Nobel Prize in chemistry awarded to three scientists for groundbreaking protein research
- In Reports
- 07:07 PM, Oct 09, 2024
- Myind Staff
On Wednesday, three scientists were jointly awarded the Nobel Prize in Chemistry for their ground-breaking discovery that deciphered the code of proteins, the molecules that are essential to life. The rapid scientific transformation has resulted from discoveries made by Demis Hassabis and John M. Jumper of Google DeepMind in the United Kingdom, as well as David Baker at the University of Washington.
Researchers can now predict how proteins twist and fold to form intricate 3D structures that can block viruses, build muscle, or break down plastic thanks to a powerful computational tool that Hassabis and Jumper developed. The capacity to create proteins with unique shapes and functions on demand was made possible by Baker's work.
“We glimpsed at the beginning that it would be possible to create a whole new world of proteins that might address a lot of the problems faced by humans in the 21st century, and now it’s becoming possible,” Baker stated on the phone during the announcement of the prize by the Royal Swedish Academy of Sciences in Stockholm. The chemical machinery of life is made up of proteins. They construct our bodies, manufacture and break other molecules, and protect us from infections. Despite being composed of amino acid strings, their 3D form dictates their function. It has been a 50-year quest to predict those shapes from their building blocks, one of biology's holy grails.
However, the issue was difficult. In 1994, researchers started a competition known as the Critical Assessment of Protein Structure Prediction (CASP), which can be compared to the Olympics of protein folding. Participants in this competition had to predict the structures of proteins whose forms had just been decoded but had not yet been made public. Development was sluggish until 2018 when Hassabis and Jumper started using artificial intelligence-based tools to solve the issue. Their second AI tool, AlphaFold2, was able to predict protein structure and proved to be just as accurate as laborious conventional methods like X-ray crystallography.
One of the founders of CASP and a computational biologist at the University of Maryland, John Moult, said he was amazed in the middle of 2020 to learn that the Google DeepMind team had cracked one of the greatest scientific puzzles. “I was there at the birth of the problem — it looked intractable, intractable, intractable. And then, suddenly, you’re there. It’s an extraordinary scientific journey,” Moult said. “You see a whole field emerging and struggling and it seems impossible, and then you get there.”
This year's second Nobel prize emphasises just how drastically artificial intelligence is altering society. The physics prize was given out for work that served as the foundation for AI. “This allows individual scientists to do so much more,” Hassabis said in an interview for the Nobel Prize website. “These systems, they are tools … they can’t figure out what the right question is to ask, what the right hypothesis or the right conjecture [is], and all of that has to come from a human scientist.” A member of the Chemistry Nobel Committee, Johan Åqvist, said that Hassabis and Jumper "have designed a fantastic, ingenious neural network that solved this problem of protein structure prediction. This is among the very first significant advances in AI science."
Using Rosetta as a tool, Baker also worked on the protein structure prediction problem. However, he went one step further and invented methods for producing entirely novel proteins, which have countless uses in the development of vaccines, the detection of chemicals in the environment, and the synthesis of novel medications.
According to Jon Lorsch, head of the National Institute of General Medical Sciences at the National Institutes of Health, which has supported Baker's lab since 1995, the field has grown tremendously. “Structure determines function, it’s as easy as that. If we can design proteins to look in a certain way, then they might have a certain function that could be useful,” Lorsch said.
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