SAN FRANCISCO — You can think of it as a World Cup of biochemical research.
Every two years, hundreds of scientists enter a global competition. Tackling a biological puzzle they call “the protein folding problem,” they try to predict the three-dimensional shape of proteins in the human body. No one knows how to solve the problem. Even the winners only chip away at it. But a solution could streamline the way scientists create new medicines and fight disease.
The contest, the Critical Assessment of Structure Prediction, was not won by academics. It was won by DeepMind, the artificial intelligence lab owned by Google’s parent company.
DeepMind specializes in “deep learning,” a type of artificial intelligence that is rapidly changing drug discovery science. A growing number of companies are applying similar methods to other parts of the long, enormously complex process that produces new medicines. These AI techniques can speed up many aspects of drug discovery and, in some cases, perform tasks typically handled by scientists.
“It is not that machines are going to replace chemists,” said Derek Lowe, a longtime drug discovery researcher and the author of In the Pipeline, a widely read blog dedicated to drug discovery. “It’s that the chemists who use machines will replace those that don’t.”
If scientists can predict a protein’s shape, they can better determine how other molecules will “bind” to it — attach to it, physically — and that is one way drugs are developed. A drug binds to particular proteins in your body and changes their behavior.
In the latest contest, DeepMind made these predictions using “neural networks,” complex mathematical systems that can learn tasks by analyzing vast amounts of data. By analyzing thousands of proteins, a neural network can learn to predict the shape of others.
Many of the academics who competed used methods that were similar to what DeepMind was doing. But DeepMind won the competition by a sizable margin — it improved the prediction accuracy nearly twice as much as experts expected from the contest winner.
This kind of AI research benefits from enormous amounts of computing power, and DeepMind can lean on the massive computer data centers that underpin Google.
“It allows us to be much more creative, to try many more ideas, often in parallel,” said Demis Hassabis, the chief executive and a co-founder of DeepMind.
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