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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
NASA NTRS1991

Three-dimensional structure of human serum albumin

The binding locations to human serum albumin (HSA) of several drug molecules were determined at low resolution using crystallographic methods. The principal binding sites are located within subdomains IIA and IIIA. Preliminary studies suggest that an approach to increasing the in vivo efficacy of drugs which are rendered less effective or ineffective by virtue of their interaction with HSA, would be the use of competitive displacement in drug therapies and/or the development of a general inhibitor to the site within subdomain IIIA. These findings also suggest that the facilitated transfer of various ligands across organ/circulatory interfaces such as liver, kidney, and brain may be associated with binding to the IIIA subdomain.

Carter, Daniel C.↗
DOE OSTI2023

HD-Bind: Encoding of Molecular Structure with Low Precision, Hyperdimensional Binary Representations

Publicly available collections of drug-like molecules have grown to comprise tens of billions of compounds due to advances in combinatorial chemistry. Traditional methods for identifying "hit" molecules from a large collection of potential drug-like candidates have relied 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 the major drawback that they require exceptional computing capabilities for even relatively small collections of molecules. Hyperdimensional Computing (HDC) is a recently-proposed learning paradigm that represents data with high-dimension binary vectors; this 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. We consider existing HDC approaches for molecular property classification and introduce two novel encodings of a commonly-used molecular representation, the extended connectivity fingerprint (ECFP). We show that HDC-based inference methods are as much as 91 times more efficient than traditional machine learning methods, and achieve an acceleration of nearly nine orders of magnitude compared to molecular docking. Our results show that HDC accelerated methods retain competitive accuracy on a number of well-studied tasks such as molecular property predictions using the MoleculeNet dataset, and bind/no-bind activity classification using the DUD-E and LIT-PCBA datasets. Our work thus motivates further investigation into molecular representation learning to develop ultraefficient pre-screening tools.

Jones, William↗
NASA NTRS2014

Effects of Radiation and Dietary Iron on Expression of Genes and Proteins Involved in Drug Metabolism

Liver function, especially the rate of metabolic enzyme activities, determines the concentration of circulating drugs and the duration of their efficacy. Most pharmaceuticals are metabolized by the liver, and clinically-used medication doses are given with normal liver function in mind. A drug overdose can result in the case of a liver that is damaged and removing pharmaceuticals from the circulation at a rate slower than normal. Alternatively, if liver function is elevated and removing drugs from the system more quickly than usual, it would be as if too little drug had been given for effective treatment. Because of the importance of the liver in drug metabolism, we want to understand any effects of spaceflight on the enzymes of the liver. Dietary factors and exposure to radiation are aspects of spaceflight that are potential oxidative stressors and both can be modeled in ground experiments. In this experiment, we examined the effects of high dietary iron and low dose gamma radiation (individually and combined) on the gene expression of enzymes involved in drug metabolism, redox homeostasis, and DNA repair. METHODS All procedures were approved by the JSC Animal Care and Use Committee. Male Sprague-Dawley rats were divided into 4 groups (n=8); control, high Fe diet (650 mg iron/kg), radiation (fractionated 3 Gy exposure from a Cs- 137 source) and combined high Fe diet + radiation exposure. Animals were euthanized 24h after the last treatment of radiation; livers were removed immediately and flash -frozen in liquid nitrogen. Expression of genes thought to be involved in redox homeostasis, drug metabolism and DNA damage repair was measured by RT-qPCR. Where possible, protein expression of the same genes was measured by western blotting. All data are expressed as % change in expression normalized to reference gene expression; comparisons were then made of each treatment group to the sham exposed/ normal diet control group. Data was considered significant at p< 0.5. RESULTS Among the redox homeostasis genes examined, metallothionein showed a significant down regulation in the radiation treated group (-3.85 fold) and a trend toward down regulation in the high Fe + rad group. Metallothionein is involved in the regulation of physiological metals and also has antioxidant activities. Among the drug metabolism genes examined, ATP binding cassette subfamily B (Abcb1b) gene expression increased more than 10-fold in both groups that received radiation treatments. This increased expression was also seen at the protein level. This ABC transporter carries many different compounds across cell membranes, including administered medications. The cytochrome P450 2E1 enzyme, a mixed-function oxidase that deactivates some medications and activates others, showed about a 2-fold increase in gene expression in both radiation-treated groups, with a trend toward increased expression at the protein level. Expression of epoxide hydrolase, which detoxifies polycyclic aromatic hydrocarbons, showed similar 2-fold increases. Among the DNA repair genes examined, expression of RAD51 was significantly down regulated (1.5 fold) in the radiation treated group. RAD51 is involved in repair of double-stranded DNA breaks. CONCLUSION This experiment used 2 different sources of physiological oxidative stress, administered separately and together, and examined their impacts on liver gene and protein expression. It is clear that significant changes occurred in expression of several genes and proteins in the radiation-treated animals. If the results from this ground analog of portions of the spaceflight environment hold true for the spaceflight environment itself, the physiological roles of the affected enzymes (drug transport and metabolism, redox homeostasis) could mean consequences in redox homeostasis or the pharmacokinetics of administered medications

