Not so fast! New model analyzes how viruses escape the immune system
MIT researchers devised a new way to computationally look at viral escape, based on models that were originally developed to analyze language. Their model can predict which sections of viral surface proteins are more likely to mutate in a way that enables viral escape. It can also identify sections that are less likely to mutate, making them good targets for new vaccines, possibly even one for cancer.
Credit: National Science Foundation/Karson Productions
I'm Bob Karson with The Discovery Files, from NSF -- the U.S. National Science Foundation.
You know why there's no vaccine for HIV? No universal flu vaccine? And what are all these new COVID variants popping up? They're all due to a little self-preservation technique viruses use (Sound effect: escape alarm sound) called 'viral escape'.
(Sound effect: cavalry charge -- bugle) As the immune system sends in troops to fight the virus, viral genetic mutations occur, that set out to change surface proteins of the virus to disguise it, while keeping it functional. Once under the radar, the antibodies don't recognize the virus and cannot attach.
MIT researchers are helping get a handle on viral escape using a linguistic model to analyze and predict patterns in protein sequences just like it does for human language. Researchers trained the model, which normally captures patterns that correspond to the "grammar" and "semantics" of human language, to capture the rules describing viral protein sequences instead.
The model predicted which sections of viral surface proteins are more or less likely to mutate in a way that contributes to viral escape.
The work may open doors to development of a flu vaccine or seek out targets for cancer vaccines to destroy tumors using the immune system, as well as predicting the behavior of COVID variants.
With this new weapon in the war against elusive harmful viruses, (Sound effect: chalkboard) chalk one up for our side.
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