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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The future of legume genetic data resources: Challenges, opportunities, and priorities

Abstract Legumes, comprising one of the largest, most diverse, and most economically important plant families, are the subject of vibrant research and development worldwide. Continued improvement of legume crops will benefit from the recent proliferation of genetic (including genomic) resources; but the diversity, scale, and complexity of these resources presents challenges to those managing and using them. A workshop held in March of 2019 addressed questions of data resources and priorities for the legumes. The workshop identified various needs and recommendations: (a) Develop strategies to effectively store, integrate, and relate genetic resources collected in different projects. (b) Leverage information collected across many legume species by standardizing data formats and ontologies, improving the state of metadata about datasets, and increasing use of the FAIR data principles. (c) Advocate for the critical role that curators exercise in integrating complex datasets into databases and adding high value metadata that enable downstream analytics and facilitate practical applications. (d) Implement standardized software and database development practices to best leverage limited developer time and expertise gained from the various legume (and other) species. (e) Develop tools and databases that can manage genetic information for the world's plant genetic resources, enabling efficient incorporation of important traits into breeding programs. (f) Centralize information on databases, tools, and training materials and establish funding streams to support training and outreach.

Bauchet, Guillaume J.↗
DOE OSTI2014

Proteogenomic strategies for identification of aberrant cancer peptides using large-scale Next Generation Sequencing data

Cancer is driven by the acquisition of somatic DNA lesions. Distinguishing the early driver mutations from subsequent passenger mutations is key to molecular sub-typing of cancers, and the discovery of novel biomarkers. The availability of genomics technologies (mainly wholegenome and exome sequencing, and transcript sampling via RNA-seq, collectively referred to as NGS) have fueled recent studies on somatic mutation discovery. However, the vision is challenged by the complexity, redundancy, and errors in genomic data, and the difficulty of investigating the proteome using only genomic approaches. Recently, combination of proteomic and genomic technologies are increasingly employed. However, the complexity and redundancy of NGS data remains a challenge for proteogenomics, and various trade-offs must be made to allow for the searches to take place. This paperprovides a discussion of two such trade-offs, relating to large database search, and FDR calculations, and their implication to cancer proteogenomics. Moreover, it extends and develops the idea of a unified genomic variant database that can be searched by any mass spectrometry sample. A total of 879 BAM files downloaded from TCGA repository were used to create a 4.34 GB unified FASTA database which contained 2,787,062 novel splice junctions, 38,464 deletions, 1105 insertions, and 182,302 substitutions. Proteomic data from a single ovarian carcinoma sample (439,858 spectra) was searched against the database. By applying the most conservative FDR measure, we have identified 524 novel peptides and 65,578 known peptides at 1% FDR threshold. The novel peptides include interesting examples of doubly mutated peptides, frame-shifts, and non-sample-recruited mutations, which emphasize the strength of our approach.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Rapid sample classification using an open port sampling interface coupled with liquid introduction atmospheric pressure ionization mass spectrometry

An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized the spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Experimental cross sections for L-shell x-ray production and ionization by protons

Tables of compiled cross sections list data for production of individual line and total L x-rays as well as for ionization of L subshells and the total L shell. The present cumulative compilation covers some six decades of measurements on targets from {sub 10}Ne to {sub 95}Am bombarded by protons ranging from 10 keV to 1 GeV. It includes data published in the period 1954–1992 from tables published in this journal, cross sections that were not reported in those tables, and new data from works published after 1992. Existing empirical, semiempirical, and theoretical analyses based on, and relative to, the pre-1993 database are reviewed. The experimental details are summarized for pre-1993 articles that were not referenced in previous compilations and, continuing the practice of these compilations, for each new publication. Covering the period 1954–December 2012, the present tabulation collects (not counting 2519 new data for L{sub β1,3,4}, L{sub β2,15},L{sub γ1}, L{sub γ2,3}, and L{sub γ4,4{sup ′}} x ray production) circa 15 500 experimental cross sections and enlarges the database from the previously published tables by 94%. -- Highlights: •An updated database is presented, increasing by 94% the earlier pre-1993 database. •The update has 40% more data from the pre-1993 period, absent in prior compilations. •The growth and possible saturation in the number of data is illustrated. •Ionization cross sections are reconverted to x-ray production cross sections. •Elements and ion energies are identified where measurements are still necessary.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Thermodynamic description of the Ti-Mo-Nb-Ta-Zr system and its implications for phase stability of Ti bio-implant materials

