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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Regioselective Arene C−H Alkylation Enabled by Organic Photoredox Catalysis

Abstract Expanding the toolbox of C−H functionalization reactions applicable to the late‐stage modification of complex molecules is of interest in medicinal chemistry, wherein the preparation of structural variants of known pharmacophores is a key strategy for drug development. One manifold for the functionalization of aromatic molecules utilizes diazo compounds and a transition‐metal catalyst to generate a metallocarbene species, which is capable of direct insertion into an aromatic C−H bond. However, these high‐energy intermediates can often require directing groups or a large excess of substrate to achieve efficient and selective reactivity. Herein, we report that arene cation radicals generated by organic photoredox catalysis engage in formal C−H functionalization reactions with diazoacetate derivatives, furnishing sp 2 –sp 3 coupled products with moderate‐to‐good regioselectivity. In contrast to previous methods utilizing metallocarbene intermediates, this transformation does not proceed via a carbene intermediate, nor does it require the presence of a transition‐metal catalyst.

Holmberg‐Douglas, Natalie↗
DOE OSTI2020

Regioselective Arene C−H Alkylation Enabled by Organic Photoredox Catalysis

Abstract Expanding the toolbox of C−H functionalization reactions applicable to the late‐stage modification of complex molecules is of interest in medicinal chemistry, wherein the preparation of structural variants of known pharmacophores is a key strategy for drug development. One manifold for the functionalization of aromatic molecules utilizes diazo compounds and a transition‐metal catalyst to generate a metallocarbene species, which is capable of direct insertion into an aromatic C−H bond. However, these high‐energy intermediates can often require directing groups or a large excess of substrate to achieve efficient and selective reactivity. Herein, we report that arene cation radicals generated by organic photoredox catalysis engage in formal C−H functionalization reactions with diazoacetate derivatives, furnishing sp 2 –sp 3 coupled products with moderate‐to‐good regioselectivity. In contrast to previous methods utilizing metallocarbene intermediates, this transformation does not proceed via a carbene intermediate, nor does it require the presence of a transition‐metal catalyst.

Holmberg‐Douglas, Natalie↗
DOE OSTI2025

Structural Basis of Sequential Enantioselective Epoxidation by a Flavin‐Dependent Monooxygenase in Lasalocid A Biosynthesis

Abstract Polyether polyketides are a structurally diverse group of natural products known for their antimicrobial and antiproliferative activities. Lasalocid A is a canonical natural polyether produced by the soil bacteriumStreptomyces lasalocidi. In lasalocid A biosynthesis, a polyene polyketide intermediate is converted into a bisepoxide by the flavin‐dependent monooxygenase enzyme Lsd18. Remarkably, Lsd18 acts on two distinct C═C groups in the substrate molecule, forming two (R,R) epoxides. We have determined the X‐ray crystal structures of Lsd18 in the substrate‐free, substrate‐bound, and product‐bound forms. Our work has revealed that Lsd18 has an extra‐large substrate‐binding pocket that allows the polyene to adopt different conformations within the enzyme pocket. This feature enables Lsd18 to epoxidate both of the C═C groups. Additionally, a subpocket located near the Lsd18 active site controls stereoselectivity by dictating which face of the C═C group is placed next to the flavin. Molecular understanding of how Lsd18 transforms a polyene into a bisepoxide during lasalocid A biosynthesis lays the foundation for the production of designer polyethers for drug development.

Chemistry↗
DOE OSTI2022

Superoxide Dismutase 1 Folding Stability as a Target for Molecular Tweezers in SOD1-Related Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation are hallmarks of many severe neurodegenerative diseases including Alzheimer's, Parkinson's and Huntington's disease. As a supramolecular ligand that binds to lysine and arginine residues, the molecular tweezer CLR01 was found to modify the aggregation pathway of disease-relevant proteins in vitro and in vivo with beneficial effects on toxicity. However, the molecular mechanisms of how tweezers exert these effects remain mainly unknown, hampering further drug development. Here, we investigate the modulation mechanism of unfolding and aggregation pathways of SOD1, which are involved in amyotrophic lateral sclerosis (ALS), by CLR01. Using a truncated version of the wildtype SOD1 protein, SOD1 bar , we show that CLR01 acts on the first step of the aggregation pathway, the unfolding of the SOD1 monomer. CLR01 increases, by ~10 °C, the melting temperatures of the A4V and G41D SOD1 mutants, which are commonly observed mutations in familial ALS. Molecular dynamics simulations and binding free energy calculations as well as native mass spectrometry and mutational studies allowed us to identify K61 and K92 as binding sites for the tweezers to mediate the stability increase. The data suggest that the modulation of SOD1 conformational stability is a promising target for future developments of supramolecular ligands against neurodegenerative diseases.