Faust, K. M.↗
DOE OSTI2022

Hepatitis C virus NS3/4A inhibitors and other drug-like compounds as covalent binders of SARS-CoV-2 main protease

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), threatens global public health. The world needs rapid development of new antivirals and vaccines to control the current pandemic and to control the spread of the variants. Among the proteins synthesized by the SARS-CoV-2 genome, main protease (M pro also known as 3CL pro ) is a primary drug target, due to its essential role in maturation of the viral polyproteins. In this study, we provide crystallographic evidence, along with some binding assay data, that three clinically approved anti hepatitis C virus drugs and two other drug-like compounds covalently bind to the M pro Cys145 catalytic residue in the active site. Also, molecular docking studies can provide additional insight for the design of new antiviral inhibitors for SARS-CoV-2 using these drugs as lead compounds. One might consider derivatives of these lead compounds with higher affinity to the M pro as potential COVID-19 therapeutics for further testing and possibly clinical trials.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Protein Innovations Advance Drug Treatments, Skin Care

Dan Carter carefully layered the sheets of tracing paper on the light box. On each sheet were renderings of the atomic components of an essential human protein, one whose structure had long been a mystery. With each layer Carter laid down, a never-before-seen image became clearer. Carter joined NASA s Marshall Space Flight Center in 1985 and began exploring processes of protein crystal growth in space. By bouncing intense X-rays off the crystals, researchers can determine the electron densities around the thousands of atoms forming the protein molecules, unveiling their atomic structures. Cultivating crystals of sufficient quality on Earth was problematic; the microgravity conditions of space were far more accommodating. At the time, only a few hundred protein structures had been mapped, and the methods were time consuming and tedious. Carter hoped his work would help reveal the structure of human serum albumin, a major protein in the human circulatory system responsible for ferrying numerous small molecules in the blood. More was at stake than scientific curiosity. Albumin has a high affinity for most of the world s pharmaceuticals, Carter explains, and its interaction with drugs can change their safety and efficacy. When a medication enters the bloodstream a cancer chemotherapy drug, for example a majority of it can bind with albumin, leaving only a small percentage active for treatment. How a drug interacts with albumin can influence considerations like the necessary effective dosage, playing a significant role in the design and application of therapeutic measures. In spite of numerous difficulties, including having no access to microgravity following the 1986 Space Shuttle Challenger disaster, the image Carter had hoped to see was finally clarifying. In 1988, his lab had acquired specialized X-ray and detection equipment a tipping point. Carter and his colleagues began to piece together albumin s portrait, the formation of its electron densities coalescing on the sheets of tracing paper he arranged on the light box. While space-grown crystals were ultimately not involved in the achievement, a year later, Carter says, we were on the cover of Science magazine, having determined the atomic structure of albumin.

Source record↗
DOE OSTI2022

Joint neutron/molecular dynamics vibrational spectroscopy reveals softening of HIV-1 protease upon binding of a tight inhibitor

Biomacromolecules are inherently dynamic, and their dynamics are interwoven into function. The fast collective vibrational dynamics in proteins occurs in the low picosecond timescale corresponding to frequencies of ~5-50 cm -1 . This sub-to-low THz frequency regime covers the low-amplitude collective breathing motions of a whole protein and vibrations of the constituent secondary structure elements, such as α-helices, β-sheets and loops. We have used inelastic neutron scattering experiments in combination with molecular dynamics simulations to demonstrate the vibrational dynamics softening of HIV-1 protease, a target of HIV/AIDS antivirals, upon binding of a tight clinical inhibitor darunavir. Changes in the vibrational density of states of matching structural elements in the two monomers of the homodimeric protein are not identical, indicating asymmetric effect of darunavir on the vibrational dynamics. Three of the 11 major secondary structure elements contribute over 40% to the overall changes in the vibrational density of states upon darunavir binding. Molecular dynamics simulations informed by experiments allowed us to estimate that the altered vibrational dynamics of the protease would contribute -3.6 kcal/mol -1 at 300 K, or 25%, to the free energy of darunavir binding. As HIV-1 protease drug resistance remains a concern, our results open a new avenue to help establish a direct quantitative link between protein vibrational dynamics and drug resistance.

