Researchers have used the protein-structure-prediction tool AlphaFold to identify1 hundreds of thousands of potential new psychedelic molecules — which could help to develop new kinds of antidepressant. The research shows, for the first time, that AlphaFold predictions — available at the touch of a button — can be just as useful for drug discovery as experimentally derived protein structures, which can take months, or even years, to determine.
The development is a boost for AlphaFold, the artificial-intelligence (AI) tool developed by DeepMind in London that has been a game-changer in biology. The public AlphaFold database holds structure predictions for nearly every known protein. Protein structures of molecules implicated in disease are used in the pharmaceutical industry to identify and improve promising medicines. But some scientists had been starting to doubt whether AlphaFold's predictions could stand-in for gold standard experimental models in the hunt for new drugs.
“AlphaFold is an absolute revolution. If we have a good structure, we should be able to use it for drug design,” says Jens Carlsson, a computational chemist at the University of Uppsala in Sweden.
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