One of the Biggest Problems in Biology Has Finally Been Solved

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 3-D 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 Lee Sedol, 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.

Scientific American spoke with Hassabis about developing AlphaFold, some of its most exciting potential applications and the ethical considerations of highly sophisticated AI.

[An edited transcript of the interview follows.]

Why did you decide to create AlphaFold, and how did you get to the point where it can now fold practically every known protein?

We pretty much started the project roughly the day after we came back from the AlphaGo match in Seoul, where we beat Lee Sedol, the world [Go] champion. I was talking to Dave Silver, the project lead on AlphaGo, and we were discussing “What’s the next big project that DeepMind should do?” I was feeling like it was time to tackle something really hard in science because we had just solved more or less the pinnacle of games AI. I wanted to finally apply the AI to real-world domains. That’s always been the mission of DeepMind: to develop…