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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Vibrational properties of heme-nitrosoalkane complexes in comparison with those of their HNO analogs, and reactivity studies towards nitric oxide and Lewis acids

C-Nitroso compounds (RNO, R = alkyl and aryl) are byproducts of drug metabolism and bind to heme proteins, and their heme-RNO adducts are isoelectronic to ferrous nitroxyl (NO-/HNO) complexes. Importantly, heme-HNO compounds are key intermediates in the reduction of NO to N 2 O and nitrite to ammonium in the nitrogen cycle. Ferrous heme-RNO complexes act as stable analogs of these species, potentially allowing for the investigation of the vibrational and electronic properties of unstable heme-HNO intermediates. In this paper, a series of six-coordinate ferrous heme-RNO complexes (where R = iPr and Ph) were prepared using the TPP 2- and 3,5-Me-BAFP 2- co-ligands, and tetrahydrofuran, pyridine, and 1-methylimidazole as the axial ligands (bound trans to RNO). These complexes were characterized using different spectroscopic methods and X-ray crystallography. The complex [Fe(TPP)(THF)(iPrNO)] was further utilized for nuclear resonance vibrational spectroscopy (NRVS), allowing for the detailed assignment of the Fe–N(R)O vibrations of a heme-RNO complex for the first time. The vibrational properties of these species were then correlated with those of their HNO analogs, using DFT calculations. Our studies support previous findings that RNO ligands in ferrous heme complexes do not elicit a significant trans effect. In addition, the complexes are air-stable, and do not show any reactivity of their RNO ligands towards NO. So although ferrous heme-RNO complexes are suitable structural and electronic models for their HNO analogs, they are unsuitable to model the reactivity of heme-HNO complexes. We further investigated the reaction of our heme-RNO complexes with different Lewis acids. Here, [Fe(TPP)(THF)(iPrNO)] was found to be unreactive towards Lewis acids. In contrast, [Fe(3,5-Me-BAFP)(iPrNO) 2 ] is reactive towards all of the Lewis acids investigated here, but in most cases the iron center is simply oxidized, resulting in the loss of the iPrNO ligand. In the case of the Lewis acid B 2 (pin) 2 , the reduced product [Fe(3,5-Me-BAFP)(iPrNH 2 )(iPrNO)] was identified by X-ray crystallography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Quantitation of chlorpromazine-bound calmodulin during chlorpromazine inhibition of gravitropism

The regulatory protein, calmodulin (CaM), controls the activity of a plasma membrane localized ATPase in plants which serves to pump calcium out of cells. Recent data are consistent with the hypothesis that activation of this pump is one of the early steps necessary for gravitropism. Chlorpromazine (CPZ), a CaM antagonist, reversibly inhibits gravitropism in oat coleoptiles at concentrations which permit normal growth rates. C-14-labeled CPZ was used to photo-affinity label endogenous CaM in vivo to learn whether the drug is actually binding to some portion of endogenous CaM when it inhibits gravitropism. Under conditions in which CPZ inhibits gravitropism for over an hour, at least 11% of the CaM in gravitropically stimulated coleoptiles is bound to CPZ. In a given CPZ experiment the degree of inhibition of gravitropism correlates well with the amount of CaM bound to CPZ.

Roux, S. J.↗
DOE OSTI2021

The Promise of Mutation Resistant Drugs for SARS-CoV-2 That Interdict in the Folding of the Spike Protein Receptor Binding Domain

In recent work, we proposed that effective therapeutic drugs aimed at treating the SARS-CoV-2 infection could be developed based on interdicting in the early steps of the folding pathway of key viral proteins, including the receptor binding domain (RBD) of the spike protein. In order to provide for a drug target on the protein, the earliest contact-formation event along the dominant folding pathway of the RBD spike protein was predicted employing the Sequential Collapse Model (SCM). The segments involved in the predicted earliest contact were suggested to provide optimal folding interdiction target regions (FITRs) for potential therapeutic drugs, with a focus on folding interdicting peptides (FIPs). In this paper, we extend our analysis to include 13 known single mutations of the RBD spike protein as well as the triple mutation B1.351 and the recent double mutation B1.617.2. The results show that the location of the FITR does not change in any of the 15 studied mutations, providing for a mutation-resistant drug design strategy for the RBD-spike protein.

