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Google AI figured out the problem of protein synthesis: diseases will recede
01.12.2021 [13:44],
Gennady Detinich

DeepMind, owned by Alphabet (Google), reports significant breakthrough in protein folding prediction. Proteins are assembled from linear sequences of amino acids, which, after synthesis, take on a unique spatial form and there are countless such forms. This is not a task for an experimenter, but for an AI, with which the DeepMind platform coped with a bang. Discovery Leads to New Drugs and More.

Of hundreds of millions of proteins (combinations of amino acids), only 0.1% of compounds have been studied, whose spatial form is also well known. Unknown proteins, as well as compounds that have not yet been confirmed experimentally, scientists are trying to predict using computers. But until now, no one could calculate with a sufficient degree of accuracy what 3D-form a protein will take from a given set and sequences of amino acids.

To determine the effectiveness of algorithms (AI) in predicting protein folding, the CASP (Critical Asessement of techniques for protein Structure Prediction) competition is held every two years. Algorithms “fold” unknown proteins, the structure of which is studied later and compared with the prediction results. In this year’s competition, DeepMind reports, the AlphaFold algorithm predicted the spatial structure of a protein with an average score of 92.4 on the Global Distance Test (GDT) metric. Note, 90 GDT scores are considered valid for experimental confirmation. This means that the algorithm did a better job than the experimenters, not to mention significantly less prediction time.

The problem of predicting protein folding is considered one of the 125 most important problems for solving modern problems, as well as one of the greatest problems of biology over the past 50 years. If the DeepMind algorithm is as good at this, as the company claims, then we can expect a breakthrough in the discovery of new drugs, vaccines and in understanding the occurrence and course of many diseases.