Why "a simple beginning" remains Darwinism's unicorn.

 Michael Behe in World Magazine — “Game Over” for Darwinism 

David Klinghoffer 

Our biologist colleague Michael Behe has written a wonderful cover story for World Magazine. His theme is how science has vindicated the words of the Psalmist: “I will praise thee; for I am fearfully and wonderfully made: marvellous are thy works; and that my soul knoweth right well.”

That inference to intelligent design — recognizing a “purposeful arrangement of parts” in biological systems, large and small — doesn’t require a scientist to draw it. It was available to the thoughtful observer of life thousands of years. But the closer and deeper that technology has permitted us to peer into such systems, the more evident it has become that they reflect a deliberate design.

Behe traces science’s progress from Aristotle to Galen to William Harvey, Marcello Malpighi, Antonie van Leeuwenhoek, and finally “John Walker, a British scientist who has studied ATP synthase for over 40 years — fully one-quarter of the time since his countryman, the naturalist Charles Darwin, first proposed his theory of evolution in 1859.” 

Walker Had the Floor 

Professor Behe was present at a “semi-secret” scientific gathering “whose theme was a specific controversial question: Did Darwinian evolution have any limitations?” ATP synthase (pictured above) is a fearfully and wonderfully made molecular machine, the “power plant of the cell.” John Walker had the floor and was discussing his area of expertise. Behe explains: 

ATP synthase is not simple. Comprising thousands of amino acid building blocks in about 10 kinds of protein chains, its intricate structure carefully directs a flow of acid particles, beginning from outside the cell, through deep channels in the machine’s organization, into the cell’s interior. Somehow, like the cascade of water over a hydroelectric dam that turns a turbine, the flow of acid through the channels rotates a central camshaft. The cams push against multiple discrete areas of a stationary region of the synthase, distorting their shapes. The distortion forces together two bound feed-chemicals, ADP and phosphate, provoking them to react to yield the energy-rich-yet-stable molecule ATP. As the camshaft completes a turn, the ATP is released into the cell, and the machine begins another cycle. Incredibly, the many copies of the machine in each person produce about 150 pounds of ATP molecules every day, but each is used rapidly as energy — in effect, recharging each cell like a reusable battery.

And Walker’s more recent studies — using the ­newest, most powerful iteration of microscopy, called “cryo-electron” microscopy — would reveal its mechanism in unprecedented detail. 

A Snipe Hunt 

But there was an obvious problem: 

By now, the scientists assembled before Dr. John Walker had run out of patience. The man had just held forth for nearly an hour on this miracle of biological architecture. Elegant and complex, precision-engineered, multiplied daily in the billions across the biosphere and on which the entirety of life depends. Finally, during the Q&A period, a questioner asked him directly: How could a mindless Darwinian process produce such a stunning piece of work?

Walker’s entire reply (paraphrasing): “Slowly, through some sort of intermediate or other.”

Far out of earshot I muttered two simple words: “Game over.”

If a Nobel laureate who has worked on one of life’s most fundamental systems for four decades can’t give an account of how it supposedly arose through a series of lucky mutations and natural selection — despite knowing its innermost workings in spectacular detail — then it’s reasonable to conclude no such account exists, and the effort to find one is a snipe hunt 

A snipe hunt is a “fool’s errand” because the so-called snipe in the metaphor is an imaginary animal. And indeed the game is over for Darwinian evolutionary theory: an unguided evolutionary explanation for what Behe calls irreducibly complex structures, including ATP synthase, will not be found. It remains for Darwin’s apologists, some of them rather vicious, to recognize this and permit the public to hear it, too. Read the rest of Behe’s essay for World here. 

Why time is no friend of Darwin.

 Fossil Friday: Walking Whales and Why All Critiques of the Waiting Time Problem Fail 

Günter Bechly 

This Fossil Friday features the reconstructed skeletons of Pakicetus (below) and Ambulocetus (above), which are so-called “walking whales” from the Eocene of Pakistan. These fossils are often celebrated as missing links and a success story for Darwinism. However, they indeed create a fatal problem for neo-Darwinism, which is known as the waiting time problem. The general problem is that the window of time established by the fossil record for the transition from “walking whales” to fully marine whales is orders of magnitude too short to accommodate the waiting times for the origin and spread of the required genetic changes, based on the standard mathematical framework of population genetics. This problem has been elaborated in a popular way in several publications of the ID community (Meyer 2013, Evolution News 2016, LeMaster 2018), and in the Illustra Media documentary Living Waters.

