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Exon Shuffling, and the Origins of Protein Folds

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800px-Protein_structure.png

A frequently made claim in the scientific literature is that protein domains can be readily recombined to form novel folds. In Darwin’s Doubt, Stephen Meyer addresses this subject in detail (see Chapter 11). Over the course of this article, I want to briefly expand on what was said there.

Defining Our Terms

Before going on, it may be useful for me to define certain key terms and concepts. I will be referring frequently to “exons” and “introns.” Exons are sections of genes that code for proteins; whereas introns are sections of genes that don’t code for proteins.Introns and exons.png

Proteins have multiple structural levels. Primary structure refers to the linear sequence of amino acids comprising the protein chain. When segments within this chain fold into structures such as helices and loops, this is referred to as secondary structure. Common units of secondary structure include α-helices and β-strands. Tertiary structure is the biologically active form of the protein, and refers to the packing of secondary structural elements into domains. Since a protein’s tertiary structure optimizes the forces of attraction between amino acids, it is the most stable form of the protein. When multiple folded domains are arranged in a multi-subunit complex, it is referred to as a quaternary structure.

A further concept is domain shuffling. This is the hypothesis that fundamentally new protein folds can be created by recombining already-existing domains. This is thought to be accomplished by moving exons from one part of the genome to another (exon shuffling). There are various ways in which exon shuffling might be achieved, and it is to this subject that I now turn.

The Mechanisms of Exon Shuffling

There are several ways in which exon shuffling may occur. Exon shuffling can be transposon-mediated, or it can occur as a result of crossover during meiosis and recombination between non-homologous or (less frequently) short homologous DNA sequences. Alternative splicing is also thought to play a role in facilitating exon shuffling.

When domain shuffling occurs as a result of crossover during sexual recombination, it is hypothesized that it takes place in three stages (called the “modularization hypothesis”). First, introns are gained at positions that correspond to domain boundaries, forming a “protomodule.” Introns are typically longer than exons, and thus the majority of crossover events take place in the noncoding regions. Second, within the inserted introns, the newly formed protomodule undergoes tandem duplication. Third, intronic recombination facilitates the movement of the protomodule to a different, non-homologous, gene.

Another hypothesized mechanism for domain shuffling involves transposable elements such as LINE-1 retroelements and Helitron transposons, as well as LTR retroelements. LINE-1 elements are transcribed into an mRNA that specifies proteins called ORF1 and ORF2, both of which are essential for the process of transposition. LINE-1 frequently associates with 3′ flanking DNA, transporting the flanking sequence to a new locus somewhere else on the genome (Ejima and Yang, 2003Moran et al., 1999Eickbush, 1999). This association can happen if the weak polyadenylation signal of the LINE-1 element is bypassed during transcription, causing downstream exons to be included on the RNA transcript. Since LINE-1’s are “copy-and-paste” elements (i.e. they transpose via an RNA intermediate), the donor sequence remains unaltered.

Long-terminal repeat (LTR) retrotransposons have also been established to facilitate exon shuffling, notably in rice (e.g. Zhang et al., 2013Wang et al., 2006). LTR retrotransposons possess a gag and a pol gene. The pol gene translates into a polyprotein composed of an aspartic protease (which cleaves the polyprotein), and various other enzymes including reverse transcriptase (which reverse transcribes RNA into DNA), integrase (used for integrating the element into the host genome), and Rnase H (which serves to degrade the RNA strand of the RNA-DNA hybrid, resulting in single-stranded DNA). Like LINE-1 elements, LTR retrotransposons transpose in a “copy-and-paste” fashion via an RNA intermediate. There are a number of subfamilies of LTR retrotransposons, including endogenous retroviruses, Bel/Pao, Ty1/copia, and Ty3/gypsy.

Alternative splicing by exon skipping is also believed to play a role in exon shuffling (Keren et al., 2010). Alternative splicing allows the exons of a pre-mRNA transcript to be spliced into a number of different isoforms to produce multiple proteins from the same transcript. This is facilitated by the joining of a 5′ donor site of one intron to the 3′ site of another intron downstream, resulting in the “skipping” of exons that lie in between. This process may result in introns flanking exons. If this genomic structure is reinserted somewhere else in the genome, the result is exon shuffling.There are of course other mechanisms that are hypothesized to play a role in exon shuffling. But this will suffice for our present purposes. Next, we will look at the evidence for and against domain shuffling as an explanation for the origin of new protein folds.

