DeepMind Makes a Breakthrough in Biology

Researchers using Google's DeepMind artificial intelligence (AI) tool have made a major breakthrough in biology. They have accurately predicted protein structures from their amino-acid sequence, often referred to as protein folding. 

DeepMind’s program, called AlphaFold, outperformed around 100 other teams in a biennial protein-structure prediction challenge called CASP, short for Critical Assessment of Structure Prediction. The results were announced on 30 November, at the start of the conference — held virtually this year — that takes stock of the exercise.

“This is a big deal,” says John Moult, a computational biologist at the University of Maryland in College Park, who co-founded CASP in 1994 to improve computational methods for accurately predicting protein structures. “In some sense the problem is solved.”

It's hard to overstate the importance of this breakthrough. Problems that took literally years of work to solve, could now be solved in hours or days of computer time.

An AlphaFold prediction helped to determine the structure of a bacterial protein that Lupas’s lab has been trying to crack for years. Lupas’s team had previously collected raw X-ray diffraction data, but transforming these Rorschach-like patterns into a structure requires some information about the shape of the protein. Tricks for getting this information, as well as other prediction tools, had failed. “The model from group 427 gave us our structure in half an hour, after we had spent a decade trying everything,” Lupas says.

Demis Hassabis, DeepMind’s co-founder and chief executive, says that the company plans to make AlphaFold useful so other scientists can employ it. (It previously published enough details about the first version of AlphaFold for other scientists to replicate the approach.) It can take AlphaFold days to come up with a predicted structure, which includes estimates on the reliability of different regions of the protein. “We’re just starting to understand what biologists would want,” adds Hassabis, who sees drug discovery and protein design as potential applications.

Update: Here's a Twitter thread, written by a professor of computational biology, that has a rather more sanguine take on the breakthrough. The TL;DR: 

But protein folding is not solved. Not only is it not even a well defined statement to say something like that (others have pointed out that there is a lot of subtlety in what one even means by "protein folding") but it's not even the winner for all the CASP14 proteins.