AlphaFold is a Google DeepMind AI system that predicts the 3D shape of a protein from its sequence of amino acids.
In plain words
A protein's shape decides what it does, but measuring one in the lab can take months or years. Predicting shape from the amino acid sequence had been an open problem for about 50 years. In the CASP14 contest, AlphaFold's predictions were often as accurate as lab results. A free database now holds over 260 million of its predictions, and Demis Hassabis and John Jumper received half of the 2024 Nobel Prize in Chemistry for it. AlphaFold 3 extends this to complexes with DNA, RNA and small molecules.
A quick example
Imagine a researcher studying a little-known protein. Instead of waiting months for a lab to solve its shape, they search the AlphaFold Protein Structure Database and, if the protein is among its 260 million entries, see a predicted 3D model.
Where you'll meet it
- Biology and medical research.
- Drug discovery, via predicted protein-molecule complexes.
Related
Sources
- PaperHighly accurate protein structure prediction with AlphaFold, Jumper et al. (Nature) · read 29 Sept 2026
- DocsAlphaFold Protein Structure Database, EMBL-EBI and Google DeepMind · read 29 Sept 2026
- DocsThe Nobel Prize in Chemistry 2024: press release, Royal Swedish Academy of Sciences · read 29 Sept 2026
- PaperAccurate structure prediction of biomolecular interactions with AlphaFold 3, Abramson et al. (Nature) · read 29 Sept 2026
Checked by WhatIsAI against the sources above · 29 Sept 2026. Spotted an error? Report it.