On the Relationship between Design and Evolution
Abstract
:1. Introduction
Definitions and Qualifications
2. Summary of The Compatibility of Evolution and Design
- Evolutionary theory, properly understood, is both scientifically correct and compatible with a certain type of biological design argument.
- The biological world itself provides notable grounds for belief in a purposeful Creator, and evolutionary theory does not defeat these grounds.
- For those worried about so-called natural evil, there is a way to join evolution with a biological design argument that actually adds credibility to evolution-based theodicies, rather than raising additional hurdles for them.
2.1. Why Bother with Design?
In most cases design is compatible with the alternative explanation, but if this is so, why not accept both design and the alternative explanation? The obvious answer is that there is no need to infer two explanations when one will do. When I learn that my children were playing in the study, the hypothesis that there has been a burglary becomes redundant as an explanation for the untidiness.
2.2. Which Version of Evolution?
If evolution is directional… then this directionality is contingent on the laws and constants of nature allowing this directionality. If evolution is highly contingent, so that running the “tape of life” again would cause a very different result, then this makes it surprising that such valuable outcomes have in practice been reached.
3. Why Scientific Evidence Is Crucial
3.1. Design and the “Preconditions” of Evolution
3.2. The Importance of Scientific Evidence
- Kojonen’s proposal is a philosophical model, not a scientific one. Scientific evidence is of secondary importance.
- KEBDA is primarily an exercise in harmonizing two distinct views (‘design’ and ‘evolution’), not in the evaluation of the empirical evidence for these views, whether individually or jointly.
- Kojonen’s model shows that evolution and design are compatible, whatever the scientific details may be. Having established this harmony, it is now just a matter of working out the details over time.
4. Scientific Problems for Kojonen’s View of Proteins
4.1. Rarity and Isolation of Proteins
4.1.1. The Work of Andreas Wagner
If functional forms are close to one another, then producing a new protein form or function would not require evolution to search through the entire vast realm of all possible arrangements of amino acids. Rather, evolution would only need to search through the adjacent space of possible forms to find viable new forms. This is a far easier task, and if functional forms are arranged in such a way, then this would explain how evolution is possible despite the rarity of functional forms.
4.1.2. Limitations of Wagner’s Research
4.1.3. Axe, Gauger, and Others on Protein Rarity and Isolation
The more crucial point that needs to be made in response [to Axe et al.] is that what matters is not just the rarity of functional forms, but also their closeness in the “biological hyperspace” of functional forms, meaning the “distance” in mutations that is required to traverse between these forms.
4.2. The State of the Field
- An enzyme could only be altered experimentally to perform a new function if its structure and active site were not substantially changed. Such “micro-transitions” could never accumulate to transform an enzyme into something fundamentally different.
- Proteins in different superfamilies have no connection to those in other superfamilies in terms of their sequences and structures. The different superfamilies represent “isolated galaxies”. (A “superfamily” is one of the broadest categories under which one can group similar proteins.)
- Researchers have “zero knowledge” of how the superfamilies are related or could have originated.
“Once you have identified an enzyme that has some weak, promiscuous activity for your target reaction, it’s fairly clear that, if you have mutations at random, you can select and improve this activity by several orders of magnitude”, says Dan Tawfik at the Weizmann Institute in Israel. “What we lack is a hypothesis for the earlier stages, where you don’t have this spectrum of enzymatic activities, active sites, and folds from which selection can identify starting points. Evolution has this catch-22: Nothing evolves unless it already exists.”
5. Scientific Problems for Kojonen’s View of the Bacterial Flagellum
5.1. Irreducible Complexity Defined
In The Origin of Species Darwin stated: “If it could be demonstrated that any complex organ existed which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down”. A system which meets Darwin’s criterion is one which exhibits irreducible complexity. By irreducible complexity I mean a single system composed of several well-matched, interacting parts that contribute to the basic function, wherein the removal of any one of the parts causes the system to effectively cease functioning.
The Irreducible Complexity Argument in a Nutshell
Since the core function of an irreducible complexity emerges only after all necessary parts are in place, it cannot plausibly be evolved in this direct way. After all, natural selection cannot select for a function that emerges only after all of the parts are in place, because selection cannot look to the future. Instead, the gradual evolution of the parts of a system like the flagellum would have to be favored by natural selection for some other reason, not because of increases in mobility.
