AlphaFold: Five years of impact

Demis Hassabis, John Jumper, Pushmeet Kohli and Anna Koivuniemi on behalf of the AlphaFold team

Since 2020, AlphaFold has accelerated the pace of science and fueled a global wave of biological discovery — an achievement recognized with a Nobel Prize

Five years ago, AlphaFold 2 solved the protein structure prediction problem, unlocking new avenues of biological research and providing our first major proof point that AI can be a powerful tool to advance science.

John Jumper, one of the most instrumental scientists behind AlphaFold shares stories about his Nobel win, the tool's unexpected applications, and the shift in architecture from AlphaFold 2 to the more comprehensive AlphaFold 3.

Proteins are the complex, microscopic machines that drive every process in a living cell. Composed of long, unique chains of amino acids, they precisely fold into a 3D structure that largely defines the protein’s function - making knowledge of this shape critical for drug discovery and understanding disease.

p53 is a cellular tumor antigen related to diseases such as cancer. It is one of the most popular proteins in the AlphaFold Protein Database.

If a protein misfolds, it can lose its function and lead to disease, like Alzheimer’s and Parkinson’s. For decades, determining these structures was a monumental task, often taking a year or more of expensive, painstaking experimental work.