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

Regulatory utility of physiologically based pharmacokinetic modeling for assessing food impact in bioequivalence studies: A workshop summary report

This workshop report summarizes the presentations and panel discussion related to the use of physiologically based pharmacokinetic (PBPK) modeling approaches for food effect assessment, collected from Session 2 of Day 2 of the workshop titled “Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches.” The US Food and Drug Administration in collaboration with the Center for Research on Complex Generics organized this workshop where this particular session titled “Oral PBPK for Evaluating the Impact of Food on BE” presented successful cases of PBPK modeling approaches for food effect assessment. Recently, PBPK modeling has started to gain popularity among academia, industries, and regulatory agencies for its potential utility during bioavailability (BA) and/or bioequivalence (BE) studies of new and generic drug products to assess the impact of food on BA/BE. Considering the promises of PBPK modeling in generic drug development, the aim of this workshop session was to facilitate knowledge sharing among academia, industries, and regulatory agencies to understand the knowledge gap and guide the path forward. This report collects and summarizes the information presented and discussed during this session to disseminate the information into a broader audience for further advancement in this area.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Fibrotic activity quantified in serum by measurements of type III collagen pro-peptides can be used for prognosis across different solid tumor types

Due to activation of fibroblast into cancer-associated fibroblasts, there is often an increased deposition of extracellular matrix and fibrillar collagens, e.g. type III collagen, in the tumor microenvironment (TME) that leads to tumor fibrosis (desmoplasia). Tumor fibrosis is closely associated with treatment response and poor prognosis for patients with solid tumors. To assure that the best possible treatment option is provided for patients, there is medical need for identifying patients with high (or low) fibrotic activity in the TME. Measuring unique collagen fragments such as the pro-peptides released into the bloodstream during fibrillar collagen deposition in the TME can provide a non-invasive measure of the fibrotic activity. Based on data from 8 previously published cohorts, this review provides insight into the prognostic value of quantifying tumor fibrosis by measuring the pro-peptide of type III collagen in serum of a total of 1692 patients with different solid tumor types and discusses the importance of tumor fibrosis for understanding prognosis and for potentially guiding future drug development efforts that aim at overcoming the poor outcome associated with a fibrotic TME.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Cohort-based pan-cancer analysis and experimental studies reveal ISG15 gene as a novel biomarker for prognosis and immunotherapy efficacy prediction

Abstract ISG15, an interferon-stimulated ubiquitin-like protein, plays a multifaceted role in tumorigenesis and immune regulation. This study comprehensively evaluates ISG15 as a prognostic biomarker and predictor of immunotherapy response through pan-cancer bioinformatics analysis and experimental validation. By integrating multiomics data from TCGA, GEO, and clinical cohorts, we found that ISG15 is significantly overexpressed in multiple cancers and generally correlates with poor prognosis. Elevated ISG15 expression is associated with increased immune checkpoint gene expression, particularly PD-L1, and immune infiltration, notably M2-like tumor-associated macrophages. Immunohistochemistry and multiplexed immunofluorescence confirmed a strong positive correlation between ISG15, PD-L1, and M2-TAM infiltration in lung and gastric cancer samples. Functional analysis at the single-cell level revealed significant associations between ISG15 and tumor proliferation, angiogenesis, and immune suppression. Immunotherapy cohort analysis demonstrated that tumors with high ISG15 expression responded favorably to PD-L1 inhibitors but exhibited resistance to CTLA-4 blockade, findings further validated in lung cancer patients receiving anti-PD-1 therapy. These results suggest that ISG15 is a promising biomarker for prognosis and immunotherapy response prediction across cancers. Its integration into clinical decision-making may enhance personalized treatment strategies, improve immunotherapy outcomes, and provide new insights into the tumor immune microenvironment, cancer progression, and potential therapeutic targets for future drug development.