Behe admits that an irreducibly complex system could in principle evolve in the tinkering, indirect fashion that Behe’s critics point to. However, he claims that, as the complexity of the system increases, the probability of such evolutionary accounts decreases. Because the proteins must fit together, the parts must be modified before serving in the new function. Thus, “analogous parts playing other roles in other systems cannot relieve the irreducible complexity of the new system; the focus simply shifts from ‘making’ the components to ‘modifying’ them” (Behe 2006, pp. 112–13). Orr (1996), who is otherwise critical of Behe’s work, surprisingly agrees with this criticism: “we might think that some of the parts of an irreducibly complex system evolved step by step for some other purpose and were then recruited wholesale to a new function. But this is also unlikely. You may as well hope that half your car’s transmission will suddenly help out in the airbag department. Such things might happen very, very rarely, but they surely do not offer a general solution to irreducible complexity”. Here, the appeal to our common human experience of designing things supports the inference that creating complex teleological order is difficult. There is, indeed, quite a bit of serendipity in parts useful for one purpose being so easily adaptable to another role.
5.2. The Exquisite Bacterial Flagellum
5.2.1. General Features
5.2.2. The Engineering Logic of the Bacterial Flagellum
- A rotary engine with stators that generate greater torque in more viscous environments using an ingeniously engineered adaptive response strategy. The motor also has a clutch to suspend propulsion when doing so is advantageous (National Science Foundation 2008; Guttenplan et al. 2010).
- A propellor-like filament (Ikeda et al. 1996).
- Maintenance processes for the motor and filament (Schuhmacher et al. 2015; Ribardo et al. 2019; Zhuang and Lo 2020).
- An assembly process that incorporates an export gate which moves target proteins outside the bacterium in the right amount at the right time to construct the hook and filament (Waters et al. 2007; Minamino et al. 2014; Tan et al. 2021).
- Processes that suspend operations and eject flagellar proteins in threatening or low-nutrient environments as a form of risk management (Ferreira et al. 2019; Nedeljković et al. 2021).
- Chemotactic navigation that employs sensors which send a chemical signal to the motor to change direction when the bacterium is moving in a direction that is not favorable (Hamadeh et al. 2011; Othmer et al. 2013).
We might think that some of the parts of an irreducibly complex system evolved step by step for some other purpose and were then recruited wholesale to a new function. But this is also unlikely. You may as well hope that half your car’s transmission will suddenly help out in the airbag department. Such things might happen very, very rarely, but they surely do not offer a general solution to irreducible complexity.(Orr 1996)
5.3. Indirect Evolution, Co-Option, Exaptation
Draper (2002) homes in on the crucial question: Are the requirements for each individual part really as strict as Behe claims? If biological parts are more malleable than Behe assumes, so that less specificity is required for fulfilling their roles, then Behe’s argument against co-option fails. Debunking Behe’s argument, then, depends on the details of how proteins work and how difficult it is to transition from one form to another, somewhat similar, form. Then, a continuous series of functional forms, leading from no flagellum to a flagellum, must exist so that no change is too large for natural selection to cross, and all modifications can be made. As with Dembski’s argument, it does seem plausible that evolving such complex systems is difficult, and the existence of such an evolutionary pathway has stringent conditions. But difficult or not, it is possible that nature does allow it. Behe thinks that the existence of such pathways is unlikely, but the existence of such pathways is fundamentally an empirical question.24
5.3.1. Co-Option on Its Own Terms
- (1)
- Availability of parts.
- (2)
- Synchronization, in which parts are available at the same time.
- (3)
- Localization, in which parts are available at the same location.
- (4)
- Coordination, in which part production is coordinated for assembly.
- (5)
- Interface compatibility, in which parts are “mutually compatible, that is, ‘well-matched’ and capable of properly ‘interacting’”. (Menuge 2004, pp. 104–5)
5.3.2. Problem 1: Confusing Sequence Similarity with an Evolutionary Pathway
Although useful for determining lines of descent… comparing sequences cannot show how a complex biochemical system achieved its function—the question that most concerns us in this book. By way of analogy, the instruction manuals for two different models of computer put out by the same company might have many identical words, sentences, and even paragraphs, suggesting a common ancestry (perhaps the same author wrote both manuals), but comparing the sequences of letters in the instruction manuals will never tell us if a computer can be produced step-by-step starting from a typewriter… Like the sequence analysts, I believe the evidence strongly supports common descent. But the root question remains unanswered: What has caused complex systems to form?25
5.3.3. Problem 2: Overstating Protein Homology
Though a complete evolutionary explanation for the bacterial flagellum is still missing, critics of Behe have argued that approximately 90% of the parts of the flagellum are similar (or homologous) to parts that have other uses, and this gives grounds for constructing a plausible evolutionary explanation for its evolution. The type III secretion system, for example, has been argued to represent a viable precursor system to the flagellum. (Musgrave 2004; Pallen and Matzke 2006).
- Two of the claimed flagellar proteins with detected similarities to other proteins are regulatory proteins with unsurprising similarity to other regulators, yet they are not structural components of the flagellum that contribute to its motility function.27
- Three of the allegedly homologous proteins had only slight sequence similarity; they were claimed to be homologous based on “structural or functional considerations”.28 Yet because evolution proceeds by modifying sequences of DNA and proteins, a lack of sequence similarity suggests these other proteins are not a viable source that could have been utilized via an evolutionary pathway.
