DNA duplication, mutation, and information

from the paper:

“One problem with this evolutionary route is that nature most often appears to evolve similar functions in unrelated protein families. Examples of active site convergence that do not involve main-chain and sequence order conservation, such as the catalytic triads from serine proteases, are far more common than the sequence- and structure-similar motifs described here (Russell, 1998), and many proteins have similar functions with no molecular similarities at all (e.g., metal and serine proteases). It is very likely that different folds, once evolved, have converged to similar functions by more conventional evolutionary events, such as point mutations”

so what is the chance to get the same function again by convergent evolution for instance?

just look at this:

unnamed
(image from http://fig.cox.miami.edu/~cmallery/255/255prot/255proteins.htm)

what do you mean?

Yes, it’s “very unlikely”, but still likely enough that it has happened many thousands of times over the history of life. IIRC it’s been estimated there’s something like 10^4 unique protein folds used by cellular life on Earth. If we sort of spread that out equally over the 4 billion year history of life on Earth, we arrive at a new protein fold emergence once every 400 million years. Now of course that’s largely an oversimplification since much of this evolution has occurred in parallel in different lineages, rather than sequentially one after another.

But regardless, that’s definitely a very long time for novel fold emergence, no doubt about it. But what is then wrong with inferring that new protein folds can and do evolve, just extremely slowly and infrequently compared to human lifespans?

Yes, they’re “very unlikely”, but not too unlikely to evolve. They have, many thousands of times. But it’s taken tens to hundreds of millions of years on average for it to happen. Why can we not make this inference? If we can study the rock layers in geology and make statistical inferences about the frequency with which something occurs in geology, why can’t we do the same in biological evolution? If we can infer that cataclysmic volcanic eruptions take on every some X number of million years to occur, why can’t we do the same with biology? Why must there be this strange gulf of nothingness following things that occur on decade-like timescales?

How is this any different from innumerable other extremely slow processes that occur on our planet? Continental drift, emergence and erosion of mountain ranges, changes in the paths taken by rivers, the sizes and shapes of lakes and oceans, the coming and going of continent-spanning forests and deserts. And so on and so forth.

Some things are quite likely to happen, so they occur correspondingly quite frequently. Some things are less likely, so they’re a bit more infrequent. Some things are even more unlikely still, so they occur even less frequently, and so on and so forth - until we get to things so unlikely to only occur on average once every 100 million years, or once in a billion, und so weiter.

IDcreationists seem to have this strange picture of the world where there is only likely things occurring all the time, and then there are completely hypothetical things that are so unlikely that they never occur at all. And there’s just no space for something in between. Historical inference that new proteins might take millions of years to evolve, while that is certainly slow and unlikely, seem to be instantly rejected as impossible.

But we’re never told why it has to be impossible, or so unlikely so as to never occur in the history of life on Earth. It seems to just be an assumption you have. A faith. A sort of axiom you refuse to consider might not be true. Either you want it demonstrated to occur to you in real time in the span of a decade at most, and if we can’t do that, you reject the possibility of it occurring in any other amount of time. A sort of “were you there” rejection of historical inference.
There are only things so likely we can show them to you right now, or impossibly unlikely things that can’t occur. Nothing in between. There are no things that take thousands of years, no things that take hundreds of thousands of years, no things that take millions of years, in your strange perception of reality.

It’s like there’s no such thing as a spectrum of likelihoods and frequencies of occurrence. The prospect that some things are so unlikely they only occur once every 200 mya is just not part of your conception of reality, and that just doesn’t make any logical sense.

So somewhere in between simple double substitutions or triple mutations that you allow can occur in the span of a few decades to maybe, MAYBE a century, and then from that on there’s nothing other that can possibly happen in evolution. There are no complex mutations that happen once every 5000 years, once every 150 000 years, once every 25 million years.

Your view of these matters just don’t make any logical sense. And you all(IDcreationists) seem to be laboring under this extremely strange view of probabilities and frequency of occurrence. “It’s now or never”.

