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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Affinity of LDR Organics to Cementitious Materials: Sorption and Leaching Tests

SRNL is working to identify and test the physiochemical interactions of organic contaminants of potential concern with minerals in grout/cementitious materials. Organic species may interact with cementitious minerals including slag, fly ash, cement, and other components/dopants like carbon in fly ash. The identification of such interactions will support the solidification process design, performance assessments for the chemicals of concern, and a proposed Resource Conservation and Recovery Act (RCRA) treatment variance the technology-based treatment standard specified for the Land Disposal Restriction (LDR) organics associated with Hanford tank waste. In FY24, a list of the 132 reasonably expected to be present LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 10 compounds spanning the identified properties were tested using sorption and leachate tests. These compounds were subject to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The tests have been completed and analysis is underway but as yet currently unavailable. The analytical results (and conclusions) will be included in a forthcoming revision to this report as soon as they are available

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Affinity of LDR Organics to Cementitious Materials: Sorption and Leaching Tests

SRNL is working to identify and test the physiochemical interactions of organic contaminants of potential concern with minerals in grout/cementitious materials. Organic species may interact with cementitious minerals including slag, fly ash, cement, and other components/dopants like carbon in fly ash. The identification of such interactions will support the solidification process design, performance assessments for the chemicals of concern, and a proposed Resource Conservation and Recovery Act (RCRA) treatment variance specified for the Land Disposal Restriction (LDR) organics associated with Hanford tank waste. Inably expected to be present LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 10 compounds, spanning the identified properties, were tested using sorption and leachate tests. These compounds were subjected to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The interactions between organic compounds were observed in traditional batch sorption and modified Toxic Characteristic Leaching Procedure (TCLP) leachate tests for a surrogate Cast Stone material with and without an activated carbon addition. Specifically, phthalic acids (negatively charged) and 4-chloroaniline (polar) sorbed strongly to unmodified Cast Stone and a group of 3 phenolic compounds (2,4,6-Trichlorophenol, Pentachlorophenol, o-Cresol) were sorbed to and were retained by Cast Stone with a 1% activated carbon amendment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Small molecule inhibitors for treatment of alpha viruses

An in vitro assay was designed to measure the activity of the alphavirus non-structural protein 2 (nsP2), which is the viral protease and is required for viral replication. By taking advantage of fluorescence-resonance energy transfer between two proteins, a protease cleavage assay was generated. This was utilized for high-throughput screening of 40,000 small molecules. Inhibitors were validated using cell-based assays to measure alphavirus infection and cytotoxicity. Certain compounds were then characterized for anti-viral efficacy in various cell lines in numerous assays. Compounds were tested against Chikungunya virus, Venezuelan Equine Encephalitis virus, Rift Valley Fever virus, and Zika virus. Three compounds (compounds I, II, and III) showed pan-alphavirus anti-viral efficacy at concentrations that did not result in cell toxicity. An additional compound, structure IV, showed broad spectrum inhibition of all viruses tested. Pharmaceutical preparations and methods of treatment including these compounds are provided herein.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Affinity and Treatment of LDR Organics in Low Activity Waste by Cementitious Materials – 26109

