LONDON — Three scientists who discovered powerful techniques to predict and even design novel proteins — the building blocks of life — were awarded the Nobel Prize in chemistry Wednesday. Their work used advanced technologies, including machine learning, and holds the potential to transform how new drugs are made.

The prize was awarded to David Baker, who works at the University of Washington in Seattle, and to Demis Hassabis and John Jumper, who both work at Google DeepMind, a British-American artificial intelligence research laboratory based in London.

Heiner Linke, chair of the Nobel Committee for Chemistry, said the award honored research that unraveled long-standing scientific mysteries.

“That was actually called a grand challenge in chemistry, and in particular in biochemistry, for decades. So, it’s that breakthrough that gets awarded today,” he said.

Proteins are complex molecules with thousands of atoms that twist, turn, loop and spiral in a countless array of shapes. The shape of a protein determines its biological function. For decades, scientists have dreamed of being able to efficiently design and build new proteins.

Baker, whose work has received funding from the National Institutes of Health since the 1990s, created a computer program called Rosetta that helped analyze information about existing proteins in comprehensive databases in order to build new proteins that don’t exist in nature.

“It seems that you can almost construct any type of protein now with this technology,” said Johan Åqvist of the Nobel committee.

Hassabis and Jumper created an AI model that has been able to predict the structure of virtually all the 200 million proteins that researchers have identified, the committee added.

The duo “managed to crack the code. With skillful use of artificial intelligence, they made it possible to predict the complex structure of essentially any known protein in nature,” Linke said.