Researchers use AI to predict nearly all known proteins

Researchers have used artificial-intelligence to predict the structures of 200 million proteins, which cover virtually every known protein on the planet.

The data covers protein strands from nearly 1 million species and was developed by London-based DeepMind, an AI company developed by Google.

The company used an artificial intelligence technique called deep learning to develop its AlphaFold network.

That database was created one year ago, with 350,000 structure predictions covering nearly every protein made by humans, mice and 19 other organisms. It now has around 1 million entries.

It will allow scientists to determine the 3D shape of almost any protein known to science with ease.

"We've been amazed by the rate at which AlphaFold has already become an essential tool for hundreds of thousands of scientists in labs and universities across the world to help them in their important work," the company said in a statement on its website.

"It's been so inspiring to see the myriad ways the research community has taken AlphaFold, using it for everything from understanding diseases, to protecting honey bees, to deciphering biological puzzles, to looking deeper into the origins of life itself."

The European Molecular Biology Laboratory's European Bioinformatics Institute was also involved in the development.

"Essentially you can think of it covering the entire protein universe," DeepMind CEO Demis Hassabis, said at a news briefing.

"We're at the beginning of a new era of digital biology."

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