An Ongoing Multidisciplinary Research Project

The waiting time problem is the subject of an ongoing multidisciplinary research project funded by Discovery Institute. We have already published the theoretical ground work in two peer-reviewed papers in mainstream science outlets (Hössjer et al. 2018, 2021). An application on the example of whale origins is forthcoming by Bechly et al. (in prep.).

The waiting time problem has been the target of scornful critique by anti-ID spokesmen (e.g., Moran 2016, Rasmussen 2021, Stern-Cardinale 2022, Farina 2022), who claimed that it is fallacious and fails to challenge Darwinism. We will address this critique in great detail in our forthcoming technical paper, but let me here briefly refute the main points for a lay audience so that you are equipped for eventual debates. 

Reviewing the Main Points 

1.) Critics often explicitly or implicitly suggest that the waiting time problem is a pseudo-problem invented by evil and stupid creationists. This is a silly and embarrassingly incompetent argument, which only shows that these critics have not only failed to grasp the problem, but also seem to be totally unaware that the waiting time problem has a long history and has been much discussed in mainstream science (especially population genetics). It even plays an important role in cancer research. They should talk to Harvard professor Martin Nowak, who is an evolutionary biologist and expert on the waiting time problem. Here are just a few references of renowned scientists publishing about this “crazy stuff” as Farina (2022) calls it: Bodmer (1970), Karlin (1973), Christiansen et al. (1998), Schweinsberg (2008), Durrett et al. (2009), Behrens et al. (2012), and Chatterjee et al. (2014). It was not before Behe & Snoke (2004, 2005) and Behe (2007, 2009) that the waiting time problem was recognized as an argument for intelligent design. Durrett & Schmidt (2008) attempted to refute Behe but arrived at a prohibitive waiting time of 216 million years for a single coordinated mutation in human evolution, while only about 6 million years are available since the origin of the human lineage from a common ancestor with chimps. Behe arrived at 1015 years by using empirical data about an actual waiting time for a coordinated mutation that conveyed chloroquine drug resistance in malaria. He simply transposed these empirical findings on humans, considering their much lower population size and much longer generation time. Durrett & Schmidt’s result was based on a mathematical model, which of course must make certain simplifications that can introduce errors. When such model calculations conflict with hard empirical data, we should trust the empirical data as pointing closer to the truth. Anyway, both numbers are prohibitive and refute the feasibility of a Darwinian mechanism of macroevolution. 

2.) Most critics considered the most powerful objection to be the “Texas sharpshooter fallacy.” They claimed that nature does not go for specific mutations as a target but is totally random. This argument fails because it presupposes the existence of many targets, which is contradicted by the rarity of function in the search space for proteins and by the common phenomenon of convergence. The argument also fails to recognize that life cannot allow for periods of maladaptation only to descend a local peak of the fitness landscape to explore other ones. Instead, life has to further adapt to its local fitness peak, which requires specific solutions for specific problems. It’s not like any beneficial mutation could do. A stem whale would have no use for a mutation that would be beneficial for a stem bird, such as improving skeletal pneumaticity. In the computer models applied in our publications on the waiting time problem we also allowed for alternative targets and fuzzy targets, so not just one pre-specified binding site, which prevents another possible critique. 

3.) Some critics failed to grasp the concept of coordinated mutations and even called it meaningless. They suggested that every individual mutation can be selected for. This shows that they did not get the simple point that in coordinated mutations each individual mutation is neutral and thus in principle cannot be selected for. Only the combination of coordinated mutations has a selection value, which is the whole point, and the reason why they were called “coordinated mutations” in the first place. 

4.) Some critics claim that the waiting time problem implies that mutations have to occur in a specific sequence. This is simply false and maybe based on a misunderstanding of the technical term “coordinate gene.” The fact is that no ID proponent ever claimed that the waiting time problem only applies for particular sequences of mutations. For any set of reasonable parameters, the waiting times for coordinated mutations (i.e., mutations that have to occur together to have a selection value) will be prohibitive, irrespective of the order of these mutations. What is true is that the waiting time problem gets even worse when such mutations also have to occur in a specific sequence. 

5.) Critics also claimed that the waiting time problem ignores recombination, which according to Farina (2022) “baselessly discounts the profound evolutionary benefit” and is “dramatically accelerating the accumulation of beneficial mutations.” This shows how ignorant the critics are of the actual technical literature, because the influence of recombination of the waiting time problem has been studied by Christiansen et al. (1998), who have shown that: “Recombination lowers the waiting time until a new genotypic combination first appears, but the effect is small [my emphasis] compared to that of the mutation rate and population size.” In our papers (Hössjer et al. 2018, 2021, Bechly et al. in prep.) we show that recombination does not affect the waiting time under realistic assumptions for parameters like mutation rates and population sizes. 

