Nobel Chemistry Prize goes to AlphaFold, Rosetta creators - another win for AI

Let’s just hope they don’t give the literature award to a bot, too

This year's Nobel Prizes are shaping up to be a triumph for AI. After awarding the physics prize to early AI pioneers yesterday, the chemistry prize has now gone to the creators of AI protein prediction platform AlphaFold and protein design tool Rosetta.

DeepMind cofounder and CEO Demis Hassabis and director John Jumper will share half of the Nobel Prize in Chemistry for their work on AlphaFold models. The second generation can predict almost all known protein structures - more than 200 million in total. 

"The team trained AlphaFold2 on the vast information in the databases of all known protein structures and amino acid sequences and the new AI architecture started delivering good results," the Nobel committee said [PDF]. 

When it entered the 2020 Critical Assessment of Protein Structure Prediction (CASP) competition, AlphaFold2 performed almost as well as X-ray crystallography (the prior gold standard in modeling protein structures) "in most cases," the committee added. "Previously, it often took years to obtain a protein structure, if at all. Now it can be done in a few minutes."

Jumper, who came to DeepMind after the Google subsidiary had already built the initial AlphaFold that improved on prior CASP results but was still only about 60 percent accurate, was essential to DeepMind 2's success, the Nobel body said. 

"AlphaFold2 was coloured by Jumper's knowledge of proteins," the committee explained. "The team also started to use the innovation behind the recent enormous breakthrough in AI: neural networks called transformers." 

So maybe some additional AI tech helped, too. 

Your bespoke protein is ready

Although AlphaFold has been fundamental in helping humans become better predictors of protein shapes, which play a critical role in their function, it can't develop drugs or make anything new. 

That's where Rosetta, designed by University of Washington biochemistry professor David Baker, comes in.

Baker developed his own protein prediction software, dubbed Rosetta, in the 1990s, and when it entered the CASP competition in 1998, it did well "in comparison to other participants," the Nobel committee said. After the competition, Baker and his team got the idea to use the software in reverse: Instead of using amino acid sequences to predict the shape of a protein, they began experimenting on whether inputting the shape of a desired protein would suggest an amino acid sequence to create it. 

Lo and behold, it worked perfectly and led to the creation of Top7, "the first protein that was entirely different to all other known existing proteins," according to the Nobel folks.

Proteins are fundamental to understanding biochemistry and are involved in the creation of biological structures like muscles, as well as chemicals like hormones and antibodies. By enabling the creation of new proteins, humans can do all sorts of things. 

"This can lead to new nanomaterials, targeted pharmaceuticals, more rapid development of vaccines, minimal sensors and a greener chemical industry – to name just a few applications," the committee said. 

The chemistry Nobel being awarded for AI development marks the second time this year. The Nobel in physics was awarded yesterday to John Hopfield for his work developing early neural networks, and to AI godfather Geoffrey Hinton for giving machines the ability to interpret information they're trained to recall. 

Three Nobels have been awarded so far this year; the first, for physiology and medicine, went to Victor Ambros and Gary Ruvkun for the discovery of microRNA, which regulates gene expression and protein production. Nobel prizes for literature and peace have not yet been handed out. ®