- Seven of claimed homologous proteins are strictly homologous to other flagellar proteins,29 what might be called “intraflagellar homology”. One cannot explain the initial evolution of the flagellum by claiming it evolved from itself, so these examples are entirely unhelpful towards explaining the how the flagellum first arose from “parts that have other uses” (Kojonen 2021, p. 117) or from “similar parts in other systems” (Kojonen 2021, p. 118), as Kojonen puts it. This tenuous argument may have been derived from Musgrave (2004, p. 81), who argues that flagellar proteins find homologues in “other systems” including “flagellins”—but flagellin is a strictly flagellar protein that only forms a subunit of the flagellum’s propellor.
- Eleven of the claimed homologous proteins were similar to proteins in the Type Three Secretory System (T3SS),30 three of which were also claimed to show intraflagellar homology.31 As quoted above, Kojonen cites the T3SS as a potential “viable precursor system to the flagellum”, but this argument has been long-criticized by intelligent design proponents (Illustra Media 2003) as well as by other scientists. More on this below.
Excursus on T3SS
One fact in favour of the flagellum-first view is that bacteria would have needed propulsion before they needed T3SSs, which are used to attack cells that evolved later than bacteria. Also, flagella are found in a more diverse range of bacterial species than T3SSs. “The most parsimonious explanation is that the T3SS arose later”, says biochemist Howard Ochman at the University of Arizona in Tucson.
[F]inding a subsystem of a functional system that performs some other function is hardly an argument for the original system evolving from that other system. One might just as well say that because the motor of a motorcycle can be used as a blender, therefore the [blender] motor evolved into the motorcycle. Perhaps, but not without intelligent design. Indeed, multipart, tightly integrated functional systems almost invariably contain multipart subsystems that serve some different function. At best the T[3]SS represents one possible step in the indirect Darwinian evolution of the bacterial flagellum. But that still wouldn’t constitute a solution to the evolution of the bacterial flagellum. What’s needed is a complete evolutionary path and not merely a possible oasis along the way. To claim otherwise is like saying we can travel by foot from Los Angeles to Tokyo because we’ve discovered the Hawaiian Islands.
5.3.4. Problem 3: Assembly Not Required?
[E]ven if all the protein parts were somehow available to make a flagellar motor during the evolution of life, the parts would need to be assembled in the correct temporal sequence similar to the way an automobile is assembled in a factory. Yet, to choreograph the assembly of the parts of the flagellar motor, present-day bacteria need an elaborate system of genetic instructions as well as many other protein machines to time the expression of those assembly instructions. Arguably, this system is itself irreducibly complex.
In 1996 [in Darwin’s Black Box] I showed that, despite thousands of papers in journals investigating how that fascinating and medically important molecular machine worked, there were no papers at all that tested how the bacterial flagellum might have arisen by a Darwinian process. The scientific literature was absolutely barren on the topic…. Twenty years on, there has been a grand total of zero serious attempts to show how the elegant molecular motor might have been produced by random processes and natural selection.(Behe 2019, p. 287; see also Behe 2007, pp. 267–68)
6. Convergent Evolution
7. Design Detection Damaged
7.1. Kojonen’s View of Design Detection
According to Ratzsch (2001), design detection typically works by first identifying artifactuality through identifying counterflow, properties that are contrary to what would be expected based on natural processes. However, when analyzing artifactual objects, features like complex teleology then function as secondary markers identifying intentional production, as opposed to what can also be accidental artifactual products, such as footprints. Here Ratzsch identifies both mind correlative order, which suggests design, and mind affinity, which almost inescapably suggests mind. He then argues that while design is typically detected by first observing counterflow, these secondary marks of design can actually provide grounds for design beliefs even in the absence of counterflow.(Kojonen 2021, pp. 164–65, original emphasis)
7.2. A Looming Epistemological Conflict
Why, then, should we think that there is something special about biology that gives grounds for the perception of design, as opposed to ordinary rocks, which also require the existence of a Creator?
It seems to me that even if we did not know about the fine-tuning evidence, our experience of creating things, and observing the properties of life, should make us suspect that our cosmos must be fine-tuned to allow for the evolution of such properties. Assume a further principle that what requires most ability also best demonstrates the existence of that ability. Then, given that the production of complex biological organisms requires far more fine-tuning than the existence or something like rocks, biological organisms better demonstrate the fine-tunedness of the cosmos.
