Durston Cont’d

_{Barry Arrington

February 3, 2009

Intelligent Design

3}_{Categories
Intelligent Design}

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Kirk Durston‘s Thoughts on Intelligent Design

In this thread, I would like to lay out my own thinking regarding a method to detect or identify examples of intelligent design. I then would like to unpack my thinking in a slow, meticulous (pedantic perhaps?) way and, if we can get that far, apply it to a few examples, including a protein, and the minimal genome.

Defining ‘Intelligent Design’:

I commonly see the term ‘intelligent design’ used in two ways. An example of the first way is in a magazine headline I saw this morning:

‘Evolution by Intelligent Design’

The above example is similar to the way ‘planning’ is used in, ‘Success through good planning.’

In this sense, we can define Intelligent Design as the ability of a mind to produce an effect that both satisfies a desired function or objective and might not otherwise likely occur. This ability emerges out of what we understand to be intelligence, defined in <a href=”http://en.wikipedia.org/wiki/Intelligence”>Wikipedia</a> as the capacities to reason, to plan, to solve problems, to think abstractly, to comprehend ideas, to use language, and to learn.

The second way I see the term intelligent design used is:

‘That traffic control system is a beautiful example of intelligent design.’

The usage of ‘intelligent design’ in the above sentence is similar to the usage of planning in, ‘That rescue operation was an excellent piece of planning.’

In this second type of usage, we can define intelligent design as an effect that satisfies a function or objective and requires a mind to produce. Other examples of intelligent design are the Sphinx and the Microsoft Vista operating system.

In the first sense, ‘intelligent design’ is an ability and in the second sense, ‘intelligent design’ is an effect, or result of that ability.

With this in mind, the definition of intelligent design that I will be using in this discussion is as follows:

Intelligent Design: 1 the ability of a mind to produce an effect that both satisfies a desired function and might not otherwise occur. 2. an effect that performs a function and that requires a mind to produce.

I realize that there are other definitions out there, some of which I do not at all agree with (e.g., Wiki’s). In general, most of the definitions of intelligent design that I see are actually specific examples, applications or results of intelligent design, rather than the defining essence of intelligent design. Ultimately, what I want to argue is that examples of intelligent design all required a mind to produce. I then want to argue that intelligent design is the most rational explanation for the protein families and the minimal genome. I will pause here in case anyone wishes to raise a question about what I’ve covered thus far. Then I will proceed to the next step.

