EVEscape Predicts Future Viral Mutations with Accurate Results

Thursday - October 12 2023, 10:50 UTC - 1 year ago

EVEscape is an artificial intelligence tool developed by researchers at Harvard Medical School and the University of Oxford that predicts future variants of concern for SARS-CoV-2 based on a model of evolutionary sequences and detailed biological and structural information about the virus.

The COVID-19 pandemic seemed like a never-ending parade of SARS-CoV-2 variants, each equipped with new ways to evade the immune system, leaving the world bracing for what would come next. But what if there were a way to make predictions about new viral variants before they actually emerge? A new artificial intelligence tool named EVEscape, developed by researchers at Harvard Medical School and the University of Oxford, can do just that. The tool has two elements: A model of evolutionary sequences that predicts changes that can occur to a virus, and detailed biological and structural information about the virus. Together, they allow EVEscape to make predictions about the variants most likely to occur as the virus evolves. In a study published today (October 11) in the journal Nature, the researchers show that had it been deployed at the start of the COVID-19 pandemic, EVEscape would have predicted the most frequent mutations and identified the most concerning variants for SARS-CoV-2. The tool also made accurate predictions about other viruses, including HIV and influenza.

The researchers are now using EVEscape to look ahead at SARS-CoV-2 and predict future variants of concern; every two weeks, they release a ranking of new variants. Eventually, this information could help scientists develop more effective vaccines and therapies. The team is also broadening the work to include more viruses. "We want to know if we can anticipate the variation in viruses and forecast new variants — because if we can, that’s going to be extremely important for designing vaccines and therapies," said senior author Debora Marks, associate professor of systems biology in the Blavatnik Institute at HMS.

The researchers first developed EVE, short for evolutionary model of variant effect, in a different context: gene mutations that cause human diseases. The core of EVE is a generative model that learns to predict the functionality of proteins based on large-scale evolutionary data across species. In a previous study, EVE allowed researchers to discern disease-causing from benign mutations in genes linked to various conditions, including cancers and heart rhythm disorders. "You can use these generative models to learn amazing things from evolutionary information — the data have hidden secrets that you can reveal," Marks said.

As the COVID-19 pandemic hit and progressed, the world was caught off guard by SARS-CoV-2’s impressive ability to evolve. The virus kept morphing, changing its structure in ways subtle and substantial to slip past vaccines and therapies designed to defeat it. "We underestimate the ability of things to mutate when they’re under pressure and have a large population in which to do so," Marks said. "Viruses are flexible — it’s almost like they’ve evolved to evolve." Watching the pandemic unfold, Marks and her team saw an opportunity to help: They rebuilt EVE into a new tool called EVEscape for the purpose of predicting viral variants. They took the generative model from EVE — which can predict mutations in viral proteins, such as the spike protein that gives SARS-CoV-2 its distinctive coronavirus shape — and fused it with detailed biological and structural predictions about the virus.