The physiochemical interactions between organic contaminants, minerals, and polymer additives in grout/cementitious materials are being identified. This research supports a proposed Resource Conservation and Recovery Act (RCRA) treatment variance relevant to the Land Disposal Restriction (LDR) organics present in Hanford tank waste. It provides the technical basis to address the aspects documented by the Environmental Protection Agency in a draft memo necessary to establish that organics can be immobilized/stabilized in a cementitious matrix. The organic species may interact with cementitious minerals, including slag, fly ash, cement, and other components/dopants like activated carbon. A list of 132 reasonably expected LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 15 compounds spanning the identified properties was tested using sorption and leachate tests. These compounds were subjected to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The interactions between organic compounds were observed in traditional batch sorption and modified TCLP leachate tests for surrogate Cast Stone material with and without activated carbon addition. Specifically, phthalic acid (negatively charged) and 4-chloroaniline (polar) sorbed strongly to unmodified Cast Stone, while a group of three phenolic compounds (2,4,6-Trichlorophenol, Pentachlorophenol, o-Cresol) sorbed to and were retained by Cast Stone with a 1% activated carbon amendment. Mixtures of these compounds demonstrated visible retention of the organics within the matrix with a quantifiable affinity of the organics to the cement. This novel testing supports the notion that organics within Hanford tank waste would be retained onto the cement phase with the addition of simple materials easily added to the formulation as part of the treatment process. To further provide additional support to this claim, models employing Flory-Huggins theory in conjunction with macromolecular and organic molecule solubility parameters and species activity coefficients are being utilized to better understand these interactions. Within this context, Van Krevelen (VK) and Hansen organic and polymer solubility parameters were used to inform the Flory-Huggins interaction parameter, allowing for a quantifiable method of evaluating polymer-solvent compatibility and, by extension, interactions with proposed binding additives (e.g., activated carbon). These models and measurement should test the hypothesis for our systems understanding and applicability of Flory-Huggins theory, and whether the prediction of organics in the polymer phase versus the aqueous phase can be confidently made using this strategy. The estimation of the organic molecular activity coefficient in these high salt-saturated aqueous systems is another factor that will be assessed. This project aims to predict and understand complicated organic interactions in these heterogenous systems, guiding optimal treatment and stabilization methodologies.

Jolin, Will [Savannah River National Laboratory (S↗
DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗
DOE OSTI2020

Engineering regulatory networks for complex phenotypes in E. coli

Regulatory networks describe the hierarchical relationship between transcription factors, associated proteins, and their target genes. Regulatory networks respond to environmental and genetic perturbations by reprogramming cellular metabolism. Here we design, construct, and map a comprehensive regulatory network library containing 110,120 specific mutations in 82 regulators expected to perturb metabolism. We screen the library for different targeted phenotypes, and identify mutants that confer strong resistance to various inhibitors, and/or enhanced production of target compounds. These improvements are identified in a single round of selection, showing that the regulatory network library is universally applicable and is convenient and effective for engineering targeted phenotypes. The facile construction and mapping of the regulatory network library provides a path for developing a more detailed understanding of global regulation in E. coli , with potential for adaptation and use in less-understood organisms, expanding toolkits for future strain engineering, synthetic biology, and broader efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗
DOE OSTI2024

High-Resolution Tandem Mass Spectrometry-Based Analysis of Model Lignin–Iron Complexes: Novel Pipeline and Complex Structures

Understanding the chemical nature of soil organic carbon (SOC) with great potential to bind iron (Fe) minerals is critical for predicting the stability of SOC. Organic ligands of Fe are among the top candidates for SOCs able to strongly sorb on Fe minerals, but most of them are still molecularly uncharacterized. To shed insights into the chemical nature of organic ligands in soil and their fate, this study developed a protocol for identifying organic ligands using ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and metabolomic tools. The protocol was used for investigating the Fe complexes formed by model compounds of lignin-derived organic ligands, namely, caffeic acid (CA), p-coumaric acid (CMA), vanillin (VNL), and cinnamic acid (CNA). Isotopologue analysis of 54/56 Fe was used to screen out the potential UHPLC-HRMS (m/z) features for complexes formed between organic ligands and Fe, with multiple features captured for CA, CMA, VNL, and CNA when 35/37 Cl isotopologue analysis was used as supplementary evidence for the complexes with Cl. MS/MS spectra, fragment analysis, and structure prediction with SIRIUS were used to annotate the structures of mono/bidentate mono/biligand complexes. The analysis determined the structures of monodentate and bidentate complexes of FeL x Cl y (L: organic ligand, x = 1–4, y = 0–3) formed by model compounds. The protocol developed in this study can be used to identify unknown organic ligands occurring in complex environmental samples and shed light on the molecular-level processes governing the stability of the SOC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Functional promiscuity of small multidrug resistance transporters from Staphylococcus aureus , Pseudomonas aeruginosa , and Francisella tularensis

