Nobel committee honors work on protein structure prediction and design.
WASHINGTON, Oct. 9, 2024 – The 2024 Nobel Prize in chemistry was awarded with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”
“The relationship between protein sequence, structure, and function is a long-standing problem that has challenged researchers from many different disciplines, including biology, chemistry, and physics,” said Michael Moloney, CEO of AIP.
“The prize highlights the power of computing to help us understand what proteins look like and how they work. And both the chemistry and physics prizes this year recognize the growing importance that artificial intelligence and machine learning are having across the breadth of modern science.
Proteins are the functional molecules of life, performing a wide range of tasks like carrying oxygen through the bloodstream, fighting off infections, facilitating chemical reactions, and upholding the structure of cells. While the human body contains hundreds of thousands of proteins, they are all made from different combinations of the same 22 amino acids.
Each protein’s role and function are determined by its 3D shape, which is itself determined by its sequence of amino acids. Calculating that structure from the amino acid sequence is a problem that has vexed researchers for decades. The advent of AI tools has offered the means to dramatically accelerate that calculation and improve our understanding of existing proteins. The process can also be reversed, to create new proteins, not found in nature, that have specific functionalities.
David Baker is a professor of biochemistry, HHMI investigator, and the director of the Institute for Protein Design at the University of Washington School of Medicine. Starting in 2003, Baker and his research group have used custom computational tools to engineer new proteins for use as medicines and nanomaterials.
Demis Hassabis and John M. Jumper are both with DeepMind Technologies, where Hassabis is co-founder and CEO and Jumper is a senior research scientist. Together, they and their team developed AlphaFold2 — an AI model that accurately predicts protein structures from amino acid sequences. With over 200 million protein structures predicted, AlphaFold2 has significantly advanced the field of structural biology, playing a crucial role in targeting diseases.
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