Comments

rna: Well, maybe the biological designer is more an object oriented software programmer than a medieval engineer. Like many darwinists, you are going beyond the current purposes of ID: you are trying to design an outline of the designer. We in ID usually think we have not yet enough data to do that, but your argument about design modalities is interesting. There is another aspect which could be interesting, anyway. Our understanding of biological design is rather limited, because we know something about the effectors (the proteins), but almost nothing about the procedures (the regulation, and the general plan). So, before trying to understand the general style of the designer, we should perhaps be able to understand more of the real design. At present, with just the protein coding part partially understood, and that 98.5% of our genome still mysterious, no to speak of any other possible epigenetic source of information, I would say that our understanding is necessarily very partial. And moreover, it is not completely true that medieval cathedrals are not modular at all. Have you never seen more than one altar in them? More than one door, or arch, or paintings with a similar religious subject, or similar tombs, and so on? All those are designed modules, which are often "shuffled" in a cathedral, or between cathedrals, to achieve similar functions in different contexts. So, maybe our designer can still have something of a medieval engineer, too.gpuccio_{February 11, 2009
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jerry #96 you got the idea exactly right: some exons code for a functional protein domain capable of folding and function independently from its context and thereby 'exon shuffling' could be a mechanism for creating novel proteins by combining these sub-proteins into novel larger proteins. It is definitely not true for all exons, some of them for instance are much to small to code for an independent protein domain but for a significant fraction. Shuffling around of genetic information is an experimentally observable fact. gpuccio #97 "Obviously, all that is easily explained in a design context: domains sre functional units, much like objects in object oriented programming. Programming is modular. Advanced programming is even more modular. That’s the way design works." But it is not the only way design can work. If for instance the medieval churches in europe were designed in that way they would consist of an aggregation of many small houses. But the dome in florence is designed as a single entity. Somehow this grand unified kind of design is not that obvious in nature.rna_{February 11, 2009
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jerry: domains are functional subunits of proteins, and the concept of domain is similar, bur not identical, to the concept of fold. Simpler proteins contain only one domain, while more complex proteins contain many domains. Each domain has its own folding. I have not read the whole article quoted by rna, but I think that the general idea is that sometimes, but not always, domain boundaries correspond to exon boundaries (but that does not necessarily mean, I think, that one domain is made of one single exon). That would make easier the "shuffling" of one domain from one protein to another. The fact is, domains are functional units of proteins. Domains and folds are in the number of thousands. They form thousands of thousands of different, and differently functional proteins. And different proteins form thousands of different multi-protein molecular machines. In other words, biological information is layered in different layers of ever increasing complexity, and each of them has functional organization. Darwinian theory would like to intepret all that as a series of lucky "shufflings": domains comne out of lucky shufflings of aminoacids (or codons, if you want); more complex proteins come out of lucky shufflings of domains; molecular machines come out of lucky shufflings of proteins. I am not aware of an explicit shuffling theory for transcriptomes and transcription regulation, but who knows? Obviously, all that is easily explained in a design context: domains sre functional units, much like objects in object oriented programming. Programming is modular. Advanced programming is even more modular. That's the way design works. But I suppose our darwinist friends would easily explain the whole Windows Vista as the product of "lucky" shuffling... (I know, I know, many of you will agree; well, maybe not with the "lucky" part). :-)gpuccio_{February 10, 2009
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rna, Thank you. Though I am not sure how much of this I understand. Are you suggesting that the exons are modules and that they are picked and chosen to form a larger protein by combining the sub proteins into a larger protein. And that each exon folds on its own? If you have some time to provide some layman English to it, it would be appreciated.jerry_{February 10, 2009
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jerry #68, gpuccio #69 There are actually examples where the boundaries of exons correlate with the boundaries of protein domains in larger proteins and protein domains are normally capable of folding independently from the remainder of the protein. See: Mingyi Liu and Andrei Grigoriev, Trends in Genetics, Vol. 20, 2004, pages 399-403. Title: "Protein domains correlate strongly with exons in multiple eukaryotic genomes – evidence of exon shuffling?" Abstract: "We conducted a multi-genome analysis correlating protein domain organization with the exon–intron structure of genes in nine eukaryotic genomes. We observed a significant correlation between the borders of exons and domains on a genomic scale for both invertebrates and vertebrates. In addition, we found that the more complex organisms displayed consistently stronger exon-domain correlation, with substantially more significant correlations detected in vertebrates compared with invertebrates. Our observations concur with the principles of exon shuffling theory, including the prediction of predominantly symmetric phase of introns flanking the borders of correlating exons. These results suggest that extensive exon shuffling events during evolution significantly contributed to the shaping of eukaryotic proteomes."rna_{February 10, 2009
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Lutepisc[93], Indeed, the secret is in the aquavit. The "e" is a norwegianism.Prof_P.Olofsson_{February 10, 2009
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Thanks for that, PO. Yes, cognoscenti spell the fish without the "e" (and, of course, they don't spell it with a "p" or "c." For those unacquainted with the delicacy, may I point you to a web site which describes the proper way to eat it? http://www.shirky.com/writings/lutefisk.htmlLutepisc_{February 10, 2009
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Lutepisc[91], That's jerry's branding of me. I have to trust him; he is after all a real Swede who knows that it is "lutfisk" and not "lutefisk."Prof_P.Olofsson_{February 9, 2009
