Skip to Content
Artificial intelligence

AI for protein folding

DeepMind has opened new paths for drug discovery and design by solving a 50-year-old problem in biology.

Concept illustration of using AI for predicting protein folding
Andrea D'aquino, protein model courtesy of AlphaFold

Key players

DeepMind, Isomorphic Labs, Baker Lab

 

Availability

Now

By the end of 2020, DeepMind, the UK-based artificial-intelligence lab, had already produced many impressive achievements in AI. Still, when the group’s program for predicting protein folding was released in November of that year, biologists were shocked by how well it worked. 

Nearly everything your body does, it does with proteins. Understanding what individual proteins do is therefore crucial for most drug development and for understanding many diseases. And what a protein does is determined by its three-dimensional shape.

A protein is made up of a ribbon of amino acids, which folds up into a knot of complex twists and twirls. Determining that shape—and thus the protein’s function—can take months in a lab. For years, scientists have tried computerized prediction methods to make the process easier. But no technique ever came close to matching the accuracy achieved by humans. 

That changed with DeepMind’s AlphaFold2. The software, which uses an AI technique called deep learning, can predict the shape of proteins to the nearest atom, the first time a computer has matched the slow but accurate techniques used in the lab. 

Scientific teams around the world have started using it for research on cancer, antibiotic resistance, and covid-19. DeepMind has also set up a public database that it’s filling with protein structures as AlphaFold2 predicts them. It currently has around 800,000 entries, and DeepMind says it will add more than 100 million—nearly every protein known to science—in the next year.  

DeepMind has spun off this work into a company called Isomorphic Labs, which it says will collaborate with existing biotech and pharma companies. The true impact of AlphaFold2 may take a year or two to be clear, but its potential is rapidly unfolding in labs around the world.

As part of our 10 Breakthrough Technologies series, explore how DeepMind shifted from playing games to solving one of the hardest problems in science.

Deep Dive

Artificial intelligence

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.