Thanks to artificial intelligence, it is possible to determine the structure of 20 million proteins
London: A database of all the known proteins around the world has been created in which with the help of artificial intelligence, the structure and shape of the protein can be searched exactly like Google and its details can be seen.
The project, named AlphaFold, has been hailed by experts as a revolutionary process that will open new doors in the treatment of cancer and disease. We will not only be able to know the diseases well but new ways of treating them will also come out.
The heart and soul of this research, however, is the software and algorithms from an organization called DeepMind that have made this long-standing task possible and named Alphafold. Proteins are the building blocks of life made up of chains of amino acids. However, most proteins are folded into a three-dimensional complex. This process is called protein folding. Although the folding instructions come from DNA, the amino acid composition makes protein folding very complicated, and so far only a handful of protein conformations have been known out of a total of 20 million proteins.
In November 2020, a research group called DeepMind announced the ‘Alphafold’ project, which can instantly predict protein folding with its algorithm. It incorporates the genetic code and all of the genome’s information, after which it predicts the shape of the protein based on the instructions. Three-dimensional images of millions and millions of proteins have been made so far.
Last year, DeepMind reported the protein structure of 20 different species, including the structure of all 20,000 proteins in the human body, which were later stored in a database. This work has now been extended to provide three-dimensional (3D) structures of millions of proteins as predicted by the software.
It covers the entire protein universe, according to Damas Hessabs, head of DeepMind. It has the complete ability to predict the proteins of plants, bacteria, animals and other organisms. Through this research we will be able to solve problems like food security, complex diseases and agricultural production.