The 2024 Nobel Prize in Chemistry has been awarded to three scientists who revolutionized the study of proteins using artificial intelligence (AI). The trio successfully “cracked the code” of nearly all known proteins, which are often called the “chemical tools of life.”
The Nobel Committee praised David Baker, a biochemist from the U.S., for achieving what they described as “the almost impossible feat of building entirely new kinds of proteins.” In addition, the committee recognized Demis Hassabis and John Jumper, both from Google DeepMind in London, for creating an AI model capable of predicting the complex structures of proteins—a scientific puzzle that had remained unsolved for half a century.
As the prize was announced in Sweden, the Nobel Committee emphasized the enormous potential of the discoveries made by these scientists. The Nobel Prize, which is regarded as one of the highest honors in science, comes with a cash reward of 11 million Swedish kronor, roughly equivalent to $1 million.
Proteins: The Building Blocks of Life
Proteins, which are made up of chains of amino acids, play a crucial role in sustaining life. They are essential in forming hair, skin, and tissue cells, in addition to reading, copying, and repairing DNA. Proteins also facilitate the transport of oxygen in the bloodstream.
Although proteins are constructed from only about 20 types of amino acids, these molecules can be arranged in an almost infinite number of combinations, resulting in highly complex three-dimensional shapes.
AI as a ‘Google Search’ for Protein Structures
This year’s Nobel Prize was divided into two parts. The first portion was awarded to Hassabis, a British computer scientist who co-founded Google DeepMind, and Jumper, an American researcher also working at DeepMind. Their work involved using AI to predict the three-dimensional shape of a protein based on its amino acid sequence. This breakthrough allowed them to predict the structure of nearly all 200 million known proteins.
Anna Wedell, a professor of medical genetics at Sweden’s Karolinska Institutet and a member of the Royal Swedish Academy of Sciences, described their achievement as “a standalone breakthrough solving a traditional holy grail in physical chemistry.”
Their AI-based program, called the AlphaFold Protein Structure Database, has been employed by more than 2 million researchers across the globe. This database acts much like a “Google search” for protein structures, enabling scientists to access predicted protein models quickly. This advancement has accelerated research in fundamental biology as well as other scientific fields. The work of Hassabis and Jumper has already earned them prestigious awards, including the 2023 Lasker and Breakthrough Prizes.
“They’ve made everything public, so more or less every field can now turn to this database and use these tools to address their particular problem,” Wedell said. She explained that the tool has opened new possibilities for many areas of research, including her own work in studying rare diseases.
Since their key research paper was published in 2021, it has been cited more than 16,000 times. David Pendlebury, head of research analysis at Clarivate’s Institute for Scientific Information, described this as “unprecedented” and highlighted the immense impact of their work. Out of 61 million scientific papers, only around 500 have been cited more than 10,000 times, he told CNN.
Before their groundbreaking work on proteins, Hassabis and Jumper collaborated on a computer program capable of competing against the world’s top players of Go, an ancient Chinese board game.
Hassabis, who was a chess prodigy as a child, also developed the popular video game Theme Park at the age of 17, according to the Royal Society, the world’s oldest scientific society, of which he is a member.
Adrian Smith, president of the Royal Society, remarked, “Today’s prize, so soon after the first unveiling of AlphaFold’s potential, is a clear recognition of AI’s transformative role in science.” He added, “As well as being one of the field’s most pioneering researchers, Demis has championed a vision of AI as an enabler that can unlock science’s great challenges and release benefits for all of society.”
Designing Proteins ‘Not Seen in Nature’
The second part of the Nobel Prize was awarded to David Baker, a professor at the University of Washington, for using computerized methods to design proteins that do not occur naturally. These newly created proteins have entirely novel functions.
Johan Aqvist, a member of the Nobel Committee, explained that Baker’s approach involved first using a computer program to “draw protein structures in new dimensions.” He then determined which sequence of amino acids would yield these structures, which allowed him to engineer proteins that had never existed in nature.
Aqvist expressed his astonishment at the variety of proteins Baker had designed, calling the range “absolutely mind-blowing.” He added, “It seems that you can almost construct any type of protein now with this technology.”
The Nobel Committee highlighted the vast potential applications of being able to design new proteins, from developing pharmaceuticals to speeding up the creation of vaccines.
This year’s chemistry prize underscores the increasing role AI is playing in scientific discovery.
AI’s Influence Across Scientific Fields
AI’s influence on science was further emphasized by the Nobel Prize in Physics, which was awarded the previous day. That prize was shared by Geoffrey Hinton, often referred to as the “Godfather of AI,” and John Hopfield for their pioneering work on artificial neural networks. These same neural networks were instrumental in the advancements made by the new Nobel laureates in chemistry.
David Pendlebury of Clarivate said that the Nobel Foundation’s selection of laureates in both physics and chemistry this year could be seen as “bold.” He remarked, “The acknowledgment of the transformational role of AI in research in two categories, back-to-back, is unprecedented.”
In both physics and chemistry, AI is being recognized as a force that is driving forward the frontiers of knowledge and enabling new breakthroughs. This year’s Nobel laureates have shown that AI can help tackle scientific challenges that have been out of reach for decades, creating new possibilities for the future of science.