DeepMind’s AlphaFold tool has determined the structures of around 200 million proteins, from almost every known organism on Earth.
The structure of the vitellogenin protein — a precursor of egg yolk — as predicted by the AlphaFold tool.From today, determining the 3D shape of almost any protein known to science will be as simple as typing in a Google search.
The 3D shape, or structure, of a protein is what determines its function in cells. Most drugs are designed using structural information, and accurate maps are often the first step to discoveries about how proteins work. According to EMBL-EBI, around 35% of the more than 214 million predictions are deemed highly accurate, which means they are as good as experimentally determined structures. Another 45% were deemed confident enough to rely on for many applications.Many AlphaFold structures are good enough to replace experimental structures for some applications. In other cases, researchers use AlphaFold predictions to validate and make sense of experimental data.
Because AlphaFold software has been available for a year, researchers have already had the capacity to predict the structure of any protein they wish. But many say that the availability of predictions in a single database will save researchers time, money — and faff.It’s another barrier of entry that you remove,” says Porta. “I’ve used a lot of AlpahFold models. I have not ever run AlphaFold myself.
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