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What’s misleading about it? If a designer can copy-paste a sequence so it’s there twice, and this adds information, then why can’t a duplication mutation that also results in the same sequence twice add information?

So what is the argument? You haven’t made one. You’ve just now stated that “minds uniquely generate information”. Why can’t mutation and selection do the same?

Take the sequence AGAAC, it’s nonfunctional and has no information (say).

Then a designer adds TC to the end of it, giving AGAACTC, which has a fitness-improving function of some sort. The designer purposefully put TC on the end to give it a biological function that aids the organisms ability to survive and reproduce. Is this added information?

Now take the same sequence AGAAC, and an insertion mutation results in AGAACTC. Why has this not added information when essentially the same thing has occurred as above?

What is your “argument” here?

If a designer can create a sequence (AGAACTC) after a lot of trial and error, calculation, simulation, and experiment, that has a useful function, and put it into an organism to help it survive and reproduce, why can’t mutation and selection do the same? Why would one resulting from design constitute information, and the other resulting from mutation and selection not? It’s the same sequence in the end, doing the same thing.

What is it the same sequence resulting from evolution lacks, that the one resulting from design has? How do we determine that the exact same sequence resulting from evolution has no information, compared to the one resulting from design? What measurement can we perform on the designed and evolved sequences, despite them being completely physically identical, that shows the evolved one has no information?

Explain yourself.

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not if the chance is so low, that it could not happen even in billions of years. if for instance the same function appears once per 10^60 sequences, then we can calculate the time it will takes to evolve it again by convergent evolution. and to get 10^60 mutations we will need far more than the age of the earth if we are talking about animals.

But is it? If we can do a historical inference like is done in geology and astronomy, and discover something occurs something like once in 100 million years on average, why should we then think the likelihood is too low for it to happen even in billions of years?

Why do we have evidence that tell us it happens once every 100 million years? Is it then not obvious that you’re wrong to think it is too unlikely to happen even in billions? What would it take to convince you otherwise? What can you really say other than you want to see it happen in real time, and then you have effectively rejected all of historical inference?

None of this makes any sense. First of all you start by saying “once per 10^60 sequences”, and then end by saying “10^60 mutations”. Mutations are not sequences, mutations happen in or to sequences.

And the frequency with which random samples of sequence space yield the function in question is not the same as “the chance of evolving it again by convergent evolution”, since neither the starting point, mutational biases, nor natural selection figures anywhere in the “frequency with which random samples of sequence space yield the function in question”.

You’re simply not making sense, and you are jumping around between terms and concepts that don’t refer to the same thing.

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all you need (at least in theory) is to show that there is indeed enough time to evolve what we see in nature. so if we agree that we need at least few specific amino acids to evolve a new organ, or even a new anatomical trait\bindng site etc, then according to the calculation the time isnt enough.

its probably true, but i think its not so different from a random event either. after all, we are talking about convergent evolution here. so the ancestral state was quite different. so what make you think we can reduce a huge number such as one in 10^60 into something like one in 10^6?

But that’s what we’re seeing in nature. Why can’t we do that historical inference? If we see there’s been about 104 new protein folds produced over the history of life on Earth, why can’t we simply infer that is roughly how rarely they evolve?

But you’re not calculating the “chance to evolve” anything. You’re just putting in the frequency of a particular function in sequence space(that you made up, didn’t measure anywhere).

Where is the starting point, mutation, and natural selection in the calculation? Where do we start, what kinds of mutations occur, and what is the fitness effects of mutations? Are you saying these things have no effect, and that we might aswell just think of evolution as if a random sequence generator?

No, it’s not “probably true”. See above.

We don’t seem to be really speaking about any particular thing, as you just invent whatever random thing you can think of in the moment.

You started by just talking about “functions at 1 in 10^60 sequences”. Then you went on to add that they must evolve convergently again. Then you started blathering about new organs in 3 mutations, or new binding sites. You’re just blathering out random shit. Nobody can make sense of whatever you’re trying to argue. Seemingly not even yourself.

