A Ubiquitin Response to Gpuccio

There is no evidence that multiple binding sites evolve. For any eukaryotic cell to preform cell division multi binding sites are required or the function cannot perform. Other examples are the ubiquitin system, ATP production, and splicing of introns.

Your example is unrealistically simple and it assumes mutation can find new function and there is no reason to believe this is true with the assumption of evolution.

Again, we see it all of the time in immunology. Random shuffling of DNA produces millions of unique antibodies, and some of those antibodies will bind to different regions in the same antigen.

You are assuming that only one protein is accumulating mutations while all other proteins remain the same. This is wrong.

Support your claim.

Every paper I have read on the topic demonstrates that mutations happen throughout a genome. Do you doubt these findings?

Your claim is that multi protein binding come from multiple mutations. Yes, mutations do happen. It is what they result in thats important and remember they are occurring in enormous sequence space where non function is larger then function.

You are trying to claim a step by step process creates an irreducibly complex systems the ubiquitin system. This is a real uphill battle.

The way you portray the potential evolution of multi-domain proteins is that all of the evolution has to happen in the multi-domain protein. You seem to overlook the possibility of binding domains evolving in other proteins that then bind to the now multi-domain protein.

The antibody example is a perfect example of how this works. A bacterial protein that binds to several antibodies through different domains in the bacterial protein fits your definition of a multi-domain protein. However, the bacterial protein didn’t evolve to bind those proteins. Instead, the antibodies evolved to bind to the bacterial protein.

You also ignore the possibility of each interaction being additive instead of happening all at once.

Definition does not matter. Is the application similar to nuclear proteins and the answer is no. Mutations that are random are almost certainly not the cause of multi protein complexes. There is simply too much FI to explain.

Why is the answer no? Is there something magical about the nucleus where physical laws are different?

And once again I have to point out that Durston nor gpuccio are measuring functional information.

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The nucleus contains lots of complex interactions and complex protein systems.

They are both estimating the quantity of functional information by estimating the substitutability of each AA. It there is no substitutability we know that the FI is equal to 20^sequence length.

Bingo. You found the math error. This is not how you compute FI.

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So does the cytoplasm and cell surface.

That would be a measure of mutual information, not functional information.

It is a functional sequence. By definition (Szostak) it is functional information.

Show me where Szostak endorses Durston’s calculations here? It cannot be found. I’m certain he would agree that you misunderstood his math.

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From: HAZEN ROBERT M, GRIFFIN PATRICK L, CAROTHERS JAMES M, et al. Functional Information and the Emergence of Biocomplexity. In: National Academy of Sciences; Avise JC, Ayala FJ, editors. In the Light of Evolution: Volume I: Adaptation and Complex Design. Washington (DC): National Academies Press (US); 2007. 2. https://www.ncbi.nlm.nih.gov/books/NBK254300/

Accordingly, we define “functional information,” I(Ex), as a measure of system complexity. For a given system and function, x (e.g., a folded RNA sequence that binds to GTP), and degree of function, Ex (e.g., the RNA–GTP binding energy), I(Ex) = −log2[F(Ex)], where F(Ex) is the fraction of all possible configurations of the system that possess a degree of function > Ex.

It’s not about the replacement of single amino acids at a time in the peptide.

For a peptide with a.a. length of ‘n’

  1. “Et” = total number of all possible peptides = n^20
  2. “Ex” = Number of all possible 'n-length peptides capable of performing the specified function ‘x’
  3. “Q” = Number of all possible single a.a. replacements for a single peptide capable of performing the specified function ‘x’

Note that:
FI = -log2(Ex/Et)

‘Ex’ is not ‘Q’. Nobody has calculated Ex. They are only searching 20n sequences for activity when actually, there are n^20 sequences possible. They only calculated ‘Q’, which only considers a microscopic fraction of Et. To be specific they’re off by a factor of (1/20)n^19 total sequences…

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And this is merely a single error in their calculation. There are so many more.

This is the estimate that both gpuccio and Durston are making.

With incorrect assumptions and mathematical errors, yes they are attempting to declare their number shuffling = FI. I agree that is their attempt. The errors however, make it an erroneous attempt.

It is an estimate for sure but both would agree to that. Do you have a better method?

Yes. I’ve partly explained it here. Computing the Functional Information in Cancer - #15 by swamidass. They have to take into account (1) the ability of common decent to create MI, and (2) alternate ways of arriving at the same function, and (3) the effect of purifying selection, and so on. Everyone of these factors biases their results upwards.

Yes. I’ve partly explained it here. Swamidass: Computing the Functional Information in Cancer . They have to take into account (1) the ability of common decent to create MI, and (2) alternate ways of arriving at the same function, and (3) the effect of purifying selection, and so on. Everyone of these factors biases their results upwards.

How do you establish functional information is increasing in cancer or is it assumed?

How do you establish that common descent can create FI or are you assuming this?