6.) Critics also claim that the problem is merely theoretical but not realistic in biological terms, e.g., because it does not apply to concrete examples or because coordinated mutations are not necessary. We will address the latter claim very thoroughly in our forthcoming paper, where we do apply the theoretical framework to the concrete example of whale origins. We will also show, based on mainstream evo-devo data, that coordinated mutations indeed are required. This is also suggested by the fact that even simple characters like skin color turned out to be highly polygenic, thus controlled by many different genes. By the way: The waiting time problem has also been applied to the concrete example of human origins by Durrett & Schmidt (2008) and Sanford et al. (2015) with prohibitive results for Darwinian evolution. 

And Finally 

Last but not least, some critics were puzzled by how papers by ID proponents on the waiting time problem could somehow make it into peer-reviewed journals like the prestigious Journal of Theoretical Biology. Well, that’s easy: because it is good peer-reviewed science and the usual censorship of the Darwinist mafia sometimes fails to sabotage the publication of inconvenient research, even though they always try very hard. It is the height of hypocrisy when the very same people turn around and claim that ID proponents don’t publish their stuff in the peer reviewed literature. Darwinists, as is well known, love to play the game of “Heads I win, tail you lose.” 

References 

Behrens S, Nicaud C & Nicodéme P 2012. An automaton approach for waiting times in DNA evolution. Journal of Computational Biology 19(5), 550–562. DOI: https://doi.org/10.1089/cmb.2011.0218

Behe MJ 2007. The Edge of Evolution. Free Press, New York (NY), 336 pp.

Behe M 2009. Waiting Longer for Two Mutations. Genetics 181(2), 819–820. DOI: https://doi.org/10.1534/genetics.108.098905

Behe MJ & Snoke DW 2004. Simulating evolution by gene duplication of protein features that require multiple amino acid residues. Protein Science 13(10), 2651–2664. DOI: https://doi.org/10.1110/ps.04802904

Behe MJ & Snoke DW 2005. A response to Michael Lynch. Protein Science 14(9), 2226–2227. DOI: https://doi.org/10.1110/ps.051674105

Bodmer WF 1970. The evolutionary significance of recombination in prokaryotes. Symposium of the Society for General Microbiology 20, 279–294.

Chatterjee K, Pavlogiannis A, Adlam B & Nowak MA 2014. The time scale of evolutionary innovation. PLoS Computional Biology 10(9):d1003818, 1–7. DOI: https://doi.org/10.1371/journal.pcbi.1003818

Christiansen FB, Otto SP, Bergman A & Feldman MW 1998. Waiting with and without Recombination: The Time to Production of a Double Mutant. Theoretical Population Biology53(3), 199–215. DOI: https://doi.org/10.1006/tpbi.1997.1358

Durrett R & Schmidt D 2008. Waiting for two mutations: with applications to regulatory sequence evolution and the limits of Darwinian evolution. Genetics 180(3), 1501–1509. DOI: https://doi.org/10.1534/genetics.107.082610

Durrett R, Schmidt D & Schweinsberg J 2009. A waiting time problem arising from the study of multi-stage carcinogenesis. Annals of Applied Probability 19(2), 676–718. DOI: https://doi.org/10.1214/08-AAP559

Farina D 2022. Exposing the Discovery Institute Part 2: Stephen Meyer. Professor Dave Explains May 13, 2022. https://youtu.be/Akv0TZI985U

Hössjer O, Bechly G & Gauger A 2018. Phase-type distribution approximations of the waiting time until coordinated mutations get fixed in a population. Chapter 12, pp. 245–313 in: Silvestrov S, Malyarenko A & Rancic M (eds). Stochastic Processes and Algebraic Structures – From Theory Towards Applications. Volume 1: Stochastic Processes and Applications. Springer Proceedings in Mathematics and Statistics 271. DOI: 10.1007/978-3-030-02825-1_12

Hössjer O, Bechly G & Gauger A 2021. On the waiting time until coordinated mutations get fixed in regulatory sequences. Journal of Theoretical Biology 524:110657, 1–37. DOI: https://doi.org/10.1016/j.jtbi.2021.110657

Karlin S 1973. Sex and infinity: A mathematical analysis of the advantages and disadvantages of genetic recombination. pp. 155–194 in: Bartlett MS & Hiorns RW (eds). The Mathematical Theory of the Dynamics of Biological Populations. Academic Press, New York (NY), xii+347 pp.

LeMaster JC 2018. Evolution’s waiting-time problem and suggested ways to overcome it—A critical survey. BIO-Complexity 2018(2), 1–9. DOI: https://doi.org/10.5048/BIO-C.2018.2

Meyer SC 2013a. Darwin’s Doubt. HarperOne, New York (NY), viii+498 pp.

