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AI Powers Pioneering Team’s Nobel Prize for Chemistry Win

Nobel Prize
Johan Jarnestad/The Royal Swedish Academy of Sciences

Insider Brief

  • Nobel Prize in Chemistry was awarded to David Baker, recognized for his pioneering work in computational protein design, while Demis Hassabis and John Jumper are honored for their development of AlphaFold2, an AI model that predicts protein structures from amino acid sequences.
  • AlphaFold2, introduced in 2020, has solved a decades-old challenge, enabling scientists to predict the structure of nearly all known proteins.
  • Baker’s designed proteins and the AlphaFold2 model open vast possibilities in medicine, biotechnology, and materials science, including applications in developing vaccines, antibiotics, and biodegradable materials.
  • Image: Johan Jarnestad/The Royal Swedish Academy of Sciences

PRESS RELEASE — The Royal Swedish Academy of Sciences has decided to award the Nobel Prize in Chemistry 2024 with one half to David Baker, University of Washington, Seattle, WA, USA and Howard Hughes Medical Institute, USA “for computational protein design” and the other half jointly to Demis Hassabis. Google DeepMind, London, UK and John M. Jumper Google DeepMind, London, UK “for protein structure prediction”.

They cracked the code for proteins’ amazing structures

The Nobel Prize in Chemistry 2024 is about pro­teins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential.

The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemi­cal reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of 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.

Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors.

The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough.

In 2020, Demis Hassabis and John Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic.

Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind.

Matt Swayne
About the author
Matt Swayne

With a several-decades long background in journalism and communications, Matt Swayne has worked as a science communicator for an R1 university for more than 12 years, specializing in translating high tech and deep tech for the general audience. He has served as a writer, editor and analyst at The Space Impulse since its inception. In addition to his service as a science communicator, Matt also develops courses to improve the media and communications skills of scientists and has taught courses.

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