University of New Orleans chemistry professor Steve Rick and computer science professor Chris Summa are part of a global research consortium studying ways to inhibit the virus that causes COVID-19.
The COVID-19 High Performance Computing Consortium is a private-public funding initiative, spearheaded by the White House Office of Science and Technology Policy, the U.S. Department of Energy and IBM to bring together federal government, industry, and academic leaders, to accelerate research for fighting the novel coronavirus.
Rick and Summa’s research is on the viral protein helicase, a promising target against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19.
The virus needs the helicase protein in order to replicate and grow inside the body. If researchers can design a drug to attach to that protein, it could inhibit the virus’ growth. However, because of the helicase’s highly flexible nature, designing a drug to fit is difficult since you may not really know the structure to target.
Rick and Summa’s research seeks to understand how the helicase protein moves and changes structure.
“From the three-dimensional structure of a protein, inhibitors can be designed to hinder replication of a virus, but the flexibility of helicase makes it a challenge for structural-based drug design,” Rick said. “We will use high performance computing, on some of the fastest computers in the world, to gain a better understanding of the flexibility of helicase.”
The UNO researchers have been granted use of a super computer—aptly named Comet—at the San Diego Supercomputing Center.
“We are running dynamics of the helicase, a fairly large protein, so we can follow how it moves,” Rick said. “The simulations allow us to see how all the atoms move. We can do that with and without a potential drug bound to it.”
Those computer simulations will be aided by an enhanced sampling method developed at the University of New Orleans that allows researchers to determine structural changes more quickly. The structures that result will be clustered into different structural groups and shared with the scientific community, so that they can be used for drug design.
“By studying how it moves, we can figure out what shapes or conformations it’s most likely to be in, which we will share with other scientists who are experts in drug design,” said Summa.