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The Secrets of the Basic Structure of Life Unveiled by Artificial Intelligence, Scientific Discovery of the Year!
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Well, I would go as far calling it the scientific discovery of the decade!
Sometimes it is easy to fill your mouth with expressions like "holy grail", "giant step" or "revolutionary discovery" when talking about a scientific achievement. But when it comes to revealing protein shapes with Googling simplicity, those words fit like a glove. This year it has been confirmed that artificial intelligence is capable of guessing the structure of these basic engines of life, proteins, one of the fundamental keys of biology. And it's a two-fold achievement: “First, because it solves a scientific problem that has been on the to-do list for 50 years. Second, it is a revolutionary technique that will greatly accelerate scientific discovery. It would have been the Discovery of the Year for either reason ”, says Holden Thorp, director of the influential scientific journal Science, which recognizes this scientific success.
Almost everyone has in mind the metaphor that DNA contains the instructions of life. Although it is the proteins that make it work: they perform these tasks, such as activating the movement of the muscles, determining the state of the tissues, transporting substances through the body or defending it from aggressions. DNA instructions alone, logically, do nothing. That manual just starts the raw materials, the amino acids, on the assembly line. They are arranged in a row on the belt so that the operators (the ribosomes) build those machines that are the proteins. They fold that row of amino acids to give proteins their extremely complex shape, a structure that determines their function: building a coffee maker is not the same as building a car engine.
Artificial intelligence is able to know if the coffee maker will be Italian, hexagonal and with a plastic handle, just by looking at the screws and the brass plates arranged in a two-dimensional row. Proteins are built by combining just 20 amino acids in myriad distributions and lengths. For this reason, deciphering the final disposition in three dimensions is an arduous and expensive job, that many laboratories cannot even consider. Deciphering these structures under normal conditions would be an effort that would take billions of years; even modest-sized proteins could take an astronomical number of possible appearances. With this achievement of computing, it is achieved in a while.
In mid-July, Baker and his colleagues published in Science that their RoseTTAFold artificial intelligence program had solved the structures of hundreds of proteins, all important for drug creation. At the same time and independently, the DeepMind scientists published their own achievement in Nature: their machine, AlphaFold, had drawn 350,000 proteins found in the human body, 44% of all known human proteins. In addition, they expect their database to grow to 130 million proteins belonging to all species, more than half the total number believed to exist. Both teams have made these structures available to all laboratories in the world, and also the tools to achieve new ones.
[link to www.science.org (secure)]
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