AI solves 50-year-old science problem in ‘stunning advance’ that could dramatically change how we fight diseases, researchers say

Andrew Griffin
·3-min read
 (Deepmind/PA)
(Deepmind/PA)

A 50-year-old science problem has been solved and could allow for dramatic changes in the fight against diseases, researchers say.

For years, scientists have been struggling with the problem of “protein folding” – mapping the three-dimensional shapes of the proteins that are responsible for diseases from cancer to Covid-19.

Google’s Deepmind claims to have created an artificially intelligent program called “AlphaFold” that is able to solve those problems in a matter of days.

If it works, the solution has come “decades” before it was expected, according to experts, and could have transformative effects in the way diseases are treated.

There are 200 million known proteins at present but only a fraction have actually been unfolded to fully understand what they do and how they work. Even those that have been successfully understood often rely on expensive and time-intensive techniques, with scientists spending years unfolding each structure and relying on equipment that can cost many millions of dollars.

DeepMind worked on the AI 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.

“Proteins are extremely complicated molecules, and their precise three-dimensional structure is key to the many roles they perform, for example the insulin that regulates sugar levels in our blood and the antibodies that help us fight infections,” Dr John Moult, chair of CASP14, said.

“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.

“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.”

During the latest test, DeepMind said AlphaFold determined the shape of around two-thirds of the proteins with accuracy comparable to laboratory experiments. The results of those tests have been published online, so that they can be scrutinised by external scientists.

Now researchers behind the project say there is still more work to be done, including figuring out how multiple proteins form complexes and how they interact with DNA.

<p>A three-dimensional digital rendering of a protein</p>Deepmind/PA

A three-dimensional digital rendering of a protein

Deepmind/PA

DeepMind is planning to submit a paper detailing its system to a peer-reviewed journal to be scrutinised by the wider scientific community.

Professor Venki Ramakrishnan, Nobel Laureate and president of the Royal Society, said: “This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology.

“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.”

DeepMind noted that among other things, the prediction of protein structures could be an important part of responses to future pandemics, and that it had already used its machine learning technology on the protein structures of the SARS-CoV-2 virus, which causes Covid-19.

Additional reporting by Press Association

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