Abstract Small multidrug resistance transporters efflux toxic compounds from bacteria and are a minimal system to understand multidrug transport. Most previous studies have focused on EmrE, the model SMR from Escherichia coli , finding that EmrE has a broader substrate profile than previously thought and that EmrE may perform multiple types of transport, resulting in substrate‐dependent resistance or susceptibility . Here, we performed a broad screen to identify potential substrates of three other SMRs: PAsmr from Pseudomonas aeruginosa ; FTsmr from Francisella tularensis ; and SAsmr from Staphylococcus aureus . This screen tested metabolic differences in E. coli expressing each transporter versus an inactive mutant, for a clean comparison of sequence and substrate‐specific differences in transporter function, and identified many substrates for each transporter. In general, resistance compounds were charged, and susceptibility substrates were uncharged, but hydrophobicity was not correlated with phenotype. Two resistance hits and two susceptibility hits were validated via growth assays and IC50 calculations. Susceptibility is proposed to occur via substrate‐gated proton leak, and the addition of bicarbonate antagonizes the susceptibility phenotype, consistent with this hypothesis.

Biochemistry & Molecular Biology↗
NASA NTRS2011

Analysis of Mars Analogue Soil Samples Using Solid-Phase Microextraction, Organic Solvent Extraction and Gas Chromatography/Mass Spectrometry

Polycyclic aromatic hydrocarbons (PAHs) are robust and abundant molecules in extraterrestrial environments. They are found ubiquitously in the interstellar medium and have been identified in extracts of meteorites collected on Earth. PAHs are important target molecules for planetary exploration missions that investigate the organic inventory of planets, moons and small bodies. This study is part of an interdisciplinary preparation phase to search for organic molecules and life on Mars. We have investigated PAH compounds in desert soils to determine their composition, distribution and stability. Soil samples (Mars analogue soils) were collected at desert areas of Utah in the vicinity of the Mars Desert Research Station (MDRS), in the Arequipa region in Peru and from the Jutland region of Denmark. The aim of this study was to optimize the solid-phase microextraction (SPME) method for fast screening and determination of PAHs in soil samples. This method minimizes sample handling and preserves the chemical integrity of the sample. Complementary liquid extraction was used to obtain information on five- and six-ring PAH compounds. The measured concentrations of PAHs are, in general, very low, ranging from 1 to 60 ng g(sup -1). The texture of soils is mostly sandy loam with few samples being 100% silt. Collected soils are moderately basic with pH values of 8-9 except for the Salten Skov soil, which is slightly acidic. Although the diverse and variable microbial populations of the samples at the sample sites might have affected the levels and variety of PAHs detected, SPME appears to be a rapid, viable field sampling technique with implications for use on planetary missions.

Orzechowska, G. E.↗
DOE OSTI2024

Potential biological control agents of Geosmithia morbida restrict fungal pathogen growth via mycoparasitism and antibiosis

