|Intelligent Design and the Origin of Information: A Response to Dennis Venema
In this article, Part 3, we:
The very first line of Dennis Venema’s first post in his “Evolution and the Origin of Biological Information” series states: “One prominent antievolutionary argument put forward by the Intelligent Design Movement (IDM) is that significant amounts of biological information cannot be created through evolutionary mechanisms — processes such as random mutation and natural selection.” (emphasis added)
While Dr. Venema accurately described this common intelligent design (ID) argument, it’s noteworthy that he chooses to use the label “antievolutionary” to describe ID. That is, of course, a pejorative term favored by the Darwin lobby and its semi-official headquarters, the National Center for Science Education.
In another recent venue, Venema misdefines ID as a purely negative argument against “evolution,” stating: “The main ID view is that some features of life are too complex to be the result of evolution, thus indicating that they were ‘designed.'”
Here, Venema’s definition of ID is wrong on two counts: First, ID is not merely a negative argument against “evolution,” and second, ID does not necessarily challenge “evolution,” depending on how one defines evolution.
If we define evolution as “change over time,” “small-scale change,” or “common descent,” then ID certainly does not challenge evolution and is not “antievolution.”
But we already knew Venema has a misguided view of ID. In my previous article in this series responding to him, we saw how Venema misstated Stephen Meyer’s basic thesis in Signature in the Cell as being a “denial of random mutation and natural selection” as a mechanism that can change the information in DNA.
Unfortunately, these misunderstandings lead Venema to set up an inaccurate method of testing of ID:
The issue is that Meyer’s case is open to refutation by counterexample, and even one counterexample would suffice. If any natural mechanism can be shown to produce “functional, information-rich genes and proteins,” then intelligent design is no longer the best explanation for the origin of information we observe in DNA, by Meyer’s own stated criteria. His entire (500+ page) argument would simply unravel.
The basic problem with Venema’s test is this: Intelligent design is not “antievolution” and has never stated that neo-Darwinian processes cannot do anything. That neo-Darwinian processes or other natural mechanisms can do some things is a true but trivial assertion as far as ID is concerned. In fact, in his book The Edge of Evolution, Michael Behe readily agrees that neo-Darwinian evolution can effect some changes in populations of organisms. ID does not deny that random mutation and natural selection are at work–it simply claims, as Michael Behe argues, that there is a limit to what they can accomplish.
Behe has further written elsewhere: “if only one mutation is needed to confer some ability, then Darwinian evolution has little problem finding it.” The question is not “Can Darwinian evolution do anything?” but rather “Can Darwinian evolution do virtually everything, as proponents of naturalism often claim?” ID proponents want to avoid presupposing answers, and instead want to follow the evidence wherever it leads. Thus, ID might frame the question like this: “What can neo-Darwinian processes accomplish, and what is best explained by intelligent causes?”***
Darwin himself correctly defined the outer boundary of the causal abilities of natural selection. He wrote that structures must evolve by “numerous, successive slight modifications.” In The Edge of Evolution, Behe postulates a “two mutation rule” where features that require two or more mutations before providing some functional advantage are unlikely to arise by random mutation and natural selection. Research is confirming Behe’s thesis.
In their 2004 peer-reviewed paper in the journal Protein Science, Behe and physicist David Snoke simulated the Darwinian evolution of protein-protein interactions that required multiple amino acids. They found that for eukaryotic organisms, evolving a simple protein-protein interaction involving two or more mutations might require more probabilistic resources (i.e., population sizes and numbers of generations) than would be generally available.
In 2008, Behe and Snoke’s would-be critics tried to refute them in the journal Genetics, but found that to obtain only two specific mutations via Darwinian evolution “for humans with a much smaller effective population size, this type of change would take > 100 million years.” The critics admitted this was “very unlikely to occur on a reasonable timescale.”
In 2010, Doug Axe published another peer-reviewed research paper which seemed to confirm Behe and Snoke’s results. He presented calculations modeling the Darwinian evolution of bacteria including a structure which required multiple mutations to yield any benefit. Axe’s model made exceedingly generous assumptions in favor of the Darwinian model. He assumed the existence of a huge population of asexually reproducing bacteria that could replicate quickly — perhaps nearly 3 times per day — over the course of billions of years. Despite the fact that bacteria have some of the highest known mutation rates, even here molecular adaptations requiring more than six mutations to function would not arise in the history of the earth.
