DeepMind has already notched up a streak of wins, showcasing AIs that have learned to play a variety of complex games with superhuman skill, from Go a

DeepMind’s protein-folding AI has solved a 50-year-old grand challenge of biology

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2021-07-05 05:00:06

DeepMind has already notched up a streak of wins, showcasing AIs that have learned to play a variety of complex games with superhuman skill, from Go and StarCraft to Atari’s entire back catalogue. But Demis Hassabis, DeepMind’s public face and co-founder, has always stressed that these successes were just stepping stones towards a larger goal: AI that actually helps us understand the world.

Today DeepMind and the organizers of the long-running Critical Assessment of protein Structure Prediction (CASP) competition announced an AI that should have the huge impact that Hassabis has been after. The latest version of DeepMind’s AlphaFold, a deep-learning system that can accurately predict the structure of proteins to within the width of an atom, has cracked one of biology’s grand challenges. “It's the first use of AI to solve a serious problem,” says John Moult at the University of Maryland, who leads the team that runs CASP.

A protein is made from a ribbon of amino acids that folds itself up with many complex twists and turns and tangles. This structure determines what it does. And figuring out what proteins do is key to understanding the basic mechanisms of life, when it works and when it doesn’t. Efforts to develop vaccines for covid-19 have focused on the virus’s spike protein, for example. The way the coronavirus snags onto human cells depends on the shape of this protein and the shapes of the proteins on the outsides of those cells. The spike is just one protein among billions across all living things; there are tens of thousands of different types of protein inside the human body alone.