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Biologist Douglas Axe on evolution’s ability to produce new functions

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17 Responses to Biologist Douglas Axe on evolution’s ability to produce new functions

  1. Interesting (reminds us that as proteins are the workhorses of the cell, that is where the thing has to create novel functions first), links and papers?

  2. related footnotes on Dr. Axe’s work:

    Nothing In Molecular Biology Is Gradual – Doug Axe PhD. – video
    Quote – “Charles Darwin said (paraphrase), ‘If anyone could find anything that could not be had through a number of slight, successive, modifications, my theory would absolutely break down.’ Well that condition has been met time and time again. Basically every gene, every protein fold. There is nothing of significance that we can show that can be had in a gradualist way. It’s a mirage. None of it happens that way. – Doug Axe PhD.
    http://www.metacafe.com/watch/5347797/

    Estimating the prevalence of protein sequences adopting functional enzyme folds: Doug Axe:
    Excerpt: The prevalence of low-level function in four such experiments indicates that roughly one in 10^64 signature-consistent sequences forms a working domain. Combined with the estimated prevalence of plausible hydropathic patterns (for any fold) and of relevant folds for particular functions, this implies the overall prevalence of sequences performing a specific function by any domain-sized fold may be as low as 1 in 10^77, adding to the body of evidence that functional folds require highly extraordinary sequences.
    http://www.ncbi.nlm.nih.gov/pubmed/15321723

    Doug Axe Knows His Work Better Than Steve Matheson
    Excerpt: Regardless of how the trials are performed, the answer ends up being at least half of the total number of password possibilities, which is the staggering figure of 10^77 (written out as 100, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000, 000). Armed with this calculation, you should be very confident in your skepticism, because a 1 in 10^77 chance of success is, for all practical purposes, no chance of success. My experimentally based estimate of the rarity of functional proteins produced that same figure, making these likewise apparently beyond the reach of chance.
    http://www.evolutionnews.org/2.....35561.html

    The Case Against a Darwinian Origin of Protein Folds – Douglas Axe – 2010
    Excerpt Pg. 11: “Based on analysis of the genomes of 447 bacterial species, the projected number of different domain structures per species averages 991. Comparing this to the number of pathways by which metabolic processes are carried out, which is around 263 for E. coli, provides a rough figure of three or four new domain folds being needed, on average, for every new metabolic pathway. In order to accomplish this successfully, an evolutionary search would need to be capable of locating sequences that amount to anything from one in 10^159 to one in 10^308 possibilities, something the neo-Darwinian model falls short of by a very wide margin.”
    http://bio-complexity.org/ojs/.....O-C.2010.1

    Not only are functional proteins found to be extremely rare, thus undermining Darwinian presuppositions, but, as Dr. Axe pointed out in the OP video, the transition of any existent functional protein to a protein of a different function, by unguided Darwinian processes, is found to be of extreme, prohibitive, difficulty as well.

    The Evolutionary Accessibility of New Enzyme Functions: A Case Study from the Biotin Pathway – Ann K. Gauger and Douglas D. Axe – April 2011
    Excerpt: We infer from the mutants examined that successful functional conversion would in this case require seven or more nucleotide substitutions. But evolutionary innovations requiring that many changes would be extraordinarily rare, becoming probable only on timescales much longer than the age of life on earth.
    http://bio-complexity.org/ojs/.....O-C.2011.1

    When Theory and Experiment Collide — April 16th, 2011 by Douglas Axe
    Excerpt: Based on our experimental observations and on calculations we made using a published population model [3], we estimated that Darwin’s mechanism would need a truly staggering amount of time—a trillion trillion years or more—to accomplish the seemingly subtle change in enzyme function that we studied.
    http://www.biologicinstitute.o.....nt-collide

    “Biologist Douglas Axe on Evolution’s (non) Ability to Produce New (Protein) Functions ” – video
    Quote: It turns out once you get above the number six [changes in amino acids] — and even at lower numbers actually — but once you get above the number six you can pretty decisively rule out an evolutionary transition because it would take far more time than there is on planet Earth and larger populations than there are on planet Earth.
    http://intelligentdesign.podom.....5_14-07_00