Titanium alloys are great candidates for applications such as biomedical implants that require biocompatibility, a low Young's modulus and a high strength. However, the properties of Ti alloys are highly dependent on phase stability. Here in the present work, a database for the Ti-Mo-Nb-Ta-Zr system has been evaluated using the CALPHAD (CALculation of PHAse Diagram) approach. The database was completed by evaluating the accuracy of previously modeled systems from literature and modeling systems that, to the best of the authors’ knowledge, had no modeling available in literature. All of the binary systems that make up the Ti-Mo-Nb-Ta-Zr system had previously modeled thermodynamic descriptions available in the literature and in most cases had multiple different descriptions available, which meant determining which previous thermodynamic description most accurately modeled the binary system with a direct focus on the bcc phase. In order to determine the accuracy of the multiple available thermodynamic descriptions from literature a combination of experimental data (also obtained from the literature) and computed thermochemical properties of the bcc phase from DFT (Density Functional Theory)-based first-principles calculations (present work) were used. Once the thermodynamic descriptions for the binary systems were chosen, focus shifted to the Ti-containing ternary systems. The Ti-Mo-Zr, Ti-Nb-Zr and Ti-Ta-Zr systems had previous thermodynamic description available in literature, which were incorporated without changes into the working database. The Ti-Mo-Ta, Ti-Nb-Ta and Ti-Mo-Nb systems had, to the authors’ knowledge, no descriptions available in the literature. Interaction parameters were determined for the Ti-Mo-Ta and Ti-Nb-Ta systems, and no interaction parameters were introduced for the Ti-Mo-Nb system. The database introduced by this work satisfactorily predicts the thermodynamics of the Ti-Mo-Nb-Ta-Zr system.

CALculation of PHAse Diagrams↗
DOE OSTI2023

Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI

The modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in describing short-range ordering (SRO) in complex liquids such as molten salts, slag in metal processing, and electrolytic solutions. Here, the present work implements the MQMQA into the Python based open-source software PyCalphad for thermodynamic calculations. This endeavor facilitates the development of MQMQA-based thermodynamic database with uncertainty quantification (UQ) and propagation (UP) using the open-source software ESPEI. A new database structure based on Extensible Markup Language (XML) is proposed for ESPEI evaluation of MQMQA model parameters. Using the KF-NiF 2 , KCl-NaCl-MgCl 2 , and CaCl 2 -CaF 2 -LiCl-LiF salt systems as examples, we demonstrate the successful implementation of MQMQA in PyCalphad through thermodynamic calculations of Gibbs energy, equilibrium quadruplet fractions, and phase diagram, as well as database development with UQ and UP using ESPEI. Furthermore, as an application of the present implementation, both the LiF–TbF 3 and LiF-HoF 3 systems have been modeled by MQMQA for the first time, which are in good agreement with experiments. The present implementation hence offers an open-source capability for performing CALPHAD modeling for complex liquids with SRO using MQMQA plus a new XML database structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Full spectrum optical constant interface to the Materials Project

Optical constants characterize the interaction of materials with light and are important properties in material design. Here we present a Python-based Corvus workflow for simulations of full spectrum optical constants from the visible and ultraviolet to hard x-ray wavelengths based on the real-space Green’s function code FEFF10 and structural data from the Materials Project (MP). The Corvus workflow manager and its associated tools provide an interface to FEFF10 and the MP database. The workflow parallelizes the FEFF computations of optical constants over all absorption edges for each material in the MP database specified by a unique MP-ID. The workflow tools determine the distribution of computational resources needed for that case. Similarly, the optical constants for selected sets of materials can be computed in a single-shot. Additionally, to illustrate the approach, we present results for several elemental solids in the periodic table, as well as a sample compound, and compare our predictions with experimental results. In addition, we provide a database of calculated results for all elements for which there is a stable elemental solid at standard conditions available in the Materials Project database. As in x-ray absorption spectra, these results are interpreted in terms of an atomic-like background and fine-structure contributions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Chemical thermodynamic data. 1. The concept of links to the chemical elements and the historical development of key thermodynamic data [plus Supplementary Electronic Annex 2]