Introns Early vs. Introns Late

It was hypothesized fairly early, after the discovery of introns in vertebrate genes, that they could have contributed to the evolution of proteins. In a 1978 article in Nature, Walter Gilbert first proposed that exons could be independently assorted by recombination within introns (Gilbert, 1978). Gilbert also hypothesized that introns are in fact relics of the original RNA world (Gilbert, 1986). According to the “exons early” hypothesis, all protein-coding genes were created from exon modules — coding for secondary structural elements (such as α-helices, β-sheets, signal peptides, or transmembrane helices) or folding domains — by a process of intron-mediated recombination (Gilbert and Glynias, 1993Dorit et al., 1990).

The alternative “introns late” scenario proposed that introns only appeared much later in the genes of eukaryotes (Hickey and Benkel, 1986Sharp, 1985Cavalier-Smith, 1985Orgel and Crick, 1980). Such a scenario renders exon shuffling moot in accounting for the origins of the most ancient proteins.

The “introns early” hypothesis was the dominant view in the 1980s. The frequently cited evidence for this was the then widespread belief in the general correspondence between exon-intron structure and protein secondary structure.

From the mid 1980s, this view became increasingly untenable, however, as new information came to light (e.g. see Palmer and Logsdon, 1991; and Patthy, 1996199419911987) that raised doubts about a general correlation between protein structure and intron-exon structure. Such a correspondence is not borne out in many ancient protein-coding genes. Moreover, the apparently clearest examples of exon shuffling all took place fairly late in the evolution of eukaryotes, becoming significant only at the time of the emergence of the first multicellular animals (Patthy,19961994).

In addition, analysis of intron splicing junctions suggested a similar pattern of late-arising exon shuffling. The location where introns are inserted and interrupt the protein’s reading frame determines whether exons can be recombined, duplicated or deleted by intronic recombination without altering the downstream reading frame of the modified protein (Patthy, 1987). Introns can be grouped according to three “phases”: Phase 0 introns insert between two consecutive codons; phase 1 introns insert between the first and second nucleotide of a codon; and phase 2 introns insert between the second and third nucleotide.

Thus, if exon shuffling played a major role in protein evolution, we should expect a characteristic intron phase distribution. But the hypothetical modules of ancient proteins do not conform to such expectations (Patthy, 19911987).

It is clear, then, that exon shuffling (at the very least) is unlikely to explain the origins of the most ancient proteins that have emerged in the history of life. But is this mechanism adequate to explain the origins of later proteins such as those that arise in the evolution of eukaryotes? I now turn to evaluate the evidence pro-and-con for the role of exon shuffling in protein origins.

The Case for Exon Shuffling

What, then, are the best arguments for exon shuffling? If the thesis is correct, a prediction would be that exon boundaries should correlate strongly with protein domains. In other words, one exon should code for a single protein domain. One argument, therefore, points to the fact that there is a statistically significant correlation between exon boundaries and protein domains (e.g., see Liu et al., 2005 and Liu and Grigoriev, 2004).

However, there are many, many examples where this correspondence does not hold. In many cases, single exons code for multiple domains. For instance, protocadhedrin genes typically involve large exons coding for multiple domains (Wu and Maniatis, 2000). In other cases, multiple exons are required to specify a single domain (e.g. see Ramasarma et al., 2012; or Buljan et al., 2010).

A further argument for the role of exon shuffling in protein evolution is the intron phase distributions found in the exons coding for protein domains in humans. In 2002, Henrik Kaessmann and colleagues reported that “introns at the boundaries of domains show high excess of symmetrical phase combinations (i.e., 0-0, 1-1, and 2-2), whereas nonboundary introns show no excess symmetry” (Kaessmann, 2002). Their conclusion was thus that “exon shuffling has primarily involved rearrangement of structural and functional domains as a whole.” They also performed a similar analysis on the nematode worm Caenorhabditis elegans, finding that “Although the C. elegans data generally concur with the human patterns, we identified fewer intron-bounded domains in this organism, consistent with the lower complexity of C. elegans genes.”

