1) Only handful of amino acids in a enzyme structures were highly conserved. (Out of hundreds, generally less than ten.)
2) Those were generally in the reaction center.
3) Almost all single sequence replacements had no measurable effect on protein structure and function.
4) Across species the "same" protein can diverge in sequence by up to 40%, while keeping the same structure. Sometimes this goes as far as 80%.
Given these basic facts, the findings in the paper aren't really surprising to anyone who studies proteins.
[Note: As with everything in biology, you can find counter examples. The histone proteins involved in DNA packing have an incredibly conserved sequence.]
Are there any folds and patterns that evolution evolution has not discovered that are also useful? I think Baker Group created a bunch of new folds. I'm not sure if they are as useful as the one discovered by Evolution. After all, Evolution had more compute power than us.
Our compute capacity isn't deployed to brute force Monte Carlo sims (mostly). So it's apples and oranges.
https://pmc.ncbi.nlm.nih.gov/articles/PMC7072414/
Oh ok, I misremembered:
"This review has focused only on small fragments of fold space with examples given for folds generated from a single secondary structure string consisting of around ten SSEs. Even in this small corner, the number of possible folds, under the current constraints, is of the order of 1000"
Who knows what might be possible if you designed a cell from scratch - perhaps you could rework all the machinery to access other parts of fold space. After all, there are some weird and wonderful machines out there like the 'Vault' (https://en.wikipedia.org/wiki/Vault_(organelle)) that can fit whole proteins inside them. Possibly a different cage-like structure could help fold designed proteins into as-before unseen structures.
i did neuroscience for grad school, and i was always amazed by how often complex neural activity could be well represented by lower dimensional representations--clean manifolds, attractor dynamics, etc. i think, in general, biology (evolution) doesn't penalize against redundancy too hard (hence things like genetic drift, neutral theory of evolution, etc.).
anyway, super cool stuff. agree with you that probs more useful to explore the search space via 'less natural' structures, given how forgiving evolution is to redundancy. probs where the most information can be found
(note: there are bigger proteins, including ones so big you can see them with the naked eye (e.g. a hair) but they consists of multiple repeats of the same small building block. There are many such building blocks. And the very few exceptions to that are "not really" part of eukaryot cells, but of cell organelles that have their own DNA)
But even if you just take the first 4 amino acids, there's half a million possible combinations. Life uses less than 1000 of those.
In other words: DNA and evolution, even with billions of years to think about it, is really a bit of a beginner when it comes to protein design. Or at least, it is pretty obvious that it's possible to do A LOT better than natural selection.
Thinking more about the question of protein _length_ - I'm also not convinced that longer proteins (more than say 750aa) would produce more novel folds. Larger proteins tend to be multi-domain; that is, a longer chain will fold into multiple compact domains, each one a separate fold.
I suppose there could be 'megafolds' out there in fold space, beyond 1000aa - like a 12-bladed beta propeller, or a beta-helix with alpha helices on the outside or some other wacky thing. Whether that would substantially increase the numbers of total folds, I doubt, but that is of course a guess.
(ref - https://pmc.ncbi.nlm.nih.gov/articles/PMC10251718/ for protein lengths)
And really? Just any random sequence gets you a new fold. I mean, it won't be very useful if you pick a random one, but it'll work and be a new one.
I think this is just an artifact of natural selection basing new proteins on existing ones, not an actual useful ("rational" if you can call natural selection rational) selection limit. I don't think that if you designed proteins from first principles you'd see this limitation in your results.
The nice thing about stable folds, is that 'nearby' sequences in sequence space - as in, point mutations - are the same fold. If each sequence had a completely different fold, then mutation would be much more destructive. Surprisingly, however, sequences that are far apart in sequence space can also adopt the same fold (convergent evolution).