There’s an age-old adage in biology: structure determines function. In order to understand the function of the myriad proteins that perform vital jobs in a healthy body—or malfunction in a diseased one—scientists have to first determine these proteins’ molecular structure. But this is no easy feat: protein molecules consist of long, twisty chains of up to thousands of amino acids, chemical compounds that can interact with one another in many ways to take on an enormous number of possible three-dimensional shapes. Figuring out a single protein’s structure, or solving the protein-folding problem, can take years of finicky experiments.
But earlier this year an artificial intelligence program called AlphaFold, developed by the Google-owned company DeepMind, predicted the 3D structures of almost every known protein —about 200 million in all. DeepMind CEO Demis Hassabis and senior staff research scientist John Jumper were jointly awarded this year’s $3-million Breakthrough Prize in Life Sciences for the achievement, which opens the door for applications that range from expanding our understanding of basic molecular biology to accelerating drug development.
DeepMind developed AlphaFold soon after its AlphaGo AI made headlines in 2016 by beating world Go champion Lee Sedol at the game. But the goal was always to develop AI that could tackle important problems in science, Hassabis says. DeepMind has made the structures of proteins from nearly every species for which amino acid sequences exist freely available in a public database.
