DeepMind and Protein Folding

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DeepMind and Protein Folding

Postby Nert » Wed Dec 05, 2018 10:49 pm

Following is a link to an article describing Google's application of their DeepMind platform to protein folding. DeepMind was entered into a competition where participants predict protein structures from a list of their amino acids. Deep Mind came in first.

https://www.theguardian.com/science/2018/dec/02/google-deepminds-ai-program-alphafold-predicts-3d-shapes-of-proteins
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Re: DeepMind and Protein Folding

Postby bruce » Thu Dec 06, 2018 3:32 am

But it cannot predict the unlikely prospect showing how a protein can miss-fold?
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Re: DeepMind and Protein Folding

Postby Nert » Thu Dec 06, 2018 5:32 pm

bruce wrote:But it cannot predict the unlikely prospect showing how a protein can miss-fold?


I think that they are looking for the "normal" results, but that's mostly a guess. I tried to dig through the CASP13 (Critical Assessment of Techniques for Protein Structure Prediction) information linked by the Guardian article, but I couldn't make much headway. The information there is well beyond my superficial understanding of these things. Maybe one of the science guys can provide some high level context.
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Re: DeepMind and Protein Folding

Postby bruce » Thu Dec 06, 2018 5:56 pm

Yes, the CASP is aimed at predicting the normal structure. It's not surprising that AI would be good at that.

FAH goals are different. FAH's goals include a thorough understanding of how and why proteins fold in a specific way and finding the exceptions (known as mis-folding). FAH is also capable of predicting normal structures, but that has never been a primary goal and it's not particularly efficient at doing that.

Many of FAH's recent studies have been broadened to include "normal" interactions, but often exceptions are also discovered which turn out to be very valuable, scientifically.
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