    The Real Barrier to Unguided Human Evolution – Ann Gauger – April 25, 2012
    Excerpt: Their results? They calculated it would take six million years for a single base change to match the target and spread throughout the population, and 216 million years to get both base changes necessary to complete the eight base binding site. Note that the entire time span for our evolution from the last common ancestor with chimps is estimated to be about six million years. Time enough for one mutation to occur and be fixed, by their account.
    To be sure, they did say that since there are some 20,000 genes that could be evolving simultaneously, the problem is not impossible. But they overlooked this point. Mutations occur at random and most of the time independently, but their effects are not independent. (Random) Mutations that benefit one trait (are shown to) inhibit another (Negative Epistasis; Lenski e-coli after 50,000 generations).
    http://www.evolutionnews.org/2.....58951.html

    More from Ann Gauger on why humans didn’t happen the way Darwin said – July 2012
    Excerpt: Each of these new features probably required multiple mutations. Getting a feature that requires six neutral mutations is the limit of what bacteria can produce. For primates (e.g., monkeys, apes and humans) the limit is much more severe. Because of much smaller effective population sizes (an estimated ten thousand for humans instead of a billion for bacteria) and longer generation times (fifteen to twenty years per generation for humans vs. a thousand generations per year for bacteria), it would take a very long time for even a single beneficial mutation to appear and become fixed in a human population.
    You don’t have to take my word for it. In 2007, Durrett and Schmidt estimated in the journal Genetics that for a single mutation to occur in a nucleotide-binding site and be fixed in a primate lineage would require a waiting time of six million years. The same authors later estimated it would take 216 million years for the binding site to acquire two mutations, if the first mutation was neutral in its effect.
    Facing Facts
    But six million years is the entire time allotted for the transition from our last common ancestor with chimps to us according to the standard evolutionary timescale. Two hundred and sixteen million years takes us back to the Triassic, when the very first mammals appeared. One or two mutations simply aren’t sufficient to produce the necessary changes— sixteen anatomical features—in the time available. At most, a new binding site might affect the regulation of one or two genes.
    http://www.uncommondescent.com.....rwin-said/

  3. There is also very good, indeed overwhelming, evidence as to why we should expect such severe constraint on the ability of proteins to mutate, step by step, amino acid by amino acid, from one function to another different function. Proteins are shown to be ‘context dependent’, meaning that the entirety of the amino acid sequence of a protein domain is involved in a specific function and is not built up gradually. The following notes flesh this ‘context dependent’ characteristic of proteins out:

    Why Proteins Aren’t Easily Recombined, Part 2 – Ann Gauger May 17, 2012
    Excerpt: In other words, even if only 10% of non-matching residues were changed, the resulting hybrid enzyme no longer functioned. Why? Because the substitution of different amino acids into the existing protein structure destabilized the fold, even though those same amino acids worked well in another context. Thus, each protein’s amino acid sequence works as a whole to help generate a proper stable fold, in a context-dependent fashion.
    http://www.evolutionnews.org/2.....59771.html

    As well, functional proteins have now been shown to have a ‘Cruise Control’ mechanism, along the entirety of a protein structure, which works to ‘self-correct’ the integrity of a entire protein structure from any random mutations imposed on it.

    Proteins with cruise control provide new perspective:
    “A mathematical analysis of the experiments showed that the proteins themselves acted to correct any imbalance imposed on them through artificial mutations and restored the chain to working order.”
    http://www.princeton.edu/main/...../60/95O56/

    Cruise Control permeating the whole of the protein structure??? This is an absolutely fascinating discovery. The equations of calculus involved in achieving even a simple process control loop, such as a dynamic cruise control loop, are very complex. In fact it seems readily apparent to me that highly advanced mathematical information must somehow ‘transcendentally permeate’ along the entirety of a protein structure, in order to achieve such control of the overall protein structure. This fact gives us clear evidence that there is far more functional information permeating proteins than meets the eye than simple rarity of amino acid sequences reveals (Szostak). Moreover this ‘oneness’ of cruise control, within the protein structure, can only ‘rationally’ be achieved through quantum computation/entanglement principles, and is inexplicable to the reductive materialistic approach of neo-Darwinism! For a sample of the equations that must be dealt with, to ‘engineer’ even a simple process control loop like cruise control for a single protein, please see this following site:

    PID controller
    A proportional–integral–derivative controller (PID controller) is a generic control loop feedback mechanism (controller) widely used in industrial control systems. A PID controller attempts to correct the error between a measured process variable and a desired setpoint by calculating and then outputting a corrective action that can adjust the process accordingly and rapidly, to keep the error minimal.
    http://en.wikipedia.org/wiki/PID_controller

