AI in 2021 Laboratory DeepMind DeepMind announced the development of AlphaFold, the company’s first digital biological neural network. The model can accurately predict the 3D structure of proteins, which determines the functions these molecules perform. “We’re just floating bags of water,” says Pushmeet Kohli, DeepMind’s vice president of research. “What makes us special are the building blocks of life: proteins. How they interact with each other is what creates the magic of life.”
AlphaFold was deemed the breakthrough invention of the year by Science magazine in 2021. In 2022, The most cited research paper in AI“People are [protein structures] “For decades we didn’t make much progress,” Kohli said. “Then AI came along.” DeepMind also AlphaFold protein structure databaseIt contains the protein structures of nearly every organism whose genome has been sequenced and is freely available to scientists around the world.
is more than 1.7 million researchers in 190 countries The company has used the technology in a variety of research endeavors, from designing plastic-eating enzymes to developing more effective malaria vaccines. A quarter of Alphafold research has been devoted to understanding cancer, COVID-19, and neurodegenerative diseases such as Parkinson’s and Alzheimer’s. Last year, DeepMind released the next generation of Alphafold, which extended its structure prediction algorithm to biomolecules such as nucleic acids and ligands.
“It’s democratized scientific research,” Kohli says. “Scientists working on neglected tropical diseases in developing countries who couldn’t get funding to calculate protein structures can now access the AlphaFold database and get these predictions for free with the click of a button.” For example, the Drugs for Neglected Diseases Initiative, one of DeepMind’s early partners, used AlphaFold to develop drugs to treat relatively understudied diseases that affect millions of people (such as sleeping sickness, Chagas disease, and leishmaniasis).
DeepMind’s latest breakthrough is called Alpha Missense. The model classifies so-called missense mutations, which are genetic changes that cause a different amino acid to be produced at a specific position in a protein. Such mutations can change the function of the protein itself, and Alpha Missense gives the mutation a likelihood score of whether it is pathogenic or benign. “Understanding and predicting these effects is essential for discovering rare genetic diseases,” Kohli says. The algorithm, released last year, has classified about 89% of missense mutations in humans. Until now, researchers have classified only 0.1% of possible mutations clinically.
“This is just the beginning,” Kohli says. Ultimately, he believes AI will enable us to create virtual cells that will dramatically accelerate biomedical research and allow biology to be studied in computers rather than in real-world labs. “With AI and machine learning, we finally have the tools to understand this incredibly sophisticated system we call life.”
This article appears in the July/August 2024 issue. WIRED UK magazine.
