Hi Nick, welcome back. You write: Your arguments and probability calculations are …

Comment on Dr. Jason Rosenhouse “Among the Creationists” by Sean Pitman.

Hi Nick, welcome back.

You write:

Your arguments and probability calculations are based on the effects of many simultaneous mutations, with no opportunities for selection between them. Thus, under your model, large moves in sequence space have to happen all-at-once. Your criticisms of that model are valid, but they say nothing about the evolutionary model, which is stepwise.

You seem to have a mistaken view of sequence space, islands within sequence space, and how mutational changes can move around within this space.

To illustrate the problem here, imagine that our population starts out on an island within a higher level of sequence space. This island is made up of many protein sequences that can all produce the same qualitative type of function to at least some selectable advantage. Along the edges of the island are sequences that are marginally beneficial while in the center of the island are sequences that are strongly beneficial for the particular type of function in question (creating a peak for the island with exponentially declining slopes toward the surrounding ocean). Surrounding this island, on all sides, are sequences that are not beneficial at all. They may be functionally detrimental to one degree or another, or they may be functionally neutral, but they aren’t selectably beneficial.

Now, say our population happens to land on the edge of such an island. A selectable advantage is suddenly realized. So, this population will be preferentially maintained by natural selection. After this point, it is very easy to move the population rapidly up the slopes of the island to the very peak of the island in relatively short order (which has the effect of reducing the size of the island that will be considered “beneficial” for the population by natural selection). The reason for this is that the sequences with a stepwise increase in selectability are very closely spaced on this island. So, improving functionality of a given type on a particular island isn’t a problem for RM/NS – even by mutations that only produce single character changes (point mutations).

The problems, of course, happen when one tries to leave the island and find other islands within sequence space. In order to do this, mutations, of various types, start to explore the sequences in the ocean around the island. Point mutations take very small steps off the island. If these point mutations land on neutral (or near neutral) areas of the ocean, they are not immediately deleted by natural selection. They can wander around a bit looking for other islands along a “random walk”. If these point mutations land on strongly detrimental regions of the surrounding ocean, natural selection quickly deletes them and the random walk starts over from the starting island. Of course, this “start over” process takes time.

Now, imagine a scenario where the next closest beneficially selectable island in sequence space is a Hamming distance of 50 non-selectable mutations (character changes) away from the starting island within a sequence space that holds 1000 character sequences. How long would it take to get to that next island? Say that your population on the starting island is at a steady state of 1e31 (the size of the number of all the bacteria on Earth). Say that our mutation rate is one mutation per 1000 character sequence per generation, and our generation time is 10 minutes. The number of non-beneficial sequences within a Hamming distance of 50 within this sequence space is ~1e65. Given these parameters, our population could explore a maximum of 1e31 sequences within the surrounding ocean in each generation. Of course, this means, on average, that it would take our population about 1e34 generations, on average, to reach an island that is just 50 character differences away from the starting island (i.e., ~1e29 years).

But, you argue, any mutations that are detrimental will be selected against my natural selection, which is true. However, this doesn’t improve the odds of success. All natural selection does in such a case is bring back to random walk sequence to the original starting point. The effect that this has is to increase the searches very close to the starting point island. However, it doesn’t really help to find something that is 50 mutational steps away any faster. If anything, it increases the average number of mutations required to achieve success.

In this light, let’s consider the rest of your specific arguments:

This doesn’t matter, since in evolution, all the mutations don’t occur at the same time. Each is exposed to long periods of selection, drift, etc. The real process is that after a substitution happens in a population (either beneficial, beneficial but with some negative side effects, or neutral, or nearly neutral but slightly deleterious), a variety of new mutations accumulate over subsequent generations. Some of these mutations are neutral, some are slightly deleterious, and some compensate for some deleterious feature introduced by a previous substitution. Compensatory substitutions, in particular, are crucial to include in the model. Creationist arguments, including yours, universally ignore the role they play.

My model does not ignore compensatory mutations at all. The effect of compensatory mutations is simply to reverse the random walk of a sequence back onto the original island from which it started. That’s all. Compensatory mutations do not help to reduce the average time required to find a qualitatively novel island within sequence space.

