A new AI tool called EVEscape uses evolutionary and biological information to predict how a virus could change to escape the immune system. 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. Researchers say the tool can help inform the development of vaccines and therapies for SARS-CoV-2 and other rapidly mutating viruses.
This work is published in Nature in the paper, “Learning from prepandemic data to forecast viral escape.”
The researchers first developed EVE (evolutionary model of variant effect) in the context of uncovering 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 implicated in 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,” said Debora Marks, PhD, associate professor of systems biology in the Blavatnik Institute at Harvard Medical School.
During the pandemic, Marks and her team saw an opportunity to apply EVE. They took the generative model from EVE—which can predict mutations in viral proteins that won’t interfere with the virus’s function—and added biological and structural details about the virus, including information about regions most easily targeted by the immune system.
“We’re taking biological information about how the immune system works and layering it on our learnings from the broader evolutionary history of the virus,” explained co-lead author Nicole Thadani, a former research fellow in the Marks lab.
Such an approach, Marks emphasized, means that EVEscape has a flexible framework that can be easily adapted to any virus.
In the new study, the team turned the clock back to January 2020, just before the COVID-19 pandemic started. Then they asked EVEscape to predict what would happen with SARS-CoV-2.
“It’s as if you have a time machine. You go back to day one, and you say, I only have that data, what am I going to say is happening?” Marks said.
EVEscape predicted which SARS-CoV-2 mutations would occur during the pandemic with accuracy similar to this of experimental approaches that test the virus’s ability to bind to antibodies made by the immune system. EVEscape outperformed experimental approaches in predicting which of those mutations would be most prevalent. More importantly, EVEscape could make its predictions more quickly and efficiently than lab-based testing since it didn’t need to wait for relevant antibodies to arise in the population and become available for testing.
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 as they demonstrated that EVEscape could be generalized to other viruses, including HIV and influenza.
“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,” notes Marks.
Additionally, EVEscape predicted which antibody-based therapies would lose their efficacy as the pandemic progressed and the virus developed mutations to escape these treatments. The tool was also able to sift through the tens of thousands of new SARS-CoV-2 variants produced each week and identify the ones most likely to become problematic.
“By rapidly determining the threat level of new variants, we can help inform earlier public health decisions,” said Sarah Gurev, a graduate student in the Marks lab from the Electrical Engineering and Computer Science program at MIT.
The team is now applying EVEscape to SARS-CoV-2 in real time, using all of the information available to make predictions about how it might evolve next. They are also testing EVEscape on understudied viruses such as Lassa and Nipah, two pathogens of pandemic potential for which relatively little information exists. Such less-studied viruses can have a huge impact on human health across the globe, the researchers noted.
The researchers publish a biweekly ranking of new SARS-CoV-2 variants on their website and share this information with entities such as the World Health Organization. The complete code for EVEscape is also freely available online.
Another important application of EVEscape would be to evaluate vaccines and therapies against current and future viral variants. The ability to do so can help scientists design treatments that are able to withstand the escape mechanisms a virus acquires.
