Understanding the Mutations of SARS-CoV-2
Research from the lab of Jana Shen looks at a mutation causing diminished effectiveness of Paxlovid.
By Andrew Tie
January 11, 2024
Featured image: Joseph Clayton and Jana Shen.
A research team in the Department of Pharmaceutical Sciences (PSC) at the University of Maryland School of Pharmacy (UMSOP) is investigating the science behind SARS-CoV-2, the virus that causes COVID-19, and therapeutics to treat it.
A new publication in the Journal of Chemical Information and Modeling, led by Jana Shen, PhD, professor of PSC and co-director of the Computer-Aided Drug Design Center, looks at nirmatrelvir, better known by its trade name Paxlovid, an antiviral drug approved by the US Food and Drug Administration (FDA) to treat mild-to-moderate COVID-19.
“There has been an incredible amount of research in the last few years to understand COVID-19 and how to treat it,” Shen said. “In order to optimize the therapeutics for this constantly evolving disease, we have to understand the basic science behind it and how drugs interact with the disease.”
Joseph Clayton, PhD, now an ORISE fellow with the FDA, and Vinicius Martins de Oliveira, PhD, now a postdoctoral fellow at Eli Lilly and Company, also collaborated on the research as part of the Shen Lab.
Paxlovid works by inhibiting the main protease (Mpro), an enzyme that helps in protein production, of SARS-CoV-2. Studies have found a rare mutation of Mpro significantly reduced the effectiveness of Paxlovid, and the Shen-led team sought to understand why.
Clayton and Martins de Oliveira started by creating the computational models of the mutant and regular Mpro bound to Paxlovid that allowed them to investigate Mpro on an atomistic level.
“In a way, our approach in using computational models acts as a powerful microscope where we can both verify results found in experimental labs and reveal details down to individual atoms,” Clayton said.
The researchers conducted molecular dynamic simulations to see the various configurations Mpro could adopt, both in the mutant and regular forms. Next, the Shen lab fed this data into an artificial neural network to detect changes between mutant and regular Mpro. The mutant Mpro showed subtle but consistent changes in an important region called the oxyanion loop that is targeted by nirmatrelvir, which is what the Shen lab believes leads to the decreased effectiveness of the drug.
“This approach leveraging our expertise in computer-aided drug design and simulating different mutations of Mpro provides incredible insight into those interactions,” Shen said. “Ultimately we think this research will help drugmakers in understanding how to best design Paxlovid for the current mutations in the virus and could serve as a model for investigating mutation effects on other protein drug targets.”
This work was completed in collaboration with Rolf Hilgenfeld’s group at the University of Lübeck, Germany. Their experimental findings revealed the mutation destabilizes Paxlovid, confirming the Shen lab hypothesis.
The computational work was supported by NIH grants R01GM098818 and R01CA256557, while the experimental work was supported by the German Center for Infection Research (project FF01.905).