Skip to Content
Artificial intelligence

DeepMind’s AI will accelerate drug discovery by predicting how proteins fold

December 3, 2018

Google DeepMind has developed a tool to predict the structure of proteins from their genetic sequence, marking a noteworthy example of using AI in the process of scientific discovery.

How it works: The system, called AlphaFold, models the complex folding patterns of long chains of amino acids, based on their chemical interactions, to form the three-dimensional shape of a protein. This is known as the “protein folding problem,” which has challenged scientists for decades.

Why it matters: The shape of a protein dictates its function in the body, so being able to predict a protein’s structure allows scientists to synthesize new protein-based drugs to treat diseases or new enzymes to break down pollutants in our environment.

Training data: The DeepMind team trained deep neural networks to predict the distances between pairs of amino acids and the angles between their chemical bonds, using the massive amounts of data available from genomic sequencing. The resulting system generates highly accurate protein structures, exceeding previous prediction techniques, the team says.

The bigger picture: DeepMind isn’t the only one working to accelerate scientific discovery with machine learning. Many other companies and researchers have sought to develop algorithms for discovering new drugs and new materials. 

Deep Dive

Artificial intelligence

This new data poisoning tool lets artists fight back against generative AI

The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. 

Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist

An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.

Unpacking the hype around OpenAI’s rumored new Q* model

If OpenAI's new model can solve grade-school math, it could pave the way for more powerful systems.

Minds of machines: The great AI consciousness conundrum

Philosophers, cognitive scientists, and engineers are grappling with what it would take for AI to become conscious.

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.