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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploiting bacterial effector proteins to uncover evolutionarily conserved antiviral host machinery

Arboviruses are a diverse group of insect-transmitted pathogens that pose global public health challenges. Identifying evolutionarily conserved host factors that combat arbovirus replication in disparate eukaryotic hosts is important as they may tip the balance between productive and abortive viral replication, and thus determine virus host range. Here, we exploit naturally abortive arbovirus infections that we identified in lepidopteran cells and use bacterial effector proteins to uncover host factors restricting arbovirus replication. Bacterial effectors are proteins secreted by pathogenic bacteria into eukaryotic hosts cells that can inhibit antimicrobial defenses. Since bacteria and viruses can encounter common host defenses, we hypothesized that some bacterial effectors may inhibit host factors that restrict arbovirus replication in lepidopteran cells. Thus, we used bacterial effectors as molecular tools to identify host factors that restrict four distinct arboviruses in lepidopteran cells. By screening 210 effectors encoded by seven different bacterial pathogens, we identify several effectors that individually rescue the replication of all four arboviruses. We show that these effectors encode diverse enzymatic activities that are required to break arbovirus restriction. We further characterize Shigella flexneri-encoded IpaH4 as an E3 ubiquitin ligase that directly ubiquitinates two evolutionarily conserved proteins, SHOC2 and PSMC1, promoting their degradation in insect and human cells. We show that depletion of either SHOC2 or PSMC1 in insect or human cells promotes arbovirus replication, indicating that these are ancient virus restriction factors conserved across invertebrate and vertebrate hosts. Collectively, our study reveals a novel pathogen-guided approach to identify conserved antimicrobial machinery, new effector functions, and conserved roles for SHOC2 and PSMC1 in virus restriction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Variable Chain Length Carboxylic Acids as Modifiers to Enhance the Antiviral Efficacy of Sodium Dodecyl Sulfate.

Non-toxic disinfectants composed of readily available commodity chemicals are needed for immediate response to the current COVID-19 pandemic. One such area is the active research field for food-grade sanitization. Combinations of levulinic acid, a five-carbon ketocarboxylic acid, and sodium dodecyl sulfate, have been frequently described for antibacterial use on food contact surfaces. Levulinic acid has been identified as a renewable feedstock but is not presently in commodity production. Other carboxylic acids, such as acetic acid, may be equally usable and food-safe. Acidic and buffered solutions were highly effective, yielding no countable surviving organisms. The high efficacy of each acid may suggest that carboxylic acid sanitizers in general have potential use against viruses.

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

Applying the ATOM drug discovery platform to small-molecule antivirals (Annual Report)

The objective of this project is to advance our understanding of the ML approaches needed to find the most potent inhibitor through an AI guided search that simultaneously optimizes for limited off-target safety activity and desirable pharmacokinetics (PK) properties. The methods will be tested for inhibiting SARS-CoV-2 activity through inhibition of the main protease as a demonstration, but the methodology will be developed to apply to any biothreat target using a small-molecule protein binding-based intervention, with limited experimental data. Computational experiments are conducted using our ATOM generative molecular design (GMD) loop software, which is the implementation of our AI/ML drug design pipeline.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. Here, the framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure --- this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Y↗
DOE OSTI2023

Development of a novel minigenome and recombinant VSV expressing Seoul hantavirus glycoprotein-based assays to identify anti-hantavirus therapeutics

Seoul virus (SEOV) is an emerging global health threat that can cause hemorrhagic fever with renal syndrome (HFRS), which results in case fatality rates of ~2%. There are no approved treatments for SEOV infections. We developed a cell-based assay system to identify potential antiviral compounds for SEOV and generated additional assays to characterize the mode of action of any promising antivirals. Here, to test if candidate antivirals targeted SEOV glycoprotein-mediated entry, we developed a recombinant reporter vesicular stomatitis virus expressing SEOV glycoproteins. To facilitate the identification of candidate antiviral compounds targeting viral transcription/replication, we successfully generated the first reported minigenome system for SEOV. This SEOV minigenome (SEOV-MG) screening assay will also serve as a prototype assay for discovery of small molecules inhibiting replication of other hantaviruses, including Andes and Sin Nombre viruses. Ours is a proof-of-concept study in which we tested several compounds previously reported to have activity against other negative-strand RNA viruses using our newly developed hantavirus antiviral screening systems. These systems can be used under lower biocontainment conditions than those needed for infectious viruses, and identified several compounds with robust anti-SEOV activity. Our findings have important implications for the development of anti-hantavirus therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Inhibition of tick-borne encephalitis virus in cell cultures by ribavirin

