Progress on computational determination of 3D protein structure

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Some potentially exciting news (though caveats abound, as ever):

‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures

An artificial intelligence (AI) network developed by Google AI offshoot DeepMind has made a gargantuan leap in solving one of biology’s grandest challenges — determining a protein’s 3D shape from its amino-acid sequence.

DeepMind’s program, called AlphaFold, outperformed around 100 other teams in a biennial protein-structure prediction challenge called CASP, short for Critical Assessment of Structure Prediction. The results were announced on 30 November, at the start of the conference — held virtually this year — that takes stock of the exercise.

“This is a big deal,” says John Moult, a computational biologist at the University of Maryland in College Park, who co-founded CASP in 1994 to improve computational methods for accurately predicting protein structures. “In some sense the problem is solved.”

The news is all over the press. Would be nice if there was a paper, but I guess the conference at which this was presented is ongoing. Hopefully there will be more details soon to back up the hype.

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Moved to “Conversation”. :slight_smile:

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Some more detail here:

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BBC also has a nice article.

One of biology’s biggest mysteries ‘largely solved’ by AI

This is a benchmark. Amp up the computing power and improve the algorithms and it is conceivable that not only known proteins can be analyzed, but hypotheticals as well. It might be possible to work backwards from a desired protein shape and polarity to the sequence. It may be possible to test life as we do not know it scenarios for exobiology.

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