Chemistry Researchers Apply Their Expertise to COVID-19

Treatments Needed

One challenge is to develop an effective treatment for COVID-19.—the aim of one collaborative effort by Professors Charlie Brooks, Anna Mapp, Corey Stephenson, Matt Soellner and their groups.

The central focus of this project is a relatively obscure human protein, TMPRSS2. This protein had no known function in the body but, last year, researchers demonstrated that it helps the SARS-CoV-2 virus to infiltrate healthy cells. During a Brooks group journal club meeting last spring, graduate student Amanda Peiffer proposed studying TMPRSS2 because, if it were deactivated by a drug, it could prevent SARS-CoV-2 infection without disrupting healthy biological processes.

Fellow graduate student Yujin Wu joined Peiffer to computationally model the 3D structure of TMPRSS2 and to study how its structure would change when exposed to 3D models of known drug molecules. By studying these structural changes in virtual, 3D space, Wu could screen thousands of known drug molecules in a relatively short time and identify which ones would likely deactivate TMPRSS2. The most promising drug candidates from the computational screen were then chosen for laboratory testing.

Peiffer, who is co-advised by Professor Anna Mapp, also recruited graduate student Julie Garlick to help evaluate promising drug candidates in the laboratory. To test for TMPRSS2 deactivation, they first needed to make and purify TMPRSS2, which was a different type of protein than they were used to working with. Garlick then developed an assay, which is a solution that would fluoresce, or light up, when active TMPRSS2 was present. If a given drug caused a decrease in fluorescence that would indicate successful TMPRSS2 deactivation.

These combined computational and experimental efforts have led the team to identify several drugs with potential to treat COVID-19., “It was this thing that we had dreamt of back in April and there really wasn’t a lot of literature on this protein Peiffer recalls. “Looking back a year later there is a lot out there. And I think that’s been one of the really exciting things, seeing our initial hunch was right!”

For Brooks, the new project was an exciting opportunity to refine his group’s computational expertise while addressing an urgent problem. “Every time there is a challenge that comes up like this, it can force you to really test and mature the methods that you’re developing in the group. I saw this as an opportunity to accelerate a lot of development that may have gone more slowly if it wasn’t directed to a specific aim.”

Rapid Screening for Immunity, Vaccine Effectiveness

Professor Ryan Bailey’s group is addressing a second key challenge -- a lack of knowledge about long-term immunity to COVID-19. Immunity can vary across individuals and whether they obtained immunity from a vaccine or from the virus itself. This uncertainty poses a challenge for determining public health guidelines like how often vaccines or potential booster shots might be needed.

Last spring, Bailey’s research on latent tuberculosis with collaborators at the Mayo Clinic came to a halt. At the same time, the Mayo Clinic began banking convalescent plasma samples from patients who had recovered from COVID-19 to use as a treatment for sick patients. Bailey, along with recent PhD graduate Cole Chapman and current graduate student Krista Meserve, saw the opportunity to use immune cells from these samples along with their expertise in diagnostics technologies to understand how natural immunity develops in response to COVID-19.

Immune system cells respond to pathogenic threats by producing molecules that act as signals for other cells in the body. The Bailey group hopes to use these signaling molecules as biomarkers of immunity in the body. By comparing biomarkers produced in cells from patients who fully recovered from COVID-19 to biomarkers produced in cells from patients who never had COVID-19, Bailey and his team aim to determine which biomarkers indicate strong immunity

“It’s two-fold: It’s a fundamental study to understand which biomarkers indicate robust response and sustained immunity against SARS-CoV-2,” Bailey explains, and “if we can find biomarkers that are suggestive of a robust native immunity, then we can track patients post-immunization and see whether they have developed that same level of immunity.”

Bailey and his team measure immune response in patient samples using tiny chips with arrays of silicon photonic sensors on them to detect certain biomarkers. To do this, they expose the chips to patient samples and laser light. When certain biomarkers are present, the way that the laser light interacts with the sensors changes. Bailey and his team then use statistical methods to correlate these changes in light with the quantity of a particular biomarker present in a sample.

This sensor technology allows them to simultaneously test for many biomarkers in a fraction of the time needed for traditional testing. Bailey explains, “There is immense value in performing many separate assays at once, and quickly.”

Although their work is ongoing, Bailey and his team have started to correlate certain biomarkers to cells from recovered COVID-19 patients that are not produced by cells from healthy patients. They hope this work will allow healthcare providers and public health officials to assess vaccine effectiveness and the longevity of COVID-19 immunity.