Another line of evidence relates to genes that appear to be chimeras of parent genes. These are typically associated with signs indicative of its mode of origin. One famous example is the jingweigene in Drosophila, which may have arisen when “the sequence of the processed Adh [alcohol dehydrogenase] messenger RNA became part of a new functional gene by capturing several upstream exons and introns of an unrelated gene” (Long and Langley, 1993).

We must take care, however, not to confuse the observed pattern of intron phase distribution, or exon/domain mapping, with proof that exon shuffling is actually the process by which this pattern arose.

Perhaps common ancestry is the cause, but this must be demonstrated and not assumed. It is the biologist’s duty to determine whether unintelligent chance-based mechanisms actually can produce novel genes in this manner. It is to this question that I now turn.

The Problems with Domain Shuffling as an Explanation for Protein Folds

While the hypothesis of exon shuffling does, taken at face value, have some attractive elements, it suffers from a number of problems. For one thing, the model at its core presupposes the prior existence of protein domains. A protein’s lower-level secondary structures (α-helices and β-strands) exist stably only in the context of the tertiary structures in which they are found. In other words, the domain level is the lowest level at which self-contained stable structural modules exist. This leaves the origins of these domains in the first place unaccounted for. But stable and functional protein domains are demonstrably rare within amino-acid sequence space (e.g. Axe, 2010Axe, 2004Taylor et al., 2001Keefe and Szostak, 2001Reidhaar-Olson and Sauer, 1990Salisbury, 1969).

A fairly recent study examined many different combinations of E. coli secondary structural elements (α-helices, β-strands and loops), assembling them “semirandomly into sequences comprised of as many as 800 amino acid residues” (Graziano et al., 2008). The researchers screened 108 variants for features that might suggest folded structure. They failed, however, to find any folded protein structures. Reporting on this study, Axe (2010) writes:

“After a definitive demonstration that the most promising candidates were not properly folded, the authors concluded that “the selected clones should therefore not be viewed as ‘native-like’ proteins but rather ‘molten-globule-like'”, by which they mean that secondary structure is present only transiently flickering in and out of existence along a compact but mobile chain. This contrasts with native-like structure, where secondary structure is locked-in to form a well defined and stable tertiary fold. Their finding accords well with what we should expect in view of the above considerations. Indeed, it would be very puzzling if secondary structure were modular.”

“For those elements to work as robust modules,” explains Axe, “their structure would have to be effectively context-independent, allowing them to be combined in any number of ways to form new folds.” In the case of protein secondary structure, however, this requirement is not met.

The model also seems to require that the diversity and disparity of functions carried out by proteins in the cell can in principle originate by mixing and matching prior existing domains. But this presupposes the ability of blind evolutionary processes to account for a specific “toolbox” of domains that can be recombined in various ways to yield new functions. This seems unlikely, especially in light of the estimation that “1000 to 7000 exons were needed to construct all proteins” (Dorit et al., 1990). In other words, a primordial toolkit of thousands of diverse protein domains needs to be constructed before the exon shuffling hypothesis even becomes a possibility. And even then there are severe problems.

A further issue relates to interface compatibility. The domain shuffling hypothesis in many cases requires the formation of new binding interfaces. Since amino acids that comprise polypeptide chains are distinguished from one another by the specificity of their side-chains, however, the binding interfaces that allow units of secondary structure (i.e. α-helices and β-strands) to come together to form elements of tertiary structure is dependent upon the specific sequence of amino acids. That is to say, it is non-generic in the sense that it is strictly dependent upon the particulars of the components. Domains that must bind and interact with one another can’t simply be pieced together like jenga tiles.

