The Nobel Prizes are embracing the AI hype. A day after the Physics prize was given to two scientists for foundational work on machine learning, the Nobel Prize in Chemistry has been awarded to three scientists who used advanced computational methods to solve a decades-old problem: understanding how proteins fold together into three-dimensional shapes.
Half of the 2024 Chemistry prize goes to David Baker, Ph.D., “for computational protein design” while the other half is split between Demis Hassabis, Ph.D., and John Jumper, Ph.D., “for protein structure prediction.” Baker is a biochemist at the University of Washington and Howard Hughes Medical Institute; Hassabis is co-founder and CEO of Google DeepMind, where John Jumper is a director.
“One of the discoveries being recognized this year concerns the construction of spectacular proteins. The other is about fulfilling a 50-year-old dream: predicting protein structures from their amino acid sequences. Both of these discoveries open up vast possibilities,” Heiner Linke, Chair of the Nobel Committee for Chemistry, said in an Oct. 9 release.
Proteins are made up of sequences of amino acids, but their functions are determined by how those amino acid chains fold together into 3D shapes. Baker’s prize comes from work in 2003 when his team used a computer model to design a new protein that doesn’t exist in nature. Baker’s group has continued to design new proteins since, the Nobel Prize Committee said in the release, including some that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors.
Hassabis and Jumper’s prize is due to much more recent work—the 2020 release of AlphaFold2, an AI model that can predict the structure of proteins based on their amino acid sequences. The model has since been used to predict the structure of almost every known protein and “became an essential tool for biopharma research nearly overnight,” president and CEO of Rome Therapeutics Rosana Kapeller, Ph.D., said in 2022.
AlphaFold2 has been used by more than two million people from 190 countries, according to the release, and can be used to understand diverse protein functions, from antibiotic resistance to breaking down plastic.