Published on December 3rd, 2020 | by Emergent Enterprise0
AI System Solves 50-year-old Protein Folding Problem in Hours
The word “transformative” has become overused or diluted when talking about the impact of emergent technologies but occasionally it is justified. This is definitely one of those times. This post from Rachael Rettner at LiveScience shares a huge advancement in biological research using AI to unfold proteins, a previously laborious and complicated task. Why is this important? Unfolding proteins is one of the major steps in conquering major diseases and viruses. The Google DeepMind AI does this almost insurmountable task in hours! Yes, artificial intelligence has potential drawbacks such as in security but when monumental advancements like this happen, the life-changing potential of AI stands out.
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An artificial intelligence company that gained fame for designing computer systems that could beat humans at games has now made a huge advancement in biological science.
The company, DeepMind, which is owned by the same parent company as Google, has created an AI system that can rapidly and accurately predict how proteins fold to get their 3D shapes, a surprisingly complex problem that has plagued researchers for decades, according to The New York Times.
Figuring out a protein’s structure can require years or even decades of laborious experimentation, and current computer simulations of protein folding fall short on accuracy. But DeepMind’s system, known as AlphaFold, required only a few hours to accurately predict a protein’s structure, the Times reported.
Proteins are large molecules that are essential for life. They are made up of a string of chemical compounds known as amino acids. These “strings” fold in intricate ways to create unique structures that determine what the protein can do. (For example, the “spike” protein on the new coronavirus allows the virus to bind to and invade human cells.)
Nearly 50 years ago, scientists hypothesized that you could predict a protein’s structure knowing just its sequence of amino acids. But solving this “protein folding problem” has proved enormously challenging because there are a mind-boggling number of ways in which the same protein could theoretically fold to take on a 3D structure, according to a statement from DeepMind.
Twenty-five years ago, scientists created an international competition to compare various methods of predicting protein structure — something of a “protein olympics,” known as CASP, which stands for Critical Assessment of Protein Structure Prediction, according to The Guardian.
In this year’s challenge, AlphaFold’s performance was head and shoulders above its competitors’. It achieved a level of accuracy that researchers were not expecting to see for years.
“This computational work represents a stunning advance on the protein-folding problem, a 50-year-old grand challenge in biology,” Venki Ramakrishnan, president of the Royal Society in the United Kingdom, who was not involved with the work, said in a statement. “It has occurred decades before many people in the field would have predicted. It will be exciting to see the many ways in which it will fundamentally change biological research.”