Immunology↗
DOE OSTI2025

Emerging Tools to Support DILI Assessment in Clinical Trials with Abnormal Baseline Serum Liver Tests or Pre-existing Liver Diseases

Abstract Based on the late Dr. Hyman Zimmerman’s observation that hepatocellular drug-induced liver injury (DILI) leading to jaundice carries a ≥ 10% fatality risk (coined as Hy’s law by others), evaluation of Drug-Induced Serious Hepatotoxicity (eDISH) continues to play a central role in the assessment of a study drug’s liability for acute hepatocellular DILI. The eDISH identifies drugs in clinical trials with DILI fatality (death or transplant) risk that may be unacceptable in a post-market setting. As a two-dimensional graph that plots peak total bilirubin (TB) versus peak serum aminotransferase levels for each patient during study drug or comparator treatment, eDISH identifies potential cases of acute, modest, and serious hepatocellular DILI for in-depth analysis of liver tests (LT) and clinical course so that the likelihood of causal association with the study drug can be determined. Unfortunately, the generalizable utility of this tool only pertains to trials enrolling patients with normal or near normal (NNN) baseline (BL) serum LTs. The eDISH does not necessarily apply to trials of patients with abnormal baseline (ABN-BL) LTs that often coincide with underlying liver disorders. Because drug development programs being reviewed by the FDA increasingly target liver disorders, we are often challenged to evaluate DILI risk in trials of patients with ABN-BL LTs. Also, the high background prevalence of metabolic dysfunction associated steatotic liver disease (MASLD) means patients with LTs above NNN may need to be enrolled in trials treating non-liver disorders to reflect the target population. Such study populations create challenges for industry and regulators because eDISH may not reliably categorize or identify potential cases of DILI for further analysis, as it so efficiently does in NNN-BL trials. We describe the main functionalities of eDISH in NNN-BL trials to understand what should be emulated by new tools or eDISH modifications. We then discuss non-eDISH–based plots that may be useful in ABN-BL trials.

Amirzadegan, Jasmine↗
DOE OSTI2025

Allosteric prediction via convolutional neural networks and protein structural and dynamical features

Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changing a protein’s functional state. As such, it is a ubiquitous aspect of protein functional regulation. Computationally predicting allosteric states is important as part of the broader challenge of functional annotation, but it also has practical implications for drug development, as targeting an allosteric site often affords greater specificity compared with targeting an orthosteric site. This study introduces a machine learning approach to predict the allosteric functional state using the small G-protein KRas as the model system, due to its implication in many types of cancer and being well studied as a result with many x-ray crystallographic structures of KRas available with different mutations and ligands bound. Using structural and dynamical features that can be cast as images, namely interatomic distances, contact maps, covariance, and mutual information, supervised learning was performed using convolutional neural networks. Two pretrained convolutional neural network architectures, GoogLeNet and ResNet18, were fine-tuned to classify KRas into active or inactive states based on these features. Across training regimes, atomic contact maps emerged as the most effective structural feature, whereas linearized mutual information outperformed covariance in capturing dynamical correlations relevant to allostery. Models achieved significant validation accuracy, with atomic contact maps yielding up to 90% accuracy. In conclusion, the findings suggest that integrating global structural rearrangements and correlated motion patterns with deep learning can reliably predict protein allosteric states, offering a promising framework for understanding allosteric regulation and developing targeted therapeutics.

Rajeshwar T., Rajitha [Oak Ridge National Laborato↗
DOE OSTI2021

Phagosomal chloride dynamics in the alveolar macrophage

Acidification in intracellular organelles is tightly linked to the influx of Cl – counteracting proton translocation by the electrogenic V-ATPase. We quantified the dynamics of Cl – transfer accompanying cargo incorporation into single phagosomes in alveolar macrophages (AMs). Phagosomal Cl – concentration and acidification magnitude were followed in real time with maximal acidification achieved at levels of approximately 200 mM. Live cell confocal microscopy verified that phagosomal Cl – influx utilized predominantly the Cl – channel CFTR. Relative levels of elemental chlorine (Cl) in hard X-ray fluorescence microprobe (XFM) analysis within single phagosomes validated the increase in Cl – content. XFM revealed the complex interplay between elemental K content inside the phagosome and changes in Cl – during phagosomal particle uptake. Cl – -dependent changes in phagosomal membrane potential were obtained using second harmonic generation (SHG) microscopy. These studies provide a mechanistic insight for screening studies in drug development targeting pulmonary inflammatory disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Transferring a Molecular Foundation Model for Polymer Property Predictions

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. Further, state-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Analytic Gradients for Equation-of-Motion Coupled Cluster with Single, Double, and Perturbative Triple Excitations