    It is in realizing the staggering level of engineering that must be dealt with, i.e. ‘intelligently designed’ beforehand, in order to achieve ‘cruise control’ for each individual protein, along the entirety of the protein structure, that it becomes apparent that Axe’s 1 in 10^77 estimate for rarity of finding specific functional proteins within ‘sequence space’ is, in all likelihood, far, far too generous. In fact the probabilities over various ‘specific’ configurations of amino acids within sequence space, which have been one of the primary arguments against neo-Darwinism thus far, simply do not even apply, at all, since the ’cause’ for the ‘non-local quantum information effect’ within proteins does not even reside within the material particles in the first place (i.e. falsification of local realism; (Einstein, Bohr, Bell, Wheeler, Aspect, Zeilinger).

    The following footnotes are further corroborating evidence that ‘protein specific’ quantum information/entanglement resides along/within the entirety of a functional protein amino acid chain constraining the chain to a specific function:

    Coherent Intrachain energy migration at room temperature – Elisabetta Collini & Gregory Scholes – University of Toronto – Science, 323, (2009), pp. 369-73
    Excerpt: The authors conducted an experiment to observe quantum coherence dynamics in relation to energy transfer. The experiment, conducted at room temperature, examined chain conformations, such as those found in the proteins of living cells. Neighbouring molecules along the backbone of a protein chain were seen to have coherent energy transfer. Where this happens quantum decoherence (the underlying tendency to loss of coherence due to interaction with the environment) is able to be resisted, and the evolution of the system remains entangled as a single quantum state.
    http://www.scimednet.org/quant.....d-protein/

    Myosin Coherence
    Excerpt: Absorbance (and emission) of frequency specific radiation (e.g. photosynthesis, vision, [biophotons]..), conversion of chemical energy into mechanical motion (e.g. ATP cleavage) and single electron transfers through biological polymers (e.g. DNA or proteins) are all quantum mechanical effects.
    http://www.energetic-medicine......Page1.html

    The mechanism and properties of bio-photon emission and absorption in protein molecules in living systems – May 2012
    Excerpt: From the energy spectra, it was determined that the protein molecules could both radiate and absorb bio-photons with wavelengths of <3??m and 5–7??m, consistent with the energy level transitions of the excitons.,,,
    http://jap.aip.org/resource/1/.....horized=no

    Physicists Discover Quantum Law of Protein Folding – February 22, 2011
    Quantum mechanics finally explains why protein folding depends on temperature in such a strange way.
    Excerpt: First, a little background on protein folding. Proteins are long chains of amino acids that become biologically active only when they fold into specific, highly complex shapes. The puzzle is how proteins do this so quickly when they have so many possible configurations to choose from.
    To put this in perspective, a relatively small protein of only 100 amino acids can take some 10^100 different configurations. If it tried these shapes at the rate of 100 billion a second, it would take longer than the age of the universe to find the correct one. Just how these molecules do the job in nanoseconds, nobody knows.,,,
    Their astonishing result is that this quantum transition model fits the folding curves of 15 different proteins and even explains the difference in folding and unfolding rates of the same proteins.
    That's a significant breakthrough. Luo and Lo's equations amount to the first universal laws of protein folding. That’s the equivalent in biology to something like the thermodynamic laws in physics.
    http://www.technologyreview.co.....f-protein/

    As to the ‘minor’ problem of protein folding itself:

    “Blue Gene’s final product, due in four or five years, will be able to “fold” a protein made of 300 amino acids, but that job will take an entire year of full-time computing.”
    Paul Horn, senior vice president of IBM research, September 21, 2000
    http://www.news.com/2100-1001-233954.html

    Networking a few hundred thousand computers together has reduced the time to a few weeks for simulating the folding of a single protein molecule:

    A Few Hundred Thousand Computers vs. A Single Protein Molecule – video
    http://www.metacafe.com/watch/4018233

  4. Not only are amino acid sequences of proteins shown to be ‘context dependent’ on the specific function of the protein, but, it turns out, that the function of the protein itself, in many cases, is context dependent on the specific function of the cell that a protein may be residing in:

    The Complexity of Gene Expression, Protein Interaction, and Cell Differentiation – Jill Adams, Ph.D. – 2008
    Excerpt: it seems that a single protein can have dozens, if not hundreds, of different interactions,,, In a commentary that accompanied Stumpf’s article, Luis Nunes Amaral (2008) wrote, “These numbers provide a sobering view of where we stand in our cataloging of the human interactome. At present, we have identified less than 0.3% of all estimated interactions among human proteins. We are indeed at the dawn of systems biology.”
    http://www.nature.com/scitable.....tion-34575

