) the amount of light or radio waves of a given wavelength absorbed by the device and (2) the known geometry of the array of capillary channels. Then, in one of two options, centrifugation would be performed to move the sweat from the capillary tubes to the region containing the electrodes, which would be used to measure the Ca(2+) content by a standard technique. In the other option, centrifugation would be performed to remove the sweat from the device to make the sweat available to other analytical instruments for measuring concentrations of substances other than Ca(2+).

Feedback, Daniel L.↗
NASA NTRS2011

Improved Devices for Collecting Sweat for Chemical Analysis

Improved devices have been proposed for collecting sweat for biochemical analysis especially for determination of the concentration of Ca2+ ions in sweat as a measure of loss of Ca from bones. Unlike commercially available sweat-collection patches used previously in monitoring osteoporosis and in qualitative screening for some drugs, the proposed devices would not allow evaporation of the volatile chemical components (mostly water) of sweat. Moreover, the proposed devices would be designed to enable determination of the volumes of collected sweat. From these volumes and the quantities of Ca2+ and/or other analytes as determined by other means summarized below, one could determine the concentrations of the analytes in sweat. A device according to the proposal would be flexible and would be worn like a commercial sweat-collection patch. It would be made of molded polydimethylsiloxane (silicone rubber) or other suitable material having properties that, for the purpose of analyzing sweat, are similar to those of glass. The die for molding the silicone rubber would be fabricated by a combination of lithography and electroplating. The die would reproducibly form, in the silicone rubber, a precisely defined number of capillary channels per unit area, each channel having a precisely defined volume. Optionally, electrodes for measuring the Ca2+ content of the sweat could be incorporated into the device. The volume of sweat collected in the capillary channels of the device would be determined from (1) the amount of light or radio waves of a given wavelength absorbed by the device and (2) the known geometry of the array of capillary channels. Then, in one of two options, centrifugation would be performed to move the sweat from the capillary tubes to the region containing the electrodes, which would be used to measure the Ca2+ content by a standard technique. In the other option, centrifugation would be performed to remove the sweat from the device to make the sweat available to other analytical instruments for measuring concentrations of substances other than Ca2+.

Feeback, Daniel L.↗
DOE OSTI2021

High-throughput screening of the ReFRAME, Pandemic Box, and COVID Box drug repurposing libraries against SARS-CoV-2 nsp15 endoribonuclease to identify small-molecule inhibitors of viral activity

SARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1–20 μM range in vitro. Furthermore, Exebryl-1, a ß-amyloid anti-aggregation molecule for Alzheimer’s therapy, was shown to have antiviral activity between 10 to 66 μM, in Vero 76, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Label-free affinity screening, design and synthesis of inhibitors targeting the Mycobacterium tuberculosis L-alanine dehydrogenase

The ability of Mycobacterium tuberculosis (Mtb) to persist in its host may enable an evolutionary advantage for drug resistant variants to emerge. A potential strategy to prevent persistence and gain drug efficacy is to directly target the activity of enzymes that are crucial for persistence. We present a method for expedited discovery and structure-based design of lead compounds by targeting the hypoxia-associated enzyme L-alanine dehydrogenase (AlaDH). Biochemical and structural analyses of AlaDH confirmed binding of nucleoside derivatives and showed a site adjacent to the nucleoside binding pocket that can confer specificity to putative inhibitors. Using a combination of dye-ligand affinity chromatography, enzyme kinetics and protein crystallographic studies, we show the development and validation of drug prototypes. Crystal structures of AlaDH-inhibitor complexes with variations at the N6 position of the adenyl-moiety of the inhibitor provide insight into the molecular basis for the specificity of these compounds. We describe a drug-designing pipeline that aims to block Mtb to proliferate upon re-oxygenation by specifically blocking NAD accessibility to AlaDH. The collective approach to drug discovery was further evaluated through in silico analyses providing additional insight into an efficient drug development strategy that can be further assessed with the incorporation of in vivo studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A framework of computer vision-enhanced microfluidic approach for automated assessment of the transient sickling kinetics in sickle red blood cells

