Let’s hold off the champagne until an actual drug is developed using this tech
The AI-powered protein-folding model AlphaFold has predicted more than 200 million proteins, nearly all such structures known to science, DeepMind said on Thursday.
Proteins are complex biological molecules produced in living organisms from instructions stored in DNA. Made from as many as 20 types of amino acids, these nano-scale chains perform vital cellular tasks to carry out all sorts of bodily functions. Knowing the three-dimensional form of proteins is important since its physical structure provides hints at how it behaves, and what purpose it serves, which helps us do things like develop drugs, and create copycat proteins for those lacking them.
Some proteins are helpful, such as those involved in digesting food while others can be harmful, such as those involved in the growth of tumors. Figuring out their complicated wriggly shapes, however, is difficult. Molecular biologists can spend years conducting experiments to decipher a protein’s structure, and AlphaFold can do this in minutes, depending on how large the molecule is, from the amino acid composition.
AlphaFold was trained on hundreds of thousands of known protein structures, and learned the relationships between the constituent amino acids and the final overall shapes. Given an arbitrary input amino acid sequence, the model can predict a 3D protein structure. Now, the model has predicted nearly all protein structures known to science.
Working together with the European Bioinformatics Institute, DeepMind has expanded its AlphaFold Protein Structure Database to contain over 200 million 3D shapes of proteins from animals to plants, bacteria to viruses – an increase of more than 200x from nearly a million molecules to at least 200 million molecules in just a year.
