AlphaFold wins the 2024 Nobel Prize in Chemistry
One day after AI took the physics prize, the 2024 Chemistry Nobel honored AlphaFold, the DeepMind model that predicts protein structures, and computational protein design.
On October 9, 2024, the day after the physics prize went to neural networks, the Nobel Prize in Chemistry followed suit. Half went to David Baker for computational protein design; the other half to Demis Hassabis and John Jumper of Google DeepMind “for protein structure prediction”. Their model, AlphaFold, is one of the clearest cases yet of AI producing a genuine scientific breakthrough.
A fifty-year-old problem
Proteins are chains of amino acids that fold into intricate three-dimensional shapes, and the shape largely determines what the protein does. Predicting that shape from the sequence alone had resisted researchers since the 1970s. In 2020, AlphaFold2 cracked it well enough to matter, predicting structures with an accuracy competitive with slow, expensive laboratory methods.
DeepMind then released predicted structures for nearly all of the roughly 200 million proteins known to science. By the time of the prize, the database had been used by more than two million researchers, in work ranging from antibiotic resistance to enzymes that break down plastic.
The same lineage
AlphaFold did not appear from nowhere. DeepMind was the lab behind AlphaGo, and the same toolkit of deep neural networks trained on large datasets sits underneath both. It is a reminder that the ImageNet-era deep learning methods reached far beyond chatbots and images.
Why it matters
Back-to-back Nobel prizes made the point that 2024 was not only the year of the chatbot. AI had become an instrument of discovery, the sort of tool that changes how other sciences are done. It also sharpened an old question: when a model does the predicting, who exactly did the science? The committee’s answer was clear enough to split the prize between building proteins by hand and predicting them by machine.