    Human Genes: Alternative Splicing (For Proteins) Far More Common Than Thought: – 2008
    Excerpt: two different forms of the same protein, known as isoforms, can have different, even completely opposite functions. For example, one protein may activate cell death pathways while its close relative promotes cell survival.
    http://www.sciencedaily.com/re.....134623.htm

    Simplest Microbes More Complex than Thought – Dec. 2009
    Excerpt: PhysOrg reported that a species of Mycoplasma,, “The bacteria appeared to be assembled in a far more complex way than had been thought.” Many molecules were found to have multiple functions: for instance, some enzymes could catalyze unrelated reactions, and some proteins were involved in multiple protein complexes.”
    http://www.creationsafaris.com.....#20091229a

    Insight into cells could lead to new approach to medicines – 2010
    Excerpt: Scientists expected to find simple links between individual proteins but were surprised to find that proteins were inter-connected in a complex web. Dr Victor Neduva, of the University of Edinburgh, who took part in the study, said: “Our studies have revealed an intricate network of proteins within cells that is much more complex than we previously thought.
    http://www.physorg.com/news196402353.html

    Supplemental notes:

    Wheel of Fortune: New Work by Thornton’s Group Supports Time-Asymmetric Dollo’s Law – Michael Behe – October 5, 2011
    Excerpt: Darwinian selection will fit a protein to its current task as tightly as it can. In the process, it makes it extremely difficult to adapt to a new task or revert to an old task by random mutation plus selection.
    http://www.evolutionnews.org/2.....51621.html

    Stability effects of mutations and protein evolvability. October 2009
    Excerpt: The accepted paradigm that proteins can tolerate nearly any amino acid substitution has been replaced by the view that the deleterious effects of mutations, and especially their tendency to undermine the thermodynamic and kinetic stability of protein, is a major constraint on protein evolvability,,
    http://www.ncbi.nlm.nih.gov/pubmed/19765975

    Corticosteroid Receptors in Vertebrates: Luck or Design? – Ann Gauger – October 11, 2011
    Excerpt: if merely changing binding preferences is hard, even when you start with the right ancestral form, then converting an enzyme to a new function is completely beyond the reach of unguided evolution, no matter where you start.
    http://www.evolutionnews.org/2.....51801.html

    “Mutations are rare phenomena, and a simultaneous change of even two amino acid residues in one protein is totally unlikely. One could think, for instance, that by constantly changing amino acids one by one, it will eventually be possible to change the entire sequence substantially… These minor changes, however, are bound to eventually result in a situation in which the enzyme has ceased to perform its previous function but has not yet begun its ‘new duties’. It is at this point it will be destroyed” Maxim D. Frank-Kamenetski, Unraveling DNA, 1997, p. 72. (Professor at Brown U. Center for Advanced Biotechnology and Biomedical Engineering)

    “A problem with the evolution of proteins having new shapes is that proteins are highly constrained, and producing a functional protein from a functional protein having a significantly different shape would typically require many mutations of the gene producing the protein. All the proteins produced during this transition would not be functional, that is, they would not be beneficial to the organism, or possibly they would still have their original function but not confer any advantage to the organism. It turns out that this scenario has severe mathematical problems that call the theory of evolution into question. Unless these problems can be overcome, the theory of evolution is in trouble.”
    Problems in Protein Evolution:

    Here are further notes that support the position that existing functional proteins are severely constrained in their ability to mutate step by step into new functions:

    Deciphering Design in the Genetic Code – Fazale Rana
    Excerpt: Sixty-four codons make up the genetic code. Because the genetic code only needs to encode 20 amino acids, some of the codons are redundant. That is, different codons code for the same amino acid. In fact, up to six different codons specify some amino acids. Others are specified by only one codon.,,,
    Genetic code rules incorporate a design that allows the cell to avoid the harmful effects of substitution mutations. For example, six codons encode the amino acid leucine (Leu). If at a particular amino acid position in a polypeptide, Leu is encoded by 5′ (pronounced five prime, a marker indicating the beginning of the codon). CUU, substitution mutations in the 3′ position from U to C, A, or G produce three new codons, 5′ CUC, 5′ CUA, and 5′ CUG, all of which code for Leu. The net effect produces no change in the amino acid sequence of the polypeptide. For this scenario, the cell successfully avoids the negative effects of a substitution mutation.
    Likewise, a change of C in the 5′ position to a U generates a new codon, 5′UUU, that specifies phenylalanine, an amino acid with similar physical and chemical properties to Leu. A change of C to an A or to a G produces codons that code for isoleucine and valine, respectively. These two amino acids also possess chemical and physical properties similar to leucine. Qualitatively, the genetic code appears constructed to minimize errors that result from substitution mutations.,,,
    The genetic code’s error-minimization properties are actually more dramatic than these results indicate. When researchers calculated the error-minimization capacity of one million randomly generated genetic codes, they discovered that the error-minimization values formed a distribution where the naturally occurring genetic code’s capacity occurred outside the distribution.18 Researchers estimate the existence of 10^18 possible genetic codes possessing the same type and degree of redundancy as the universal genetic code. All of these codes fall within the error-minimization distribution. This finding means that of 10^18 possible genetic codes, few, if any, have an error-minimization capacity that approaches the code found universally in nature.
    http://www.reasons.org/biology.....netic-code

    As well, the ‘errors/mutations’ that are found to occur in protein sequences are found to be ‘regulated errors’:

    Cells Defend Themselves from Viruses, Bacteria With Armor of Protein Errors – Nov. 2009
    Excerpt: These “regulated errors” comprise a novel non-genetic mechanism by which cells can rapidly make important proteins more resistant to attack when stressed,
    http://www.sciencedaily.com/re.....134701.htm

    In fact there is little hope of a truly random (i.e. Darwinian) mutation making it through the gauntlet of the ribosome:

    The Ribosome: Perfectionist Protein-maker Trashes Errors
    Excerpt: The enzyme machine that translates a cell’s DNA code into the proteins of life is nothing if not an editorial perfectionist…the ribosome exerts far tighter quality control than anyone ever suspected over its precious protein products… To their further surprise, the ribosome lets go of error-laden proteins 10,000 times faster than it would normally release error-free proteins, a rate of destruction that Green says is “shocking” and reveals just how much of a stickler the ribosome is about high-fidelity protein synthesis.

  5. Creationist and evolutionary biologist Todd Wood recently blogged about a recent study in Nature suggesting that protein evolution is much easier than typically claimed around here:

    Their second experiment of examining binding to a nonnative binding partner speaks to the ongoing research project of some ID scholars who want to show that a protein really can’t evolve even a new function. In the past, this type of research has been accomplished by substitutions targeted to residues that are known to be important to protein function. The results of these studies have shown that multiple substitutions are necessary to convert one protein function to another, which is consistent with McLaughlin et al.’s discovery that two substitutions are necessary to fully change the specificity of PSD95pdz3 to a different binding partner. Whereas ID scholars have concluded based on their research that such conversions are improbable (impossible?) because they involve coordinated mutations, McLaughlin et al. found a plausible intermediate, Gly330Thr, which binds to both binding partners. Since there’s a functional intermediate, it’s at least plausible that this protein could evolve a new function.

    Now we could argue about how general McLaughlin’s findings are, and maybe even whether a nonspecific PSD95pdz3 would be beneficial or detrimental. I expect that’s exactly how the ID response will go (I have not at this point read any ID blog posts about this paper), and I wouldn’t be surprised if some blogger finds a way to spin this paper to support ID claims.

    Anyone want to tackle how we can “spin this to support ID claims” ?

  6. Great! Axe is really doing a wonderful work, on the most important problem.

    So, just for clarity, I would like to remind a few numbers:

    a) Behe suggest, in TEOE, an empirically observed limit of about 2-3 mutations (let’s say 13 bits maximum) for “evolution in action”.

    b) I have proposed, many times, to use, for any biological context, an upper threshold of about 35 mutations (150 bits) as a really gross higher threshold in assessing dFSCI for a protein, computed, as usual, giving all possible exaggerated concessions to the neo darwinian model. My purpose was to lower DEmbski’s UPB (500 bits), and to have a more realistic threshold for biological events. That would be the upper limit of any biological RV transition.

    c) Axe, using a model that is certainly much more accurate than my gross approximations, and supported by his personal experimental research, is offering here a veri credible empirical limit for the same thing: 6 mutations (about 26 bits).

    I do believe that he is very near to truth.