In his 2010 paper in the journal BIO-Complexity Douglas Axe reports on an experiment conducted using β-lactamase enzymes which illustrates this difficulty (Axe, 2010). Take a look at the following figure, excerpted from the paper:

Beta lactamase comparison.png

The top half of the figure (labeled “A”) reveals the ribbon structure of the TEM-1 β-lactamase (left) and the PER-1 β-lactamase (right). The bottom half of the figure (labeled “B”) reveals the backbone alignments for the two corresponding domains in the two proteins. Note the high level of structural similarity between the two enzymes. Axe attempted to recombine sections of the two genes to produce a chimeric protein from the domains colored green and red. Since the two parent enzymes exhibit extremely high levels of structural and functional similarity, this should be expected to work. No detectable function was identified in the chimeric construct, though, presumably as a consequence of the substantial dissimilarity between the respective amino-acid sequences and the interface incompatibility between the two domains.

This isn’t by any means the only study demonstrating the difficulty of shuffling domains to form new functional proteins. Another study by Axe (2000) described “a set of hybrid sequences” from “the 50%-identical TEM-1 and Proteus mirabilis β-lactamases,” which were created such that the “hybrids match[ed] the TEM-1 sequence except for a region at the C-terminal end, where they [were] random composites of the two parents.” The results? “All of these hybrids are biologically inactive.”

In fact, in the few cases where protein chimeras do possess detectable function, it only works for the precise reason that the researchers used an algorithm (developed by Meyer et al., 2006) to carefully select the sections of a protein structure that possess the fewest side-chain interactions with the rest of the fold, and chose parent proteins with relatively high sequence identity (Voigt et al., 2002). This only serves to underscore the problem. Even in the Voigt study, the success rate was quite low, even with highly favorable circumstances, with only one in five chimeras possessing discernible functionality.

Conclusion

To conclude, although there is some indirect inferential evidence for the role of exon shuffling in protein evolution, a consideration of how such a process might work in reality reveals that the hypothesis itself is fraught with severe difficulties.

This article was originally published at Evolution News & Views (part 1; part 2)