Moran L 2016. Targets, arrows, and the lottery fallacy. Sandwalk Jan. 14, 2016. https://sandwalk.blogspot.com/2016/01/targets-arrows-and-lottery-fallacy.html

Rasmussen MN 2021. Waiting Time Problem” and imaginary hurdles for evolution. Pandas Thumb June 12, 2021. https://pandasthumb.org/archives/2021/06/ID-and-imaginary-hurdles.html

Sanford J, Brewer W, Smith F & Baumgardner J 2015. The waiting time problem in a model hominin population. Theoretical Biology and Medical Modelling 12:18, 1–18. DOI: https://doi.org/10.1186/s12976-015-0016-z

Schweinsberg J 2008. The waiting time for m mutations. Electronic Journal of Probability13, 1442–1478. DOI: https://doi.org/10.1214/EJP.v13-540

Stern-Cardinale D 2022. Creation Myth: The “Waiting Time Problem” Creation MythsFebruary 15, 2022. https://youtu.be/F748itCI_es 

Primeval tech vs. modern tech.

 Why AlphaFold Has Not Solved the Protein-Folding Problem.

Paul Nelson 

The online database AlphaFold represents an amazing breakthrough by any measure of the word “breakthrough.” Biology is a much stronger science today for having AlphaFold in its analytical armamentarium.

But the algorithm, powerful as it is, has NOT solved the protein-folding problem, if we take that problem to mean this:

predicting the three-dimensional conformation of a protein strictly from its primary DNA sequence, ab initio.

An analogy to natural language may help. Suppose I give you a character string in English which you’ve never seen before, with no surrounding semantic context, and no corresponding lexicon or dictionary referents, even approximate. Here are two such words — these are words used weekly in Nelson family conversations for over 25 years:

googlimasha

mecky

My wife and daughters know EXACTLY what these words mean. Do you? Unless we’ve told you, almost certainly not. (Scroll down to the end for their meanings.) As far as the reader is concerned, these words are singletons, and you can only guess at their meanings (functional roles in English).

AlphaFold uses existing sequences and their known conformations / structures to predict unknown structures. Under the natural language analogy, AlphaFold levers itself off the existing genetic and proteomic dictionaries. But if a sequence exists as a singleton, in an isolated region of sequence space, AlphaFold performs poorly. Which means the protein folding problem, in its original form, remains unsolved. 

Yours to Discover 

A new unpublished MS by Yves-Henri Sanejouand of the French National Centre for Scientific Research is worth your attention, in relation to the protein folding problem, but also the high frequency of unique (singleton) proteins in eukaryotic species. See, “On the unknown proteins of eukaryotic proteomes.” The fascinating implications of Sanejouand’s preliminary analysis are yours to discover.

But if one extends one’s scope to include ALL nucleic acid sequences on Earth (not just eukaryotes), things get really wild. In a new paper, in press at Environmental Microbiology, Eugene Koonin and colleagues argue that — given their sequence diversity — viruses on Earth must have many independent origins. See, “The global virome: how much diversity and how many independent origins?” 

No Current Viable Theory  

After you read Koonin et al.’s paper, reflect for a moment on its implications. The vast majority of nucleic acid diversity on this planet is unique, represented by singletons (emphasis added): 

…we can also roughly estimate the size of the virus pangenome, in other words, the total number of genes in the virosphere. Large viruses encompass many poorly conserved, species-specific genes that obviously represent the bulk of the virus pangenome. Assuming 10 such unique genes per virus species, there would be 108 to 1010 unique virus genes altogether, a vast gene repertoire, to put it modestly. 

All these sequences must have been processed through a ribosome, borrowed from a free-living cell. There is currently no viable theory for the replication of viral genomes without the simultaneous presence of organismal systems (basically, ribosomes) to be hijacked. Thus the evolutionary clock for the origin of 108 to 1010 viral genes cannot start ticking until the origin of ribosomes. 

This appears to be the Mother of All Waiting Times Problems.

Oh, and those words I mentioned earlier? “Googlimasha” is a noun. It means “what Paul made that afternoon for dinner, but doesn’t want to tell his daughters when he picks them up at the end of their school day, because they will complain that they’re not in the mood for pork chops, or whatever, and Paul — having just slaved over dinner prep — simply isn’t interested in their spoiled suburban bellyaching.”

As for “mecky,” it can be a noun but most often is an adjective. It describes the hybrid state of “heck” and “messy,” in other words, an awful situation getting steadily worse. In its noun form, it is a term of endearment for Paul himself, frequently used by his daughter who is now a high school science teacher in Yonkers, NY.