AlphaFold Predictions Driven by Memorization

https://www.nature.com/articles/s41467-024-51801-z

by __jochen__ • 2 years ago

2 2 2 years ago

dekhn• 2 years ago

This work focuses almost entirely on a single category of proteins: fold-switchers. That is, proteins that can adopt two distinct conformations depending on the state of the system. Sort of like a flip-flop.

Anyway, its conclusions are a bit grandiose, we already would have expected AF2 and 3 to do poorly on predicting both structures of a fold-switcher. And nobody really thinks that AF "learns the protein's energy function"- AF3 does nothing of the sort.

Most of AF3's abilities are memorization, but that's not a bad thing. It's already been shown to generalize out of class but also work poorly where there is poor data density (either coevolutionary data, or structural data).

__jochen__• 2 years ago

Agreed, that this is a limited scope for what AF does. Nevertheless, it seems interesting to confirm that its primary strengths are memorization, which is not surprising.

AlphaFold Predictions Driven by Memorization

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