I have no idea what you’re even talking about. Do you? What do these numbers even represent? Where is natural selection in these numbers? Where is the starting point considered? Where do the effect of mutation rate and frequencies figure? I see these things considered nowhere, which implies you either don’t know how to include them, and/or you think they make no difference. Probably both.

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you are begging the question. you assume that evolution is true and thus there is no problem with the time. i can say the same about ID you know.

so what is your assumption? how many mutations required to get the lambda repressor from non-lambda repressor?

im talking about two different things here: the chance to get the same function again by convergent evolution, and the chance to get a new function by multiple amino acids changes. so as for the second claim, do we agree that at least few amino acids changes are needed to evolve a new function such as new binding site? as for my first claim, what do you think is the chance to evolve the same trait again (say a binding site) by convergent evolution?

Are you implying that sedimentary rocks don’t contain information, or are you saying that they do contain information but that this has been generated by a mind?

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Let’s eat, Grandpa!

Duplication event, new information…

Let’s eat, Grandpa!
Let’s eat, Grandpa!

Mutation event…

Let’s eat, Grandpa!
Let’s eat Grandpa!

Note, the duplication event is new information, because it can altered independently.

New function. Grandpa gone. Kids full.

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This is quite cleaver :slight_smile: A process of intelligently guided information generation.

If on the other hand you make a random changes to the letters the information will quickly break down into gibberish.

True in most cases, but not every. Some result in selection for cannibalistic kiddies.

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No, I have concluded evolution is true based on a lot of evidence. With this conclusion already established I then infer an approximate frequency with which new proteins evolve. And you seem completely incapable of explaining why I can’t make such an inference, demanding instead that I calculate the prior probability of something evolving using nothing but the frequency with which the function exists in protein sequence space, in total ignorance of any knowledge of starting point, mutation spectra, natural selection, or anything else that clearly would be relevant.

Sorry, I don’t play whack-a-mole.

And that chance would depend strongly on a host of factors that figure nowhere in any of your posts. You simply pick an imaginary number which you postulate is the frequency of function in protein sequence space, and then you just mindlessly assume that’s also the probability of evolving the same function by convergent evolution, and just as insanely that it is also the number of mutations it takes to evolve the function. All of it is total gibberish.

More whack-a-mole. Sorry, I don’t play that.

Depends on all those factors I mentioned. What is the probability that a designer will create the same binding site twice in very different organisms, but then create a lot of different ones for everything else?

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Not if there is selection for meaning in addition to the random changes.

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This doesn’t make any sense. How can you say a protein fold (a particular arrangement of amino acid residues in three-dimensional space) is the same as protein function (useful action of the protein)? Or is this one of your incoherent ramblings? It seems you also think that because some polypeptide is folded, therefore its functional, but that is not true (and the authors agree with me: see some paragraphs below).

More importantly, the calculated 1 in 10^63 (or 10^-63) figure is the probability of finding a sequence resembling the 92-residue long N-terminal domain of the lambda repressor protein (NtD-LRP) from the total number of sequences that can be generated from all combinations of 92 amino acids, if we randomly pick these amino acids from the 20 naturally occurring amino acids. The total number of possible sequences in the sequence space for proteins containing 92 amino acids is 20^92 or ~4.95 × 10^119 sequences, if we randomly sample from all 20 naturally occurring amino acids. The authors calculated the probability (10^-63) of finding sequences that folded and functioned like NtD-LRP if we randomly searched through that sequence space. It seems the authors made a similar calculation to Hubert Yockey’s on the spontaneous biogenesis of cytochrome c since they cited him:

Citation 19 is this Hubert article:

https://doi.org/10.1016/0022-5193(77)90044-3

The calculation appears to have nothing to do with the evolution of the N-terminal domain of lambda repressor, just its formation from scratch. However, we know the protein did not emerge spontaneously, it most likely evolved from simpler precursors, so the calculation is irrelevant to the origin of its fold or any other fold in nature.