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"PO, unsoiled establishment type" Quite right, PO. Dr. Fuller, are you listening? Would you care to comment on this?Lutepisc_{February 9, 2009
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Apollos, thank you. So the equation should be: ζE = ΔH(Xfa(ti), Xfb(tj))gpuccio_{February 9, 2009
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Testing Greek: Δ Δ δ δ Ζ Ζ ζ ζ GP, If the above shows up correctly, the issue is most likely with use of the trailing semicolon. The preview (unfortunately) allows its omission, however it is definitely required for proper formatting. HTML codes will not show up in the post without the trailing semicolon. ΑπολλωςApollos_{February 9, 2009
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jerry[74,85], Thanks for the tip but I'll be content with the dull future my current research holds in promise. Conversing directly with Kirk is certainly an option that we might pursue. I understand if he prefers to focus on his research and dissertation though. PO, unsoiled establishment typeProf_P.Olofsson_{February 9, 2009
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No, it shows correctly in the preview, but is changed in the process of posting. It shoud be: Zeta (greek character) E = Delta (greek character) H, and then the rest.gpuccio_{February 9, 2009
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I see that the equation from The Durston paper did not appear correctly in the above post. I try again: ?E = ?H (Xfa(ti), Xfb(tj))gpuccio_{February 9, 2009
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Prof P. Why don't you converse with Kirk directly? Since you are not soiled with our sins, and are on record as part of the anti ID establishment you should not cause Kirk any dismay. Your two articles are credentials enough for you to pursue this further. Did you see the last paragraph of my comment #74? There is a bright future in this for you.jerry_{February 9, 2009
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Peter: I am not happy that the discussion remain truncated. It is a discussion which, however, will have to be taken again, and soon enough. I don't know how Kirk was going to guide the discussion, but I would like to suggest a few points which certainly could stimulating contribution. 1) If we accept the definitions given up to now, functional information can be defined according to Hazen's equation: I(Ex) = - log2[M(Ex)/N] Please notice that Hazen is assuming an uniform distribution of the protein sequences, which is the only reasonable position for a biochemical system where all four nucleotides have similar probabilities in each position of the sequence. Anyway, if anybody has objections to that, he should state those objections clearly and explicitly, so that we can discuss them now. I have alredy invited Prof. Olofsson to comment on that, but he has not yet obliged. That said, the problem remains of how to compute the functional state, M(Ex). There are two ways of doing that. First of all, I would suggest that for the moment we define the functional state with reference to the specific function defines for the protein we are considering, and, as stated by Kirk, according to a definite threshold of function: Ex is therefore one specific function, measured with reference to a specific minimum level. In other words, Ex is binary (it is either absent or present), and M(Ex) is the number of sequences in the search space for which Ex is present. The two ways to compute M(Ex) are: direct and indirect. The direct way consists in knowing with some approximation the real number of sequences which will express Ex. While that is at present impossible with absolute precision for any known protein, because we know too little of protein function and of the structure of the protein space, still many comsiderations, both qualitative and quantitative, can already be made to try to assess at least the range of orders of magnitude which we can expect for M(Ex). Moreover, our knowledge is rapidly increasing due to the dtat coming from the field of protein engineering. But this subject is very vast, and I would stop here at the moment (but we can deepen any aspect of that issue), to pass to the second way. The second way to compute M(Ex) is probably the one Kirk was trying to describe in detail, because it is given in his paper "Measuring the functional sequence complexity of proteins" (with Chiu, Abel, and Trevors), which I invite all those interested to read with great attention. In brief, the method consists in measuring the functional information as the reduction of uncertainty in a protein family with respect to the random state. I quote from the paper: "The measure of Functional Sequence Complexity, denoted as ?, is defined as the change in functional uncertainty from the ground state H(Xg(ti)) to the functional state H(Xf(ti)), or ? = ?H (Xg(ti), Xf(tj)).(6) The resulting unit of measure is defined on the joint data and functionality variable, which we call Fits (or Functional bits). The unit Fit thus defined is related to the intuitive concept of functional information, including genetic instruction and, thus, provides an important distinction between functional information and Shannon information" So, just to make an example, if you look at table 1 in the paper, you will see that for ribosomal protein S12, a protein of 121 aminoacids, the analysis performed on 603 different sequences of the same protein in different species shows that, while the ground state has an uncertainty (H) of 523 bits, the reduction of that uncertainty in the functional set is of 359 bits: therefore, that is the value in Fits for that protein according to this method of measurement. I would like to invite further discussion on these poiints. If we accept them, the points still to be discussed are: a) defining a threshold for what a random process can achieve in some definite biological system b) discussing the possible role of necessity (NS, special configurations of the search space, like in the transition from an existing protein to another, and any other possible model of necessity which can reduce the role of random processes). c) discussing the role of function definition in the above procedure, in particular in reference to the often mentioned objection that evolution can attain "any possible function".gpuccio_{February 9, 2009
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Kirk, Too bad indeed. I originally requested this new thread so you could address my comments and questions and I'm sorry it got you into an awkward position.Prof_P.Olofsson_{February 9, 2009
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Kirk, Thanks for your informative comments. Best of luck. Would it be possible for another of our very erudite bloggers to pick up where Kirk left off? I was really hoping to learn more about the absolute limit of nature to generate functional information.Peter_{February 9, 2009