Beyond this, I’ll point out that I’m not arguing that mutations need to occur at the same time. They don’t. Mutations can and generally do occur one at a time and are generally comprised of single-character mutations. Multi-character mutations (indels) can also occasionally occur, and these types of mutations can make long leaps into the ocean of sequence space, far away from the original island. However, the odds of successfully landing on any part of any other island within sequence space is not statistically improved. The average time to success is still the same.

Also, proteins are much more flexible than, say, English. It is commonplace to find protein families where 50% or even 80% of the amino acids have changed, yet the structure and function remain the same. Not so for English. Protein evolution is more like language evolution, where most / all of the words can be modified, the resulting languages are incomprehensible to each other, but the same message can be communicated via different sentence, each within the overall context of its language.

What you’re talking about here are entirely different non-connected islands within sequence space that have the same type of functionality. In other words, it is possible to say the same thing in a very different way. The same is true with protein-based systems. It is possible to produce the same qualitative type of function with very different protein sequences. That, however, doesn’t solve the problem.

Beyond this, it is not generally true that most of the amino acid residues of a protein can be modified without a loss of function. As already explained, most protein-based systems suffer an exponential loss of function for each individual amino acid residue change in the sequence. It is for this reason that most of sequence space is simply not functional nor are most sequences even capable of forming stable protein folds. It is also for this reason that the beneficial islands in sequence space have sharp peaks and steep slopes.

Your arguments are rather like arguing that French and Romanian could not have evolved from a common ancestor, because if you take a French sentence and randomly mutate most of the letters in each of the words, you get something incomprehensible. This is nothing like the actual proposed historical process, and so is not a rebuttal of it. Language space is surely huge just like sequence space, and it is surely true that most random assemblages of sounds don’t mean anything in any modern or extinct language, yet languages have evolved nonetheless, through a long process of step-by-step changes, with the participating humans mostly or completely oblivious.

This is a mistaken analogy for the very reason that humans are intelligent and can make leaps within sequence space that cannot be made by random mutations in a comparable amount of time. You mistakenly assume that human languages evolve via the same mechanism as Darwinian evolution. They do not.

Beyond this, different human languages are effectively the same with the exception that different letters and words are used for the very same ideas. The same can be true of protein-based systems. Note, however, that the problems for evolutionary progress from lower to higher level systems is the same for human languages as it is for protein-based systems. As in the human-language system, there are many possible ways of saying the same thing. However, these many possible ways of saying the same thing get farther and farther apart in sequence space as the thing that is trying to be said increases in the required minimum number of characters that have to be used to get the idea across. The very same thing is true of protein-based systems. While there are many very different options of producing the very same type of system, these options become more and more widely spaced in sequence space with each step up the ladder of minimum structural threshold requirements. That is why it doesn’t matter what “language” once uses, one cannot get from a given higher level island within sequence space to any other, regardless of the “language” that would be recognized in a given environment, in a reasonable amount of time.

Another problem here is that you seem to imagine that going from lower-level to higher-level systems is a smooth process where there are no significant gaps between lower-level and higher-level islands within different levels of sequence space. That’s just not a correct vision of sequence space (human language or otherwise). The lower level islands are also separated from higher level islands by gaps comprised of non-beneficial sequences. And, these minimum gap distances become linearly wider and wider with each step up the ladder of functional complexity.

Other examples of this mistake in your comment:

The reason for this is because there is an “experimentally observed exponential decline in the fraction of functional proteins with increasing numbers of mutations (Bloom et al. 2005).”

…and again:

Bloom goes on to point out that, “Experiments have demonstrated that proteins can be extremely tolerant to single substitutions; for example, 84% of single-residue mutants of T4 lysozyme and 65% of single-residue mutants of lac repressor were scored as functional. However, for multiple substitutions, the fraction of functional proteins decreases roughly exponentially with the number of substitutions, although the severity of this decline varies among proteins.”

…and again:

In short, most mutations that affect a region or island cluster of thermodynamically stable sequences in sequence space are destabilizing in such a way that each additional mutation has an exponentially destabilizing effect. Obviously, this means that the vast majority of sequences in sequence space would not produce viably stable proteins.