Comments
Zachriel: Some further reflections. Just to show how vague your concept of "known biological function" is: Sodium bicarbonate has certainly a known biological function. Buffer systems based on it are essential for our survival. I agree with you that proteins are a special example, because of their folding properties and biochemical activities of the residues, which allow gradual "molding" to specific functions. That's why protein engineering is possible. What you need is some starting property which can be intentionally selected and then bottom up engineered. That's what the weak ATP binding is in the paper. NS can do the same only if the starting property and the individual intermediates confer a reproductive advantage to real biological replicators in a real, or appropriately simulated, natural environment.gpuccio
February 27, 2015
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There is no such thing as a natural protein fold. All protein folding is supernatural.Mung
February 27, 2015
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Zachriel: I said: "We can certainly say that in a random library there are some proteins which exhibit some biological function, in the specific case weak ATP binding" And you say: "ATP-binding is a known biological function" So, here we agree. I said: "which as far as we know would be of no use in a real biological context " And you do not comment. Have you any evidence that the original proteins have been shown to be of some use in a real biological context? Or do you agree that there is no evidence of that? I said: "and could never be the object of a process of NS." which is obviously the consequence of the previous statement (the one you have not commented). You say: "If there’s a selection gradient, then natural selection could work on that gradient to increase functionality." But that is obviously not true if we don't start from a property which is naturally selectable. A selection gradient is not enough. You need a starting naturally selectable property and a gradient of naturally selectable states. Here you ave neither. There is no evidence that the original sequences are naturally selectable. There is some evidence (in a following paper) that even the final engineered proteins is not naturally selectable. You say: "This is just a proof of concept. It shows that random sequences can fold into the complex conformations necessary for protein function, and that these can then be optimized through selection." And I agree. But again, your statement cleverly conflates natural selection and intelligent selection (engineering). To sum up (Intelligent selection for dummies): a) Natural selection is a special form of selection where what is selected is always a reproductive advantage in replicators in a natural environment (or in a correct model of a natural environment), and nothing else. That reproductive advantage must be demonstrated in the starting state and in each intermediate state which is supposed to be selected. b) Intelligent selection is any form of selection where an environment explicitly measures a property and reacts to the measurement by promoting or repressing the result of variation according to the measurement. In intelligent selection, both the measurement system and the active intervention on the result of variation are realized by special configurations of the system which implement the measurement and the intervention, and connect the two things. In intelligent selection any property can be selected at any desired level, provided that the system is configured (usually, maybe always, by design) so that it can attain the result.gpuccio
February 27, 2015
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DNA_Jock @76: Pitiful. Are you denying that reproductive advantage is the only property which is selected by NS? Obviously, it is the only property that anyone is allowed to test is one wants to derive conclusions about NS. The experiment I quoted repeatedly (rugged landscape) was about phage infectivity, and I have repeatedly stated that it is a good experiment testing NS. Obviously, infectivity for phages and growth for bacteria are forms of the same thing: reproduction. And reproductive advantage is the property selected by NS. Back-pedalling? Pitiful. If you go on with this tone, I will probably not answer any more.gpuccio
February 27, 2015
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Joe, Much as I hesitate to engage you,
Proteins can grow? Evidence please. Proteins are not stalagmites, nor are they living organisms.
Can you think of a way that a single point mutation could cause a protein to "grow" longer by Poisson(21) amino acids? Hint: the new amino acids get added to the C-terminus... LOLDNA_Jock
February 26, 2015
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gpuccio writes:
DNA_Jock: Wrong. There is no problem is designing an experiments which models natural selection is a somewhat reliable way. One has to be aware of possible differences between the experimental model and the true scenario, but is the experimental model is a good model, at least for the important aspects, it is certainly useful. What is not useful is a bad model.
Fantastic! I am happy that you have finally come around to my way of thinking. Just remember that "That's not the experiment I would have done?" is NOT a valid objection.
I am not selecting growth because I find it “desirable”, but because it is the only property which corresponds to the differential growth which is the mechanism in NS.
So this is the reason why, according to you, 'growth' is the one, unique property that I am allowed to design experiments to optimize. Cool. Would bacteriophage infectivity count too? [Cue back-pedalling]DNA_Jock
February 26, 2015
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Proteins can grow? Evidence please. Proteins are not stalagmites, nor are they living organisms.Joe
February 26, 2015
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Yes, and babies are very short with respect to the median length of human beings ... Proteins can grow. Catalytic activity is achievable even with dipeptides, particularly when they are attached to a larger molecule (which does not have to be the remainder of a protein).Hangonasec
February 26, 2015
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It shows that random sequences can fold into the complex conformations necessary for protein function, and that these can then be optimized through selection.
