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Shown here is the structure of the NEMO protein. A team from ORNL conducted extensive molecular dynamics work on Summit by using both quantum mechanics and machine-learning methods to look at the binding affinity of NEMO and 3CLpro in humans and other species and to consider the structural models derived from the sequences of other coronaviruses. Image courtesy Nature Communications, Dan Jacobson/ORNL.

A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.

The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines

ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.

An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy

To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.

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.

ORNL’s collaboration with Cincinati Children’s Hospital Medical Center will leverage the lab’s expertise in high-performance computing and safe, secure recordkeeping. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy

There are more than 17 million veterans in the United States, and approximately half rely on the Department of Veterans Affairs for their healthcare.

Computational biophysicist Ada Sedova is using experiments and high-performance computing to explore the properties of biological systems and predict their form and function, including research to accelerate drug discovery for COVID-19. Photo credit: Jason Richards, Oak Ridge National Laboratory, U.S. Dept. of Energy.

Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology

Omar Demerdash

With the rise of the global pandemic, Omar Demerdash, a Liane B. Russell Distinguished Staff Fellow at ORNL since 2018, has become laser-focused on potential avenues to COVID-19 therapies.

XACC enables the programming of quantum code alongside standard classical code and integrates quantum computers from a number of vendors. This animation illustrates how QPUs complete calculations and return results to the host CPU, a process that could drastically accelerate future scientific simulations. Credit: Michelle Lehman/Oak Ridge National Laboratory, U.S. Dept. of Energy

In the early 2000s, high-performance computing experts repurposed GPUs — common video game console components used to speed up image rendering and other time-consuming tasks 

Coronavirus graphic

In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.

The image visualizes how the team’s multitask convolutional neural network classifies primary cancer sites. Image credit: Hong-Jun Yoon/ORNL

As the second-leading cause of death in the United States, cancer is a public health crisis that afflicts nearly one in two people during their lifetime.