Artificial intelligence from Deepmind simulated 20,000 human protein structures
DEPMIind specialists have gathered the most complete database of human protein structures created by Alphafold neural network. The set contains 20,000 three -dimensional models.
Today with @emblebi, we’re launching the #AlphaFold Protein Structure Database, which offers the most complete and accurate picture of the human proteome, doubling humanity’s accumulated knowledge of high-accuracy human protein structures — for free: https://t.Co/ vtbgmtkkhy 1/ pic.Twitter.COM/XGBQTN2FUC
– Deepmind (@deepmind) July 22, 2021
The first version of the algorithm predicted the protein structure with an accuracy of 98.5%, and Aderinser – Page also calculated the position of about 60% of amino acids in these chains. Scientists hope that this will help to build a proteomic map that includes all the proteins encoded by the human genome.
According to researchers, Alphafold surpasses the particle accelerator and other devices used to study the structure of proteins over the past 50 years. In particular, scientists managed to accurately determine the structure of molecules associated with diabetes, tungsten syndrome and other diseases that had not previously been able to identify experimentally.
In addition to human proteins, researchers conducted calculations for two dozen living organisms, including fruit flies, mice and yeast. In total, the algorithm simulated 350,000 protein structures.
In the near future, scientists plan to expand the base and determine the three -dimensional structure of 100 million proteins known to science. They hope that this will bring humanity closer to understanding the structure of living organisms and inventing new types of drugs.
Recall that in March, scientists from NVIDIA and Harvard University developed artificial intelligence, accelerating the analysis of the human genome.
In July, researchers from the University of California at San Francisco presented a neuro interface that allowed a paralyzed man to speak.
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