Bergasa-Caceres, Fernando↗
DOE OSTI2021

Enhancement of anticancer drug sensitivity in multidrug resistance cells overexpressing ATP-binding cassette (ABC) transporter ABCC10 by CP55, a synthetic derivative of 5-cyano-6-phenylpyrimidin

Highlights: • Multidrug resistance (MDR) in cancer is one of the major obstacles in chemotherapy. • ABCC10 mediates resistance to wide spectrum of chemotherapeutic agents, but only limited number of studies are available. • Overexpression of ABCC10 has been linked to various types of cancers including colorectal, gastric and lung cancer. • CP55 is a potent ABCC10 inhibitor which enhances the anticancer drug sensitivity in ABCC10-overexpression MDR cells. ATP-binding cassette (ABC) transporter C10 (ABCC10), also named multidrug resistance protein 7 (MRP7), is a member of ABC transporter superfamily and has been revealed to transport a wide range of chemotherapeutic agents including taxanes, epothilone B, Vinca alkaloids, and anthracyclines. In our previous study, a 5-cyano-6-phenylpyrimidin derivative CP55 was synthesized and found significantly reversal effect of multidrug resistance (MDR) mediated by ABCB1. In this study, we found CP55 also efficiently reversed MDR mediated by ABCC10. Our in vitro study showed that co-treatment with CP55 significantly increased the efficacy of ABCC10-substrate anticancer drugs in MDR cells overexpressing ABCC10. Furthermore, we showed that treatment with CP55 increased the intracellular accumulation of [{sup 3}H]-labeled anticancer drugs and in-turn decreasing drug efflux by inhibiting the transport activity, without altering ABCC10 protein ex-pression level or cellular localization. Potential CP55-ABCC10 interactions were predicted via docking analysis using human ABCC10 homology model and obtained high docking score. Therefore, CP55 represents a promising therapeutic agent in the combinational treatment of chemo-resistant cancer related to ABCC10.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Structural basis of promiscuous substrate transport by Organic Cation Transporter 1

Organic Cation Transporter 1 (OCT1) plays a crucial role in hepatic metabolism by mediating the uptake of a range of metabolites and drugs. Genetic variations can alter the efficacy and safety of compounds transported by OCT1, such as those used for cardiovascular, oncological, and psychological indications. Despite its importance in drug pharmacokinetics, the substrate selectivity and underlying structural mechanisms of OCT1 remain poorly understood. Here, we present cryo-EM structures of full-length human OCT1 in the inward-open conformation, both ligand-free and drug-bound, indicating the basis for its broad substrate recognition. Comparison of our structures with those of outward-open OCTs provides molecular insight into the alternating access mechanism of OCTs. We observe that hydrophobic gates stabilize the inward-facing conformation, whereas charge neutralization in the binding pocket facilitates the release of cationic substrates. These findings provide a framework for understanding the structural basis of the promiscuity of drug binding and substrate translocation in OCT1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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

Identification of inhibitors against SARS-CoV-2 variants of concern using virtual screening and metadynamics-based enhanced sampling

Among the variants of SARS-CoV-2, some are more infectious than the Wild-type. Interestingly, these mutations enable the virus to evade the therapeutic efforts. Hence, there is a need for candidate drug molecules that can potently bind with all the variants. Here we have adopted a strategy combining virtual screening, molecular docking followed by rigorous sampling by metadynamics simulations to find candidate molecules. From our results we found four highly potent drug candidates that can bind to the Spike-RBD of all the variants of the virus. Additionally, we also found that certain signature residues on the RBM region commonly bind to each of these inhibitors. Thus, our study not only gives information on the chemical compounds, but also residues on the proteins which could be targeted for future drug and vaccine development studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Structural insights into the mechanism of overcoming Erm-mediated resistance by macrolides acting together with hygromycin-A

The ever-growing rise of antibiotic resistance among bacterial pathogens is one of the top healthcare threats today. Although combination antibiotic therapies represent a potential approach to more efficiently combat infections caused by susceptible and drug-resistant bacteria, only a few known drug pairs exhibit synergy/cooperativity in killing bacteria. Here, we discover that well-known ribosomal antibiotics, hygromycin A (HygA) and macrolides, which target peptidyl transferase center and peptide exit tunnel, respectively, can act cooperatively against susceptible and drug-resistant bacteria. Remarkably, HygA slows down macrolide dissociation from the ribosome by 60-fold and enhances the otherwise weak antimicrobial activity of the newest-generation macrolide drugs known as ketolides against macrolide-resistant bacteria. By determining a set of high-resolution X-ray crystal structures of drug-sensitive wild-type and macrolide-resistant Erm-methylated 70S ribosomes in complex with three HygA-macrolide pairs, we provide a structural rationale for the binding cooperativity of these drugs and also uncover the molecular mechanism of overcoming Erm-type resistance by macrolides acting together with hygromycin A. Altogether our structural, biochemical, and microbiological findings lay the foundation for the subsequent development of synergistic antibiotic tandems with improved bactericidal properties against drug-resistant pathogens, including those expressing erm genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research

Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.

