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A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.

Neutron scattering experiments show electric charges, shown in red, blue and grey, in the SARS-CoV-2 main protease site where telaprevir binds to the structure. The experiments provide critical data for the design of small-molecule drugs to treat COVID-19. Credit: Jill Hemman and Michelle Lehman/ORNL, U.S. Dept. of Energy

Scientists have found new, unexpected behaviors when SARS-CoV-2 – the virus that causes COVID-19 – encounters drugs known as inhibitors, which bind to certain components of the virus and block its ability to reproduce.  

Distinguished Inventors

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

Paul Kent, shown above posing with Summit in April 2018, received the 2020 ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy

The annual Director's Awards recognized four individuals and teams including awards for leadership in quantum simulation development and application on high-performance computing platforms, and revolutionary advancements in the area of microbial

An organic solvent and water separate and form nanoclusters on the hydrophobic and hydrophilic sections of plant material, driving the efficient deconstruction of biomass. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

Experiments led by researchers at ORNL have determined that several hepatitis C drugs can inhibit the SARS-CoV-2 main protease, a crucial protein enzyme that enables the novel coronavirus to reproduce.

coronavirus

NellOne Therapeutics has licensed a drug delivery system from the Department of Energy’s Oak Ridge National Laboratory that is designed to transport therapeutics directly to cells infected by SARS-CoV-2, the virus causing COVID-19.

The first neutron structure of the SARS-CoV-2 main protease enzyme revealed unexpected electrical charges in the amino acids cysteine (negative) and histidine (positive), providing key data about the virus’s replication. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

To better understand how the novel coronavirus behaves and how it can be stopped, scientists have completed a three-dimensional map that reveals the location of every atom in an enzyme molecule critical to SARS-CoV-2 reproduction.

Analyses of lung fluid cells from COVID-19 patients conducted on the nation’s fastest supercomputer point to gene expression patterns that may explain the runaway symptoms produced by the body’s response to SARS-CoV-2. Credit: Jason B. Smith/ORNL, U.S. Dept. of Energy

A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.