Google Unveils A.I. for Predicting Behavior of Human Molecules
Artificial intelligence is giving machines the power to generate videos, write computer code and even carry on a conversation.
It is also accelerating efforts to understand the human body and fight disease.
On Wednesday, Google DeepMind, the tech giant’s central artificial intelligence lab, and Isomorphic Labs, a sister company, unveiled a more powerful version of AlphaFold, an artificial intelligence technology that helps scientists understand the behavior of the microscopic mechanisms that drive the cells in the human body.
An early version of AlphaFold, released in 2020, solved a puzzle that had bedeviled scientists for more than 50 years. It was called “the protein folding problem.”
Proteins are the microscopic molecules that drive the behavior of all living things. These molecules begin as strings of chemical compounds before twisting and folding into three-dimensional shapes that define how they interact with other microscopic mechanisms in the body.
Biologists spent years or even decades trying to pinpoint the shape of individual proteins. Then AlphaFold came along. When a scientist fed this technology a string of amino acids that make up a protein, it could predict the three-dimensional shape within minutes.
When DeepMind publicly released AlphaFold a year later, biologists began using it to accelerate drug discovery. Researchers at the University of California, San Francisco, used the technology as they worked to understand the coronavirus and prepare for similar pandemics. Others used it as they struggled to find remedies for malaria and Parkinson’s disease.
The hope is that this kind of technology will significantly streamline the creation of new drugs and vaccines.
“It tells us a lot more about how the machines of the cell interact,” said John Jumper, a Google DeepMind researcher. “It tells us how this should work and what happens when we get sick.”
The new version of AlphaFold — AlphaFold3 — extends the technology beyond protein folding. In addition to predicting the shapes of proteins, it can predict the behavior of other microscopic biological mechanisms, including DNA, where the body stores genetic information, and RNA, which transfers information from DNA to proteins.
“Biology is a dynamic system. You need to understand the interactions between different molecules and structures,” said Demis Hassabis, Google DeepMind’s chief executive and the founder of Isomorphic Labs, which Google also owns. “This is a step in that direction.”
The company is offering a website where scientists can use AlphaFold3. Other labs, most notably one at the University of Washington, offer similar technology. In a paper released on Tuesday in the scientific journal Nature, Dr. Jumper and his fellow researchers show that it achieves a level of accuracy well beyond the state of the art.
The technology could “save months of experimental work and enable research that was previously impossible,” said Deniz Kavi, a co-founder and the chief executive of Tamarind Bio, a start-up that builds technology for accelerating drug discovery. “This represents tremendous promise.”