LeGrand, Scott↗
DOE OSTI2025

Resolving SPARC–HSA binding kinetics with an ultrasensitive photonic sensor based on bound states in the continuum

Secreted protein acidic and rich in cysteine (SPARC) is critical in cell-matrix interactions and tissue remodeling. It influences tumor progression through its affinity for human serum albumin (HSA) - the most abundant plasma protein, which also plays a crucial role in drug delivery. Strong molecular binding leads to a dissociation constant KD in the nanomolar range. Thus, determining KD requires detecting sub-nanomolar concentrations with ultrasensitive methods. This may be crucial for elucidating the nature of SPARC-HSA binding, as their interaction remains a subject of debate. Capturing these interactions accurately requires a platform capable of resolving rapid binding kinetics at extremely low analyte concentrations. In this work, we report on a microfluidics-integrated photonic nanostructure that supports bound states in the continuum (BICs) and is optimized for studying the fast kinetics of high-affinity protein-protein interactions. The unprecedented capability of detecting sub-nanomolar concentrations allows quantifying KD between SPARC and HSA beyond the state of the art. We leverage an all-dielectric photonic crystal slab (PhCS) sustaining two BIC branches arising from gapped Dirac cone dispersion. HSA is covalently immobilized on the PhCS bonded to a PDMS microfluidic chamber. SPARC dissociation is carried out using PBS buffer (pH 7.4), ensuring complete protein release through precise control of the flow rate and continuous spectral monitoring of the BICs. The measured KD=8.2±0.8 nM confirms the strong affinity of SPARC for HSA. This study highlights the potential of BIC-based sensing as a versatile tool for investigating protein interactions. These results also have implications for the optimization of drug delivery systems and cancer treatment strategies.

Albumin↗
DOE OSTI2023

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[ 18 F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [ 18 F]Nifene, displaying similar pKa and binding affinity to nicotine. Time–activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

2-FA85380↗
NASA NTRS1996

Protein crystallization studies

The Structural Biology laboratory at NASA Marshall Spaceflight Center uses x-ray crystallographic techniques to conduct research into the three-dimensional structure of a wide variety of proteins. A major effort in the laboratory involves an ongoing study of human serum albumin (the principal protein in human plasma) and its interaction with various endogenous substances and pharmaceutical agents. Another focus is on antigenic and functional proteins from several pathogenic organisms including the human immunodeficiency virus (HIV) and the widespread parasitic genus, Schistosoma. My efforts this summer have been twofold: first, to identify clinically significant drug interactions involving albumin binding displacement and to initiate studies of the three-dimensional structure of albumin complexed with these agents, and secondly, to establish collaborative efforts to extend the lab's work on human pathogens.

Lyne, James Evans↗
DOE OSTI2022

Crystal Structure of CYP3A4 Complexed with Fluorol Identifies the Substrate Access Channel as a High-Affinity Ligand Binding Site

Cytochrome P450 3A4 (CYP3A4) is a major human drug-metabolizing enzyme, notoriously known for its extreme substrate promiscuity, allosteric behavior, and implications in drug–drug interactions. Despite extensive investigations, the mechanism of ligand binding to CYP3A4 is not fully understood. We determined the crystal structure of CYP3A4 complexed with fluorol, a small fluorescent dye that can undergo hydroxylation. In the structure, fluorol associates to the substrate channel, well suited for the binding of planar polyaromatic molecules bearing polar groups, through which stabilizing H-bonds with the polar channel residues, such as Thr224 and Arg372, can be established. Mutagenesis, spectral, kinetic, and functional data confirmed the involvement but not strict requirement of Thr224 for the association of fluorol. Collectively, our data identify the substrate channel as a high-affinity ligand binding site and support the notion that hydrophobic ligands first dock to the nearby peripheral surface, before migrating to the channel and, subsequently, into the active site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Allosteric Tuning of Caspase–7: Establishing the Nexus of Structure and Catalytic Power

Caspase-7 (C7), a cysteine protease involved in apoptosis, is a valuable drug target for its role in human diseases (e. g., Parkinson's, Alzheimer's, sepsis). The C7 allosteric site has great potential for small-molecule targeting, but numerous drug discovery efforts have identified precious few allosteric inhibitors. Here we present the first selective, drug-like inhibitor of C7 along with several other improved inhibitors based on our previous fragment hit. We also provide a rational basis for the impact of allosteric binding on the C7 catalytic cycle by using an integrated approach including X-ray crystallography, stopped-flow kinetics, and molecular dynamics simulations. Our findings suggest allosteric binding disrupts C7 pre-acylation by neutralization of the catalytic dyad, displacement of substrate from the oxyanion hole, and altered dynamics of substrate binding loops. This work advances drug targeting efforts and bolsters our understanding of allosteric structure–activity relationships (ASARs).