Chemical thermodynamic data remain a keystone for geochemical modeling and reactive transport simulation as applied to an increasing number of applications in the earth sciences, as well as applications in other areas including metallurgy, material science, and industrial process design. The last century has seen the development of a large body of thermodynamic data and a number of major compilations. The past several decades have seen the development of thermodynamic databases in digital form designed to support computer calculations. However, problems with thermodynamic data appear to be persistent. One problem pertains to the use of inconsistent primary key reference data. Such data pertain to elemental reference forms and key, stoichiometrically simple chemical species including metal oxides, CO 2 , water, and aqueous species such as Na + and Cl - . A consistent set of primary key data (standard Gibbs energies, standard enthalpies, and standard entropies for key chemical species) for 298.15K and 1 bar pressure is essential. Thermochemical convention is to define the standard Gibbs energy and the standard enthalpy of an individual chemical species in terms of formation from reference forms of the constituent chemical elements. We propose a formal concept of “links” to the elemental reference forms. This concept involves a documented understanding of all reactions and calculations leading to values for a formation property (standard Gibbs energy or enthalpy). A valid link consists of two parts: (a) the path of reactions and corrections and (b) the associated data, which are key data. Such a link differs from a bare “key” or “reference” datum in that it requires additional information. Some or all of its associated data may also be key data. In evaluating a reported thermodynamic datum, one should identify the links to the chemical elements, a process which can be time-consuming and which may lead to a dead end (an incomplete link). The use of two or more inconsistent links to the same elemental reference form in a thermodynamic database will result in an inconsistency in the database. Thus, in constructing a database, it is important to establish a set of reliable links (generally resulting in a set of primary reference data) and then correct all data adopted subsequently for consistency with that set. Recommended values of key data have not been constant through history. We review some of this history through the lens of major compilations and other influential reports, and note a number of problem areas. Finally, we illustrate the concepts developed in this paper by applying them to some key species of geochemical interest, including liquid water; quartz and aqueous silica; and gibbsite, corundum, and the aqueous aluminum ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Global reconstructed daily surge levels from the 20th Century Reanalysis (1871–2010)

Studying the effect of global patterns of wind and pressure gradients on the sea level variation (storm surge) is a key issue in understanding the recent climate change effect on the dynamical state of the ocean. The analysis of the spatial and temporal variability of storm surges from observations is a difficult task to accomplish since observations are not homogeneous in time, scarce in space, and moreover, their temporal coverage is limited. A recent global surge database developed by AVISO (DAC, Dynamic Atmospheric Correction) fulfilled the lack of data in terms of spatial coverage, but not regarding time extent, since it only includes the last two decades (1992–2014). In this work, we use the 20th Century Reanalysis V2 (20CR), which spans the years 1871 to 2010, to statistically reconstruct daily maximum surge levels at a global scale. A multivariate linear regression model is fitted between daily mean ERA-interim sea level pressure fields and daily maximum surge levels from DAC. Following, the statistical model is used to reconstruct daily surges using mean sea level pressure fields from 20CR. The verification of the statistical model shows good agreements between DAC levels and the reconstructed surge levels from the 20CR. The validation of the reconstructed surge with tide gauges, distributed throughout the domain, shows good accuracy both in terms of high correlations and small errors. A time series comparison is also depicted at specific tide gauges for the beginning of the 20th century, showing a high concordance. Therefore, this work provides to the scientific community, a daily database of maximum surge levels; which correspond to an extension of the DAC database, from 1871 to 2010. This database can be used to improve the knowledge on historical storm surge conditions, allowing the study of their temporal and spatial variability.

