The 2024 Nobel Prize in Chemistry was awarded one half to Demis Hassabis and John Jumper (Google DeepMind) for their work on protein structure prediction, and the other half to David Baker (University of Washington) for computational protein design.
Source: nobelprize.org
In plain terms
A protein is a long chain of amino acids that folds into a complex three-dimensional shape, and it is that folded shape which governs how it acts inside the cell. Working out that shape from the amino acid sequence alone remained an open problem for some fifty years. AlphaFold 2, the artificial intelligence model introduced by the DeepMind team in 2020, broke that deadlock: the associated database has been able to index the structures of more than 200 million proteins, the vast majority of those catalogued by science on Earth. The 2024 Nobel Prize in Chemistry honours that prediction on one side and, on the other, the reverse operation — designing new proteins computationally — carried out by David Baker.
The prize and its laureates
| Parameter | Value |
|---|---|
| Award | 2024 Nobel Prize in Chemistry |
| First half | Demis Hassabis and John Jumper (Google DeepMind) |
| Work recognised | Protein structure prediction |
| Second half | David Baker (University of Washington) |
| Work recognised | Computational protein design |
| Model involved | AlphaFold 2, introduced by the DeepMind team in 2020 |
| Problem solved | Predicting a protein's three-dimensional structure from its amino acid sequence |
| Age of the bottleneck | about 50 years |
| Coverage of the associated database | more than 200 million protein structures |
Technical explanation
1. From sequence to shape — A protein is specified by its amino acid sequence, but what interests the biologist is its complex three-dimensional structure. Getting computationally from the first to the second is the fundamental biological problem that stayed open for fifty years, and it is the one AlphaFold 2 solved.
2. A database on the scale of catalogued life — The breakthrough did not stop at a handful of demonstration proteins: the database associated with the model indexes more than 200 million structures, covering the vast majority of the proteins catalogued on Earth by science.
3. The other half of the prize, the inverse problem — Where prediction runs from sequence to shape, the computational protein design recognised in David Baker starts from the intended goal and works back to a protein to be built. The 2024 prize brings the two directions together.
What the breakthrough unlocks
| Field | What the models make possible |
|---|---|
| Pharmacological research | drastic acceleration of the work |
| Vaccines | development of new vaccines |
| Enzyme engineering | enzymes capable of degrading plastic |
| Cell biology and virology | fine-grained understanding of cellular and viral mechanisms |
Causal chain
Predicting a protein's structure, a fundamental biological problem left open for some fifty years → development of an artificial intelligence model by the DeepMind team → AlphaFold 2, introduced in 2020, predicts the three-dimensional structure from the amino acid sequence alone → indexing of more than 200 million structures in the associated database → acceleration of pharmacological research, vaccines, enzyme engineering and the study of cellular and viral mechanisms → 2024 Nobel Prize in Chemistry, shared with David Baker's computational protein design.
Sources
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