Yes, but that competition is using lots of proteins that are similar to other known proteins, as far as I understand.
There is also a lot of sub-structure that helps - similar parts of proteins tend to fold in similar ways, so even if you don't have real predictive power on unknown sequences, you may do quite well for a protein that is 90% the same as one in the training set - you will be quite correct on ~90% of the folds, even if your pretty way off on the remaining 10%.
Note that all of this is not to minimize the success of what AlphaFold achieved. I am just trying to explain how you can do well at this problem without having discovered some deeper deterministic structure in protein folds.
There is also a lot of sub-structure that helps - similar parts of proteins tend to fold in similar ways, so even if you don't have real predictive power on unknown sequences, you may do quite well for a protein that is 90% the same as one in the training set - you will be quite correct on ~90% of the folds, even if your pretty way off on the remaining 10%.
Note that all of this is not to minimize the success of what AlphaFold achieved. I am just trying to explain how you can do well at this problem without having discovered some deeper deterministic structure in protein folds.