Optima in Evolution

This data does very little to support evolution by natural selection and neutral changes. You need to show all proteins can evolve not some small subset. As you need to show all proteins have local optimums and that local optimums exist such that functional space is almost equal to sequence space.

How many people would have to buy tickets with 100 balls? 50^94 people. We better start increasing the population quickly :slight_smile:

Heh. No Bill, we don’t. Showing how the process works once is enough to falsify the ID-Creationist claim protein evolution is impossible.


False. All we need to show is that evolutionary processes can find function. We don’t make a lottery winner win the lottery again just to prove they won it the first time.


Pulling numbers out of thin air isn’t evidence.

That’s how the antibodies evolve, so you’re wrong.


Hey Bill, this evidence you referred to. Where is it?

Can you at least point out to John and T that they don’t understand that the lottery argument is fallacious?

Antibodies don’t evolve. They are generated by a biological system. They also don’t test the more challenging proteins that evolution has to produce such as alpha actin 1.

You are committing the equivocation fallacy of conflating “rare” with “can’t evolve”. Perhaps you should focus on that.

Those two sentences don’t connect to one another. The variable region of an antibody is randomized sequence, and many antibodies have function. If what you claim is true, then we shouldn’t find any functional antibodies or abzymes, yet we do.

“Sure you showed how this tree grew from a seed. I demand you now show me how every tree in the forest grew from a seed!” :slightly_smiling_face:


It’s not clear to me that it is, so, no.

Yes they do. They evolve by mutation and natural selection. That’s the basis for the adaptive immune system. The genes encoding the antibody protein are mutated and recombined, and the results subject to selection.

And that system of generation employs evolution to find and attack novel antigens(which can be other proteins, which means the immune system evolves protein-protein interfaces) and even enzymatic activities.

Nobody claims the adaptive immune system has evolved alpha actin 1(alpha actin 1 evolved from from other actin-like proteins), so that statement is completely irrelevant and frankly nonsensical.


This is very disappointing that you don’t realize this. Your understanding of the issues is not what I thought it was.

You haven’t even looked at the data, Bill.

Meaning he understands the issue while you don’t. So what else is new?

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Your familiarity with the data relevant to these issues is nonexistent.

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Size and structure of the sequence space of repeat proteins


All studied repeat families have rugged energy landscapes with multiple local energy minima. Note that the emergence of this multi-valley landscape is a consequence of the interactions between amino acids: models of independent positions ( E 1) only admit a single energy minimum corresponding to the consensus sequence. This multiplicity of minima allow us to collapse multiple sequences to a small number of coarse-grained attractor basins. These basins suggest that mutations between sequences within one coarse-grained basin are much more likely than mutating into sequences in other basins. In general, our results paint a picture of further subdivisions within a family, and define sub-families due to the fine grained interaction structure. Going beyond single families, this analysis suggest a view in which natural proteins all live in a global evolutionary landscape, of which families would be basins, or clusters of basins, with a hierarchical structure [32].
This overall picture of the sequence energy landscape is reminiscent of the hierarchical picture of the structural energy landscape of globular proteins, an overall funneled shape with tiers within tiers [38]. The form of the energy landscape forcibly shapes the accessible evolutionary paths between sequences. The rugged and further subdivided structure shows that the uncovered constraints are global, and not just pairwise between specific residues. Therefore even changing two residues together, as is often done in laboratory experiments, is not enough to recover the evolutionary trajectories. While other approaches have explored local accessible directions of evolution [39], our results suggest more global, non local modes of evolution between clusters.

I have blasted the sequence of the human MYH7 protein against the proteome of cartilaginous fishes. The best match is with the myosin heavy chain of Rhincodon typus.
The level of identity is 80,82%. The bit score is 3165. This means that the degree of conservation through deep time (let’s say about 410 Millions years) is very high.
So with this analysis, I know which AAs within the human protein exhibit conservation through deep time. However, in order to test my hypothesis that most of the neutral missense mutations you are referring to do indeed land at non conserved positions, I would need a list of say 20 to 30 such neutral missense mutations, with their precise positions within the protein. Do you have such list?

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Ensembl is a good place to start.


Just in case the link doesn’t bring up the variant table, that option is found on the left hand side at the top of the page under genetic variation. You can mess with the headings on the table to better organize it.

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Another issue to look at is that AA substitutions that are neutral yet take two nucleic acid substitutions. The odds of two specific fixed nucleic acid mutations is much less than 1. The challenge of fixation by drift appears to be very unlikely in this scenario. I think this would be something very interesting to model if you find mutations existing in the population that are not becoming fixed.

We have to be mindful that the diversity of gene sequences we are observing across different species to be caused by evolutionary mechanisms they have to go through the fixation process.

Yeah, and seeing that they are different between species is how we know that they did.


That’s bad math because it commits the Sharpshooter fallacy. You are assuming that the two base change needed to produce an amino acid change is required and the only change that can happen. In essence, you are arguing that you can’t get a lottery winner in just a few drawings because the odds of winning are 1 in 150 million.

What you need to calculate as a baseline is the probability of neutral mutations producing any amino acid change through two substitution mutations.