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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 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↗
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↗
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↗
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↗
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↗
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↗