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Researchers have doubted how useful the AI protein-structure tool will be in discovering medicines — now they are learning how to deploy it effectively.
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.
Efforts to apply AlphaFold to finding new drugs have been met with considerable scepticism, says Brian Shoichet, a pharmaceutical chemist at the University of California, San Francisco. “There is a lot of hype. Whenever anybody says ‘such and such is going to revolutionize drug discovery’, it warrants some scepticism.”
www.nature.com
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.
Efforts to apply AlphaFold to finding new drugs have been met with considerable scepticism, says Brian Shoichet, a pharmaceutical chemist at the University of California, San Francisco. “There is a lot of hype. Whenever anybody says ‘such and such is going to revolutionize drug discovery’, it warrants some scepticism.”
AlphaFold found thousands of possible psychedelics. Will its predictions help drug discovery?
Researchers have doubted how useful the AI protein-structure tool will be in discovering medicines — now they are learning how to deploy it effectively.
www.nature.com
