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Rogers, David

Publications and source records attributed to Rogers, David.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 2 (Lowest Temperature Extracted Protein Coordinate Trajectories)

Protein-only trajectories of the lowest-temperature window (310K) extracted from temperature replica-exchange molecular dynamics simulations of 23 different SARS CoV-2 systems, including S Protein ACE2-receptor binding-domain, MPro, PLPro, NSP3 ADRP (X-domain/macrodomain/phosphatase), NSP15 (endoribonuclease), NSP9, NSP10, NSP16, and N-protein N-terminus. Systems were prepared with charmm-gui and simulated using the GROMACS simulation software suite. Trajectories are provided in compressed dcd format with accompanying coordinate/topology files in pdb and psf formats. This data supplements the data release, DOI: 10.13139/OLCF/1650650 ('SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 1 (Simulation Initial Conditions and Parameters)')

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 3 (Raw Temperature Replica Exchange Molecular Dynamics Trajectories)

Raw temperature replica-exchange molecular dyanmics trajectories of 23 different SARS CoV-2 Systems including S Protein ACE2-receptor binding-domain, MPro, PLPro, NSP3 ADRP (X-domain/macrodomain/phosphatase), NSP15 (endoribonuclease), NSP9, NSP10, NSP16, and N-protein N-terminus. Systems were prepared with charmm-gui and simulated using the GROMACS simulation software suite. Non-demuxed, i.e. discontinuous/constant temperature window, trajectories are provided in compressed GROMACS xtc and full trr formats. This data supplements the data releases DOI: 10.13139/OLCF/160650 'SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 1 (Simulation Initial Conditions and Parameters)' and DOI: 10.13139/OLCF/1657844 'SARS-CoV2 Protein-Ligand Simulation Dataset: Layer 2 (Extracted Protein Coordinate Trajectories)'

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

XVis: Visualization for the Extreme-Scale Scientific Computation Ecosystem (Final Report)

Scientific computing is no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis. This report reviews the accomplishments of the XVis project to prepare scientific visualization for Exascale computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

XVis: Visualization for the Extreme-Scale Scientific Computation Ecosystem. Final Report

Scientific computing is no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/0 limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis. This report reviews the accomplishments of the XVis project to prepare scientific visualization for Exascale computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Optimizing radionuclide sequestration in anion nanotraps with record pertechnetate sorption

The elimination of specific contaminants from high concentrations of competitors poses a significant challenge. Rather than relying on a single direct interaction, the cooperation of multiple functionalities is an emerging strategy for adsorptive materials design to achieve this requisite affinity. Here, we describe that the interaction with the analyte of interest can be altered by modifying the local environment of the direct contact site, as demonstrated by manipulating the affinity of pyridinium-based anion nanotraps toward pertechnetate. Systematic control of the substituent effect allows the resulting anion nanotraps to combine multiple features as ideal pertechnetate scavengers with exceptional performances, substantially overcoming the long-term challenge of TcO 4- segregation under extreme conditions of super acidity and basicity, strong irradiation field, and high ionic strength. The top material exhibits the highest sorption capacity together with unprecedented extraction efficiencies after a single treatment from conditions relevant to the used nuclear fuel (Hanford tank wastes, 95%) and legacy nuclear wastes (Savannah River Sites, 80%) among materials reported thus far.

36 MATERIALS SCIENCE↗
DOE OSTI2019

STDA05-18 P6 Milestone Delivery

The following table provides evidence for each implemented feature with links to the completed merge requests (evidence that the implementation is merged into the master branch) and a link to the excerpt from the VTK-m User's Guide documenting the feature

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Cinema Toolkit

Cinema is a workflow and toolkit for capturing, storing and exploring extreme scale scientific data. It is a highly interactive image-based approach to data analysis and exploration that promotes investigation of large scientific datasets, and is easily integrated into existing workflows through extensions to widely used open source tools. In short, many different images of the dataset are captured and stored in a database, along with metadata describing the images. This provides a method of exploration that is unlike other current methods. This novel approach supports interactive exploration of a wide range of results, while still significantly reducing data movement and storage. The Cinema toolkit includes database specifications and software such as database writers, database viewers, algorithms and other support software that enable a wide variety of applications to write, operate on, and view Cinema databases.

ECP↗
DOE OSTI2017

Framework for Analysis and Visualization of Simulation Data (VizAly)

As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the cosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational data sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing platforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.

Wendelberger, Joanne↗
DOE OSTI2017

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Year-end report FY17.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem: Mid-year report FY17 Q2

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Probing Small-Molecule Degradation to Counter Enzyme Promiscuity

Enzymes that degrade specific small molecules could save lives by neutralizing threats from chemical agents in the blood or environment, or by starving pathogenic cells, but promiscuous interactions with other molecules typically limit their effectiveness by blocking the enzyme active site. An obvious solution would be to re-engineer the enzyme to enhance catalytic fidelity, but lack of understanding about how enzymes discriminate between molecules remains a formidable challenge to this approach. Our recent work in collaboration with the University of Texas (UT) suggested a new approach and a model system for understanding enzyme specificity. Asparaginase enzymes catalyze degradation of asparagine, which forms the basis of a medical treatment. Competition by the abundant and chemically similar molecule, glutamine, interferes with asparagine decomposition, thus hindering enzyme efficacy. Asparaginase is advantageous as a model degradation enzyme because variants that demonstrate different binding affinities and catalytic rates can be compared. Here, we leveraged Sandia and the University of Maryland's strengths in molecular simulation, and UT experimental expertise in asparaginase modification and functional assays, to understand asparaginase specificity. Our results advanced a new hypothesis about asparaginase catalytic mechanism that explains for the first time why proximity between the substrate's alpha-carboxyl and carboxamide is absolutely required for catalysis. Based on those insights, we developed the first mutant (Q59L) asparaginase from E. coli that lacks activity toward glutamine. We used that mutant to show that glutaminase activity is required to kill cancer cells that have asparagine synthetase enzymes (ASNS), but not ASNS-negative cancer cells.

59 BASIC BIOLOGICAL SCIENCES↗