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Researchers Use AI to Fight Coronavirus

circuit board with COVID molecule and eye-shaped traces, illustration

Researchers used an AI model to understand the molecular mechanisms underlying SARS-CoV-2 transmission and evolution.

Credit: U.S. Embassy in Georgia

Michigan State University researcher Guowei Wei and his team used an artificial intelligence model to find answers about the COVID-19 omicron variant. The researchers report omicron and other variants are evolving increased infectivity and antibody resistance according to the AI model.

The researchers analyzed almost 1.5 million SARS-CoV-2 genome sequences taken from people with COVID-19, and identified 683 unique mutations in the region of the SARS-CoV-2 spike protein that attaches to the human ACE2 receptor on the surface of human cells for virus cell entry. Then, they used an AI model to predict how these mutations affect the binding strength of spike protein and ACE2 as well as spike protein and 130 antibodies that created from prior infection or vaccination.

"With this AI model we can predict how infectious each variant is, how often vaccinated individuals become infected when exposed to the virus, and how well vaccines protect against new variants without using extra experimental data," Wei says.

From MSU Today
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