The occurrence of vaso-occlusive crisis greatly depends on the competition between the sickling delay time and the transit time of individual sickle cells, i.e., red blood cells from sickle cell disease (SCD) patients, while they are traversing the circulatory system. Many drugs for treating SCD work by inhibiting the polymerization of sickle hemoglobin (HbS), effectively delaying the sickling process in sickle cells (SS RBCs). Most previous studies on screening anti-sickling drugs, such as voxelotor, rely on in vitro testing of sickling characteristics, often conducted under prolonged deoxygenation for up to 1 hour. However, since the microcirculation of RBCs typically takes less than 1 minute, the results of these studies may be less accurate and less relevant for in vitro-in vivo correlation. In our current study, we introduce a computer vision-enhanced microfluidic framework designed to automatically capture the transient sickling kinetics of SS RBCs within a 1-min timeframe. Our study has successfully detected differences in the transient sickling kinetics between vehicle control and voxelotor-treated SS RBCs. This approach has the potential for broader applications in screening anti-sickling therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enhanced Configurational Sampling Approaches to Alchemical Ligand Binding Free Energy Simulations: Current Status and Challenges

In this study, ligand binding free energy simulations (LB-FES) have been routine tasks in modern drug discovery campaign. A long-standing challenge for LB-FES is the difficulty in adequately sampling nontrivial environmental reorganizations in response to ligand binding. Therefore, various enhanced configurational sampling (ECS) approaches were devised to speed up fluctuations of relevant slow degrees of freedom (SDOF) and ensure simulation convergence. However, in contrast to the achievements in parametrization, software performance, and workflow automation, efficient ECS methodology suitable for high throughput screening remains in an early stage of development. Here, a review of ECS developments with LB-FES is presented, revisiting current approaches and underlining the major technical pitfalls and challenges. This Perspective focuses on alchemical LB-FES on account of their predominant role in high throughput drug screening as well as the established partnership with ECS. The critical aspects of designing ECS approaches, from both theoretical and applied perspectives, are described. This work is intended to provide a contemporary review of the scientific, technical, and practical issues associated with the accelerating convergence of alchemical LBFES.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A deep generative model for deciphering cellular dynamics and in silico drug discovery in complex diseases

Human diseases are characterized by intricate cellular dynamics. Single-cell transcriptomics provides critical insights, yet a persistent gap remains in computational tools for detailed disease progression analysis and targeted in silico drug interventions. Here we introduce UNAGI, a deep generative neural network tailored to analyse time-series single-cell transcriptomic data. This tool captures the complex cellular dynamics underlying disease progression, enhancing drug perturbation modelling and screening. When applied to a dataset from patients with idiopathic pulmonary fibrosis, UNAGI learns disease-informed cell embeddings that sharpen our understanding of disease progression, leading to the identification of potential therapeutic drug candidates. Validation using proteomics reveals the accuracy of UNAGI’s cellular dynamics analysis, and the use of the fibrotic cocktail-treated human precision-cut lung slices confirms UNAGI’s predictions that nifedipine, an antihypertensive drug, may have anti-fibrotic effects on human tissues. UNAGI’s versatility extends to other diseases, including COVID, demonstrating adaptability and confirming its broader applicability in decoding complex cellular dynamics beyond idiopathic pulmonary fibrosis, amplifying its use in the quest for therapeutic solutions across diverse pathological landscapes.

Neural Network↗
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 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 OSTI2023

DNA-encoded chemical libraries yield non-covalent and non-peptidic SARS-CoV-2 main protease inhibitors

The development of SARS-CoV-2 main protease (M pro ) inhibitors for the treatment of COVID-19 has mostly benefitted from X-ray structures and preexisting knowledge of inhibitors; however, an efficient method to generate M pro inhibitors, which circumvents such information would be advantageous. As an alternative approach, we show here that DNA-encoded chemistry technology (DEC-Tec) can be used to discover inhibitors of M pro . An affinity selection of a 4-billion-membered DNA-encoded chemical library (DECL) using M pro as bait produces novel non-covalent and non-peptide-based small molecule inhibitors of M pro with low nanomolar K i values. Furthermore, these compounds demonstrate efficacy against mutant forms of M pro that have shown resistance to the standard-of-care drug nirmatrelvir. Overall, this work demonstrates that DEC-Tec can efficiently generate novel and potent inhibitors without preliminary chemical or structural information.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2006