Abstract Thousand cankers disease of Juglans (walnut) and Pterocarya (wingnut) spp. (Fagales: Juglandaceae) is caused by the fungal pathogen Geosmithia morbida Kolarík, Freeland, Utley, and Tisserat (Hypocreales: Bionectriaceae) and bark beetle pest/vector, Pityophthorus juglandis Blackman (Coleoptera: Curculionidae). To further the development of biological management strategies for thousand cankers disease, we assessed the ability of 14 endophytic Trichoderma (Hypocreales: Hypocreaceae) isolates and the commercially available isolate T. afroharzianum strain KRL-AG2 to inhibit the in vitro growth of three different G. morbida isolates via mycoparasitism and antibiosis. To identify factors that may affect field success of candidate biological control agents, we quantified the growth responses of Trichoderma spp. and the commercially available entomopathogenic fungus, Beauveria bassiana (Bals.-Criv.) Vuill. (Hypocreales: Cordycipitaceae) strain GHA, to the plant secondary metabolite and antimicrobial compound, juglone in vitro. A total of 12 Trichoderma isolates (from six different Trichoderma species) demonstrated antagonistic activity towards G. morbida in dual-plate assays. Juglone consistently reduced the growth of B. bassiana strain GHA and 14 of the 15 screened Trichoderma isolates in vitro. Additionally, one metabolite-producing Trichoderma isolate, TN4-47, completely inhibited the growth of all three G. morbida isolates across all tested metabolite concentrations and had comparatively greater tolerance to juglone compared to other Trichoderma isolates. Future lines of research should focus on characterizing the active antagonistic compound present in the metabolite filtrates, determine the mode of action of the active component(s), and elucidate how abiotic and biotic factors may influence the growth, persistence, and antagonistic activity of candidate biological control agents in planta .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optimization of Species-Selective Reversible Proteasome Inhibitors for the Treatment of Malaria

Abstract Malaria remains a critical global health challenge, with increasing resistance to frontline therapies necessitating novel drug targets. The proteasome has emerged as a promising target for antimalarial drug discovery. This study describes efforts to optimize a series of species-selective reversible inhibitors targeting the Plasmodium falciparum 20S proteasome. Starting from the carboxypiperidine scaffold identified through a high-throughput viability screen, we conducted iterative structure–activity relationship studies, leading to the development of highly potent and selective inhibitors with good oral bioavailability. Lead compounds demonstrated nanomolar potency against P. falciparum blood-stage parasites and selective inhibition of the parasite proteasome over the human counterpart. Cryo-EM structural studies confirmed binding at the β5 subunit, while in vivo pharmacokinetic studies identified promising candidates for further development. These findings support proteasome inhibition as a viable strategy for novel antimalarial drug development.

Gahalawat, Suraksha [UT Southwestern Medical Cente↗
DOE OSTI2023

A combinatorial droplet microfluidic device integrated with mass spectrometry for enzyme screening

Mass spectrometry (MS) enables detection of different chemical species with a very high specificity; however, it can be limited by its throughput. Integrating MS with microfluidics has a tremendous potential to improve throughput and accelerate biochemical research. In this work, we introduce Drop-NIMS, a combination of a passive droplet loading microfluidic device and a matrix-free MS laser desorption ionization technique called nanostructure-initiator mass spectrometry (NIMS). This platform combines different droplets at random to generate a combinatorial library of enzymatic reactions that are deposited directly on the NIMS surface without requiring additional sample handling. The enzyme reaction products are then detected with MS. Drop-NIMS was used to rapidly screen enzymatic reactions containing low (on the order of nL) volumes of glycoside reactants and glycoside hydrolase enzymes per reaction. MS “barcodes” (small compounds with unique masses) were added to the droplets to identify different combinations of substrates and enzymes created by the device. We assigned xylanase activities to several putative glycoside hydrolases, making them relevant to food and biofuel industrial applications. Overall, Drop-NIMS is simple to fabricate, assemble, and operate and it has potential to be used with many other small molecule metabolites.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Efficient Synthesis of High-Performance Anion Exchange Membranes by Applying Clickable Tetrakis(dialkylamino)phosphonium Cations

