DeepMind's AI Accelerates the Discovery of Drugs by Predicting Protein Folding
Google DeepMind has developed a tool to predict the structure of proteins based on their genetic sequence. This is a remarkable example of the use of AI in scientific discovery.  Here's how it works: The system, called AlphaFold, models the complex folding patterns of long chains of amino acids based on their chemical interactions to form the three-dimensional shape of a protein. This is known as the "protein folding problem" that has been challenging scientists for decades.
Why it matters: The shape of a protein determines its function in the body, allowing scientists to predict the structure of a protein
Training data: The DeepMind team trained deep neural networks To predict the distances between amino acid pairs and the angles between them their chemical bonds, using the vast amounts of data available in genomic sequencing. The resulting system generates highly accurate protein structures that exceed previous forecasting techniques.
The larger image: DeepMind is not the only one to accelerate scientific discovery through machine learning. Many other companies and researchers have tried to develop algorithms for the discovery of new drugs and new materials.