Understanding the process of molecular photoexcitation is crucial in various fields, including drug development, materials science, photovoltaics, and more. The electronic vertical excitation energy is a critical property, for example in determining the singlet-triplet gap of chromophores. However, a full understanding of excited-state processes requires additional explorations of the excited-state potential energy surface and electronic properties, which is greatly aided by the availability of analytic energy gradients. Owing to its robust high accuracy over a wide range of chemical problems, equation-of-motion coupled-cluster with single and double excitations (EOM-CCSD) is a powerful method for predicting excited state properties, and the implementation of analytic gradients of many EOM-CCSD (excitation energies, ionization potentials, electron attachment energies, etc.) along with numerous successful applications high- lights the flexibility of the method. In specific cases where a higher level of accuracy is needed or in more complex electronic structures, the inclusion of triple excitations becomes essential, for example, in the EOM-CCSD* approach of Saeh and Stanton. In this work, we derive and implement for the first time the analytic gradients of EOMEE-CCSD*, which also provides a template for analytic gradients of related ex- cited state methods with perturbative triple excitations. Here, the capabilities of analytic EOMEE-CCSD* gradients are illustrated by several representative examples.

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

Influence of Steric and Electronic Properties of P2 Groups on Covalent Inhibitor Binding to SARS-CoV-2 Main Protease

The main protease (MPro) of SARS-CoV-2 is a critical enzyme required for viral replication, making it a prime target for antiviral drug development. Covalent inhibitors, which form a stable interaction with the catalytic C145, have demonstrated strong inhibition of MPro, but the influence of steric and electronic properties of P2 substituents, designed to engage the S2 substrate-binding subsite within the MPro active site, on inhibitor binding affinity remains underexplored. Here, in this study, we design and characterize two hybrid covalent inhibitors, BBH-3 and BBH-4, and present their X-ray crystallographic structures in complex with MPro, providing molecular insights into how their distinct P2 groups, a dichlorobenzyl moiety in BBH-3 and an adamantyl substituent in BBH-4, affect binding conformation and active site adaptability. Comparative structural analyses with previously characterized inhibitors, including BBH-2 and Mcule-5948770040, reveal how the P2 bulkiness and electronic properties influence active site dynamics, particularly through interactions with the S2 and S5 subsites. The P2 group of BBH-3 induces conformational shifts in the S2 helix and the S5 loop, while BBH-4 displaces M49, stabilizing its binding through hydrophobic interactions. Isothermal titration calorimetry further elucidates the impact of P2 modifications on inhibitor affinity, revealing a delicate balance between enthalpic and entropic contributions. The data demonstrate that BBH-3 exhibits less favorable binding, affirming that dichlorobenzyl substitution at the P2 position has a more negative impact on the affinity for MPro than bulky saturated cyclic groups. This underscores the feature that MPro active site malleability may be accompanied by a conformational strain.

SARS-CoV-2↗
DOE OSTI2022

Intramolecular C–C Bond Formation Links Anthraquinone and Enediyne Scaffolds in Tiancimycin Biosynthesis

First discovered in 1989, the anthraquinone-fused enediynes are a class of DNA-cleaving bacterial natural products composed of a DNA-intercalating anthraquinone moiety and a 10-membered enediyne warhead. However, until recently, there has been a lack of genetically amenable hosts and sequenced biosynthetic gene clusters available for solving the biosynthetic questions surrounding these molecules. Herein, we have identified and biochemically and structurally characterized TnmK1, a member of the alpha/beta-hydrolase fold superfamily responsible for the C-C bond formation linking the anthraquinone moiety and enediyne core together in tiancimycin (TNM) biosynthesis. In doing so, two intermediates, TNM H and TNM I, in anthraquinone-fused enediyne biosynthesis, containing an unprecedented cryptic C16 aldehyde group, were identified. Here, this aldehyde plays a key role in the TnmK1-catalyzed C-C bond formation via a Michael addition, representing the first example of this chemistry for the alpha/ beta-hydrolase fold superfamily. Additionally, TNM I shows sub-nanomolar cytotoxicity against selected cancer cell lines, indicating a new mechanism of action compared to previously known anthraquinone-fused enediynes. Together, the findings from this study are expected to impact enzymology, natural product biosynthesis, and future efforts at enediyne discovery and drug development.

