We previously discussed the AI model AlphaFold 3 from Google DeepMind, which models RNA and DNA. It’s important to note that AlphaFold models are designed to predict the structures of proteins. Yesterday, DeepMind CEO Demis Hassabis, DeepMind senior research scientist John Jumper, and University of Washington professor David Baker were awarded the 2024 Nobel Prize in Chemistry.

These three Nobel laureates contributed to our understanding of proteins responsible for various functions both inside and outside the human body. Notably, the Nobel Committee referenced Baker’s groundbreaking work in the field of computational protein design. Since 2003, Baker and his research team have been designing completely new proteins using amino acids and computer assistance. These chemicals contribute to the development of drugs, vaccines, and nanomaterials.

Hassabis and Jumper, along with the entire DeepMind team, have gained recognition for their impactful work on AlphaFold 2 over the years. Since the 1970s, scientists have been attempting to find a way to predict the final folded structure of a protein based solely on its constituent amino acids. DeepMind created an AI algorithm with AlphaFold 2 that is capable of doing just that. Since 2020, the software has successfully predicted the structures of 200 million proteins.

Heiner Linke, the chair of the Nobel Chemistry Committee, made the following remarks during his speech:

“One of the discoveries recognized this year relates to the wonderful structure of proteins. The other fulfills a 50-year-old dream: predicting protein structures from amino acid sequences.”

“Both of these discoveries open up great possibilities.”


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