This year's Nobel Prize in Chemistry has been awarded for protein research. American scientist David Baker received half of the prize for computational protein design. British scientist Demis Hassabis and American scientist John M. Jumper got the other half for protein structure estimation.
What is the reason for giving the Nobel Prize in Chemistry to protein research? In fact, proteins are the main reason behind the diversity of life around. These can be called the building blocks of life. But scientists like to call them 'chemical tools fundamental to life'.It is this protein that controls and manages the chemical reactions that are the basis of life. Protein also acts as a structural unit of hormones, antibodies and various organs or tissues.
This year's Nobel-winning scientists have cracked the code behind the structure of that protein. To put it simply, they have hacked the protein!
Let's be clear. Any protein is usually made up of 20 different amino acid combinations. That is, these amino acids can be said to be the basic building blocks of life. Amino acids combine to form proteins, and they control all biological chemical reactions.19th century scientists knew about this importance of protein. Knew, the structural unit of life is protein. But it was not until the 1950s that the process of understanding these details began. Prior to this, scientists had not found a way to analyze proteins.
At that time, two researchers from Cambridge University, John Kendrew and Max Perutz, created the first three-dimensional model of proteins through X-ray crystallography. For this, they were awarded the Nobel Prize in 1962.
Afterward, the researchers primarily used X-ray crystallography to create images of nearly 200,000 proteins. This laid the foundation for this year's Nobel Prize. How? The story dates back to 2003.
There was a time when people thought it was impossible to create proteins that didn’t exist in nature. David Baker shattered that notion. In 1998, he wrote a program in a relatively old coding language called Fortran. He named it Rosetta. Later, Rosetta was converted into the C++ language and became Rosetta2 or Rosetta++. And this Rosetta worked wonders!
With his research team, Baker first designed a protein structure. To determine what kind of amino acid sequence would be required to create it, Rosetta searched for the structures of known proteins. These structures were stored on a server. Rosetta picked some sequences from one protein, some from another, and by combining different fragments of proteins, the team of scientists designed the desired protein!
Now it was time for testing. The necessary gene was introduced into bacteria (many people may be familiar with how insulin, a diabetes treatment, is produced by inserting genes into bacteria). The bacteria’s body produced amino acids from the gene, which then formed the protein. Through X-ray crystallography, the structure was examined, and the scientists were astonished to discover that David Baker’s Rosetta had achieved the impossible. Using a computer, Baker had successfully created an entirely new type of artificial protein!
He didn’t stop at just designing this unusual protein. Together with his team of scientists, he continued to design one unique protein after another. Some of these proteins were used in pharmaceuticals, some in vaccine development; others were used to create nanomaterials and ultra-small sensors.
Now let's talk about the second study. This involves predicting protein structures. As mentioned earlier, amino acids combine to form proteins. These amino acids are connected like a long string, creating a three-dimensional structure. One crucial thing to understand here is that the function of a protein depends on its structure. Since the 1970s, researchers have been trying to predict protein structures by examining amino acid sequences. This task is extremely difficult. But just four years ago, Demis Hassabis and John Jumper came forward with a solution to this challenging problem. How did they solve it? Well, with AI, of course!
The AI that makes the impossible possible. This was once again proven in 2020 when these two scientists developed an AI model called AlphaFold2. Using this model, researchers virtually simulated and arranged amino acids to predict the structure of 200 million proteins. This isn’t just revolutionary for chemistry or biochemistry; it’s a groundbreaking step in understanding human and other animal bodies, as well as medical science. Since then, over 2 million people from 190 countries have already used the AlphaFold2 model. It’s being used to better understand issues like antibiotic resistance and to design enzymes that can break down plastics.
Without proteins, life wouldn’t be possible. And now, thanks to this year’s Nobel-winning trio of scientists, we can design proteins as we wish, predict the structure and function of these new sequences of amino acids, and this research will undoubtedly be considered one of the most invaluable contributions to human history.
To end with a bit of a fun question: Who actually won this Nobel Prize—scientists or AI? After the Nobel Prize in Physics, this year’s Chemistry Nobel raises the question even more strongly!"
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