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

Low complexity domains of the nucleocapsid protein of SARS-CoV-2 form amyloid fibrils

The self-assembly of the Nucleocapsid protein (NCAP) of SARS-CoV-2 is crucial for its function. Computational analysis of the amino acid sequence of NCAP reveals low-complexity domains (LCDs) akin to LCDs in other proteins known to self-assemble as phase separation droplets and amyloid fibrils. Previous reports have described NCAP’s propensity to phase-separate. Here we show that the central LCD of NCAP is capable of both, phase separation and amyloid formation. Within this central LCD we identified three adhesive segments and determined the atomic structure of the fibrils formed by each. Those structures guided the design of G12, a peptide that interferes with the self-assembly of NCAP and demonstrates antiviral activity in SARS-CoV-2 infected cells. Our work, therefore, demonstrates the amyloid form of the central LCD of NCAP and suggests that amyloidogenic segments of NCAP could be targeted for drug development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Structural basis of agonist specificity of α 1A -adrenergic receptor

α 1 -adrenergic receptors (α 1 -ARs) play critical roles in the cardiovascular and nervous systems where they regulate blood pressure, cognition, and metabolism. However, the lack of specific agonists for all α 1 subtypes has limited our understanding of the physiological roles of different α 1 -AR subtypes, and led to the stagnancy in agonist-based drug development for these receptors. Here we report cryo-EM structures of α 1A -AR in complex with heterotrimeric G-proteins and either the endogenous common agonist epinephrine or the α 1A -AR-specific synthetic agonist A61603. These structures provide molecular insights into the mechanisms underlying the discrimination between α 1A -AR and α 1B -AR by A61603. Guided by the structures and corresponding molecular dynamics simulations, we engineer α 1A -AR mutants that are not responsive to A61603, and α 1B -AR mutants that can be potently activated by A61603. Together, these findings advance our understanding of the agonist specificity for α 1 -ARs at the molecular level, opening the possibility of rational design of subtype-specific agonists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structural insights into the modulation of coronavirus spike tilting and infectivity by hinge glycans

Abstract Coronavirus spike glycoproteins presented on the virion surface mediate receptor binding, and membrane fusion during virus entry and constitute the primary target for vaccine and drug development. How the structure dynamics of the full-length spikes incorporated in viral lipid envelope correlates with the virus infectivity remains poorly understood. Here we present structures and distributions of native spike conformations on vitrified human coronavirus NL63 (HCoV-NL63) virions without chemical fixation by cryogenic electron tomography (cryoET) and subtomogram averaging, along with site-specific glycan composition and occupancy determined by mass spectrometry. The higher oligomannose glycan shield on HCoV-NL63 spikes than on SARS-CoV-2 spikes correlates with stronger immune evasion of HCoV-NL63. Incorporation of cryoET-derived native spike conformations into all-atom molecular dynamic simulations elucidate the conformational landscape of the glycosylated, full-length spike that reveals a role of hinge glycans in modulating spike bending. We show that glycosylation at N1242 at the upper portion of the stalk is responsible for the extensive orientational freedom of the spike crown. Subsequent infectivity assays implicated involvement of N1242-glyan in virus entry. Our results suggest a potential therapeutic target site for HCoV-NL63.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Disruption of a key ligand-H-bond network drives dissociative properties in vamorolone for Duchenne muscular dystrophy treatment

Duchenne muscular dystrophy is a genetic disorder that shows chronic and progressive damage to skeletal and cardiac muscle leading to premature death. Antiinflammatory corticosteroids targeting the glucocorticoid receptor (GR) are the current standard of care but drive adverse side effects such as deleterious bone loss. Through subtle modification to a steroidal backbone, a recently developed drug, vamorolone, appears to preserve beneficial efficacy but with significantly reduced side effects. We use combined structural, biophysical, and biochemical approaches to show that loss of a receptor-ligand hydrogen bond drives these remarkable therapeutic effects. Moreover, vamorolone uniformly weakens coactivator associations but not corepressor associations, implicating partial agonism as the main driver of its dissociative properties. Additionally, we identify a critical and evolutionarily conserved intramolecular network connecting the ligand to the coregulator binding surface. Interruption of this allosteric network by vamorolone selectively reduces GR-driven transactivation while leaving transrepression intact. Our results establish a mechanistic understanding of how vamorolone reduces side effects, guiding the future design of partial agonists as selective GR modulators with an improved therapeutic index.

59 BASIC BIOLOGICAL SCIENCES↗