Moreover, as Nagel (2012, p. 6) points out, the design intuition (and resistance to Darwinism as an unguided process) is often based on an “untutored reaction of incredulity to the reductionist neo-Darwinian account of the origin and evolution of life. It is prima facie implausible that life as we know it is the result of a sequence of physical accidents together with the mechanism of natural selection”.(Kojonen 2021, p. 163, citing Nagel 2012)
7.3. Mind over Matter
7.4. Kojonen’s Model Undercuts Itself
7.4.1. Element 1: Direct vs. Indirect Design
7.4.2. Element 2: Continuity of Non-Agent Causes
7.4.3. Element 3: The Foundations of Design Detection
7.5. Brief Conclusion
7.6. The Theist on the Street and a Helpful Design Detection Analogy
8. Summary and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
1 | All of this depends, to a notable extent, on a given person’s background beliefs. |
2 | To elaborate, for example, Kojonen writes: “[I]f the salvaging operation is to be successful, the evidence of biological teleology needs to be shown to provide at least some support for the rationality of religious belief, even while accepting evolutionary explanations as true or probably true” (Kojonen 2021, p. 5, emphasis added). And: “the biological design argument developed here should be understood as a primarily philosophical argument, rather than a scientific one” (Kojonen 2021, p. 6). “However, in this book, the validity of the essential scientific claims of evolutionary biology will be accepted as the starting point of my inquiry. I invite proponents of ID, as well, to assume the plausibility of evolution for the sake of the argument, and to join me in asking if the falsity of the conclusion of design really follows from it” (Kojonen 2021, p. 7, emphasis added). |
3 | As we understand him, Kojonen does not exclude divine interventions from organic history in the sense of prohibiting them or even as a supplement to evolutionary processes per se. Instead, he is simply interested in building an account that does not require any such inventions. See Kojonen (2021, pp. 28–30, 145–204) and Kojonen (2022b). |
4 | Kojonen states that the “preconditions” of evolution, including the “library of forms”, are “an emergent consequence of the laws of chemistry and physics” (Kojonen 2021, p. 123). |
5 | For more on conjunctive explanations and (also) explanatory goodness, see Glass (2012, 2022), Glass and McCartney (2014), (Glass and Schupbach, forthcoming), and Glass (2017). |
6 | Evolution is commonly understood to explain teleology (or the appearance of teleology) itself via reference to a non-teleological process. It is understood as an attempt to reduce teleology to non-teleological causes, and in this way explain the very same evidence that was the given as grounds for inferring design. Thus, once we already have an explanation for biological teleology by way of Darwinism, it is then argued that we no longer have a need for any further explanations. The traditional Darwinian claim is that the question “what processes are responsible for the apparent teleology of biological nature” has already been definitely answered by the theory of evolution, with no need for further explanations. However, if evolution is understood to depend on “laws of form” and to act more as a search engine than as an independent creator like the architect, then it seems to me that Darwinism pushes back the question of the general origin of biological teleology to the laws of nature, and does not yet fully explain this teleological order. If natural selection works, then it can be asked whether its functionality is better explained by reference to design or by reference to chance. This would leave room for a theistic conjunctive explanation of teleology, following Gray’s line of argument on the dependence of evolution on design. |
7 | Kojonen believes that the detectability of design can be discerned by rigorous argument, common sense, and/or intuitive apprehension, given certain background beliefs and other considerations. |
8 | See Footnote 3. |
9 | Kojonen also holds that his model allows for elements of both contingency and directionality together in complementary ways (Kojonen 2021, p. 131). |
10 | Kojonen also cites the work of Wagner and others in support of his view (Kojonen 2021, pp. 123–35). See our discussion below. |
11 | Kojonen (2021, p. 122) frames the matter as follows: “It seems, then, that defending the power of the evolutionary mechanism requires assuming that the landscape of possible biological forms has some fairly serendipitous properties…. The ability of evolution to generate teleology appears to depend on teleology…” So, the need for preconditions, smooth fitness landscapes, and the like is part of Kojonen’s case for design or “teleology”. It is precisely the ‘design’ of these “serendipitous properties” that allows ‘evolution’ to succeed. But if empirical evidence shows that no such “properties” exist, then Kojonen’s appeal to design (in this instance) does not add explanatory benefit to his account of how evolution can find biological forms. |
