During the 2022 mpox outbreak scientists looked for better ways to prevent and treat the disease. Researchers in Italy identified twelve antibodies from people who had been infected or vaccinated. Because it was not clear which viral proteins those antibodies targeted, a team at The University of Texas at Austin used the AlphaFold 3 artificial intelligence model to predict the likely targets among roughly thirty-five surface proteins.
AlphaFold 3 indicated with high confidence that several antibodies bind to a protein called OPG153. Follow-up laboratory work verified the prediction, and an engineered form of OPG153 given to mice triggered production of neutralizing antibodies. The study was published in Science Translational Medicine.
Researchers say the approach — starting from antibodies, finding the viral target and then engineering an antigen — could produce vaccine antigens or antibody therapies that are cheaper and easier to make than whole-virus vaccines. Patent applications have been filed and the work received partial funding from the Welch Foundation.
Difficult words
- outbreak — a sudden increase in disease cases
- antibody — a blood protein that fights germsantibodies
- protein — a molecule that makes structures or performs functionsproteins
- artificial intelligence — computer programs that can perform human-like tasks
- antigen — a substance that triggers an immune responseantigens
- patent — a legal right to control an invention's use
- neutralize — to stop a pathogen's ability to cause harmneutralizing
- engineer — to design or change something for a purposeengineered
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Would you prefer a vaccine made from a single protein rather than a whole-virus vaccine? Why or why not?
- What are the possible advantages of using artificial intelligence in vaccine research?
- Do you think patents for these discoveries help or harm public health? Explain briefly.
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