Editor’s note: To read more about how UChicago is on the frontlines of the coronavirus pandemic, visit the Confronting COVID-19 website.
As COVID-19 makes its way around the world, scientists are working around the clock to analyze the virus to find new treatments and cures and predict how it will propagate through the population.
Some of their most powerful tools are supercomputers and particle accelerators, including those at Argonne National Laboratory, a U.S. Department of Energy laboratory affiliated with the University of Chicago.
X-rays for the cure
To make drugs that work against COVID-19, we first need to find a biochemical “key”—an inhibitor molecule that will nestle perfectly into the nooks and crannies of one or more of the 28 proteins that make up the virus. While researchers have already sequenced the genes of the virus, they also need to know what the shape of each protein looks like when it is fully assembled.
This requires a technique called macromolecular X-ray crystallography, in which scientists grow tiny crystals and then illuminate them in an incredibly high-energy X-ray beam to get a snapshot of its physical structure. Such X-ray beams exist only at a few specialized sites around the world, and one of them is Argonne’s Advanced Photon Source.
By mid-March, researchers from around the country had used the Advanced Photon Source to characterize roughly a dozen proteins from SARS-CoV-2. They even managed to catch glimpses of several of them with potential inhibitor molecules “in action.”
“The fortunate thing is that we have a bit of a head start,” said Bob Fischetti, who heads the Advanced Photon Source’s efforts in life sciences. “This virus is similar but not identical to the SARS outbreak in 2002, and 70 structures of proteins from several different coronaviruses had been acquired using data from APS beamlines prior to the recent outbreak.”
That means researchers have background information on how to express, purify and crystallize these proteins, which makes the structures come more quickly, “right now about a few a week,” he said.
Fischetti compared finding the right inhibitor for a protein to discovering a perfectly sized and shaped Lego brick that would snap perfectly into place. “These viral proteins are like big sticky balls—we call them globular proteins,” he said. “But they have pockets or crevices inside of them where inhibitors might bind.”
By using the X-rays, scientists can gain an atomic-level view of the recesses of a viral protein and see which possible inhibitors—either pre-existing or yet-to-be-developed—might reside best in the pockets of different proteins.
The difficulty with pre-existing inhibitors is that they tend to bind only weakly to COVID-19 proteins, which might mean extremely high doses that could cause complications in patients. According to Fischetti, the research teams are looking for an inhibitor that would have a much stronger affinity, enabling it to be administered as a drug that would have many fewer or no side effects.
Fischetti said the rapid pace of collaborative science with one common essential goal is unlike anything else he has seen in his career. “Everything is just moving so incredibly fast, and there are so many moving pieces that it’s hard to keep up with,” he said.
Computing the COVID-19 crisis
Supercomputers can play a role in searching for inhibitors, too. As part of the COVID-19 High Performance Computing Consortium, researchers at Argonne and the University of Chicago are joining forces with researchers from government, academia and industry in an effort that combines the power of 16 different supercomputing systems.