Tools & Techniques
What DeepMind’s leap means for structure-based drug developers
AlphaFold’s biggest impact on biopharma will be opening more targets to structure-based approaches, more quickly
AlphaFold’s biggest impact on biopharma will be opening more targets to structure-based approaches, more quickly.
The step change in protein folding prediction pioneered by Alphabet’s DeepMind stands to widen the funnel of targets tackled with structure-based platforms, including newly discovered proteins from emerging pathogens.
The jump in accuracy between DeepMind’s winning 2020 submission to a structure prediction competition and the one it submitted two years prior, as well as the wide margin by which the Alphabet Inc. (NASDAQ:GOOG) unit beat its competitors, was universally celebrated as a major advance in the 50-year-old protein folding problem.
“It’s a quantum leap forward in terms of the ability to predict structure from sequence,” said Jonathan Drachman, CEO of de novo protein design company Neoleukin Therapeutics Inc.
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