It is true that most mutations have this effect, but this doesn’t matter, since they happen for the most part one at a time, and (1) selection removes the severely deleterious mutations, and (2) the slightly deleterious ones can later be corrected by compensatory substitutions.

While both of your points here are true, they really don’t help to lessen the average time required to fine a novel beneficial island within sequence space (as already explained). My point in referencing the experiments of Bloom et. al. was to show you how the islands of beneficial sequences actually appear in sequence space. They are islands with steep slopes and sharply pointed peaks as I originally said.

The “vast majority of sequences” therefore don’t matter, since evolution doesn’t have to search through all possible sequences in order to explain the data. To explain the data, it just has to, *sometimes*, find *some* of the paths between proteins with different-but-related sequences but the same function, and, occasionally, find *some* of the paths between proteins with different-but-related sequences and different functions. It doesn’t have to do it *all* the time for *everything*, because the data indicates that failures are common (extinctions are observed, imperfect adaptations are observed), and the data indicate that biology doesn’t occupy all of functional space or sequence space, just little bits of it.

There are two misconceptions here. The first is, as already explained, that moving around between sequences that are located on the same island with the same type of function is very easy for RM/NS. This is not a problem whatsoever. However, this doesn’t get you a new type of function. Such mutations stay on the very same island and produce the very same type of function with “different-but-related sequences”. As you know, this isn’t the same thing as finding a different island with a qualitatively new type of function.

Now, you also claim that “occasionally” some of the paths between “different-but-related protein sequences” can be found with “different functions”. This is the entire question at hand. What is the average expected time for such a feat to be realized? – at various levels of functional complexity? You simply don’t know since you believe that, regardless of the level of functional complexity, that closely-spaced steppingstone islands exist somewhere in sequence space whereby random mutations can actually get from one novel island to the next without having to make much of a random walk. This claim of yours (identical to the claim of Jason Rosenhouse), simply doesn’t reflect what is known about sequence space at various levels of functional complexity. There simply are no such closely-space islands at higher levels of functional complexity that are actually known, and no reason to think that such a situation will ever be discovered.

But, you write, “The data indicate that biology doesn’t occupy all of functional space or sequence space, just little bits of it.”

That’s just the point. Since a population can only occupy the tiniest fraction of sequence space at a higher level of functional complexity, the finding of novel islands at the same level or higher involves crossing vast gaps of non-beneficial sequences that do in fact exist between each one of these higher-level islands and the next closest island. And that, my friend, is the fundamental problem for the ToE.

It also suggests that as sequence space increases in size by 20^N, the ratio of viable vs. non-viable sequences, not just systems, decreases exponentially. – Sean Pitman

This is just the all-at-once fallacy repeated again.

No, it isn’t. What it means is that your one-at-a-time mutations simply cannot cross the resulting gap distances in a reasonable amount of time beyond very low levels of functional complexity. It’s the very same problem regardless of if there are many random mutations at a time or just one random mutation at a time. The odds of success are the same.

You conclude with:

And, this effect only gets exponentially worse and worse with each step up the ladder of functional complexity. – Sean Pitman

This is raw assertion, not something your references say, and you haven’t defined the “ladder of functional complexity” anyway. Most of protein complexity involves fusing protein domains or evolving binding sites between them, these are pretty trivial processes.

I have defined the “ladder of functional complexity” (as have others in literature) as the minimum size and specificity of the parts required to produce a given type of function. In other words, some protein-based systems have a minimum amino acid residue requirement of only a dozen or so specifically arranged residues, while other protein-based systems have a minimum requirement of several thousand specifically arranged residues. These systems are on very different levels of functional complexity. And, the sequences spaces needed to hold these different systems are also very different when it comes to the ratio of beneficial vs. non-beneficial and the resulting distances between the beneficial islands of proteins within these sequence spaces.

As far your comments on junk-DNA, that’s a separate topic. I’ll have to respond at a later time.

FLAGELLUM

See the table at Panda’s Thumb from Pallen & Matzke 2006. There is a lot more to the argument than just the 10 proteins homologous to nonflagellar T3SS.