Tick-borne encephalitis virus (TBEV) belonging to arboviruses is a major member of zoonotic pathogens. TBEV infection causes severe human encephalitis without specific antiviral drugs. Due to its use of antiviral drug against a wide range of viruses, we investigated antiviral effect of ribavirin against TBEV in susceptible human cell lines A549 and SH-SY5Y. Ribavirin displayed minor cytotoxicity on multiple cell lines. Ribavirin obviously impaired TBEV replication and protected the infected cells from cytopathic effect. Importantly, ribavirin markedly inhibited TBEV propagation, as evidenced by impairment of TBEV production and viral RNA replication. Treatment with ribavirin (co-treatment and post-treatment) led to a dose-dependent reduction in TBEV titers as well as the viral RNA levels. Antiviral protein myxovirus resistance A mRNA expression was significantly up-regulated and signal transducer and activator of transcription 3 was activated in TBEV-infected A549 cells upon the ribavirin treatment. Induction of inflammatory cytokine tumor necrosis factor alpha by TBEV was decreased in A549 cells with the treatment of ribavirin, whereas interleukin 1 beta release appeared to be unaffected. These results suggest that ribavirin might represent a promising safe and effective antiviral drug against TBEV.

Tang, Wan-Da↗
DOE OSTI2023

Structure-based design of SARS-CoV-2 papain-like protease inhibitors

The COVID-19 pandemic is caused by SARS-CoV-2, an RNA virus with high transmissibility and mutation rate. Given the paucity of orally bioavailable antiviral drugs to combat SARS-CoV-2 infection, there is a critical need for additional antivirals with alternative mechanisms of action. Papain-like protease (PL pro ) is one of the two SARS-CoV-2 encoded viral cysteine proteases essential for viral replication. PL pro cleaves at three sites of the viral polyproteins. In addition, PLpro antagonizes the host immune response upon viral infection by cleaving ISG15 and ubiquitin from host proteins. Therefore, PL pro is a validated antiviral drug target. In this study, we report the X-ray crystal structures of papain-like protease (PL pro ) with two potent inhibitors, Jun9722 and Jun9843 . Subsequently, we designed and synthesized several series of analogs to explore the structure-activity relationship, which led to the discovery of PL pro inhibitors with potent enzymatic inhibitory activity and antiviral activity against SARS-CoV-2. Together, the lead compounds are promising drug candidates for further development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A quantitative model used to compare within-host SARS-CoV-2, MERS-CoV, and SARS-CoV dynamics provides insights into the pathogenesis and treatment of SARS-CoV-2

The scientific community is focused on developing antiviral therapies to mitigate the impacts of the ongoing novel coronavirus disease 2019 (COVID-19) outbreak. This will be facilitated by improved understanding of viral dynamics within infected hosts. Here, using a mathematical model in combination with published viral load data, we compare within-host viral dynamics of SARS-CoV-2 with analogous dynamics of MERS-CoV and SARS-CoV. Our quantitative analyses using a mathematical model revealed that the within-host reproduction number at symptom onset of SARS-CoV-2 was statistically significantly larger than that of MERS-CoV and similar to that of SARS-CoV. In addition, the time from symptom onset to the viral load peak for SARS-CoV-2 infection was shorter than those of MERS-CoV and SARS-CoV. These findings suggest the difficulty of controlling SARS-CoV-2 infection by antivirals. We further used the viral dynamics model to predict the efficacy of potential antiviral drugs that have different modes of action. The efficacy was measured by the reduction in the viral load area under the curve (AUC). Our results indicate that therapies that block de novo infection or virus production are likely to be effective if and only if initiated before the viral load peak (which appears 2–3 days after symptom onset), but therapies that promote cytotoxicity of infected cells are likely to have effects with less sensitivity to the timing of treatment initiation. Furthermore, combining a therapy that promotes cytotoxicity and one that blocks de novo infection or virus production synergistically reduces the AUC with early treatment. Our unique modeling approach provides insights into the pathogenesis of SARS-CoV-2 and may be useful for development of antiviral therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Chloropyridinyl Esters of Nonsteroidal Anti-Inflammatory Agents and Related Derivatives as Potent SARS-CoV-2 3CL Protease Inhibitors