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

BBO-10203 inhibits tumor growth without inducing hyperglycemia by blocking RAS-PI3Kα interaction

BBO-10203 is an orally available drug that covalently and specifically binds to the rat sarcoma (RAS)–binding domain of phosphoinositide 3-kinase α (PI3Kα), preventing its activation by HRAS, NRAS, and KRAS. Here, it inhibited PI3Kα activation in tumors with oncogenic mutations in KRAS or PIK3CA and in tumors with human epidermal growth factor receptor 2 (HER2) amplification or overexpression. In preclinical models, BBO-10203 caused significant tumor growth inhibition across multiple tumor types and showed enhanced efficacy in combination with inhibitors of cyclin-dependent kinase 4/6 (CDK4/6), estrogen receptor (ER), HER2, and KRAS-G12C mutant, including in tumors harboring mutations in Kelch-like ECH-associated protein 1 (KEAP1) and serine/threonine kinase 11 (STK11). Notably, these antitumor effects occurred without inducing hyperglycemia, because insulin signaling does not depend on RAS-mediated PI3Kα activation to promote glucose uptake.

Simanshu, Dhirendra K. [Frederick National Laborat↗
DOE OSTI2023

Structure-guided approach to modulate small molecule binding to a promiscuous ligand-activated protein

Ligand-binding promiscuity in detoxification systems protects the body from toxicological harm but is a roadblock to drug development due to the difficulty in optimizing small molecules to both retain target potency and avoid metabolic events. Immense effort is invested in evaluating metabolism of molecules to develop safer, more effective treatments, but engineering specificity into or out of promiscuous proteins and their ligands is a challenging task. To better understand the promiscuous nature of detoxification networks, we have used X-ray crystallography to characterize a structural feature of pregnane X receptor (PXR), a nuclear receptor that is activated by diverse molecules (with different structures and sizes) to up-regulate transcription of drug metabolism genes. We found that large ligands expand PXR’s ligand-binding pocket, and the ligand-induced expansion occurs through a specific unfavorable compound-protein clash that likely contributes to reduced binding affinity. Removing the clash by compound modification resulted in more favorable binding modes with significantly enhanced binding affinity. We then engineered the unfavorable ligand-protein clash into a potent, small PXR ligand, resulting in marked reduction in PXR binding and activation. Structural analysis showed that PXR is remodeled, and the modified ligands reposition in the binding pocket to avoid clashes, but the conformational changes result in less favorable binding modes. Thus, ligand-induced binding pocket expansion increases ligand-binding potential of PXR but is an unfavorable event; therefore, drug candidates can be engineered to expand PXR’s ligand-binding pocket and reduce their safety liability due to PXR binding.

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

Analysis of putative quadruplex-forming sequences in fungal genomes: novel antifungal targets?

Fungal infections cause >1 million deaths annually and the emergence of antifungal resistance has prompted the exploration for novel antifungal targets. Quadruplexes are four-stranded nucleic acid secondary structures, which can regulate processes such as transcription, translation, replication and recombination. They are also found in genes linked to virulence in microbes, and ligands that bind to quadruplexes can eliminate drug-resistant pathogens. Using a computational approach, we quantified putative quadruplex-forming sequences (PQS) in 1359 genomes across the fungal kingdom and explored their presence in genes related to virulence, drug resistance and biological processes associated with pathogenicity in Aspergillus fumigatus. Here we present the largest analysis of PQS in fungi and identify significant heterogeneity of these sequences throughout phyla, genera and species. PQS were genetically conserved in Aspergillus spp. and frequently pathogenic species appeared to contain fewer PQS than their lesser/non-pathogenic counterparts. GO-term analysis identified that PQS-containing genes were involved in processes linked with virulence such as zinc ion binding, the biosynthesis of secondary metabolites and regulation of transcription in A. fumigatus. Although the genome frequency of PQS was lower in A. fumigatus, PQS could be found enriched in genes involved in virulence, and genes upregulated during germination and hypoxia. Moreover, PQS were found in genes involved in drug resistance. Quadruplexes could have important roles within fungal biology and virulence, but their roles require further elucidation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking

A critical step in structure-based drug discovery is predicting whether and how a candidate molecule binds to a model of a therapeutic target. However, substantial protein side chain movements prevent current screening methods, such as docking, from accurately predicting the ligand conformations and require expensive refinements to produce viable candidates. Here, we present the development of a high-throughput and flexible ligand pose refinement workflow, called “tinyIFD”. The main features of the workflow include the use of specialized high-throughput, small-system MD simulation code mdgx.cuda and an actively learning model zoo approach. We show the application of this workflow on a large test set of diverse protein targets, achieving 66% and 76% success rates for finding a crystal-like pose within the top-2 and top-5 poses, respectively. We also applied this workflow to the SARS-CoV-2 main protease (M pro ) inhibitors, where we demonstrate the benefit of the active learning aspect in this workflow.

