The Failures of Mathematical Anti-Evolutionism
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The Failures of Mathematical Anti-Evolutionism (Jason Rosenhouse) (z-lib.org)
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conveying the expected action and the intended purpose. (Gitt, Compton, and Fernandez 2011, 16) They go on to assert that “Universal Information” is always produced by intelligent design, and that organismal genomes comprise an instance of it. However, we have already noted that DNA does not know that it contains information. At the cellular level, everything is just 184 6 information and combinatorial search physics and chemistry. So it is very hard to see what “expected action” and “intended purpose” could possibly mean in this context. When DNA is in the presence of the correct cellular transcription systems certain effects are seen to occur, but it is just an abuse of language to describe this in intentional terms. Gitt, Compton, and Fernandez have built notions of intelligent design right into their definition of information. They are welcome to do so, but then it is very unclear that DNA actually contains information at all. I have belabored this discussion of Gitt’s writing for two rea- sons. The first is that he was the creationist speaker I mentioned all the way back in Section 1.3, the one who received a standing ovation and was praised for having presented an especially powerful apologetic argument. The argument in his conference presentation was precisely the one described here. Gitt is highly regarded among young-Earth creationists, which lends some importance to his writing. The second reason is that his willingness to hold forth about information, while never stating anything with sufficient precision to make cogent statements about biology, is entirely typical of anti-evolution writing in this area. As I noted in Section 1.3, where anti-evolutionists see a devastating argument against evolution, scientists just see an absurd caricature of a major branch of mathematics. 6.6 protein space revisited Let us return to the anti-evolutionist’s search metaphor. For our present purposes, we will assume it is “protein space” that needs to be searched. Eden’s argument at the Wistar conference, and the probabilistic anti-evolution arguments discussed in Chapter 5, focused primarily on the size of the space. It was argued that the rarity of functional proteins in the vast space of possibilities militated against the ability of evolution to find anything useful. We replied that any argument of this sort must pay careful attention to both the probabilistic and geometric structure of the space. If most of protein space has a 6.6 protein space revisited 185 probability close to zero of ever appearing in nature, then the vastness of the space as a whole is irrelevant. And if the functional proteins are arranged like stepping-stones, then it does not matter that they are rare in the space overall. In such a case, the very rarity of functional proteins could actually make them easier for evolution to find since deviations from the “one true path” will be quickly punished by natural selection. A recent line of argument in anti-evolutionist writing takes aim specifically at the geometric structure of the space, rather than at the probabilistic structure. It is claimed that useful proteins are actually not arranged like stepping-stones. Instead, the argument continues, they represent tiny, isolated, islands of functionality in an ocean of useless proteins. Their main piece of evidence in defense of this claim is a series of “mutagenesis” experiments carried out by protein chemist Douglas Axe, the results of which were published in Axe (2004). Such experiments involve inducing mutations in specific genes for the purpose of better understanding either the gene’s function or the protein it produces. Experiments of this sort have been part of biology’s toolkit since the 1920s, when it was discovered that X-rays could induce mutations. Whereas X-rays and other natural mutagens induce random mutations, today the technology exists to induce mutations at specific sites along a gene’s sequence. Appropriately, this technique is known as “site-directed mutagenesis.” Axe studied an enzyme called TEM-1 penicillinase, which breaks down penicillin and other antibiotics. The idea was to produce a large library of mutants and to determine the fraction of them that retained some function, even if just in a rudimentary form. In the terminology of our search metaphor, Axe sought to investigate the neighborhood in protein space surrounding this particular enzyme. The conclusion of the experiment might, in principle, have been that a large fraction of the mutants retained at least some function, implying that this neighborhood was teeming with possible stepping-stones for evolution to exploit. However, the actual finding was different. Axe 186 6 information and combinatorial search found that functional mutants were exceedingly rare, implying that this particular enzyme was exquisitely sensitive to any change. ID proponent Stephen Meyer explains what he takes to be the significance of this result: [Axe’s] experiments revealed that, for every DNA sequence that generates a short functional protein fold of just 150 amino acids in length, there are ten to the seventy-seventh power nonfunctional combinations – ten to the seventy-seventh amino acid arrangements – that will not fold into a stable three-dimensional protein structure capable of performing a biological function. … Thus, for every functional gene or protein fold there is a vast, exponentially large number of corresponding nonfunctional sequence through which the evolutionary process would need to search. Axe’s experimentally derived estimate placed that ratio – the size of the haystack in relation to the needle – at 10 77 nonfunctional sequences for every functional gene or protein fold. Download 0.99 Mb. Do'stlaringiz bilan baham: |
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