Microfluidic Devices for Studying Biomolecular Interactions

Microfluidic devices for monitoring biomolecular interactions have been invented. These devices are basically highly miniaturized liquid-chromatography columns. They are intended to be prototypes of miniature analytical devices of the laboratory on a chip type that could be fabricated rapidly and inexpensively and that, because of their small sizes, would yield analytical results from very small amounts of expensive analytes (typically, proteins). Other advantages to be gained by this scaling down of liquid-chromatography columns may include increases in resolution and speed, decreases in the consumption of reagents, and the possibility of performing multiple simultaneous and highly integrated analyses by use of multiple devices of this type, each possibly containing multiple parallel analytical microchannels. The principle of operation is the same as that of a macroscopic liquid-chromatography column: The column is a channel packed with particles, upon which are immobilized molecules of the protein of interest (or one of the proteins of interest if there are more than one). Starting at a known time, a solution or suspension containing molecules of the protein or other substance of interest is pumped into the channel at its inlet. The liquid emerging from the outlet of the channel is monitored to detect the molecules of the dissolved or suspended substance(s). The time that it takes these molecules to flow from the inlet to the outlet is a measure of the degree of interaction between the immobilized and the dissolved or suspended molecules. Depending on the precise natures of the molecules, this measure can be used for diverse purposes: examples include screening for solution conditions that favor crystallization of proteins, screening for interactions between drugs and proteins, and determining the functions of biomolecules.

Wilson, Wilbur W.↗
DOE OSTI2021

High-throughput virtual laboratory for drug discovery using massive datasets

Time-to-solution for structure-based screening of massive chemical databases for COVID-19 drug discovery has been decreased by an order of magnitude, and a virtual laboratory has been deployed at scale on up to 27,612 GPUs on the Summit supercomputer, allowing an average molecular docking of 19,028 compounds per second. Over one billion compounds were docked to two SARS-CoV-2 protein structures with full optimization of ligand position and 20 poses per docking, each in under 24 hours. GPU acceleration and high-throughput optimizations of the docking program produced 350× mean speedup over the CPU version (50× speedup per node). GPU acceleration of both feature calculation for machine-learning based scoring and distributed database queries reduced processing of the 2.4 TB output by orders of magnitude. The resulting 50× speedup for the full pipeline reduces an initial 43 day runtime to 21 hours per protein for providing high-scoring compounds to experimental collaborators for validation assays.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Supercomputing Pipelines Search for Therapeutics Against COVID-19

The urgent search for drugs to combat SARS-CoV-2 has included the use of supercomputers. The use of general-purpose graphical processing units (GPUs), massive parallelism, and new software for high-performance computing (HPC) has allowed researchers to search the vast chemical space of potential drugs faster than ever before. We developed a new drug discovery pipeline using the Summit supercomputer at Oak Ridge National Laboratory to help pioneer this effort, with new platforms that incorporate GPU-accelerated simulation and allow for the virtual screening of billions of potential drug compounds in days compared to weeks or months for their ability to inhibit SARS-COV-2 proteins. Here, this effort will accelerate the process of developing drugs to combat the current COVID-19 pandemic and other diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

IMPECCABLE: Integrated Modeling Pipeline for COVID Cure by Assessing Better Leads

ABSTRACT The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can deliver this combination of higher quality and speed. Here, we describe an Integrated Modeling PipEline for COVID Cure by Assessing Better LEads (IMPECCABLE) that employs multiple methodological innovations to overcome this fundamental limitation. We also describe the computational framework that we have developed to support these innovations at scale, and characterize the performance of this framework in terms of throughput, peak performance, and scientific results. We show that individual workflow components deliver 100× to 1000× improvement over traditional methods, and that the integration of methods, supported by scalable infrastructure, speeds up drug discovery by orders of magnitudes. IMPECCABLE has screened ~10 11 ligands and has been used to discover a promising drug candidate. These capabilities have been used by the US DOE National Virtual Biotechnology Laboratory and the EU Centre of Excellence in Computational Biomedicine.

97 MATHEMATICS AND COMPUTING↗