Google DeepMind Scientists Win Nobel Prize in Chemistry for AI-Powered Protein Modeling
Demis Hassabis and John Jumper, key figures from Google’s DeepMind, alongside biochemist David Baker, have won the 2024 Nobel Prize in Chemistry. They were recognized for pioneering breakthroughs in protein structure prediction and design, crucial advancements with far-reaching impacts in biology and medicine.
BREAKING NEWS
— The Nobel Prize (@NobelPrize) October 9, 2024
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry 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.” pic.twitter.com/gYrdFFcD4T
The Nobel Prize committee awarded Hassabis and Jumper for developing AlphaFold, an AI model that precisely predicts protein structures from amino acid sequences—a feat previously unsolved for half a century. AlphaFold’s accuracy has already accelerated research in drug discovery and vaccine development, with a database of over 200 million protein structures now freely accessible to researchers worldwide.
Work that once took years now takes just a few minutes thanks to this year’s chemistry laureates.
— The Nobel Prize (@NobelPrize) October 9, 2024
2024 #NobelPrize laureates Demis Hassabis and John Jumper have used their AI model AlphaFold2 to calculate the structure of all human proteins. They also predicted the structure of… pic.twitter.com/3xAKhbhYUv
Baker, from the University of Washington, was honored for his complementary work in computational protein design, which has enabled the creation of synthetic proteins for various applications, from pharmaceuticals to environmental solutions.
In a statement, Hassabis expressed his hopes for AlphaFold as a “proof point of AI's incredible potential to accelerate scientific discovery,” while Jumper highlighted the model's impact in supporting experimental biology.