Dear Mensur Dlakic, Thank you so much for the feedback and for the Grishin reference, I will definitely look into his work. I completely understand not having the time to read through a full preprint
And you are right to be skeptical, I was too. A result like that could easily be a statistical fluke. But the thing is, I found a similar coincidence when I was looking at the sweet-tasting proteins Thaumatin and Monellin, which are also classic examples of convergent evolution. In that system, I found two separate "sockets" with no known function. One of them, a two-residue segment (Thaumatin 157-158 Chain A vs. Monellin 30-31 Chain A), aligned with an RMSD of just 0.049 A. finding two of these statistically improbable geometric echoes in completely unrelated systems is what got me thinking about this whole "Geometric Deep Homology" idea. It's a very curious puzzle. Thanks again for the discussion!
While you wait for an answer, in case you have not asked this question to an AI/LLM, the the answer looks to be
At a minimum you will have to include the following (for those who don't want to read your preprint)
What is the length of the region you are referring to here.
As an aside, asking GPT to compare the two proteins brings up the following.
Ref: https://www.cell.com/structure/fulltext/S0969-2126%2896%2900055-X
GenoMax, Thank you for the excellent and rigorous feedback. That is a critical question. The region I am referring to is a four-residue constellation. The near-perfect identity (RMSD = 0.096 Å) is achieved through a "core-bridge" mechanism (it needs to use backbone super) A rigid Core (2 residues): Val174 (Kinesin) vs. Ile258 (Myosin), which function as identical B-strands. A flexible Bridge (2 residues): Ser175 (Kinesin) vs. Gln259 (Myosin), which connect the core via a loop (Kinesin) and a B-strand (Myosin), respectively, while maintaining geometric integrity.
I appreciate you engaging with this idea