    My value of 150 bits is certainly too high, but my only purpose in proposing it was only to have a really unquestionable higher limit to say that a protein exhibits dFSCI.

    Behe’s limit is empirical, and probably very realistic, but it is true that, if we want to consider transitions that could have occurred in very big Time Spans, his empirical models are too limited. Nehe’s limit remains absolutely valid for shorter Time Spans, and/or less numerous populations, and/or lower reproduction rate (such as multicellular organisms, and specifically mammals).

    Axe’s value is extremely credible: it is in accord with mathemathical models and with empirical observations. It is, as far as I can say, the best assessment of what pure RV can, or cannot, do in a maximal biologic context (maximum Time Span, bacterial populations).

    It is interesting to observe that a 6 AAs limit for random transitions would still allow for all microevolutionary events known (which are usually of 1-2 mutations most), and for much more (all the possible evolutionary events of 3-6 AAs complexity). But, at the same time, it would probably cut out of darwinian range many possible “intermediate complexity” events, such as many transitions in the context of existing structures and protein domains, as documented in Axe’s paper:

    http://bio-complexity.org/ojs/.....O-C.2010.4

    The origin of basic protein domains, obviously, cannot even begin to be considered, with these numbers.

  7. The origin of basic protein domains, obviously, cannot even begin to be considered, with these numbers.

    But we can put them into an objective nested hierarchy, and that proves common descent by unguided mutation and natural selection is a better explanations, a trillions and trillions of times better explanation than ID, because an intelligent designer could have done it trillions of trillions of ways different.

  8. Does anyone know if they have published the mathematical model they used?

  9. JoeCoder:

    Even if we take the study at face value, no-one disputes the idea that if there are functional intermediates that are easily obtainable through very minor changes, then the fitness landscape might be traversible from a to b to c. The question is, how often is this really the case?

    After decades of searching for these intermediates (whether at the macro organismal level, or at the micro protein level), it is pretty well understood that, as a general rule, functional oases are sparse indeed. So the fact that researchers have identified, after years of effort and lots of research, an occasional potential intermediate in one or two cases is not really much help for the evolutionary story. In fact, a good argument can be made that these occasional results are the exceptions that prove the rule.

  10. Hi GPuccio and All,

    It is nice to be back. Can I ask you some questions, if you don’t mind?

    1. Did you write up as a single note here at UD any of your interesting detailed comments that you posted some months back when you discussed these issues from the probabilistic perspective with Elizabeth Liddle, if I remember rightly? If you did, where can I find it, please?

    2. I posted some notes on my blog and elsewhere and got myself some pretty tough arguments thrown in my face :) Because I am not a biologist, I would be extremely interested to know your opinion:

    2.1. Are you aware of Shaposhnikov’s experiments on aphids? It is claimed in the Russian biological literature that Georgiy Shaposhnikov actually succeeded in getting reproductive isolation of populations of aphids in as short a period as just three months (half a dozen generations, if I am not mistaken). Is it true, is it credible? Trouble is he always had to waste his time trying to defend himself from his hardline Darwinist colleagues who accused him of being a Lamarkist. Anyhow, this work that he did in the 1950-s-60-s has actually been published. Evolutionists in Russia rumour that not long before he died he continued his experiments and allegedly crossed the border of the aphid genus. This however was not published, so one can only guess. Whatever mechanisms were involved, epigenetic or not, he spotted reproductive isolation (he did not get as far as proving the existence of numerous progeny, because it required him waiting for some more generations of aphids, which he did not or could not do). I don’t know whether anyone else could replicate his experiments, and I don’t expect many people in the West to be aware of his work. Anyway, the point is, mutation rates can be extremely high. It is argued that such an extremely high rate of speciation is due to the fact that the selective pressure was a result of just one factor, type of host plant, literally nothing else.

    2.2. As another example, I saw in wikipedia (well, yes, this notorious wikipedia) a page with alleged experimental proofs of evolution (many of those are strawman). But there among other things they claim that some reptiles actually developed in a timespan of just under 40 years some new functionality, novel organs of the digestive system. Your opinion on this? Could that have been a result of some latent genes which were not expressed until such times as something triggered it? I know very little in this, I just doubt it could be possible for true novelty to emerge without intelligent guidance (as usual with ID).

