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American biochemist David Baker and Google DeepMind scientists Sir Demis Hassabis and John Jumper have jointly won the Nobel Prize in Chemistry for his or her work in unlocking the biological secrets of proteins that form the idea of life and health.
Baker received half of the SKr11 million ($1.06 million) prize for his research on computer-aided protein design and the DeepMind duo received the opposite half for predicting protein structure, the Nobel Assembly said on Wednesday Stockholm with.
The prize recognizes major advances in techniques for understanding how proteins work and interact to make living cells function. The methods, including DeepMind's artificial intelligence-based AlphaFold models, have raised hopes that they could possibly be powerful tools in developing recent therapies for difficult-to-treat diseases.
Baker, director of the Institute for Protein Design on the University of Washington, achieved “the just about inconceivable feat of constructing entirely recent forms of proteins,” the Nobel laureates said. Hassabis and Jumper had “developed an AI model to resolve a 50-year-old problem: predicting the complex structures of proteins.”
“Both discoveries open up enormous possibilities,” said Heiner Linke, chairman of the Nobel Chemistry Committee.
In a phone call with the Nobel Committee after the announcement, Baker said he felt “deeply honored” and stood “on the shoulders of giants” given the contributions of other researchers. “Our recent AI methods are far more powerful than traditional scientific modeling methods. I'm really enthusiastic about all of the ways protein design can now make the world a greater place in health, medicine and medicine. . . in technology and sustainability,” he added.
Baker has been using computer-aided design because the early 2000s to construct novel proteins from the 20 different constructing blocks, called amino acids, that make up most of them. His teams have made recent structures to be used in vaccines, nanomaterials and tiny sensors.
In 2022, Hassabis and Jumper's teams used the AlphaFold AI model to construct essentially the most complete and accurate database thus far for nearly every known protein. The breakthrough, involving about 200 million proteins, is predicted to significantly reduce the time required for biological discoveries.
Hassabis, co-founder and chief executive of Google DeepMind, the Silicon Valley giant's AI research arm, described the AlphaFold innovation in March as a more efficient method to “search for a needle in a haystack.”
“That’s what science actually matters. . . If you possibly can frame an issue in this fashion, some of these AI systems that we are actually developing might be very useful.”
The third iteration of AlphaFold, which DeepMind unveiled in May, goes beyond proteins and examines other biochemical networks that sustain life in our body's cells. AlphaFold 3 covers the genetic codes of DNA and RNA in addition to ligands, molecules that bind to others and might be necessary markers of disease.
The Nobel Committee said there have already been many applications of AlphaFold models, resembling developing vaccines and searching for brand new enzymes within the protein database that would break down plastics.
DeepMind has spun off a drug discovery arm often called Isomorphic Labs to construct on AlphaFold's scientific breakthroughs. Hassabis told the Financial Times this 12 months that the aim was to make use of the model to shorten the typical discovery phase – when potential drugs are identified before clinical trials – from five years to 2.
“AlphaFold has given researchers an unprecedented ability to predict what proteins 'seem like' in three dimensions,” said Michael Dennis, scientific director of CAS, a division of the American Chemical Society. “The impact of this technology on understanding disease mechanisms and the event of medicine and recent therapies is immense.”
The Chemistry Prize is the third of six annual Nobel Prizes announced on consecutive weekdays. The winners of the literary awards shall be announced on Thursday, followed by Peace on Friday and Economy on Monday.