Tetrakis(dialkylamino)phosphonium (TKDAAP) compounds exhibit extraordinary base resistance, a prerequisite feature for high-performance anion exchange membranes (AEMs). It is, however, challenging to synthesize a TKDAAP compound with reactive functionality that can be used to link the cation to a polymer backbone. In this study, two TKDAAP compounds with alkyne functionality were synthesized and incorporated into an azide-modified SBS triblock copolymer backbone via Cu(I)-catalyzed alkyne–azide cycloaddition (CuAAC) “click” chemistry. The properties of the resulting AEMs were characterized. It was found that (1) the triazole linker between the cation and the polymer backbone was stable under alkaline conditions; (2) varying the substituents of TKDAAP compounds could dramatically alter the stability; and (3) increasing the hydrophilicity of the AEM was an efficient way to enhance its ionic conductivity. Using clickable TKDAAP compounds makes it easy to combine various cations into polymer backbones with adjustable cation content, thus potentially leading to an efficient way to screen a wide variety of polyelectrolyte structures to identify the most promising candidates for high-performance AEMs.

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

Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronically active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX 3 ) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX 3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX 3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Biosynthesis of bioprivileged, linear molecules via novel carboligase reactions

Over the award period, we made progress on the three aims. We screened twenty-five carboligases for activity coupling twenty-one possible -keto acids (Aim 1). The carboligases were selected across a diverse set of protein sequences. Using Q-Exactive UHPLC-MS, we tested a total of 210 coupled products per enzyme and generated a dataset of 5250 enzyme-substrate activity relationships. We identified multiple enzymes that had activity for synthesizing suberic acid and heptanoic acid (Aim 2). We built a random forest model for predicting the activity of each enzyme toward substrates on which it was not tested using the data from Aim 1. Finally, we evaluated growth defects that occurred due to expression of different carboligases in E. coli (Aim 3). We were able to identify specific metabolites and putative pathways that, when supplemented in the media, recovered the growth defect associated with the presence of specific carboligases. We are in the process of publishing two manuscript describing the methods for high-throughput screening of enzyme promiscuity, using machine learning to predict activity on untested substrates, and enzyme activity data we collected. This project has produced enabling data for biosynthesis of a range of new-to-nature compounds to support biomanufacturing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

SARS-CoV2 billion-compound docking

Abstract This dataset contains ligand conformations and docking scores for 1.4 billion molecules docked against 6 structural targets from SARS-CoV2, representing 5 unique proteins: MPro, NSP15, PLPro, RDRP, and the Spike protein. Docking was carried out using the AutoDock-GPU platform on the Summit supercomputer and Google Cloud. The docking procedure employed the Solis Wets search method to generate 20 independent ligand binding poses per compound. Each compound geometry was scored using the AutoDock free energy estimate, and rescored using RFScore v3 and DUD-E machine-learned rescoring models. Input protein structures are included, suitable for use by AutoDock-GPU and other docking programs. As the result of an exceptionally large docking campaign, this dataset represents a valuable resource for discovering trends across small molecule and protein binding sites, training AI models, and comparing to inhibitor compounds targeting SARS-CoV-2. The work also gives an example of how to organize and process data from ultra-large docking screens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

New high-throughput endstation to accelerate the experimental optimization pipeline for synchrotron X-ray footprinting

Synchrotron X-ray footprinting (XF) is a growing structural biology technique that leverages radiation-induced chemical modifications via X-ray radiolysis of water to produce hydroxyl radicals that probe changes in macromolecular structure and dynamics in solution states of interest. The X-ray Footprinting of Biological Materials (XFP) beamline at the National Synchrotron Light Source II provides the structural biology community with access to instrumentation and expert support in the XF method, and is also a platform for development of new technological capabilities in this field. Hee, the design and implementation of a new high-throughput endstation device based around use of a 96-well PCR plate form factor and supporting diagnostic instrumentation for synchrotron XF is described. This development enables a pipeline for rapid comprehensive screening of the influence of sample chemistry on hydroxyl radical dose using a convenient fluorescent assay, illustrated here with a study of 26 organic compounds. The new high-throughput endstation device and sample evaluation pipeline now available at the XFP beamline provide the worldwide structural biology community with a robust resource for carrying out well optimized synchrotron XF studies of challenging biological systems with complex sample compositions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