Despite the very small probability of picking structurally and functionally similar sequences to the Ntd-LRP, the authors found many functional variants via selection:

If the authors cared about whether these sequences folded similarly to the Ntd-LR regardless of whether these folded sequences were functional or not (because you can have a fold similar to the Ntd-LR without it being functional) they would have gotten even more target sequences, as they stated:

The number of functional sequences observed in the study amounted to “4 × 10^20” based on the examination of 32 residues (they did not examine all 92 residues).

Yes.

No, the chance to get a fold similar to the N-terminal domain of the lambda repressor protein is small, if we randomly sampled it’s sequence space, based on their calculation. You are extrapolating from their findings to all other protein folds, which is highly inappropriate.

In addition its important you remember the authors looked at only 32 (out of >80) residues, which calls for cautious interpretation of their “extraordinarily rough calculation”. Read their words:

I am not too sure of my analysis, so criticism is welcome. This is the paper SCD cited, which is about the relative contributions of component residues to the structure and function of in the N-terminal domain of lambda repressor protein:

https://doi.org/10.1002/prot.340070403

There is. You have been fooled by the ID movement’s misuse of the term “fold.” In the real world, folds are structural categories not restricted to particular functions and functions are not restricted to particular folds.

I don’t see how. What I do remember is that there aren’t that many different folds–they are greatly outnumbered by the number of different functions. The immunoglobulin fold is a fine example of this.

There simply aren’t many new folds, and they are not required for new functions.

https://www.sciencedirect.com/science/article/abs/pii/S0022283684715828

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To quote @swamidass

Homoplasy is similarity that is NOT consistent with a tree, and therefore NOT well explained by common ancestry alone. These are the exception to the rule of phylogeny.

Homology is similarity that is consistent with a tree, and therefore well explained by common ancestry alone. These are the rule.

Both Homoplasy and Homology are types of similarity. If common descent were true, we would expect to see mainly Homology, with some Homoplasy, and that is what we see.

BLAST is a way of measuring similarity between sequences, but it does not use a tree to do so. So, effectively, it groups Homoplasy and Homology together and makes no distinction between them.

SIFTER group sequences by a tree, so it tries to ignore Homoplasy and focus on Homology.

If similarity was explained merely by common design for common purposes, we expect BLAST to work better than SIFTER. However, we see that SIFTER works better than BLAST. That is what we expect if common descent is true.

By the way, you were rebutting the argument that more complex stuff evolves from simpler stuff by showing me a picture which includes both myoglobin and haemoglobin, which is evidence more “complex structure” proteins evolve from more “simple structure” proteins.

https://amp.reddit.com/r/DebateEvolution/comments/gqsn1r/extinct_proteins_resurrected_to_reconstruct_the/

so what is the chance to get the same function again by convergent evolution for instance?

Have you heard of non-homologous isofunctional enzymes?

[Addit:] Now that I think about it a bit more, I can think of some testable predictions/refutations about non-homologous isofunctional enzymes comparing evolution vs common design regarding phylogeny of kinds and evolutionary optima. Can you think of any?

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I haven’t been following this discussion, but this comment seems to repeat our earlier discussion. No, demonstration of new features via mutation and selection cannot falsify an ID hypothesis, because the designer may have guided each step along the way.

A sender and receiver must agree on the interpretation of the coding. When it come to DNA there is no mystery here: interpretation and function is determined by the laws of chemistry.

If you wish of suggest a better argument, then you could start by presenting an alternative definition of information is inadequate.

Lets eat GrandMa. :laughing:

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Can it falsify it in a practical way? I think so if you can build a mathematical model that explains it. Although you could make the same comment with gravity that we can not eliminate Gods actions we can attribute most of the observed action to the properties of matter.

In the case of a 3D printer the generated code is algorithmically processed to form a function. The same case for biology. The laws of chemistry are not the sole determining factor. It’s also the architecture of the cell that determines the outputs such as protein synthesis and reproduction.

In both cases algorithms are involved vs direct mental interpretation. The ultimate source of the original code and the code receiving algorithms can be inferred to require a mind.