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Kirk: we do understand, but it's a real pity! I hope we can hear from you as soon as it is convenient for you.gpuccio_{February 9, 2009
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Sounds like the work of one of Canada's biggest academic assholes -Larry Moran http://www.evolutionnews.org/2008/04/censorship_of_intelligent_desi.htmlDaveScot_{February 9, 2009
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The DNEA (Darwinian Narrative Enforcement Agency) appears to gotten through to Kirk. It was only a matter of time...DaveScot_{February 9, 2009
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Durston Diccont’d?sparc_{February 9, 2009
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Jerry: You could give a look at the SCOP classification of proteins. Superfamilies could more or less correspond to your concept of islands. Proteins are not probably millions, but there are certainly a lot of them. Individual folds are probably in the range of a few thousands, with abou one thousand representing 60-70% of known proteins. And yes, proteins which fold are rare, even if nobody knows exactly how rare. And each fold is certainly an island. And there are not "sub-proteins" which fold. Fodling is a very complex process, which we still do not understand completely. Indeed, given a primary sequence, it is still very difficult to know if it will fold. Some proteins are multi-domain: they are very big, and include more than one fold in their structure. But most proteins have a single domain. Folding is not enough for functionality, but it is necessary. Beyond folding, a protein has to have an active site, which is responsible for function, and which the correct folding positions in the correct way. Moreover, many proteins have to undergo conformational changes ahter binding their ligand, and those changes are essential to function. Moreover, the more complex proteins cannot fold spontaneously: they need other very complex proteins, called chaperones, to help their folding. The way the most complex chaperones work is sitll a mystery. And it is still more complex than that. The relationship between primary sequence and folding is very unpredictable. Just to give an example, bacterial hemoglobin, which is one of the first examples of a myoglobin, has a folding which is almost identical to human myoglobin, but its primary sequence is completely different, sharing only about 20% homology with the human protein. And the function is the same. Other times, just a single aminoacid change will prevent both folding and function. And I agree with you, we should talk more about biological matters. ID is much more powerful and self-evident when biological realities are correctly understood.gpuccio_{February 9, 2009
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I think most of us understand, KD.tribune7_{February 9, 2009
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Hello all. Due to my involvement in this discussion, I have placed myself in an awkward position, the details of which I would like to keep confidential. To avoid further complications, I have decided to withdraw from contributing further. I do apologize for this. Again, I think it best to keep the details confidential.KD_{February 9, 2009
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gpuccio, Thank you for your explanation. One of the things that would be nice to have on the site are faqs about the science of micro biology itself. That maybe too much as it may prove endless. But we frequently talk about technical things and sometimes with little knowledge. What I was trying to understand was if the whole folds, and I realize how it folds is due to the physics of the attraction and repelling of the individual amino acids, does that mean that the parts will also fold and potentially be useful. I realize the folding of a sub protein may be quite different than the folding of the whole protein since the forces will be different. From what I understand, Kirk said it is extremely rare for a protein to fold. And in protein sequence space there are great differences between one foldable island and another. Each island is a set of possibly millions/billions of foldable proteins, each just a little bit different from its neighbor but eventually you run into neighbors on all sides that do not fold and thus cannot be useful. These islands also consist of sub proteins of a larger protein that also fold. And also the proteins in these islands may fold completely different from its neighbor because the differences between the two could represent a different force set due to just one change. So what I am trying to understand is just what do these isolated islands consist of. It is one thing to say they are rare but I was trying to understand this process better and do it at a level that is understandable for a non expert in the field. We have a new tool in our basket and we know so little about it. It is here that Prof O's expertise could be of use since we are dealing with instances of a phenomena and how can one form the proper probability distributions to analyze them. Maybe Prof O should look into this since he could become the expert in this upcoming field of the probability distributions of protein functionality.jerry_{February 9, 2009
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kf[71], I suppose you can say odds and mean probability, but the mathematical definition of odds is the ratio p/(1-p).Prof_P.Olofsson_{February 9, 2009
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Jerry and GP: the fact that with introns and exons we can have multiple proteins coded for with the same DNA strand implies multiple layering of codes. That reminds me of the microcontroller programmer's trick form the bad old days of scant memories -- imagine a friend just reminded me of his early-mid 70's 1 MB RAM for video coding research that cost US$ 1 millions . . . -- by which the same storage was interpreted by one framing as code to be executed and by another as data to execute upon! I never even TRIED that trick. The levels of sophistication of the design of the cell are getting deeper and deeper. (I assume by now we have all seen the NHK video on the self-assembly of the flagellum, where the length of the elbow is set by the uncoiled string length of the protein being sent up the pipe, based on catalytic effects . . .] Dah is be SERIOUS engineering, mon! Gkairosfocus_{February 9, 2009
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SuperPO: Somehow, it seems from my background I have heard "odds of 1 IN 6" (fractional = probability], and "odds of 1 TO 5" [a weird sort of improper, correspondence "ratio"] both used. Gkairosfocus_{February 9, 2009
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Ah Atom: I suspect a video RAM hardware headache . . . G PS: been using AVG for ~ 5 y, with reasonable success.kairosfocus_{February 9, 2009
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