Google-owned DeepMind cracks 50-year-old 'protein folding problem'

DeepMind, the British artificial intelligence (AI) company owned by Google, has solved a 50-year-old problem in biology. 

DeepMind's AI system, AlphaFold, cracked the so-called 'protein folding problem' – figuring out how a protein's amino acid sequence dictates its 3D atomic structure. 

A protein’s structure is closely linked with its function, and the ability to predict its structure unlocks a greater understanding of what it does and how it works.   

AlphaFold's neural network was trained with 170,000 known protein sequences and their different structures.

The system registered an average accuracy score of 92.4 out of 100 for predicting protein structure, and a score of 87 in the category for most challenging proteins. 

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Because almost all diseases, including cancer and Covid-19, are related to a protein's 3D structure, the AI could pave the way for faster development of treatments and drug discoveries by determining the structure of previously-unknown proteins. 

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A three-dimensional digital rendering of a protein. The 50-year-old 'protein folding problem' may have been cracked by artificial intelligence created in the UK by Google-owned AI lab DeepMind, paving the way for faster development of treatments and drug discoveries

A three-dimensional digital rendering of a protein. The 50-year-old 'protein folding problem' may have been cracked by artificial intelligence created in the UK by Google-owned AI lab DeepMind, paving the way for faster development of treatments and drug discoveries

'This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology,' said President of the Royal Society Venki Ramakrishnan.

'It has occurred decades before many people in the field would have predicted. 

'It will be exciting to see the many ways in which it will fundamentally change biological research.'

London-based DeepMind is one of the world's leading AI research centres, developing intelligent software that can do everything from play a game of chess to painting landscapes.

The firm is perhaps best known for its AlphaGo AI program that beat a human professional Go player Lee Sedol, the world champion, in a five-game match.   

But DeepMind is has been turning its attention to using AI for some of the most pressing scientific conundrums.

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The firm has worked on the project with the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), a group of scientists who have been looking into the matter since 1994.

CASP is a biannual competition for teams of researchers to test their protein structure prediction methods against. 

DeepMind has previously submitted iterations of AlphaFold to CASP, but its submission this year sets a new precedent for accuracy. 

'We have been stuck on this one problem – how do proteins fold up – for nearly 50 years,' said Dr John Moult, chair of CASP14. 

'To see DeepMind produce a solution for this, having worked personally on this problem for so long and after so many stops and starts, wondering if we'd ever get there, is a very special moment.'

Proteins are large complex molecules that our cells need to function properly, made up of chains of amino acids.

Each protein has an intricate 3D structure that defines what it does and how it works.    

'Even tiny rearrangements of these vital molecules can have catastrophic effects on our health, so one of the most efficient ways to understand disease and find new treatments is to study the proteins involved,' said Dr Moult. 

'There are tens of thousands of human proteins and many billions in other species, including bacteria and viruses, but working out the shape of just one requires expensive equipment and can take years.'

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