‘New era in digital biology’: AI reveals structures of almost all known proteins |  Science

‘New era in digital biology’: AI reveals structures of almost all known proteins | Science

What a difference a year makes. Twelve months ago, artificial intelligence (AI) company DeepMind stunned many scientists by releasing predicted structures for some 350,000 proteins, part of the work recognized as Science2021 Breakthrough of the Year Yesterday, DeepMind and its partners went much, much further. The company has revealed the likely structures of nearly all known proteins, more than 200 million from bacteria to humans, an astonishing achievement for AI and a potential treasure trove for drug development and evolutionary research.

“We are now releasing the structures for the entire protein universe,” Demis Hassabis, founder and CEO of DeepMind, said at a news conference in London.

The structure premium comes from AlphaFold, one of the new AI programs that has cracked the protein folding problem, the long-standing challenge of accurately deriving the 3D shapes of proteins from their amino acid sequences. AlphaFold’s newly predicted structures were released yesterday into an existing database through a partnership with the European Molecular Biology Laboratory’s European Bioinformatics Institute (EMBL-EBI). The database “has given structural biologists this powerful new tool where you can look up the 3D structure of a protein almost as easily as you can Google a keyword,” Hassabis said.

Eric Topol, director of the Scripps Research Translational Institute, echoed the astonishment of many outside scientists. “AlphaFold is the extraordinary and important life science advance that demonstrates the power of AI,” he tweeted. “With this new addition of structures illuminating almost the entire protein universe, we can expect more biological mysteries to be solved every day.”

The release of the DeepMind structure is “remarkable,” Ewan Burney, EMBL’s deputy director-general, said at the press conference. “It will make many researchers around the world think about what experiments they can do now.”

The proteins solubilized by AlphaFold come from organisms ranging from bacteria to plants and vertebrates, including mice, zebrafish and humans. Kathryn Tunyasuvunakool, a DeepMind researcher, said it took AlphaFold roughly 10 to 20 seconds to make each protein prediction. The company had to work closely with EMBL-EBI, she noted, to figure out how to represent the vast number of structures in the database.

DeepMind says more than 500,000 researchers have already used the database since it launched last year. Hassabis predicts a “new era in digital biology” in which drug developers can go from AI-predicted structures of proteins important to any medical condition to using AI to design small molecules that affect those proteins — and therefore to treat a disease.

Others use the structure predictions to develop vaccine candidates, investigate fundamental questions in biology, such as how the so-called nuclear pore complex keeps track of which molecules enter the cell’s nucleus, or study the evolution of proteins when life first evolved .

However, Hassabis warned that the release of the structures is only a starting point. “There’s obviously a lot of biology and a lot of chemistry that needs to be done.”

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