    3. What I can’t quite understand in the business of protein evolution is that I don’t see how the hardness of new functional domain emergence/generation can disprove evolution at higher levels, i.e. at the level of tissue or whole organs. As far as I know, humans and bacteria use mostly the same proteins (correct me if I am wrong). If that is the case, evolutionists can say, okay, we don’t know the mechanism of new domains emerging but higher up in the organisation everything is explainable from the evolutionist standpoint.

    Many Thanks.

  11. Correction to 2.1. I rather mean speciation rates, not mutation rates (if these experimental results are true).

  12. Dr S, good to see you. The lizards developed a valve, which other closely related lizards have, strongly suggesting activation of a pre programmed adaptation not incremental from scratch evo. I think the jury is still out on just what happened, per what was briefly reported, I would love more detailed comment. Cf blind fish. KF

  13. OT: Here is another classic example of the ‘fit, damn you, fit!’ method of science that Darwinists practice:

    Study shows butterfly wings contain same toxin as sea snail – October 16, 2012
    Excerpt: The great orange tip butterfly belongs to the Pieridae family of White and Yellow butterflies and inhabits temperate Asian climates such as those found in the island nations of the Philippines, Indonesia and Malaysia. They are all white save for the upper half of their upper wings which are bright orange. They are the largest of the lepidopteran family. In studying H. glaucippe the research team homogenized the wings and bodies of sample specimens allowing them to extract proteins found in them. In so doing, they discovered the presence of one, glacontryphan-M, a peptide toxin that had previously only been found in a species of sea snail: Conus marmoreus, more commonly known as the marble cone snail. C. marmoreus injects toxic chemicals into its prey via a harpoon, paralyzing it, which allows for easy consumption. One of the toxic chemicals it uses is the same peptide the research team has found in the wingtips of H. glaucippe, leading to questions regarding the lineage of both species and if they perhaps evolved from a shared distant relative.
    http://phys.org/news/2012-10-b.....snail.html

    Related notes:

    Bernard d’Abrera on Butterfly Mimicry and the Faith of the Evolutionist – October 5, 2011
    Excerpt: For it to happen in a single species once through chance, is mathematically highly improbable. But when it occurs so often, in so many species, and we are expected to apply mathematical probability yet again, then either mathematics is a useless tool, or we are being criminally blind.,,, Evolutionism (with its two eldest daughters, phylogenetics and cladistics) is the only systematic synthesis in the history of the universe that proposes an Effect without a Final Cause. It is a great fraud, and cannot be taken seriously because it outrageously attempts to defend the philosophically indefensible.
    http://www.evolutionnews.org/2.....51571.html

    Nobel Prize-Winning Physicist Wolfgang Pauli on the Empirical Problems with Neo-Darwinism – Casey Luskin – February 27, 2012
    Excerpt: “In discussions with biologists I met large difficulties when they apply the concept of ‘natural selection’ in a rather wide field, without being able to estimate the probability of the occurrence in a empirically given time of just those events, which have been important for the biological evolution. Treating the empirical time scale of the evolution theoretically as infinity they have then an easy game, apparently to avoid the concept of purposesiveness. While they pretend to stay in this way completely ‘scientific’ and ‘rational,’ they become actually very irrational, particularly because they use the word ‘chance’, not any longer combined with estimations of a mathematically defined probability, in its application to very rare single events more or less synonymous with the old word ‘miracle.’” Wolfgang Pauli (pp. 27-28) -
    http://www.evolutionnews.org/2.....56771.html

    Murray Eden, as reported in “Heresy in the Halls of Biology: Mathematicians Question Darwinism,” Scientific Research, November 1967, p. 64.
    “It is our contention that if ‘random’ is given a serious and crucial interpretation from a probabilistic point of view, the randomness postulate is highly implausible and that an adequate scientific theory of evolution must await the discovery and elucidation of new natural laws—physical, physico-chemical, and biological.” Murray Eden, “Inadequacies of Neo-Darwinian Evolution as a Scientific Theory,” Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution, editors Paul S. Moorhead and Martin M. Kaplan, June 1967, p. 109.

  14. See publications at the Biologic Institute for Douglas D. Axe and Ann K. Gauger.

    See also Peer-Reviewed & Peer-Edited Scientific Publications Supporting the Theory of Intelligent Design February 1, 2012

    See also Douglas D. Axe, and Ann K. Gauger, at Google Scholar

  15. I’m glad that this kind of research is being done. If we can gather more evidence in this area (especially along the lines of the kind of research Ralph Seelke has done and Behe’s first adaptive rule) and publicize it, then almost half our work in the biological arena is done.

