DeepMind AI Solves 50-Year Protein Folding Challenge
Alphabet's DeepMind team wins a major biennial contest by using its AlphaFold AI to accurately predict the 3D structures of complex proteins, a breakthrough that promises to accelerate disease treatment research.
Alphabet's DeepMind team achieves a massive medical breakthrough as its AlphaFold AI system wins a grand challenge in protein folding. Proteins perform the essential work within our cells, but researchers must understand their complex three-dimensional folds to determine what they actually do. This knowledge is a critical prerequisite for developing many new medical treatments for devastating diseases.
Predicting these 3D structures from a one-dimensional amino acid sequence is a notoriously difficult computational problem that scientists have pursued for fifty years. A typical protein features so many possible structural configurations that brute force calculation would take longer than the age of the universe to solve. While traditional experimental methods like X-ray crystallography provide answers, they remain slow and expensive processes that delay vital medical research.
AlphaFold successfully tackles this challenge by predicting protein structures with near-atomic accuracy in two-thirds of the test cases during the biennial CASP contest. By providing a fast and highly accurate computational alternative to traditional methods, this AI system gives researchers a powerful new tool. This capability ultimately allows the medical community to analyze cells and viruses much more quickly as they work to understand and combat various diseases.