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.
Estimating the prevalence of protein sequences adopting functional enzyme folds: Doug Axe: 2004
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.
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.
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.”
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.
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 , 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.
“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.
The Real Barrier to Unguided Human Evolution – Dr. 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).
More from Dr. 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.
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.
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 – Dr. 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.
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: 2008
“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.”
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:
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.
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.
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.
Cellular Communication through Light
Excerpt: Information transfer is a life principle. On a cellular level we generally assume that molecules are carriers of information, yet there is evidence for non-molecular information transfer due to endogenous coherent light. This light is ultra-weak, is emitted by many organisms, including humans and is conventionally described as biophoton emission.
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.,,,
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.
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
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
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.”
Human Genes: Alternative Splicing 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.
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.”
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.
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.
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,,
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.
“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.
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,
In fact there is little hope of a truly random (i.e. Darwinian) mutation ever 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.