The Nobel Prize in Chemistry has been shared between biochemist David Baker of the University of Washington, USA for his work on computational protein design, and Google DeepMind's CEO and founder Demis Hassabis and John Jumper, a senior research scientist at the company, for their work on AI tools for protein structure prediction.
The Royal Swedish Academy of Sciences which awards the prize said: “The Nobel Prize in Chemistry 2024 is about proteins, life’s ingenious chemical tools.”
It said Baker has succeeded with the “almost impossible feat” of building entirely new kinds of proteins, while Hassabis and Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures.
“These discoveries hold enormous potential,” the academy said. “Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind,” it said.
Proteins are a fundamental building block of chemistry: they control and drive all the chemical reactions that together are the basis of life, and can also function as hormones, signal substances, antibodies and can be used to form different tissues.
“One of the discoveries being recognised 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,” says Heiner Linke, chair of the Nobel Committee for Chemistry.
In 2003, Baker managed to design a new protein that was unlike any other protein - and since then his research group has produced many more which can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors.
In 2020, Hassabis and Jumper presented an AI model called AlphaFold2 which has helped predict the structure of "virtually" all the 200 million proteins that researchers have identified, the academy said.
Google DeepMind said that, before AlphaFold, predicting the structure of a protein was a complex and time-consuming process. AlphaFold’s predictions, made freely available through the AlphaFold Protein Structure Database, have given more than 2 million scientists and researchers from 190 countries a powerful tool for making new discoveries. The AlphaFold 2 paper, published in 2021, remains one of the most-cited publications of all time, Google Deepmind said.
In a statement released after being informed of the award Hassabis said: “I’ve dedicated my career to advancing AI because of its unparalleled potential to improve the lives of billions of people. AlphaFold has already been used by more than two million researchers to advance critical work, from enzyme design to drug discovery. I hope we'll look back on AlphaFold as the first proof point of AI's incredible potential to accelerate scientific discovery."
Jumper added: “Computational biology has long held tremendous promise for creating practical insights that could be put to use in real-world experiments. AlphaFold delivered on this promise. Ahead of us are a universe of new insights and scientific discoveries made possible by the use of AI as a scientific tool.”
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