I’ve responded to your argument extensively at:

http://www.detectingdesign.com/flagellum.html

There is no point in discussing this until we resolve your misconception about the ability of single proteins to evolve along narrow paths through huge sequence space, in some cases retaining the same function, in other cases changing function.

Those paths exist. Phylogenies of proteins are one of the proofs. The branches of the phylogenies are actual statistical estimates of these paths. They exist both for cases where all the proteins at the tips have the same function, and for cases where some of the proteins at tips of the tree have different functions.

Phylogenies say nothing of the gap distances between the proposed steppingstones and how the distance between these steppingstones can be traversed along “narrow paths” via random mutations – which is the main problem with your flagellar evolution papers. You simply wave your hand and blindly assume that the gap distances are small enough because of the phylogenetic relationships or similarities between proteins within different systems. You see, the problem isn’t with the similarities. The problem for your mechanism is with the number of required non-selectable differences to get from one system, from one steppingstone, to the next. Phylogenetic similarities do suggest a common origin of some kind, but they do not tell you that the mechanism of RM/NS was in fact capable of producing the required differences – a key mistake on the part of evolutionists such as yourself.

For example, the steppingstones you list off in your flagellar evolution pathway are each far too far apart in sequence space for random mutations to get from any one to any other in a reasonable amount of time. The required non-selectable changes are simply far far too numerous for your theory to be tenable. Beyond this, as confirmation of this problem, not one of your proposed steps from one steppingstone to the next has been demonstrated in the lab. If these steppingstones are truly as close together as you seem to imagine, such a demonstration should be no problem. Take the wild-type system for one steppingstone and show how, given the appropriate selective environment, the next steppingstone in your sequence is actually reachable.

Sean Pitman Also Commented

Dr. Jason Rosenhouse “Among the Creationists”
I have no fear, thanks to God and His mercy, and no one is free of bias – not even you. You’ve simply traded one religion for another. It is still possible that your current bias blinds you to what would otherwise be obvious.


Dr. Jason Rosenhouse “Among the Creationists”

No, I think science would have discredited them if their ideas were not supported by observation and experimentation.

Exactly, so why not at least try to do the same for my ideas, which are quite easily falsifiable?

I know, you can’t do it yourself, but you’re quite sure that if I publish my ideas in a mainstream science journal that someone out there will know how to shoot my theory all to shreds. Right? This sounds like a no-brainer! Why not just published my ideas and test them against the big boys? It must be that I’m afraid to get shot down! and that’s why I don’t publish… Don’t you think?

I guess that’s why I went on live radio to debate Jason Rosenhouse? – because I was afraid that he’d show me how silly my ideas are on public radio? – how the Darwinian mechanism is so clearly capable of creating all kinds of things regardless of their level of functional complexity? If I was so afraid of getting smashed to pieces by some of these Darwinian big shots, why take such public risks? – even in their own blogs and public forums? Why not just hide out in my own little ghetto?

Come on now. You have to know that I’d love to be able to publish my ideas on the statistical limits to the Darwinian mechanism in a science journal like Nature or Science or any mainstream science journal. I really would. The problem, as I’ve already explained, is that no one is going to publish, in any mainstream science journal, any argument for intelligent design or creative intelligence (even if the intelligence were a “natural” intelligence like some kind of intelligent alien life form) as the origin of various kinds of biological machines. It just doesn’t happen these days without someone getting fired over it. So, the next best thing is to take the argument directly to them and challenge them in their own blogs, on the radio, and on television, etc. There’s nothing else I can do. My hands are tied.

In any case, do let me know when you’re willing to reasonably define what it would take for you to recognize a phenomenon as a true “miracle” or when you’re able to present something, anything, that explains how the Darwinian mechanism of RM/NS can actually work beyond very low level of functional complexity.

Until then, what are you really contributing here? What are you trying to say? – that you don’t know but someone else probably does? That you’re skeptical about everything and nothing could possibly convince you of the existence of God or any other designer of life? – not even if you were to personally witness some of the most fantastic miracles described in the Bible? Good luck with that… but you’re just fooling yourself in your efforts never to be tricked by anything. You’re missing out on a great deal that life has to offer.

Still, I wish you all the best.


Dr. Jason Rosenhouse “Among the Creationists”
All the best to you… yet again 😉


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