12 | A brief word about Kojonen’s analysis of evolutionary algorithms is in order. Kojonen draws on the work of ID thinkers, such as William Dembski, to argue that evolution on its own is insufficient to explain the rise of biological complexity and diversity (Kojonen 2021, pp. 97–115). In his response to Kojonen’s account, Jeavons (2022) focuses on Kojonen’s argument that biological fitness landscapes were fine-tuned so that evolutionary searches would achieve predetermined outcomes. Although Jeavons (2022) does not frame it as such, his insightful analysis of evolutionary algorithms poses severe challenges to Kojonen’s premise that the landscapes could have been sufficiently fine-tuned solely due to fine-tuning of the laws of physics and the universe’s initial conditions. Jeavons (2022) states that “additional feedback mechanisms must generally be added to modify the properties of the evolutionary algorithm in a goal-directed way during a run, based on some information about its current performance”. He then states that the adjustments must be based on such variables as the current population and individuals’ current fitness. Consequently, no fitness landscape resulting solely from the initial fine-tuning would allow for an effective evolutionary search in every biological context. For example, if a search was performed effectively for large populations of ants in the late Cretaceous period in one environment, it would likely not allow for successful evolutionary searches in many other contexts, such as the evolution of the first cetaceans. Instead, multiple infusions of new information would have been required to continuously tailor evolutionary searches to achieve desired outcomes. Jeavons (2022) states, “to achieve significant results, an evolutionary algorithm must be carefully tailored to the problem in hand, and the problem itself must have appropriate properties”. Somewhat curiously, neither Kojonen (2022b) nor Jeavon himself acknowledge or solve these difficulties for Kojonen’s model. |
13 | Proteins carry out the large majority of the work in a given cell, so they are crucial for virtually all forms of biological life. |
14 | More fully, ‘sequence space’ is roughly all the possible ways that amino acids can be linked together. Of these many different ways, only a small percentage actually produce a functional protein. By way of analogy: There are many ways that letters in the English alphabet can be arranged in, say, a one-hundred-letter sequence. But of all these ways, only a tiny fraction will form meaningful English sentences. Similarly, only a tiny fraction of the ways that amino acids can be combined will actually produce functional proteins. In short, it is a needle-in-a-haystack scenario. |
15 | Elsewhere in CED, Kojonen cites in support of his view of the “laws of form” the work of Michael Denton and others (Kojonen 2021, pp. 123–25). He also explores convergent evolution, drawing in particular on the work of Simon Conway Morris (Kojonen 2021, pp. 125–28). Our discussion below also applies to the work of these thinkers, mutandis mutatis. |
16 | Other experiments by Gauger et al. (2010) broke 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 just two mutations were required to restore function, Darwinian evolution became stuck, unable to restore the full function. |
17 | For example, Venema (2018) cites intrinsically disordered proteins (IDPs), noting they “do not need to be stably folded in order to function” and therefore represent a type of protein with sequences that are less tightly constrained and are presumably therefore easier to evolve. Yet IDPs fulfill fundamentally different types of roles (e.g., binding to multiple protein surfaces) compared to the proteins with well-defined structures that Axe (2004) studied (e.g., crucial enzymes involved in catalyzing specific reactions). Axe (2018) also responds by noting that Venema (2018) understates the complexity of IDPs. Axe (2018) points out that IDPs are not entirely unfolded, and “a better term” would be to call them “conditionally folded proteins”. Axe (2018) further notes that a major review paper on IDPs cited by Venema (2018) shows that IDPs are capable of folding—they can undergo “coupled folding and binding”; there is a “mechanism by which disordered interaction motifs associate with and fold upon binding to their targets” (Wright and Dyson 2015). That paper further notes that IDPs often do not perform their functions properly after experiencing mutations, suggesting they have sequences that are specifically tailored to their functions: “mutations in [IDPs] or changes in their cellular abundance are associated with disease” (Wright and Dyson 2015). In light of the complexity of IDPs, Axe (2018) concludes:
Venema (2018) also argues that functional proteins are easy to evolve. He cites Neme et al. (2017), a team that genetically engineered E. coli to produce a ∼500 nucleotide RNA (150 of which are random) that encode a 62 amino-acid protein (50 of which are random). The investigators reported that 25% of the randomized sequences enhance the cell’s growth rate. Unfortunately, they misinterpreted their results—a fact pointed out by Weisman and Eddy (2017), who raised “reservations about the correctness of the conclusion of Neme et al. that 25% of their random sequences have beneficial effects”. Here is why they held those reservations: the investigators in Neme et al. (2017) did not compare the growth of cells containing inserted genetic code with normal bacteria but rather with cells that carry a “zero vector”—a stretch of DNA that generates a fixed 350 nucleotide RNA (the randomized 150 nucleotides are excluded from this RNA). Weisman and Eddy (2017) explain how the zero vector “is neither empty nor innocuous”, since it produces a “a 38 amino-acid open reading frame at high levels” of expression. Yet since this “zero vector” and its transcripts provide no benefit to the bacterium, its high expression wastes cellular resources, which, as Weisman and Eddy (2017) note, “is detrimental to the E. coli host”. The reason the randomized peptide sometimes provided a relative benefit to the E. coli bacteria is because, in some cases (25%), it was probably interfering with production of the “zero vector” transcript and/or protein, thus sparing the E. coli host from wasting resources. As Weisman and Eddy (2017) put it, it is “easy to imagine a highly expressed random RNA or protein sequence gumming up the works somehow, by aggregation or otherwise interfering with some cellular component”. Axe (2018) responds to Neme et al. (2017) this way:
In other words, at the molecular level, this random protein was not performing some complex new function but rather was probably interfering with its own RNA transcription and/or translation—a “devolutionary” hypothesis consistent with Michael Behe’s thesis that evolutionarily advantageous features often destroy or diminish function at the molecular level (Behe 2019). In any case, what Neme et al. (2017) showed is that a quarter of the randomized sequences were capable of inhibiting E. coli from expressing this “zero vector”, but they provided no demonstrated benefit to unmodified normal bacteria. Finally, Venema (2018) cites Cai et al. (2008) to argue for the de novo origin of a yeast protein, BSC4, purportedly showing that “new genes that code for novel, functional proteins can pop into existence from sequences that did not previously encode a protein”. However, the paper provides no calculations about the rarity of the protein’s sequence nor its ability to evolve by mutation and selection. Rather, the evidence for this claim is entirely inferred, indirect, and based primarily upon the limited taxonomic range of the gene, which led the authors to infer it was newly evolved. Axe (2018) offers an alternative interpretation:
|
18 | The function of chorismate mutase is to catalyze the conversion of chorismate to prephenate through amino acid side chains in its active site, thereby restricting chorismate’s conformational degrees of freedom. Essentially, it is merely providing a chamber or cavity that holds a particular molecule captive, thereby limiting that molecule’s ability to change. In contrast, beta-lactamase requires the precise positioning and orientation of amino acid side chains from separate domains that contribute to hydrolyzing the peptide bond of the characteristic four-membered beta-lactam ring. This function requires a more complex fold compared to chorismate mutase. Axe (2004) specifically compares beta-lactamase to chorismate mutase and notes that the beta-lactamase fold “is made more complex by its larger size, and by the number of structural components (loops, helices, and strands) and the degree to which formation of these components is intrinsically coupled to the formation of tertiary structure (as is generally the case for strands and loops, but not for helices)”. |
19 | For example, Hunt (2007) argues that relatively short peptides that perform simple functions could first evolve, which could then in turn evolve into more complex proteins that have rarer sequences. Research has shown that some short polypeptides derived from a random library can frequently perform simple functions (see e.g., Keefe and Szostak 2001). However, their ability to further evolve into complex enzymes appears extremely improbable, because functional paths in sequence space would not likely extend to regions containing even modestly complex proteins. The planet analogy in the main text illustrates why: suppose a tiny region around one pole of our hypothetical planet contained a high percentage of traversable land. Even so, a continuous path to the other pole still would not likely exist if a much larger region around the other pole contained a miniscule percentage of traversable land. |
20 | Axe (2011) replies to this objection as follows:
This objection is further rebutted by the planet analogy in the main text, which shows that extreme rarity directly correlates with isolation. |
21 | The area comparisons for the planet were calculated by comparing the proportion of functional sequences for each protein by the percolation threshold in sequence space as defined in percolation theory. The percolation threshold represents the proportion of randomly distributed occupied sites in a lattice below which long continuous paths of neighboring occupied sites become rare. The threshold has been identified for multi-dimensional lattices as approximately the reciprocal of the number of a site’s nearest neighbors (Gaunt et al. 1976). In the context of protein sequence space, it is approximately the reciprocal of the average number of sequences accessible in a single mutation, which is typically less than 10,000. The planet’s traversable land divided by the traversable land corresponding to the percolation threshold of a two-dimensional lattice was set equal to the protein’s proportion of functional sequences divided by its percolation threshold. |
22 | Kojonen tries to overcome this problem by arguing that the physical properties of proteins are “finely-tuned” to bias the clustering of functional sequences such that a very narrow path could extend to complex proteins with rare functional sequences. The biasing would result in the prevalence of functional sequences along a path to a new protein being much higher than in other regions of sequence space. But such biasing could not possibly assist the evolution of most proteins. Biasing in the distribution of functional sequences in sequence space due to physical laws is arguably subject to the same constraints as the biasing in play in the algorithms employed by evolutionary search programs. Consequently, protein evolution falls under “No Free Lunch” theorems that state that no algorithm will in general find targets (e.g., novel proteins) any faster than a random search. An algorithm might assist in finding one target (e.g., specific protein), but it would just as likely hinder finding another (Miller 2017; Footnote 12). Thus, although Kojonen acknowledges that proteins are sometimes too rare to have directly emerged from a random search, he fails to appreciate the extent to which rarity necessitates isolation and why this must often pose a barrier to further protein evolution. Different proteins have completely different compositions of amino acids, physical properties, conformational dynamics, and functions. Any biasing that might assist in the evolution of one protein would almost certainly oppose the evolution of another. In other words, the probability of a continuous path leading to some proteins would be even less likely than if the distribution of functional sequences were random. |
