Google DeepMind scientists win Nobel chemistry prize

Two scientists at Google DeepMind and an American biochemist have been awarded the 2024 Nobel prize in chemistry for breakthroughs in predicting and designing the structure of proteins.

Demis Hassabis, DeepMind’s British founder, and John Jumper, who led the development of the company’s AI model AlphaFold– which predicts the structure of proteins based on their chemical sequence– share half of the prize.

The other half was awarded to Prof David Baker, of the University of Washington, whose computational research has led to the creation of entirely new kinds of proteins, with applications in vaccines, nanomaterials and tiny sensors.

The winners were announced by the Royal Swedish Academy of Sciences in Stockholm, and will share the 11m Swedish kronor (£810,000) prize for computational protein design and protein structure prediction.

Heiner Linke, the chair of the Nobel committee for chemistry, said: “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.”

Speaking at a press briefing immediately after the announcement, Baker said he had been woken by a phone call from the academy telling him he had won, and described how the ambition to create entirely new proteins began as a dream more than 20 years ago. Advances in computing and scientific understanding in the intervening years had paved the way for this vision to have a meaningful impact in the world, he said, including in the design of novel vaccines for coronavirus.

“We glimpsed at the beginning that it might be possible to create a whole new world of proteins that address a lot of the problems faced by humans in the 21st century,” Baker said. “Now it’s becoming possible.”

Proteins control and drive all the chemical reactions that are the basis of life. They function as hormones, antibodies and the building blocks of different tissues. Baker’s mission was to design new proteins that do not exist in nature, and in 2003, he succeeded. Since then, his group has produced novel proteins with wide-ranging applications in medicine and materials science.

Proteins generally consist of 20 different amino acids, which are linked together in long strings that fold up to make three-dimensional structures. It is these structures – as well as the chemical composition – that determine how proteins will interact and whether, for instance, they will bind to a drug in the body. Since the 1970s, scientists have been working on predicting protein’s three-dimensional structures from their chemical sequences, but the problem was notoriously difficult and progress was slow.

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Four years ago, there was a breakthrough. In 2020, Hassabis and Jumper announced the development of an AI model called AlphaFold 2. With its help, they have been able to predict the structure of virtually all the 200m proteins that researchers have identified. Since their breakthrough, AlphaFold 2 has been used by more than 2 million people from 190 countries in applications such as understanding antibiotic resistance and developing enzymes that can decompose plastic.

Dr Annette Doherty, the president of the Royal Society of Chemistry, said: “The benefits of this research are remarkable, as we can all look forward to applications improving our health and wellbeing. I am sure that their work will prove as inspirational to future generations as the discoveries of their predecessors who have been awarded this most prestigious honour.”