We report the design and synthesis of a series of new 5-chloropyridinyl esters of salicylic acid, ibuprofen, indomethacin, and related aromatic carboxylic acids for evaluation against SARS-CoV-2 3CL protease enzyme. These ester derivatives were synthesized using EDC in the presence of DMAP to provide various esters in good to excellent yields. Compounds are stable and purified by silica gel chromatography and characterized using 1 H-NMR, 13 C-NMR, and mass spectral analysis. These synthetic derivatives were evaluated in our in vitro SARS-CoV-2 3CLpro inhibition assay using authentic SARS-CoV-2 3CLpro enzyme. Compounds were also evaluated in our in vitro antiviral assay using quantitative VeroE 6 cell-based assay with RNAqPCR. A number of compounds exhibited potent SARS-CoV-2 3CLpro inhibitory activity and antiviral activity. Compound 9a was the most potent inhibitor, with an enzyme IC 50 value of 160 nM. Compound 13b exhibited an enzyme IC 50 value of 4.9 µM. However, it exhibited a potent antiviral EC 50 value of 24 µM in VeroE6 cells. Remdesivir, an RdRp inhibitor, exhibited an antiviral EC 50 value of 2.4 µM in the same assay. We assessed the mode of inhibition using mass spectral analysis which suggested the formation of a covalent bond with the enzyme. To obtain molecular insight, we have created a model of compound 9a bound to SARS-CoV-2 3CLpro in the active site.

3CLpro inhibitors↗
DOE OSTI2024

Structural Studies of Inhibitors with Clinically Relevant Influenza Endonuclease Variants

Vital to the treatment of influenza is the use of antivirals such as Oseltamivir (Tamiflu) and Zanamivir (Relenza); however, antiviral resistance is becoming an increasing problem for these therapeutics. The RNA-dependent RNA polymerase acidic N-terminal (PA N ) endonuclease, a critical component of influenza viral replication machinery, is an antiviral target that was recently validated with the approval of Baloxavir Marboxil (BXM). Despite its clinical success, BXM has demonstrated susceptibility to resistance mutations, specifically the I38T, E23K, and A36 V mutants of PAN. To better understand the effects of these mutations on BXM resistance and improve the design of more robust therapeutics, this study examines key differences in protein–inhibitor interactions with two inhibitors and the I38T, E23K, and A36 V mutants. Differences in inhibitor binding were evaluated by measuring changes in binding to PA N using two biophysical methods. The binding mode of two distinct inhibitors was determined crystallographically with both wild-type and mutant forms of PA N . Collectively, these studies give some insight into the mechanism of antiviral resistance of these mutants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Discovery of SARS-CoV-2 Papain-like Protease Inhibitors through a Combination of High-Throughput Screening and a FlipGFP-Based Reporter Assay

The papain-like protease (PL pro ) of SARS-CoV-2 is a validated antiviral drug target. Through a fluorescence resonance energy transfer-based high-throughput screening and subsequent lead optimization, we identified several PL pro inhibitors including Jun9-72-2 and Jun9-75-4 with improved enzymatic inhibition and antiviral activity compared to GRL0617, which was reported as a SARS-CoV PL pro inhibitor. Significantly, we developed a cell-based FlipGFP assay that can be applied to predict the cellular antiviral activity of PL pro inhibitors in the BSL-2 setting. X-ray crystal structure of PL pro in complex with GRL0617 showed that binding of GRL0617 to SARS-CoV-2 induced a conformational change in the BL2 loop to a more closed conformation. Molecular dynamics simulations showed that Jun9-72-2 and Jun9-75-4 engaged in more extensive interactions than GRL0617. Overall, the PL pro inhibitors identified in this study represent promising candidates for further development as SARS-CoV-2 antivirals, and the FlipGFP-PL pro assay is a suitable surrogate for screening PL pro inhibitors in the BSL-2 setting.

60 APPLIED LIFE SCIENCES↗