23 | Proteins are chains of amino acids that fold into stable three-dimensional shapes determined by molecular interactions between their constituent amino acids. These “protein folds” determine the specific function that a given protein is then able to perform in the cell (Dobson 2003; Onuchic and Wolynes 2004; Dill et al. 2008). Due to their importance in determining biological functions, protein folds can be considered “the smallest unit of structural innovation in the history of life” (Meyer 2013, p. 191). |
24 | The paragraph concludes with the sentence: “The existence of similar parts in other systems, for example, does provide supporting evidence for evolvability (Musgrave 2004; Pallen and Matzke 2006)”. We will take up this particular claim below. Note also Kojonen (2021)’s appeal to co-option in his response to Behe on page 122. |
25 | Behe (2007, p. 95) likewise notes: “modern Darwinists point to evidence of common descent and erroneously assume it to be evidence of the power of random mutation”. See also a more recent discussion in Behe (2019, pp. 287–91). |
26 | The proteins are: FlgD, FlgH, FlgI, FlgJ, FlgM, FlgN, FlhE, FliB, FliD, FliE, FliL, FliO, FliS, FliT, FliZ. |
27 | The proteins are: FlhDC. |
28 | The proteins are: FliK, FliJ, FliG. |
29 | The proteins are: FlgE, FlgK, FlgL, FlgBCFG. |
30 | The proteins are: FlhA, FlhB, FliF, FliP, FliQ, FliR, FliH, FliI, FliM, FliN, FliC. |
31 | The proteins are: FliM, FliN, FliC. |
32 | The four proteins are FlgH, FlgI, FliS, FliT. |
33 | To elaborate, the injectisome is found in a small subset of gram-negative bacteria that have a symbiotic or parasitic association with eukaryotes. Since eukaryotes evolved over a billion years after bacteria, this suggests that the injectisome arose after eukaryotes, relatively late in the history of life. However, flagella are found across the range of bacteria, and the need for chemotaxis and motility (i.e., using the flagellum to find food) is thought to have arisen very early—perhaps being present as early as the last bacterial common ancestor. Most certainly, the need for chemotaxis and motility preceded the need for parasitism, which means we would expect that the flagellum long predates the injectisome. Indeed, given the narrow distribution of injectisome-bearing bacteria, and the very wide distribution of bacteria with flagella, parsimony suggests the flagellum long predates injectisome rather than the reverse. |
34 | Presumably, the probabilities are independent in each case. The whole point of convergent evolution is that independent evolutionary lineages led to the same outcome in organic history. |
35 | Of course, Kojonen could reply by trying to dissipate these probabilities by appealing to deeper laws of nature, laws of form, or other fundamental features of matter. If the deep structure of nature constrains the development of life by causing it to ‘cluster’ around similar biological forms, then perhaps the probability of the repeated emergence of these forms is higher than expected. But this response is problematic in two ways. First, it plainly runs against actual data we have on protein rarity and isolation, including the rates and time needed for mutations or other changes to produce new proteins. Second, Kojonen cannot take this line of thinking very far if he also wants his model to be compatible with versions of evolution that allow (significant) for contingency. Recall that, though Kojonen himself emphasizes the laws of form (and laws of nature that underlie them), he is nonetheless keen to claim that his model is compatible with mainstream interpretations of evolutionary theory, including ones that allow for a notable degree of contingency and chance. |
36 | Of course, it is possible for Kojonen to reply that some clusters of similarities, such as nested hierarchies, are better explained by common ancestry, whereas other similarities, which appear to be isolated, are better explained by convergent evolution. But the problem with this possible reply is three-fold. First, it does not take seriously Kojonen’s own claim that convergence is “ubiquitous”. To the extent that Kojonen accepts the pervasiveness of convergence in biology is likewise the extent to which the proposed reply is untenable. If convergence is persuasive, is it plausible that convergent similarities never include similarities that are part of a nested hierarchy, for example? Second, the possible reply above also does not solve a deep problem in the other direction: to the extent that similarities are due to common ancestry is also the extent to which convergence does not explain these similarities. But this is a problem, because Kojonen’s view of convergence is ultimately rooted in his understanding of design—it arises from the laws of form, which are themselves the result of designed laws of nature. So, to the extent that Kojonen wishes to use common ancestry to explain similarities (such as those in nested hierarchies) is also the extent to which his use of ‘design’ does not add explanatory value to ‘evolution’. Third, and more generally, the burden is on Kojonen to make these matters clear. He assumes that similarity implies common ancestry (in his view of protein evolution and reply to Behe), yet at other times, he seems to think (other?) similarities point to convergent evolution (and design). Kojonen should resolve this tension by providing a principled ground to demarcate the two that does not damage the explanatory value of ‘design’ and that also avoids internal tension between ‘design’ and ‘evolution’. |
37 | The full quote is helpful. Kojonen (2021) writes:
It seems, then, that defending the power of the evolutionary mechanism requires assuming that the landscape of possible biological forms has some fairly serendipitous properties. (Kojonen 2021, p. 122, emphases added) Kojonen (2021) elsewhere writes:
|
38 | Pretty clearly, we will not assume that Kojonen’s argument for design (KEBDA) is correct given that such an assumption would beg the question at issue. Our epistemological concerns target ways of knowing that make this argument possible in the first place. |
39 | Kojonen draws on Mats Wahlberg’s argument (or analogy) of “computer-generated fugues in order to argue that the products of a design process incorporating random elements can still evidence design” (Kojonen 2021, p. 169). Even if human agents were to listen to such a fugue and mistakenly believe that every element of it was designed (when, in fact, some elements are randomly generated), they are still correct that “the sounds they hear are expressive of intelligence and intent” (Kojonen 2021, p. 170). So, this example apparently shows that design might still be detectable even if humans are mistaken about certain aspects of it. Perhaps, then, Kojonen can reply to our argument by saying that even if humans are mistaken about ‘direct design’, they can still be said to reliably detect design in some notable sense. By way of reply: First, we will show below that Kojonen’s model undercuts humans’ ability to detect design in the way required by Wahlberg’s argument (or analogy). Second, it is arguably the case that, relative to the justification of design beliefs, ‘direct design beliefs’ (“Someone made hummingbirds!”) are more fundamental than ‘detailed design beliefs’, as we might call them (“Someone made every detail of hummingbirds!”). Thus, permissible mistakes about the latter may not be relevant to the epistemic permissibility (and troubling implications) of mistakes about the former. Third, it is not entirely clear that, in Wahlberg’s example, fugues are “random” in a sense that would be relevant to the current discussion. |
40 | An ‘agent’ cause, by contrast, is the direct action of an agent. |
41 | Accordingly, our argument does not fall prey to Kojonen’s critique of Dawkins’s claim that evolution can produce design without a designer and is thus a “consciousness-raiser” that ought to prompt a person to be wary of design (see Kojonen 2021, pp. 145–46). Kojonen (2021, p. 145) responds to Dawkins by saying, “Suppose for the sake of argument that a divine designer is actually responsible for the laws of form (and other environmental factors) that enable evolution. In that case, evolution would be dependent on design, and therefore evolution would not actually show us that evolution can produce design without a designer”. But this critique of Dawkins does not apply to our argument. First, Kojonen’s line of thinking fails to address the larger points we are making about (i) the implications of evolution for ‘direct design’ beliefs and (ii) the broader continuity of non-agent causes that would be apparent to a person who accepted Kojonen’s model. Second, in the quote above, Kojonen seems to move illicitly from ontology to epistemology: from the fact that there is a designer (and design of the type he proposes), it does not follow that evolution itself would not point human observers in the other direction. It is entirely possible that, in some notable sense, evolution might obscure the signal of design. The fact of design does not entail evidence of design. (Similarly, the fact of design likewise does not entail the lack of defeaters to evidence of design.) |
42 | Of course, each of Kojonen’s illustrations is not (simply) given to show that humans can detect design directly or indirectly. Kojonen deploys them for an array of purposes. But our point here is that, insofar as these illustrations support the idea that (on Kojonen’s model) human beings can reliably detect design based on biological phenomena, these illustrations are instead undercut by the fact that Kojonen’s model actually damages the foundational dispositions or beliefs involved in design detection that undergird (this use of) these illustrations. Moreover, Kojonen’s illustrations do not seem to address our points about direct design and non-agent continuity. Biological complexity could in principle be designed (or compatible with design), but that does not mean there would be sufficient evidence of such, especially given some of the key elements of Kojonen’s proposal. So, too, with Kojonen’s view of human technology and the need for fine-tuning to make it possible (Kojonen 2021, p. 173–74). Even if such fine-tuning did exist, a person who accepted Kojonen’s key claims (about evolution, non-agent causes, and so on) would likely have little evidence of it. Interestingly, in his discussion of human technology, Kojonen seems to move away from biological data and, instead, openly cites data from other areas, including mathematics and commonsense physics. Perhaps this is a tacit admission of one of our key points: in Kojonen’s model, the biological evidence on its own may not in fact point to design. |
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Dilley, S.; Luskin, C.; Miller, B.; Reeves, E. On the Relationship between Design and Evolution. Religions 2023, 14, 850. https://doi.org/10.3390/rel14070850
Dilley S, Luskin C, Miller B, Reeves E. On the Relationship between Design and Evolution. Religions. 2023; 14(7):850. https://doi.org/10.3390/rel14070850
Chicago/Turabian StyleDilley, Stephen, Casey Luskin, Brian Miller, and Emily Reeves. 2023. "On the Relationship between Design and Evolution" Religions 14, no. 7: 850. https://doi.org/10.3390/rel14070850
APA StyleDilley, S., Luskin, C., Miller, B., & Reeves, E. (2023). On the Relationship between Design and Evolution. Religions, 14(7), 850. https://doi.org/10.3390/rel14070850