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

The molecular basis of pyrazinamide activity on Mycobacterium tuberculosis PanD

Pyrazinamide has been a mainstay in the multidrug regimens used to treat tuberculosis. It is active against the persistent, non-replicating mycobacteria responsible for the protracted therapy required to cure tuberculosis. Pyrazinamide is a pro-drug that is converted into pyrazinoic acid (POA) by pyrazinamidase, however, the exact target of the drug has been difficult to determine. Here we show the enzyme PanD binds POA in its active site in a manner consistent with competitive inhibition. The active site is not directly accessible to the inhibitor, suggesting the protein must undergo a conformational change to bind the inhibitor. This is consistent with the slow binding kinetics we determined for POA. Drug-resistant mutations cluster near loops that lay on top of the active site. These resistant mutants show reduced affinity and residence time of POA consistent with a model where resistance occurs by destabilizing the closed conformation of the active site.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Language models for the prediction of SARS-CoV-2 inhibitors

The COVID-19 pandemic highlights the need for computational tools to automate and accelerate drug design for novel protein targets. We leverage deep learning language models to generate and score drug candidates based on predicted protein binding affinity. We pre-trained a deep learning language model (BERT) on ∼9.6 billion molecules and achieved peak performance of 603 petaflops in mixed precision. Our work reduces pre-training time from days to hours, compared to previous efforts with this architecture, while also increasing the dataset size by nearly an order of magnitude. For scoring, we fine-tuned the language model using an assembled set of thousands of protein targets with binding affinity data and searched for inhibitors of specific protein targets, SARS-CoV-2 Mpro and PLpro. We utilized a genetic algorithm approach for finding optimal candidates using the generation and scoring capabilities of the language model. Our generalizable models accelerate the identification of inhibitors for emerging therapeutic targets.

Blanchard, Andrew E.↗
DOE OSTI2021

A GPC2 antibody-drug conjugate is efficacious against neuroblastoma and small-cell lung cancer via binding a conformational epitope

Glypican 2 (GPC2) is a MYCN-regulated, differentially expressed cell-surface oncoprotein and target for immune-based therapies in neuroblastoma. Here, we build on GPC2’s immunotherapeutic attributes by finding that it is also a highly expressed, MYCN-driven oncoprotein on small-cell lung cancers (SCLCs), with significantly enriched expression in both the SCLC and neuroblastoma stem cell compartment.By solving the crystal structure of the D3-GPC2-Fab/GPC2 complex at 3.3 Å resolution, we further illustrate that the GPC2-directed antibody-drug conjugate (ADC; D3-GPC2-PBD), that links a human GPC2 antibody (D3) to DNA-damaging pyrrolobenzodiazepine (PBD) dimers, binds a tumor-specific, conformation-dependent epitope of the core GPC2 extracellular domain. We then show that this ADC induces durable neuroblastoma and SCLC tumor regression via induction of DNA damage, apoptosis, and bystander cell killing, notably with no signs of ADC-induced in vivo toxicity. Furthermore, these studies provide preclinical data to support the clinical translation of ADCs targeting GPC2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Structures of drug-specific monoclonal antibodies bound to opioids and nicotine reveal a common mode of binding

Opioid-related fatal overdoses have reached epidemic proportions. Because existing treatments for opioid use disorders offer limited long-term protection, accelerating the development of newer approaches is critical. Monoclonal antibodies (mAbs) are an emerging treatment strategy that targets and sequesters selected opioids in the bloodstream, reducing drug distribution across the blood-brain barrier, thus preventing or reversing opioid toxicity. We previously identified a series of murine mAbs with high affinity and selectivity for oxycodone, morphine, fentanyl, and nicotine. To determine their binding mechanism, we used X-ray crystallography to solve the structures of mAbs bound to their respective targets, to 2.2 Å resolution or higher. Structural analysis showed a critical convergent hydrogen bonding mode that is dependent on a glutamic acid residue in the mAbs’ heavy chain and a tertiary amine of the ligand. Further, characterizing drug-mAb complexes represents a significant step toward rational antibody engineering and future manufacturing activities to support clinical evaluation.

60 APPLIED LIFE SCIENCES↗