Geology↗
DOE OSTI2020

Online multimedia retrieval on CPU–GPU platforms with adaptive work partition

Nearest neighbors search is a core operation found in several online multimedia services. These services have to handle very large databases, while, at the same time, they must minimize the query response times observed by users. This is specially complex because those services deal with fluctuating query workloads (rates). Consequently, they must adapt at run-time to minimize the response times as the load varies. In this paper, we address the aforementioned challenges with a distributed memory parallelization of the product quantization nearest neighbor search, also known as IVFADC, for hybrid CPU–GPU machines. Overall, our parallel IVFADC implements an out-of-GPU memory execution scheme to use the GPU for databases in which the index does not fit in its memory, which is crucial for searching in very large databases. The careful use of CPU and GPU with work stealing led to an average response time reduction of 2.4 as compared to using the GPU only. Also, our approach to adapt the system to fluctuating loads, called Dynamic Query Processing Policy (DQPP), attained a response time reduction of up to 5 vs. the best static (BS) policy for moderate loads. The system has attained high query processing rates and near-linear scalability in all experiments. We have evaluated our system on a machine with up to 256 NVIDIA V100 GPUs processing a database of 256 billion SIFT features vectors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) organizes cooperation between the major nuclear data evaluation projects in the world. The NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established to promote the exchange of information on nuclear data evaluation, measurement, nuclear model calculation, validation, and related topics, and to provide a framework for cooperative activities between the participating projects. The working party assesses nuclear data improvement needs and addresses these needs by initiating joint activities in the framework of dedicated WPEC subgroups. Studies recently completed comprise a number of works related to nuclear data covariance and associated processing issues, as well as more specific studies related to the resonance parameter representation in the unresolved resonance region, the gamma production from fission product capture reactions, the {sup 235}U capture cross section, the EXFOR database, and the improvement of nuclear data for advanced reactor systems. Ongoing activities focus on the evaluation of {sup 239}Pu in the resonance region, scattering angular distribution in the fast energy range, and reporting/usage of experimental data for evaluation in the resolved resonance region. New activities include two subgroups on improved fission product yield evaluation methodologies and on modern nuclear database structures. Future activities under discussion include a pilot project for a Collaborative International Evaluated Library Organization (CIELO) and methods to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data. In addition to the above mentioned short-term task-oriented subgroups, WPEC also hosts a longer-term subgroup charged with reviewing and compiling the most important nuclear data requirements in a high priority request list (HPRL)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Improved Cumulative Fission Yield Measurements with Fission Spectrum Neutrons on 235 U

Two isotopically-characterized targets of high-purity (99.84±0.03%) 235 U-oxide and a neutron dosimetry package were exposed to a pulsed neutron irradiation using the Godiva critical assembly at the National Criticality Experiments Research Center. Following irradiation, the fissioned targets were counted with a broad-energy germanium detector. Estimates of the total fissions for each target were made using measurements of well-known fission products. The total fission values were then used to measure the fission yields of 21 fission products with half-lives between 636 and 119,700 seconds. Mean values of seventeen of the measured fission products fell within the 95% confidence level of the Evaluated Nuclear Data Files VII.1/b (ENDF/B-VII.1) using the larger of the two uncertainties: 84g Br, 89 Rb, 91 Sr, 93 Y, 97 Zr, 101 Mo, 105 Ru, 128 Sn, 129 Sb, 130g Sb, 131 Sb, 131m Te, 133 I, 135 I, 141 Ba, 142 Ba, and 142 La. Seven isotopes were measured to better precision than is listed in the ENDF/B-VII.1 database: 89 Rb, 93 Y, 128 Sn, 129 Sb, 130g Sb, 131m Te, and 133 I. Four of the measured isotopes were found to be statistically different from the ENDF/B-VII.1 database: 94 Y, 134 Te, 134 I, and 138 Xe. Two of the isotopic analyses conducted in this paper fit the parent and daughter data simultaneously. The parent-daughter pairs measured in this way were the 134 Te/I and 142 Ba/La pairs. The fission yield results obtained in this way are unique, especially for 134 I, because the parent and daughter half-lives are so close. Here, given the limited number of direct measurements of the 134 Te/I pair from fast neutron induced fission and the seemingly high estimate for 134 Te from previous work, it is likely that the value in this paper is more accurate; however, additional measurements of this pair are needed to validate this assertion.