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

Comparison of Equilibrium and Nonequilibrium Approaches for Relative Binding Free Energy Predictions

Alchemical relative binding free energy calculations have recently found important applications in drug optimization. A series of congeneric compounds are generated from a preidentified lead compound, and their relative binding affinities to a protein are assessed in order to optimize candidate drugs. While methods based on equilibrium thermodynamics have been extensively studied, an approach based on nonequilibrium methods has recently been reported together with claims of its superiority. However, these claims pay insufficient attention to the basis and reliability of both methods. Here we report a comparative study of the two approaches across a large data set, comprising more than 500 ligand transformations spanning in excess of 300 ligands binding to a set of 14 diverse protein targets. Ensemble methods are essential to quantify the uncertainty in these calculations, not only for the reasons already established in the equilibrium approach but also to ensure that the nonequilibrium calculations reside within their domain of validity. If and only if ensemble methods are applied, we find that the nonequilibrium method can achieve accuracy and precision comparable to those of the equilibrium approach. Compared to the equilibrium method, the nonequilibrium approach can reduce computational costs but introduces higher computational complexity and longer wall clock times. There are, however, cases where the standard length of a nonequilibrium transition is not sufficient, necessitating a complete rerun of the entire set of transitions. This significantly increases the computational cost and proves to be highly inconvenient during large-scale applications. Our findings provide a key set of recommendations that should be adopted for the reliable implementation of nonequilibrium approaches to relative binding free energy calculations in ligand-protein systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Proteomic Profiling of Intra-Islet Features Reveals Substructure-Specific Protein Signatures

Despite their diminutive size, islets of Langerhans play a large role in maintaining systemic energy balance in the body. New technologies have enabled us to go from studying the whole pancreas, to isolated whole islets, to partial islet sections, and now to islet substructures isolated from within the islet. Using a microfluidic nanodroplet-based proteomics platform coupled with laser capture microdissection (LCM), we present an in-depth investigation of protein profiles specific to regions within the islet. These regions studied include the vascular tissue containing interface boundary, micro-vascular tissue internal to the islet, isolated endocrine cells, islet sections with vasculature intact, and finally acinar tissue from around the islet. Unique protein signatures observed in the inner vasculature potentially indicate increased innervation and intra-islet neuron-like crosstalk compared to external vasculature. We also demonstrate the utility of these data for isolating localized structure-specific drug-target interactions using existing protein/drug binding databases.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

In vitro and in vivo evidence for actin association of the naphthylphthalamic acid-binding protein from zucchini hypocotyls

The N-1-naphthylphthalamic acid (NPA)-binding protein is part of the auxin efflux carrier, the protein complex that controls polar auxin transport in plant tissues. This study tested the hypothesis that the NPA-binding protein (NBP) is associated with the actin cytoskeleton in vitro and that an intact actin cytoskeleton is required for polar auxin transport in vivo. Cytoskeletal polymerization was altered in extracts of zucchini hypocotyls with reagents that stabilized either the polymeric or monomeric forms of actin or tubulin. Phalloidin treatment altered actin polymerization, as demonstrated by immunoblot analyses following native and denaturing electrophoresis. Phalloidin increased both filamentous actin (F-actin) and NPA-binding activity, while cytochalasin D and Tris decreased both F-actin and NPA-binding activity in cytoskeletal pellets. The microtubule stabilizing drug taxol increased pelletable tubulin, but did not alter either the amount of pelletable actin or NPA-binding activity. Treatment of etiolated zucchini hypocotyls with cytochalasin D decreased the amount of auxin transport and its regulation by NPA. These experimental results are consistent with an in vitro actin cytoskeletal association of the NPA-binding protein and with the requirement of an intact actin cytoskeleton for maximal polar auxin transport in vivo.

