No real clue what this stuff is about, way over my head, but kudos on an article where it's all there on the page instead of needing scripts to pull text and images from different places!
This approach is pretty much like the TED approach from a few years back. As far as I remember there wasn’t a ridiculous amount of fold diversity there either. It turns out evolution isn’t averse to a bit of liberal protein plagiarism.
"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"
cool post! it's funny how many things in this world are naturally graphs. i think it's neat how, especially in biology, a lot of high-dimensional objects, like protien sequences, converge onto lower-dimensional representations, like protein 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
No real clue what this stuff is about, way over my head, but kudos on an article where it's all there on the page instead of needing scripts to pull text and images from different places!
This approach is pretty much like the TED approach from a few years back. As far as I remember there wasn’t a ridiculous amount of fold diversity there either. It turns out evolution isn’t averse to a bit of liberal protein plagiarism.
https://www.science.org/doi/10.1126/science.adq4946
They found "several thousand" novel folds? I had remembered that there were around 1000:
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"
What plagiarism even means in context of proteins? That one protein steals a fold of another protein without giving proper credit to it?
cool post! it's funny how many things in this world are naturally graphs. i think it's neat how, especially in biology, a lot of high-dimensional objects, like protien sequences, converge onto lower-dimensional representations, like protein 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
This crashed my browser. Use reader mode.