In 2010, research published by molecular biologist Ann Gauger of the Biologic Institute, Ralph Seelke at the University of Wisconsin-Superior, and two other biologists provided empirical backing to the claims of Axe and Behe. Their team started by breaking a gene in the bacterium E. coli required for synthesizing the amino acid tryptophan. When the bacteria’s genome was broken in just one place, random mutations were capable of “fixing” the gene. But when two mutations were required to restore function, Darwinian evolution could not do the job.
These results suggest that on a reasonable timescale, there is too much complex and specified information in many proteins and enzymes to be generated by Darwinian processes. The reason, as Axe’s 2000 and 2004 papers in Journal of Molecular Biology suggest, is that functional amino acid sequences are very rare.
Drs. Axe, Gauger, and Seelke are by no means the only scientists to observe the rarity of functional amino acid sequences. A leading college-level biology textbook states that “even a slight change in primary structure can affect a protein’s conformation and ability to function.” Likewise, evolutionary biologist David S. Goodsell writes:
[O]nly a small fraction of the possible combinations of amino acids will fold spontaneously into a stable structure. If you make a protein with a random sequence of amino acids, chances are that it will only form a gooey tangle when placed in water.
Goodsell goes on to assert that “cells have perfected the sequences of amino acids over many years of evolutionary selection.” But if functional protein sequences are rare, then natural selection will be unable to take proteins from one functional sequence to the next without getting stuck at some maladaptive or non-beneficial stage.
So when we test a particular protein to assess its origin, a very important question is: Is there a step-wise Darwinian pathway by which new genes and proteins can evolve? This mirrors Darwin’s observation that, under his model, evolution requires that structures evolve by “numerous successive slight modifications.”
Venema’s hope that perhaps we can observe one gene or protein evolving by a stepwise Darwinian pathway does not imply that all genes or proteins are amenable to stepwise Darwinian evolution via numerous successive slight modifications. Some genes and proteins might be within what Behe calls the “edge of evolution,” but some might be beyond it.
Venema seeks to refute ID wholesale and prove neo-Darwinian evolution through what he calls “one counterexample.” But this reflects a fundamental misunderstanding of ID. Research from pro-ID scientists is beginning to understand and elaborate exactly where the “edge of evolution” lies, and the observation that one gene or protein might be within the “edge” does not imply that all are.
In subsequent responses to Dr. Venema, we’ll assess whether the empirical examples cited by Venema are actually within the “edge of evolution” and if they shows, as he suggests, that natural selection and random mutation can produce “functional, information-rich genes and proteins.”
[1.] Michael J. Behe & David W. Snoke, “Simulating Evolution by Gene Duplication of Protein Features That Require Multiple Amino Acid Residues,” Protein Science, Vol. 13:2651-2664 (2004).
[2.] Rick Durrett and Deena Schmidt, “Waiting for Two Mutations: With Applications to Regulatory Sequence Evolution and the Limits of Darwinian Evolution,” Genetics, Vol. 180: 1501-1509 (November 2008).
[3.] Douglas D. Axe, “The Limits of Complex Adaptation: An Analysis Based on a Simple Model of Structured Bacterial Populations,” BIO-Complexity, Vol. 2010(4):1-10.
[4.] Ann K. Gauger, Stephanie Ebnet, Pamela F. Fahey, and Ralph Seelke, “Reductive Evolution Can Prevent Populations from Taking Simple Adaptive Paths to High Fitness,” BIO-Complexity, Vol. 2010 (2).
[5.] Douglas D. Axe, “Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds,” Journal of Molecular Biology, Vol. 341: 1295-1315 (2004); Douglas D. Axe, “Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme Exteriors,” Journal of Molecular Biology, Vol. 301: 585-595 (2000).
[6.] Neil A. Campbell and Jane B. Reece, Biology, p. 84 (7th ed, 2005).
[7.] David S. Goodsell, The Machinery of Life, pp. 17, 19 (2nd ed, Springer, 2009).
*** Regarding properly testing ID, the statement “Thus, ID might frame the question like this: ‘What can neo-Darwinian processes accomplish, and what is best explained by intelligent causes?’,” shows that we must test various causes and determine their causal abilities and compare and contrast the mechanisms. Of course that’s a very general statement, and my purpose here is not to get into ID’s specific causal abilities. For a discussion of where I’ve done that extensively in the past, please see: A Positive, Testable Case for Intelligent Design.