AlphaFold co-inventor becomes 100th scholar associated with UChicago to receive Nobel Prize
University of Chicago alum John Jumper was awarded a share of the 2024 Nobel Prize in Chemistry on Oct. 9 for developing an AI model that predicts the complex folded structures of proteins.
The Royal Swedish Academy of Sciences honored Jumper, who received his master’s degree in 2012 and his Ph.D. from the University of Chicago in 2017, along with Demis Hassabis, for their work on “protein structure prediction.” The prize is also shared with Prof. David Baker of the University of Washington “for computational protein design.”
Jumper is the 100th scholar associated with the University to receive a Nobel Prize.
“It’s absolutely extraordinary,” said Jumper. “I’ve been a computational biologist a long time, and I like to say in talks: we need this to work. We need computation to solve the problems of biology, and I just love that it’s starting to work.”
Jumper and Hassabis are co-inventors of the AlphaFold system, released by a company called Google DeepMind. The Nobel committee wrote they “have utilised artificial intelligence to successfully solve a problem that chemists wrestled with for over 50 years: predicting the three-dimensional structure of a protein from a sequence of amino acids.”
Scientists around the world have painstakingly assembled the genetic sequences for everything from corn to E. coli to humans. But the genetic sequence is only a starting point—most of the work in a cell is done by proteins, which are created from the genetic sequence but then folded into complex 3-D configurations to carry out their functions. Knowing the shapes of the proteins is crucial for understanding how cells work and, for example, designing drugs to work on diseases. But predicting how a protein would fold based solely on its genetic data remained elusive for decades.
DeepMind released an open-source version of a program called AlphaFold in July 2021, which has proved extraordinarily good at predicting the shapes proteins will take. Since then, according to Nature, it has been used by more than half a million researchers and resulted in thousands of papers on topics ranging from antibiotic resistance to crop resilience.
Jumper said, “What I love about all of this is…we could draw a straight line from what we do to people being healthy because of what we learn about biology in the cell and everything else, and it’s just extraordinary.”
Jumper received his Ph.D. in theoretical chemistry from the University of Chicago in 2017; his thesis examined how to apply machine-learning techniques to the study of protein dynamics. He was advised by Profs. Karl Freed and Tobin Sosnick, and afterward worked as a postdoctoral researcher in Sosnick’s lab before moving to Google DeepMind.
Freed is the Henry G. Gale Distinguished Service Professor Emeritus of the Department of Chemistry and James Franck Institute. Tobin Sosnick is the William B. Graham Professor of Biochemistry and Molecular Biology, and currently serves as chair of the department. He is also a member of the Institute for Biophysical Dynamics.
