Brown University biologist Kenneth R. Miller has posted a reply to my challenge to him to give a quantitative account for the extreme rarity of the origin of chloroquine resistance in malaria. I’m grateful to him for doing so. Although I strongly disagree with nearly everything he wrote, his essay gives the public a chance to see directly how one informed Darwinist reacts to a basic empirical challenge to the theory. This is the last in a series of four posts responding to it.
In my last three posts (here, here, and here) I showed that Miller’s claims concerning the evolution of the chloroquine-transporting protein PfCRT of malaria were at best contrary to strong experimental evidence and at worst simply wrong. That section occupied less than a third of his essay. Now I’ll move on to the remaining two-thirds. Mercifully, that can be dealt with more briefly here, because in previous writings I have already answered almost all the objections he raises. For most of that final portion Miller simply calls on the prominent biologists Sean Carroll and Joseph Thornton for help. My answers to Carroll’s old arguments are here and here.
Just one issue remains. In a section titled "Rigging the Odds" (the link to that section in HTML is more bluntly called "Fabricating the Odds"), Miller objects to my saying that if two new protein binding sites were required to evolve for some new, useful, selectable function, the likelihood would be about the square of the odds of one new selectable protein binding site evolving. I put the latter odds at about 1 in 1020, about the same as the odds of malaria developing chloroquine resistance (which I dubbed a "Chloroquine Complexity Cluster," or CCC). The odds of two required sites evolving in my model would then be around 1 in 1040 — a very large number indeed, and what I argued was the "edge," the limit, of Darwinian evolution. That would be a big problem for the theory since most proteins occur in cells as complexes of six or more.
Miller grants the value of 1 in 1020 for purposes of discussion ("Let’s accept Behe’s number of 1 in 1020 for the evolution of a complex mutation like his CCC"). But he balks at multiplying the odds for the development of two required sites to get the ultra-huge value of 1040, calling it a "breathtaking abuse of statistical genetics." It’s more likely he lost his breath from the speed at which he switched models.
He points to what might happen with chloroquine and a second anti-malarial drug of the same efficacy:
Chloroquine resistance arose in just a decade and a half, and is now common in the gene pool of this widespread parasite. Introduce a new drug for which the odds of evolving resistance are also 1 in 1020, and we can expect that it will take just about as long, 15 years, to evolve resistance to the second drug. Once you get that first CCC established in a population, the odds of developing a second one are not CCC squared. Rather, they are still 1 in 1020. Behe gets his super-long odds by pretending that both CCCs have to arise at once, in the same cell, purely by chance. They don’t…
Miller shows here that he has simply misunderstood the central argument of The Edge of Evolution. In my book I stipulated that the two sites were interdependent, linked: "Now suppose that, in order to acquire some new, useful property, not just one but two new protein-binding sites had to develop." The sites are defined as belonging to the subset of beneficial traits named "Only Selectable When Partner Site Has Also Evolved." In my thought experiment, there is no selectable property in the presence of only one such site. I postulated that only when the two have developed do we get such an effect. (For example, suppose in Miller’s inapt illustration above the two drugs were chemically tied together — perhaps they were simply different regions of the same molecule. In that case resistance would have to be developed against both at once to do any good. And the likelihood of that would indeed be the multiple of the odds of developing resistance against each one separately.)
Miller’s incongruous response essentially is to say: "No, I have decided to change your own model. I will switch the premise to one in which each protein binding site will necessarily be beneficial by itself." Much worse, he doesn’t tell his readers that’s what he’s doing. His writing leads them to believe he is describing the same situation as I did. Let me be clear, if Miller had simply said that he thought there would be no actual situations in nature like I modeled — that the subset was empty; that never in reality would two new protein binding sites be needed before any new selectable property resulted — then that would have been fine. We could have argued amicably about whether that was true. But he didn’t. Instead he conjured an entirely separate scenario, and then claimed it was I — not he — who was "fabricating," trying to deceive readers with a "statistical trick"!