Short random sequences-> 80 amino acids is very short with respect to the median length of polypeptides known to exist in living organisms.Joe
February 26, 2015
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gpuccio: in the specific case weak ATP binding, which as far as we know would be of no use in a real biological context ATP-binding is a known biological function. See Matte & Delbaere, ATP?binding Motifs, in Encyclopedia of Life Sciences, Wiley-Blackwell 2002. gpuccio: and could never be the object of a process of NS. If there's a selection gradient, then natural selection could work on that gradient to increase functionality. This is just a proof of concept. It shows that random sequences can fold into the complex conformations necessary for protein function, and that these can then be optimized through selection. Returning to the original claim: Jonathan M: But stable and functional protein domains are demonstrably rare within amino-acid sequence space Functional proteins are found in about 10^-11 random sequences.Zachriel
February 26, 2015
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Zachriel: We can certainly say that in a random library there are some proteins which exhibit some biological function, in the specific case weak ATP binding, which as far as we know would be of no use in a real biological context and could never be the object of a process of NS. And we can say that simple methods of intelligent protein engineering can transform that property, through a gradient of affinity, into a strong ATP binding. Which, as far as we know (and there is also a paper about that) would be of no use in a real biological context and could never be the object of a process of NS. Are you satisfied with that summary?gpuccio
February 26, 2015
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DNA_Jock: Wrong. There is no problem is designing an experiments which models natural selection is a somewhat reliable way. One has to be aware of possible differences between the experimental model and the true scenario, but is the experimental model is a good model, at least for the important aspects, it is certainly useful. What is not useful is a bad model. You say: "My understanding from these statements is that any experiment I could set up to prove the in vivo “selectability” of random peptides would be an example of Intelligent Selection, since I would be selecting some function as desirable (e.g.‘growth’), setting the context for its appearance and measuring it." No. If I select growth of a bacterial system as the measured outcome, I am building an acceptable model of NS. Why? Because reproductive advantage is exactly the only property that is supposed to be selected in NS. So, if I make an experiment where the outcome is differential growth, I am on a good path to model NS. I am not selecting growth because I find it "desirable", but because it is the only property which corresponds to the differential growth which is the mechanism in NS. Not so if I choose a weak ATP binding, and then transform it into a strong ATP binding by methods of active engineering, which have nothing to do with a selection based on differential growth (NS). It is so simple. But if one does not want to accept a true concept, one will never accept it.gpuccio
February 26, 2015
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Gpuccio, I am not lying. You have defined “Intelligent Selection" as follows:
IS is any situation in which the system actively measures some property of the mutated object and reacts to that measure in a specific way. [Emphasis added]
And noted
IS requires a conscious intelligent agent who recognizes some function as desirable, sets the context to develop it, can measure it at any desired level, and can intervene in the system to expand any result which shows any degree of the desired function. IOWs, both the definition of the function, the way to measure it, and the interventions to facilitate its emergence are carefully engineered. It’s design all the way.
My understanding from these statements is that any experiment I could set up to prove the in vivo “selectability” of random peptides would be an example of Intelligent Selection, since I would be selecting some function as desirable (e.g.‘growth’), setting the context for its appearance and measuring it. And since:
Using examples of Intelligent Selection to derive conclusions about Natural Selection is methodological error or cheat, because they are two different things, whatever their possible origin. It’s as simple as that.
Szostak’s experiment is a poor model of the natural process because it has the formal properties of IS, not of NS: selection of a property by measurement, and controlled variation + amplification in cycles of and re-selection based on new measurements.
So how on earth could I design an experiment that did not involve “Intelligent Selection”. It can’t be done. Using YOUR definitions. For instance, if I were to replace an essential peptide sequence with a random peptide, and then iteratively mutate and select for growth in vivo, that would be “Intelligent Selection”, and therefore a “methodological error or cheat” according to your definitions, right?DNA_Jock
February 25, 2015
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gpuccio: there is no doubt at all that some proteins in the initial random library exhibit weak binding to ATP. And there is no doubt that we can call this “a function” gpuccio: Instead, he has done a different thing. Rather, he has done an additional thing. Not only did the experiment show that there are functional proteins in random sequences, but it showed that there is a selectable pathway to increased function.Zachriel
February 25, 2015
