it seems everyone discussing this is always using the term beneficial to apply to morphological effect, something which Behe affirms and is in fact relying on in his rule. The other metric seems to be the integrity of the protein with itself and the bonds it makes with other proteins. Obviously this cannot always continue to degrade. I’m looking to make the strongest case for evolutionists, so to me it seems that more sustainable bonds might be found under the unknown category. Benign results might make an umbrella for shifting function, but still not de novo.
That isn’t correct @John_Detwiler. We are not using “beneficial” to refer to morphologic effect.
We aren’t evolutionists really, so…
In evolutionary science, we don’t think functions arise without any precursors. So, this isn’t a problem. Do you have an evidence of things that arose without precursors? I’ve looked all over and haven’t found any.
for one, I don’t see a reason that any of the results might not have positive phenotypic effect. I don’t think Behe is focusing on phenotype, he’s saying positive phenotypic effect is what cements the genotypic effects, which he claims are almost always negative from a stability perspective. I’m trying to imagine what sustainable genotypic effects would look like given the allowable results of this tool. Obviously “slightly beneficial” is not even one of the results possible in the program, so I’m trying to see how stronger bonds might be classified. Anything unknown seems to at least allow for that. I read somewhere that a regression analysis was done on the number of new folds discovered over time that gave great results with high confidence. I don’t remember where it is though
Yes, and the evidence he presents is from PolyPhen which does not demonstrate that there was a negative genotypic effect in any way:
Behe does think that mutations (essentially) always destabilize a protein, but this is not established with evidence. It is merely an assertion, countered by immense amounts of evidence.
There is software (not polyphen) that can estimate the stability of proteins. Would it be important or interesting to you to see what that software tells us about these mutations? Would it make a difference if it showed that none of these mutations were strongly predicted to destabilize the protein?
To be clear, did you see the original table?
I confess that I really didn’t follow what you are saying here. Behe (and polyphen-2) are absolutely focusing on the phenotype. Proteins are phenotypes!
Obviously “slightly beneficial” is not even one of the results possible in the program, so I’m trying to see how stronger bonds might be classified. Anything unknown seems to at least allow for that.
As I mentioned above, the classification of “unknown” simply means that there is no data with which to make any sort of prediction regarding functional effect, most often because the variant in question could not be successfully aligned with the reference sequence. An “unknown” result doesn’t tell us anything.
You are asking a different question that Behe,
I think you are confusing “beneficial” with “protein stability.” We can study the protein stability of these mutations with other programs.
@davecarlson that isn’t precisely right.
Behe is arguing that there is a disconnect between morphological fitness and biochemical complexity. Damaging genes, in his view, can increase organismal fitness, and is the most common way of increasing fitness. So his argument depends on (among many other things) treating these two as different and objectively measureable things.
As we have seen (and Lenski explains), polyphen doesn’t tell him what he needs it to tell him (other than as a quirk using "damaged). He thinks it tells us if the mutation “damages” a protein or not, but it doesn’t. Yes, it is fairly shocking, that Behe rests the premise of his book on something this incorrect, but he does.
@John_Detwiler, have you read this article yet?
To be more precise I should say phenotypic effect.
but you just said aren’t really an evolutionist right? So who is “we”?
I’m just looking to build the case for climbing Mt. Improbable. I’m trying to characterize what results might look like given the software that was used.
Good point. I wasn’t thinking about the broader context.
Doesn’t change anything I wrote, and the data and reasoning equally undermines Behe’s hypothesis.
I’m a Christian that follows Jesus. My worldview does not rest on evolution, but on Jesus. I am not an evolutionist. Many of the atheists here too, do not rest their worldview on evolution. Many of us affirm evolutionary science, but that doesn’t make us “ists.”
Given the software used, the results should look just like it does. There is not one thing in that Polar Bear paper that challenges evolutionary science, and quite a bit that supports it. Behe just misread the paper. It is hard to help someone who just misread the clear plain text of the paper.
I’m not sure of a better word for the outward effects of an SNP visible to natural selection than “phenotype”. Yes, obviously there is a context in which a protein itself is a phenotype of it’s own DNA sequence. Behe’s rule is not about that per se. My understanding is that it is possible for a person to see two different metrics, one that describes the strength of the bonds in a protein and those it makes with substrates, and another that describes the outside the box effects of such changes on the organism. It is my understanding that polyphen, in part, compares sequences to known databases and scores them based on similarity to give an indication if a given sequence is moving towards them at the level of secondary structure.
It is not possible in the way you are thinking, or in the way Behe needs it to be. However, as I already pointed out,
And about this:
This is true, only in part.
Yes, that’s why I said it seems like he cherry picked. I’m not overly concerned with Behe’s reputation, as I had developed the idea of his “1st adaptive rule of evolution” long before he ever published it.
So the thing is @John_Detwiler, there are many ways to build up complexity that Behe neglects. Neutral and even destructive evolution can be very constructive at a bimolecular level. You might want to brush up on this: Constructive Neutral Evolution. The only way that devolution becomes a problem is if you ignore all the ways that functional complexity is built up.
do you mean “on the whole”?
No, I mean that it does not demonstrate a “negative genotypic effect” in any way. He misunderstands the output of the program.
Polyphen does run the results against pdb for structure and even a database for secondary structure. This obviously returns results that will highly correlate with stability.
If proteins mostly lose stability or binding affinity each generation but never gain an equal amount in the same or other proteins, that is obviously not sustainable or “beneficial”