Miller’s efforts to divert readers’ attention from features that require multiple mutations follows inexorably from Darwinism’s profound Achilles’ heel. Let’s play off Miller’s two-antimalaria-drugs example to help see what it is. He wrote that, sure, the odds of malaria developing resistance to chloroquine are about 1 in 1020. But if a second drug came along the odds would still be 1 in 1020. They wouldn’t be multiplied, he said.
Well, we can note that the odds of developing resistance to the malaria drug atovaquone are only about 1 in 1012. We can then ask, why is the probability so much better for atovaquone than for chloroquine? And following Miller’s lead we can ask, if malaria developed resistance to atovaquone at a frequency of 1 in 1012, shouldn’t it subsequently develop resistance to chloroquine at 1 in 1012? Why not just another round of 1 in 1012? Why the jump to 1 in 1020?
Enter Achilles and his heel. It turns out that the odds are much better for atovaquone resistance because only one particular malaria mutation is required for resistance. The odds are astronomical for chloroquine because a minimum of two particular malaria mutations are required for resistance. Just one mutation won’t do it. For Darwinism, that is the troublesome significance of Summers et al.: "The findings presented here reveal that the minimum requirement for (low) CQ transport activity … is two mutations."
Darwinism is hounded relentlessly by an unshakeable limitation: if it has to skip even a single tiny step — that is, if an evolutionary pathway includes a deleterious or even neutral mutation — then the probability of finding the pathway by random mutation decreases exponentially. If even a few more unselected mutations are needed, the likelihood rapidly fades away.
Without telling his readers, Miller switches from my model to one with the tendentious assumption that new protein binding sites would necessarily always be helpful on their own. (New protein binding — that sounds so nice. What could possibly go wrong?) Yet one mutation in the chloroquine-resistance protein isn’t helpful at all. In fact the best evidence indicates it is harmful on its own. Two mutations are needed before it’s helpful. So why should we think that just one binding site must always be helpful? Who made up that rule? The answer is that we have no particular reason to think it, and good reason to disbelieve it.
So what should we conclude from all this? Miller grants for purposes of discussion that the likelihood of developing a new protein binding site is 1 in 1020. Now, suppose that, in order to acquire some new, useful property, not just one but two new protein-binding sites had to develop. In that case the odds would be the multiple of the two separate events — about 1 in 1040, which is somewhat more than the number of cells that have existed on earth in the history of life. That seems like a reasonable place to set the likely limit to Darwinism, to draw the edge of evolution.
References for the series:
Farooq, U. and Mahajan, R. C. 2004. Drug resistance in malaria. J. Vector. Borne. Dis. 41:45-53.
Jucker, M. and Walker, L. C. 2013. Self-propagation of pathogenic protein aggregates in neurodegenerative diseases. Nature 501: 45-51.
Kublin, J. G. et al. 2003. Reemergence of chloroquine-sensitive Plasmodium falciparum malaria after cessation of chloroquine use in Malawi. J. Infect. Dis. 187:1870-1875.
Lakshmanan, V., et al. 2005. A critical role for PfCRT K76T in Plasmodium falciparum verapamil-reversible chloroquine resistance. EMBO J. 24:2294-2305.
Paget-McNicol, S. and Saul, A. 2001. Mutation rates in the dihydrofolate reductase gene of Plasmodium falciparum. Parasitology 122:497-505.
Summers, R. L. et al. 2014. Diverse mutational pathways converge on saturable chloroquine transport via the malaria parasite’s chloroquine resistance transporter. Proc. Natl. Acad. Sci. U. S. A 111:E1759-E1767.
Wang, X. et al. 2005. Decreased prevalence of the Plasmodium falciparum chloroquine resistance transporter 76T marker associated with cessation of chloroquine use against P. falciparum malaria in Hainan, People’s Republic of China. Am. J. Trop. Med. Hyg. 72:410-414.
White, N. 1999. Antimalarial drug resistance and combination chemotherapy. Philos. Trans. R. Soc. Lond B Biol. Sci. 354:739-749.
White, N. J. 2004. Antimalarial drug resistance. J. Clin. Invest 113:1084-1092.