    I’ll have to take another look at Edge of Evolution along with the criticisms of it. While the book may not have been 100% spot on in some respects, I think the basic points he raised in many of his examples still stand.

    And it certainly is easier to see how isolated fitness peaks are from each other to get an idea of where evolutionary limits are rather than taking a given feature and estimating it’s probability of being produced by evolutionary means based on traits of that feature alone.
    The former is more convincing to someone who buys into the idea that there is “no goal” of producing any given feature – and thus chooses to use that to escape falsification.

  16. Eugene S:

    Nice to hear from you again!

    1. No, I did not post the whole reasoning as a single note. But I have recently discussed it and summed it up with Zachriel here:

    http://www.uncommondescent.com.....ent-436926

    at post #498.

    The original diascussion is here:

    http://www.uncommondescent.com.....selection/

    The long discussion with Lizzie starts more or less at post #62, but you could look mainly at the last posts, especially #216.

    I am very interested in going on with this kind of analysis, if anyone is interested in offering input.

    2.1:

    Any change that happens in such a short time is almost certainly not due to RV. It can certainly be the result of active adaptational mechanisms.

    I believe that, given the chrinological frame, nothing is known about the molecular basis of the changes you refer to.

    My firm view is that credible causal inferences about biological information can be done only where enough is known of the molecular mechanisms.

    That’s why I never engage in discussions about phenotypic changes whose molecular basis is not known. That is also the reason why darwinists only speak of phenotypic changes whose molecular basis is not known. That often creates problems of communication between me and them ! :)

    2.2:

    Please, see previous point. You say:

    Could that have been a result of some latent genes which were not expressed until such times as something triggered it?

    Absolutely. RV + NS is not even an option, with these time spans.

    3:

    Indeed, it’s the other way round.

    First of all, basic protein domain go on emerging throughout the whole span of natural history, even if it is true that many of them emerged in LUCA, and the the rate of emergence constantly decreases in time. But even at the mammal level new domains continue to emerge. Therefore, if protein domains are a sign of design, then design has been going on throughout natural history.

    But the important point is: protein domains are the simplest level of functional organization.

    The only reason why I always discuss them, is that we have enough understanding of their molecular basis, and of the genes that encode the information for the. Afetr all, protin coding genes are the only part of the genome that we understand quite extensively.

    At higher levels of organization, design is even more obvious that in the “simple” protein domains, but the analysis is more difficult. I will make some examples:

    a) Behe has clearly shown that, at the level of molecular machines, the problem arises of irreducible complexity. Most proteins do not act alone, but are integrated in complex molecular machines, each of which is made of many different proteins, each extremely complex, each perfectly integrated with the other complex proteins, amny of them exclusive of the specific molecular machine.

    The bacterial flagellum is still an unsurmountable problem for darwinism. Don’t believe the ad hoc propaganda of darwinists on that point: they have nothing to explain it.

    And we have hubdreds, thousands, of other copmplex molecular machines whose functionall complexity is huge.

    I don’t discuss them usually because, again, I need to bring the discussion to dFSCI calculation, to be able to make absolutely incontrovertible points, and it is much easier to do that with single strings with single defined functions, like individual protein coding genes.

    b) Cell differentiation iin multicellular beings: that happens thorugh an extremely complex network of transcription factor and other components, whose workings we are just starting to analyze. As a consequence of that, a single genome implements hundreds of different transciptomes and proteomes, for each cell type and cell state.

    That is a complete mystery at present. We have no idea of the procedures by which that is implemented. We don’t know how they work, and, especially, we don’t known how and where they are written and stored.

    Of one thing I am certain: those procedures are mmuch more complex than protein domains.

    c) The complex organization of organs and systems. Just two examples: the mammalian immune system and human central nervous system. Do you really believe that the spacial and functional organization of those machines, by far more complex and more efficient of anything else we know, are really a result of a few bits changed in the genome? Don’t believe it for a moment! That’s just the last, extreme, desperate lie of a false theory that has been clouding human cognition for decades.

  17. GPuccio, KF,

    Many Thanks for your comprehensive answers. I would have suspected that was the case regarding the lizards Podarcis sicula.

    GP, I got your point regarding phenotypic change. It would be really nice if you could come up with an original post here that one can easily refer to.

    Yes, function and rules (as opposed to constraints) are signs of intelligence for sure even more so in biosystems.

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