Roy Gilbert

Researchers match DeepMind’s AlphaFold2 protein folding power with faster, freely available model

DeepMind stunned the biology world late last year when its AlphaFold2 AI model predicted the structure of proteins (a common and very difficult problem) so accurately that many declared the decades-old problem “solved.” Now researchers claim to have leapfrogged DeepMind the way DeepMind leapfrogged the rest of the world, with RoseTTAFold, a system that does nearly the same thing at a fraction of the computational cost. (Oh, and it’s free to use.)

AlphaFold2 has been the talk of the industry since November, when it blew away the competition at CASP14, a virtual competition between algorithms built to predict the physical structure of a protein given the sequence of amino acids that makes it up. The model from DeepMind was so far ahead of the others, so highly and reliably accurate, that many in the field have talked (half-seriously and in good humor) about moving on to a new field.

But one aspect that seemed to satisfy no one was DeepMind’s plans for the system. It was not exhaustively and openly described, and some worried that the company (which is owned by Alphabet/Google) was planning on more or less keeping the secret sauce to themselves — which would be their prerogative but also somewhat against the ethos of mutual aid in the scientific world. That concern seems to have been at least partly mooted by work from University of Washington researchers led by David Baker and Minkyung Baek, published in the latest issue of the journal Science. Baker, you may remember, recently […]

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