Breakthrough A.I. Makes Huge Leap Toward Solving 50-Year-Old Problem in Biology | Smart News

Life on Earth relies on microscopic machines called proteins that are vital to everything from holding up the structure of each cell, to reading genetic code, to carrying oxygen through the bloodstream. With meticulous lab work, scientists have figured out the precise, 3-D shapes of about 170,000 proteins—but there are at least 200 million more to go, Robert F. Service reports for Science magazine.

Now, the artificial intelligence company DeepMind, which is owned by the same company that owns Google, has developed a tool that can predict the 3-D shapes of most proteins with similar results to experiments in the lab, Cade Metz reports for the New York Times. While lab experiments can take years to tease out a protein structure, DeepMind’s tool, called AlphaFold, can come up with a structure in just a few days, per Nature’s Ewen Callaway. The tool could help speed up studies in medicine development and bioengineering.

Molecular biologists want to know the structures of proteins because the shape of a molecule determines what it’s able to do. For instance, if a protein is causing damage in the body, then scientists could study its structure and then find another protein that fits it like a puzzle piece to neutralize it. AlphaFold could accelerate that process.

“This is going to empower a new generation of molecular biologists to ask more advanced questions,” says Max Planck Institute evolutionary biologist Andrei Lupas to Nature. “It’s going to require more thinking and less pipetting.”

DeepMind tested out AlphaFold by entering it in a biennial challenge called Critical Assessment of Structure Prediction, or CASP, for which Lupas was a judge. CASP provides a framework for developers to test their protein-prediction software. It’s been running since 1994, but the recent rise of machine learning in protein structure prediction has pushed participants to new levels. AlphaFold first participated last year and scored about 15% better than the other entries, per Science magazine. This year, a new computational strategy helped AlphaFold leave the competition in the dust.

Proteins are made of chains of chemicals called amino acids that are folded up into shapes, like wire sculptures. There are 20 kinds of amino acids, each with their own chemical characteristics that affect how they interact with others along the strand. Those interactions determine how the strand folds up into a 3-D shape. And because these chains can have dozens or hundreds of amino acids, predicting how a strand will fold based just on a list of amino acids is a challenge.

But that’s exactly what CASP asks participants to do. CASP assessors like Lupas have access to the answer key—the 3-D structure of a protein that was determined in a lab, but not yet published publicly. AlphaFold’s entries were anonymized as “group 427,” but after they solved structure after structure, Lupas was able to guess that it was theirs, he tells Nature.

“Most atoms are within an atom diameter of where they are in the experimental structure,” says CASP co-founder

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