For decades, working out the shape of a single protein could cost a scientist years of painstaking lab work — then an AI called AlphaFold learned to do it in minutes and went on to map nearly every protein known to science, some 200 million of them, giving the - Space Daily

For much of modern biology, working out the shape of a single protein was slow, difficult lab work. Even one result could take months, and in tougher cases researchers could spend years trying to pin down the three-dimensional form of a molecule.

That changed when AlphaFold, an artificial intelligence system built for protein structure prediction, showed it could deliver answers in minutes rather than over the course of a career. The advance marked a major turning point for a long-running problem in structural biology.

The impact quickly grew beyond a single technical breakthrough. AlphaFold went on to generate structures for nearly every protein known to science, a collection described as roughly 200 million proteins. Just as important, the data was made freely available, giving researchers broad access instead of limiting progress to labs with the time and resources to solve structures one by one.

The importance of that shift is hard to overstate. Protein shape helps explain how molecules function, how cells work and where disease processes may go wrong. By shrinking a painstaking experimental task into a rapid computational one, AlphaFold changed the pace of biological research and opened a vast shared resource for scientists worldwide.