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DNA_Jock and Zachriel: I am rather tired of your tricks. The problem is not with the word "function". The problem is with the methodology and the conclusions. As you should know, I have no special concept of what is function and what is not. If you read my OP here: https://uncommondescent.com/intelligent-design/functional-information-defined/ you will easily see that in my procedure to detect dFSCI any function is valid and can be used to measure a specific functional information. Function is any way an object can be used to do something and have some result. So, I have no objections to considering a weak binding to ATP a function. The simple fact that you both insist in arguing in that sense shows that either you don't understand what I clearly say, or you are playing tricks. Now, I will try to be even more clear, if possible. As I have stated explicitly many times, there is no doubt at all that some proteins in the initial random library exhibit weak binding to ATP. And there is no doubt that we can call this "a function", defining it, for example: "Any molecule which binds to ATP". Fine. No problems. Now, let's say that the purpose of Szostak was to demonstrate that some sequences in the initial random library had this function. It's rather easy. The simple fact that he easily succeeded in selecting and enriching them by ATP columns is proof of the function. He could very well stop there. Or he could simply go on describing these sequences with weak ATP binding as they were, and trying to show why and how they bound to ATP. The result? We would know that in a random library sequences which bind weakly to ATP are present with a frequency such and such. No problems. Instead, he has done a different thing. He has engineered a protein with strong ATP binding form the initial sequences. And then the paper analyzes the properties of this engineered protein. OK, that's fine. What does this prove? Simply, that we can intelligently engineer a protein with strong ATP binding from a sequence with weak ATP binding. No problems with that. So, the conclusions should have been: We have shown that sequences with weak ATP binding are present in a random library with such and such frequency. We have not really said anything else about those sequences. Then, for some strange personal reasons, we have shown that protein engineering works. This is not exactly the tone of the conclusions. That's why I stick to my idea: bad paper, bad methodology, ideological ambiguity. And completely irrelevant to the ID neo darwinism debate. And here is a new pearl from DNA_Jock:
Well, according to your definition of natural (as opposed to ‘intelligent’) selection, such evidence is impossible to come by, by definition. Do you have any evidence that they can’t be naturally selected in a biological system?
This is, apparently, an explicit lie (OK, I have said it). It is not true, at all, that "according to my definition" such evidence is impossible to come by. In my post #27, in this same thread, I write to Hangonasec: "Knockout rescue experiments are certainly more appropriate as models of NS. That is exactly the difference with the Szostak paper." And I have pointed out to you, for example, the rugged landscape paper as a good example of an experiment testing natural selection. Again, you are (intentionally?) equivocating my words. It is perfectly possible to show that a protein is naturally selectable. But you have to do it. Szostak has not done it. Therefore we have no evidence that any of the original proteins in the random library is naturally selectable. Now, you must stop with this ridiculous habit of saying that I must show that they were not naturally selectable. In science, something has a property only if you show that it has that property. It is not the duty of the general public to demonstrate that an object has not a property. It is the duty of those who think that the object has a property to demonstrate that it has it, or that there are reasons to believe that. So, my point is simple. For the neo darwinist scenario, the only relevant function is to be naturally selectable. The Szostak paper demonstrates that some sequences in a random library have weak binding to ATP. It also demonstrates that we can engineer a strong binding to ATP from them by the usual procedures of protein engineering. In no way it demonstrates that the same result can be obtained in a lab scenario which tests for natural selection. It could have been done, but it has not been attempted. That's why the paper is irrelevant to the ID neo darwinism debate, unless we consider it as evidence that design can achieve results. This is my position. You will certainly go on with your tricks but, unless you offer true arguments about these points, I have nothing else to say.gpuccio
February 24, 2015
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Zachriel at #60: I had not seen you #45. It is not a real acknowledgement, but I appreciate it just the same. A simple: OK, I was wrong when I said: "The original random protein exhibited enzymatic activity." would have been more elegant, IMO.gpuccio
February 24, 2015
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Box: Moreover Keefe and Szostak, 2001 is even mentioned in the OP Yes, it's the same claim in both cases. What is your point?Zachriel
February 24, 2015
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follow up on #63: Moreover Keefe and Szostak, 2001 is even mentioned in the OP ... because it is the same article to which I refer in #63 ... as indicated by Jonathan M.Box
February 24, 2015
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Zachriel Jonathan M: Keefe and Szostak, 2001
Jonathan M mentioned the paper in an 2013 article. excerpt:
The Problems with Domain Shuffling as an Explanation for Protein Folds While the hypothesis of exon shuffling does, taken at face value, have some attractive elements, it suffers from a number of problems. For one thing, the model at its core presupposes the prior existence of protein domains. A protein's lower-level secondary structures (alpha-helices and beta-strands) exist stably only in the context of the tertiary structures in which they are found. In other words, the domain level is the lowest level at which self-contained stable structural modules exist. This leaves the origins of these domains in the first place unaccounted for. But stable and functional protein domains are demonstrably rare within amino-acid sequence space (e.g. Axe, 2010; Axe, 2004; Taylor et al., 2001; Keefe and Szostak, 2001; Reidhaar-Olson and Sauer, 1990; Salisbury, 1969).
Box
February 24, 2015
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DNA_Jock: No Zachriel, you don’t understand: the initial peptides showed weak ATP binding, which is not a “function”, whereas the final peptides showed strong ATP binding, which IS a “function”, according to gpuccio Got it! http://www.youtube.com/watch?v=iQrLPtr_ikEZachriel
February 24, 2015