42 ENGINEERING↗
DOE OSTI2019

Surface albedo and reflectance: Review of definitions, angular and spectral effects, and intercomparison of major data sources in support of advanced solar irradiance modeling over the Americas

This study defines albedo and reflectance in the context of solar applications. It examines the main sources of surface albedo data that can be used to help solar irradiance modeling efforts, such as undertaken by the National Renewable Energy Laboratory (NREL) over the Americas, for instance, per the National Solar Radiation Database (NSRDB). The MODIS-based albedo database, as used as input to derive historical time series of solar irradiance in the current version of the NSRDB, is compared to other sources of global gridded data over the Americas in general and some specific areas in particular. The particular role of snow cover is analyzed. It is found that, in the current MODIS-based NSRDB implementation, snow-impacted areas have been assigned a too high albedo in general because of the lack of consideration for the antagonistic effect of surface roughness, among other factors. Other albedo databases, such as CMSAF, MINES-ParisTech or the ERA5 reanalysis, do not display such high albedos at latitudes above ~40 degrees N. The gap-free and snow-free MODIS MCD43GF product is found affected by a long-term downward trend over some areas and out-of-phase seasonal effects over other areas, in comparison with MERRA-2 reanalysis data in particular. Comparisons with actual albedo measurements at the arid Desert Rock site in Nevada also show that albedo data derived from land surface models are affected by systematic bias. Five albedo databases are intercompared for the area around Ivanpah Playa, California, which has great importance in both remote sensing and solar applications. Various aspects of the proper usage of albedo data in solar radiation modeling are discussed, regarding calculations of both the backscattering process and reflections on a tilted surface: spatial resolution, temporal resolution, angular effects, and spectral effects. An important distinction is made between the use of albedo data at ~4 km resolution for backscattering calculations and at ~10 m resolution for transposition calculations to tilted planes, which might additionally require spectral information for monofacial or bifacial PV applications. It is shown that the tilted calculations usually performed in solar resource assessments are far from realistic in the case of most large-scale PV applications, for which a more suitable methodological approach is described. For such needs, the limitations of the current sources of high-resolution reflectance data are discussed. The impact of surface albedo estimation errors on the estimation of backscattered irradiance over snowy areas is evaluated. It is found non-negligible, and even large under cloudy conditions.

14 SOLAR ENERGY↗
DOE OSTI2024

Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics

The importance of data curation has been recognized in multiple areas of research; however, the discussion of this important issue is only beginning to emerge in materials science. In this Perspective, we highlight the benefits of using the standardized data curation protocols in materials science and discuss current gaps in accurate and reproducible data reporting using case studies drawn from high-impact materials science papers and well-known databases such as the Crystallography Open Database (COD) and the Cambridge Structural Database (CSD). We argue that both experimental and computational materials scientists need to embrace a culture of rigorous data curation as part of modern research data management. We propose a sample data curation pipeline for materials chemistry and illustrate its use by creating two new materials chemistry databases. Here, we hope that this perspective will serve to catalyze further discussion and promote the continuous development of rigorous data curation practices within the materials science research community. We posit that adherence to best practices of data curation will promote and enhance the reliability, reproducibility, and integrity of materials research and enable the development of reliable AI and machine learning models that critically depend on the use of quality data.

Chemical structure↗
DOE OSTI2026

First-Principles Evaluation of Proton Hopping in Tetrahedral Oxide Motifs

Proton-conducting oxides (PCOs) are important materials used as ionic conductors for energy conversion technologies. Existing research efforts on PCO optimization and discovery generally focus on complex perovskite-based oxides that require doping and alloying to engineer oxygen deficiency and high proton conductivity. However, the variety of chemical compositions and coordination environments in oxides poses challenges for efficient materials design. In this computational study, we construct a database of simplified motifs to elucidate the relationship between fundamental materials chemistry and proton kinetics. Specifically, we focus on the zincblende crystal structure as a proxy for tetrahedral metal–oxide (M–O) coordination environments. We systematically quantified the effects of cation type, oxidation states, and M–O bond lengths on the proton hopping barrier, and found that strong M–O bonds and metal cations with large and variable oxidation states (e.g., Mo 6+ , V 5+ ) lead to smaller proton hopping barriers. By mapping the candidate cations and their preferred bond geometries onto materials databases such as the Inorganic Crystal Structure Database (ICSD) and Materials Project, we identified real materials containing the corresponding metal–oxide units. In general, we observed good agreement between the calculated proton hopping barriers obtained in real crystal structures and those predicted by our motif database. We also discuss the limitations of our model and possible future extensions to improve its predictive capabilities. Overall, our model provides a first step for the rational design and quick screening of energy-efficient PCOs.

organic↗
DOE OSTI2020

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

In this work, we present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

60 APPLIED LIFE SCIENCES↗