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2020 m. lapkričio 30 d., pirmadienis

AI is able to predict the structure of simple proteins. Nobody knows how it does that

 "It's a somewhat misleading picture: DNA is often referred to as the "blueprint of life", but "list of components" would be more appropriate. Because the biochemical information is stored in the DNA, according to which cells produce proteins that are necessary for almost every life process. But initially there is only a long chain of linked amino acid building blocks. How these fold into the three-dimensional nanomachines that keep life in single-cell organisms or huge organisms like gray whales going is a well-protected secret of nature even after decades of intensive research. 

It's like a three-dimensional moving puzzle 

According to a press release, the British company Deep Mind, a subsidiary of the Google holding Alphabet, is now in the process of solving the mystery. An AI program called Alpha Fold can predict with amazing reliability how an amino acid chain in a cell will fold into a functioning biomolecule. You can think of it as a three-dimensional moving puzzle in which millions of atoms have to find their place. 

The AI ​​is unable to explain why this happens. But even the knowledge of the folding result is progress, as experts explain. With Alpha Fold, the developers have taken part in an international competition in which computer programs compete to predict the three-dimensional structure of proteins based solely on the one-dimensional sequence of building blocks. The company's team used machine learning; the software was able to predict 70 out of 100 structures very precisely. The jury of the competition knew the structure of the proteins through so-called crystal structure analyzes. The shape of molecules is determined by X-rays in a very complex and not always successful process. 

The competition focused on comparatively simple proteins, but for these the folding problem is now "essentially solved", according to the company's press release. Many experts would not go that far. "It is fantastic and of great scientific value to have a method that produces atomic models so successfully. However, I don't really think the 'code of protein folding' has been cracked," says Gunnar Schröder, head of the Computational Structural Biology research group at the research center Jülich. "Alpha Fold is basically like knowing a person who can experimentally determine a protein structure in a matter of hours but doesn't tell us how to do it." 

The shape determines the function of the nanomachines 

The question of the three-dimensional shape of a protein is not only of academic interest. The shape determines the function of these nanomachines, which are involved in all life processes, be it breathing, digesting, speaking, walking or thinking. Every cell is bulging with these nanometer-sized biomolecules. That is why they are also important targets for pharmaceuticals. Even without it being clear how the AI ​​comes to its structural predictions, it can help the researchers in their work. "The reported accuracy of the method is outstanding," says Alexander Schug, head of the "Multiscale Biomolecular Simulation" research group at the Karlsruhe Institute of Technology. The conventional methods of structure elucidation could be improved by Alpha Fold, "which is not only relevant for basic research but also for pharmaceutical and medical research.""

Using more simple language, seeing the spatial structures of proteins will make it easier for drug developers to select molecules that can affect those structures, e.g. block interactions with coronavirus or stop cancer cell division. Good times are starting for those who are serious about biotechnology.

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