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No Zachriel, you don't understand: the initial peptides showed weak ATP binding, which is not a "function", whereas the final peptides showed strong ATP binding, which IS a "function", according to gpuccio, as in "I indicated that the final functional protein which is described and analyzed in the paper was engineered. " And we all know that turning something non-functional into something functional requires engineering. See? gp writes:
Have you any evidence that the proteins in the original random library had any catalytic activity?
Yes, some of them catalyzed the reaction glucose -> 3-deoxyhexosulose.
This is the point I made. Please, answer.
That was NOT the point you made. You did not use the word “catalytic”. Please stop making stuff up.
And have you any evidence that the proteins in the original random library can be naturally selected in a biological system?
Well, according to your definition of natural (as opposed to ‘intelligent’) selection, such evidence is impossible to come by, by definition. Do you have any evidence that they can’t be naturally selected in a biological system? Are you ready to explain why binding is necessary for catalysis yet?DNA_Jock
February 24, 2015
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gpuccio: ... acknowledge ... See #45. gpuccio: What do you mean? They were selected because they bound to ATP Yes. That alone shows that they were functional from the get-go, which was the claim. However, we also know that they increased their specificity through rounds of selection showing a gradient of function. This is not what is expected of a simple chemical affinity. We even have a phylogeny of those that were most successful, and they trace back to four progenitor molecules.Zachriel
February 24, 2015
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Zachriel: "If it were merely a simple chemical affinity, as you suggested above, there would be no selection gradient." What do you mean? They were selected because they bound to ATP: "For rounds 1±9, we used a butyl-agarose pre-column (Sigma) and incubated the ¯owthrough with the ATP-af®nity column. Rounds 14±16 included two ATP-agarose selection steps, and rounds 17 and 18 included three ATPagarose selection steps. For reiterated selection steps the eluted material was puri®ed away from ATP on a denaturing Ni-NTA column and reverse transcribed again before the subsequent selection step." "A chemical affinity" is your words, not mine. I said: "They certainly exhibited some binding to ATP", and it simply means that the two molecules, the protein and ATP, bind together, and you can isolate the protein by ATP columns and elution. Which is how they selected them. I really don't understand what you are trying to say (if you are really trying to say something). And I acknowledge, with some sadness, that you were not decent enough.gpuccio
February 24, 2015
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This is precisely how mathematicians use the term. Dice throwing is a random process.
But even the dice doesn't spin randomly, there are forces that determine the result! If we knew every one of them we could predict the result 100%, it has happened with a coin.JimFit
February 24, 2015
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DNA_Jock: Just answer this simple question: Have you any evidence that the proteins in the original random library had any catalytic activity? This is the point I made. Please, answer. And have you any evidence that the proteins in the original random library can be naturally selected in a biological system? This is the other point I made. Please, answer.gpuccio
February 24, 2015
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gpuccio: I indicated that the final functional protein which is described and analyzed in the paper was engineered. It was the result of rounds of amplification and selection for functional activity, yes. gpuccio: The original proteins in the library were not the final engineered protein. They certainly exhibited some binding to ATP, but we know nothing more about their “function”. The function was selectable. If it were merely a simple chemical affinity, as you suggested above, there would be no selection gradient.Zachriel
February 24, 2015
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So, in this context, “binding” is the same thing as having “enzymatic activity”.
In what context? Where is your logic?
In the context of the ability of evolving peptides to achieve particular functions, then avid binding is utterly equivalent to efficient catalysis and specific binding is utterly equivalent to specific catalysis. Which you would realize if you bothered to fill in the blank in my little riddle above, instead of merely asserting "This is wrong." You are aware that binding is necessary for catalysis. Good. Could you explain why binding is necessary for catalysis? [In your defense, I remember a lecturer who introduced the Haldane relationship as if it were a semi-magical property of enzymes; it isn't - rather it is a necessary consequence of the chemical equivalence of binding and catalysis...] This is basic biochemistry.DNA_Jock
February 24, 2015
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Zachriel: I indicated that the final functional protein which is described and analyzed in the paper was engineered. The original proteins in the library were not the final engineered protein. They certainly exhibited some binding to ATP, but we know nothing more about their "function". Certainly, there is absolutely nothing in the paper that shows that they are naturally selectable molecules. Or that they have any enzymatic function. Which was my initial statement, and has not changed at all. Because it is perfectly true. Now, you could at least be decent enough to admit that you were wrong about the enzymatic activity of those molecules. If you want.gpuccio
February 24, 2015
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The paper shows that the functional proteins existed in the original set of random sequences.
And that is of no help to unguided evolution.Joe
February 24, 2015
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Box: Zachriel the incorrigible Gpuccio indicated that the functional proteins were engineered, when, in fact, functional proteins were in the original population of random sequences.Zachriel
February 24, 2015
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