Non-NASA Center↗
DOE OSTI2019

De novo design of a homo-trimeric amantadine-binding protein

The computational design of a symmetric protein homo-oligomer that binds a symmetry-matched small molecule larger than a metal ion has not yet been achieved. We used de novo protein design to create a homo-trimeric protein that binds the C 3 symmetric small molecule drug amantadine with each protein monomer making identical interactions with each face of the small molecule. Solution NMR data show that the protein has regular three-fold symmetry and undergoes localized structural changes upon ligand binding. A high-resolution X-ray structure reveals a close overall match to the design model with the exception of water molecules in the amantadine binding site not included in the Rosetta design calculations, and a neutron structure provides experimental validation of the computationally designed hydrogen-bond networks. Exploration of approaches to generate a small molecule inducible homo-trimerization system based on the design highlight challenges that must be overcome to computationally design such systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Binding mechanism and binding free energy of amino acids and citrate to hydroxyapatite surfaces as a function of crystallographic facet, pH, and electrolytes

Hydroxyapatite (HAP) is the major mineral phase in bone and teeth. The interaction of individual amino acids and citrate ions with different crystallographic HAP surfaces has remained uncertain for decades, creating a knowledge gap to rationally design interactions with peptides, proteins, and drugs. In this contribution, we quantify the binding mechanisms and binding free energies of the 20 end-capped natural amino acids and citrate ions on the basal (001) and prismatic (010)/(020) planes of hydroxyapatite at pH values of 7 and 5 for the first time at the molecular scale. We utilized over 1500 steered molecular dynamics simulations with highly accurate potentials that reproduce surface and hydration energies of (hkl) hydroxyapatite surfaces at different pH values. Charged residues demonstrate a much higher affinity to HAP than charge-neutral species due to the formation of superficial ion pairs and ease of penetration into layers of water molecules on the mineral surface. Binding free energies range from 0 to -60 kJ/mol and were determined with ~10% uncertainty. The highest affinity was found for citrate, followed by Asp(-) and Glu(-), and followed after a gap by Arg(+), Lys(+), as well as by His(+) at pH 5. The (hkl)-specific area density of calcium ions, the protonation state of phosphate ions, and subsurface directional order of the ions in HAP lead to surface-specific binding patterns. Amino acids without ionic side groups exhibit weak binding, between -3 and 0 kJ/mol, due to difficulties to penetrate the first layer of water molecules on the apatite surfaces. We explain recognition processes that remained elusive in experiments, in prior simulations, discuss agreement with available data, and reconcile conflicting interpretations. In conclusion, the findings can serve as useful input for the design of peptides, proteins, and drug molecules for the modification of bone and teeth-related materials, as well as control of apatite mineralization.

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

Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models

Cancer is a heterogeneous disease in that tumors of the same histology type can respond differently to a treatment. Anti-cancer drug response prediction is of paramount importance for both drug development and patient treatment design. Although various computational methods and data have been used to develop drug response prediction models, it remains a challenging problem due to the complexities of cancer mechanisms and cancer-drug interactions. To better characterize the interaction between cancer and drugs, we investigate the feasibility of integrating computationally derived features of molecular mechanisms of action into prediction models. Specifically, we add docking scores of drug molecules and target proteins in combination with cancer gene expressions and molecular drug descriptors for building response models. The results demonstrate a marginal improvement in drug response prediction performance when adding docking scores as additional features, through tests on large drug screening data. We discuss the limitations of the current approach and provide the research community with a baseline dataset of the large-scale computational docking for anti-cancer drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Advanced drug development and manufacturing

X-ray fluorescence (XRF) spectrometry has been used for detecting binding events and measuring binding selectivities between chemicals and receptors. XRF may also be used for estimating the therapeutic index of a chemical. For estimating the binding selectivities of a chemical versus chemical analogs, for measuring post translational modification of proteins, and for drug manufacturing.

Birnbaum, Eva R.↗
DOE OSTI2021

Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions

Abstract New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. Here, we review the computational approaches to predicting protein–ligand interactions in the context of drug discovery, focusing on methods using artificial intelligence (AI). We begin with a brief introduction to proteins (targets), ligands (e.g. drugs) and their interactions for nonexperts. Next, we review databases that are commonly used in the domain of protein–ligand interactions. Finally, we survey and analyze the machine learning (ML) approaches implemented to predict protein–ligand binding sites, ligand-binding affinity and binding pose (conformation) including both classical ML algorithms and recent deep learning methods. After exploring the correlation between these three aspects of protein–ligand interaction, it has been proposed that they should be studied in unison. We anticipate that our review will aid exploration and development of more accurate ML-based prediction strategies for studying protein–ligand interactions.

59 BASIC BIOLOGICAL SCIENCES↗