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DeepMind AI breakthrough helps solve how diseases invade cells by predicting protein structures
- Google’s artificial intelligence unit takes a giant step to predict the structure of proteins
- Understanding how proteins will interact with other molecules has implications for research on new diseases like Covid-19
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Google’s artificial intelligence unit took a giant step to predict the structure of proteins, potentially decoding a problem that has been described as akin to mapping the genome.
DeepMind Technologies’ AlphaFold reached the threshold for “solving” the problem at the latest Critical Assessment of Structure Prediction competition. The event started in 1994 and is held every two years to accelerate research on the topic.
Different folds in a protein determine how it will interact with other molecules, and understanding them has implications for discovering how new diseases like Covid-19 invade our cells, designing enzymes to break down pollutants and improving crop yields.
DeepMind became a subsidiary of Google after a 2014 acquisition and is best known for its gamer AI, teaching itself to beat Atari video games and defeating world-renowned Go players like Lee Sedol. The company’s ambition has been to develop AI that can be applied to broader problems, and it has so far created systems to make Google’s data centres more energy efficient, identify eye disease from scans and generate human-sounding speech.
DeepMind also won the competition in 2018 at the first time of entering, when it accurately predicted the structure of 25 out of 43 proteins.
“These algorithms are now becoming strong enough and powerful enough to be applicable to scientific problems,” DeepMind Chief Executive Officer Demis Hassabis said in a call with reporters. After four years of development “we have a system that’s accurate enough to actually have biological significance and relevance for biological researchers.”
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