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Nobel Prize In Chemistry Awarded For Unlocking Proteins' Secrets

David Baker, Demis Hassabis, and John M. Jumper have worked on different aspects of protein designs and prediction.

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Dr. Alfredo Carpineti

Dr. Alfredo Carpineti headshot

Dr. Alfredo Carpineti

Senior Staff Writer & Space Correspondent

Alfredo (he/him) has a PhD in Astrophysics on galaxy evolution and a Master's in Quantum Fields and Fundamental Forces.

Senior Staff Writer & Space Correspondent

EditedbyFrancesca Benson
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Francesca Benson

Copy Editor and Staff Writer

Francesca Benson is a Copy Editor and Staff Writer with a MSci in Biochemistry from the University of Birmingham.

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the nobel prize medal, with underneath the text the 2024 nobel prize in chemistry on a red background

The prize was awarded for understanding proteins and creating new ones.

Image Credit: Nobel Foundation, Modified by IFLScience

The winners of the 2024 Nobel Prize in Chemistry are David Baker for computational protein design, plus Demis Hassabis and John M. Jumper for an AI model used for protein structure prediction. The prize is worth 11 million Swedish kronor (around US$1 million at time of publishing), half of which will go to Baker and the other half will be shared by Hassabis and Jumper. 

Proteins are the building blocks of life, not just something for gym-goers to grow their muscles – they are crucial for biological functions. Hormones, enzymes, and antibodies are examples of proteins. Proteins help make up the different tissues in our bodies and allow our bodies to work. 

Proteins are chains of smaller molecules called amino acids. There are hundreds of amino acids in nature, but life on Earth uses 20. Thanks to different arrangements in the chains of amino acids and variations in folding, proteins exist in a myriad of forms and functions, and the Nobel Prize this year recognizes discoveries related to two aspects of this. 

In 2003, David Baker and his team were the first to design a completely new protein unlike any other seen before. This has led to the development of more and more new proteins that have found applications in drug development, vaccines, and even tiny sensors.

The other half of the prize focuses on understanding how a series of amino acids leads to certain protein structures in the first place. A quest that started in the 70s was finally solved four years ago when the Google DeepMind team used AI - which also helped two scientists win the Nobel Prize in Physics this year - to understand how the three-dimensional structure of proteins forms. 

With the machine learning AlphaFold2, Hassabis, Jumper, and their team were able to predict the structure of virtually all 200 million known proteins. Over two million people have used the AI model, leading to applications from fighting antibiotic resistance to developing enzymes that can decompose plastic.

“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,” Heiner Linke, Chair of the Nobel Committee for Chemistry, said in a statement


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